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Ersözlü E, Rauchmann BS. Analysis of Resting-State Functional Magnetic Resonance Imaging in Alzheimer's Disease. Methods Mol Biol 2024; 2785:89-104. [PMID: 38427190 DOI: 10.1007/978-1-0716-3774-6_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
Alzheimer's disease (AD) has been characterized by widespread network disconnection among brain regions, widely overlapping with the hallmarks of the disease. Functional connectivity has been studied with an upward trend in the last two decades, predominantly in AD among other neuropsychiatric disorders, and presents a potential biomarker with various features that might provide unique contributions to foster our understanding of neural mechanisms of AD. The resting-state functional MRI (rs-fMRI) is usually used to measure the blood-oxygen-level-dependent signals that reflect the brain's functional connectivity. Nevertheless, the rs-fMRI is still underutilized, which might be due to the fairly complex acquisition and analytic methodology. In this chapter, we presented the common methods that have been applied in rs-fMRI literature, focusing on the studies on individuals in the continuum of AD. The key methodological aspects will be addressed that comprise acquiring, processing, and interpreting rs-fMRI data. More, we discussed the current and potential implications of rs-fMRI in AD.
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Affiliation(s)
- Ersin Ersözlü
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Department of Geriatric Psychiatry and Developmental Disorders, kbo-Isar-Amper-Klinikum Munich East, Academic Teaching Hospital of LMU Munich, Munich, Germany
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Department of Neuroradiology, University Hospital, LMU Munich, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
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2
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Quan M, Wang Q, Qin W, Wang W, Li F, Zhao T, Li T, Qiu Q, Cao S, Wang S, Wang Y, Jin H, Zhou A, Fang J, Jia L, Jia J. Shared and unique effects of ApoEε4 and pathogenic gene mutation on cognition and imaging in preclinical familial Alzheimer's disease. Alzheimers Res Ther 2023; 15:40. [PMID: 36850008 PMCID: PMC9972804 DOI: 10.1186/s13195-023-01192-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/13/2023] [Indexed: 03/01/2023]
Abstract
BACKGROUND Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and known pathogenic gene mutation on different cognitive domains and circuit imaging markers in preclinical FAD. METHODS One hundred thirty-nine asymptomatic subjects in FAD families, including 26 APOEε4 carriers, 17 APP and 20 PS1 mutation carriers, and 76 control subjects, went through a series of neuropsychological tests and MRI scanning. Test scores and imaging measures including volumes, diffusion indices, and functional connectivity (FC) of frontostriatal and hippocampus to posterior cingulate cortex pathways were compared between groups and analyzed for correlation. RESULTS Compared with controls, the APOEε4 group showed increased hippocampal volume and decreased FC of fronto-caudate pathway. The APP group showed increased recall scores in auditory verbal learning test, decreased fiber number, and increased radial diffusivity and FC of frontostriatal pathway. All three genetic groups showed decreased fractional anisotropy of hippocampus to posterior cingulate cortex pathway. These neuropsychological and imaging measures were able to discriminate genetic groups from controls, with areas under the curve from 0.733 to 0.837. Circuit imaging measures are differentially associated with scores in various cognitive scales in control and genetic groups. CONCLUSIONS There are neuropsychological and imaging changes in the preclinical stage of FAD, some of which are shared by APOEε4 and known pathogenic gene mutation, while some are unique to different genetic groups. These findings are helpful for the early identification of Alzheimer's disease and for developing generalized and individualized prevention and intervention strategies.
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Affiliation(s)
- Meina Quan
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Qi Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Wei Qin
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Wei Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Fangyu Li
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Tan Zhao
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Tingting Li
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Qiongqiong Qiu
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Shuman Cao
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Shiyuan Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Yan Wang
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Hongmei Jin
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Aihong Zhou
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Jiliang Fang
- grid.464297.aGuang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Longfei Jia
- grid.413259.80000 0004 0632 3337Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China ,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China ,grid.24696.3f0000 0004 0369 153XClinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China ,grid.24696.3f0000 0004 0369 153XBeijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China ,grid.24696.3f0000 0004 0369 153XCenter of Alzheimer’s Disease, Beijing Institute for Brain Disorders, Beijing, China ,grid.419897.a0000 0004 0369 313XKey Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China. .,National Center for Neurological Disorders and National Clinical Research Center for Geriatric Diseases, Beijing, China. .,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, China. .,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China. .,Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing, China.
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3
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Sendi MSE, Zendehrouh E, Ellis CA, Fu Z, Chen J, Miller RL, Mormino EC, Salat DH, Calhoun VD. The link between static and dynamic brain functional network connectivity and genetic risk of Alzheimer's disease. Neuroimage Clin 2023; 37:103363. [PMID: 36871405 PMCID: PMC9999198 DOI: 10.1016/j.nicl.2023.103363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 02/23/2023] [Accepted: 02/24/2023] [Indexed: 03/03/2023]
Abstract
Apolipoprotein E (APOE) polymorphic alleles are genetic factors associated with Alzheimer's disease (AD) risk. Although previous studies have explored the link between AD genetic risk and static functional network connectivity (sFNC), to the best of our knowledge, no previous studies have evaluated the association between dynamic FNC (dFNC) and AD genetic risk. Here, we examined the link between sFNC, dFNC, and AD genetic risk with a data-driven approach. We used rs-fMRI, demographic, and APOE data from cognitively normal individuals (N = 886) between 42 and 95 years of age (mean = 70 years). We separated individuals into low, moderate, and high-risk groups. Using Pearson correlation, we calculated sFNC across seven brain networks. We also calculated dFNC with a sliding window and Pearson correlation. The dFNC windows were partitioned into three distinct states with k-means clustering. Next, we calculated the proportion of time each subject spent in each state, called occupancy rate or OCR and frequency of visits. We compared both sFNC and dFNC features across individuals with different genetic risks and found that both sFNC and dFNC are related to AD genetic risk. We found that higher AD risk reduces within-visual sensory network (VSN) sFNC and that individuals with higher AD risk spend more time in a state with lower within-VSN dFNC. We also found that AD genetic risk affects whole-brain sFNC and dFNC in women but not men. In conclusion, we presented novel insights into the links between sFNC, dFNC, and AD genetic risk.
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Affiliation(s)
- Mohammad S E Sendi
- Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, Atlanta, GA, USA; Department of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA, USA; Current affiliation: McLean Hospital and Harvard Medical School, Boston, MA, USA; Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University Atlanta, GA, USA.
| | - Elaheh Zendehrouh
- Department of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA, USA; Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University Atlanta, GA, USA
| | - Charles A Ellis
- Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, Atlanta, GA, USA; Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University Atlanta, GA, USA
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University Atlanta, GA, USA; Georgia State University, Atlanta, GA, USA
| | - Jiayu Chen
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University Atlanta, GA, USA; Georgia State University, Atlanta, GA, USA
| | - Robyn L Miller
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University Atlanta, GA, USA; Georgia State University, Atlanta, GA, USA
| | | | - David H Salat
- Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Boston, MA, USA
| | - Vince D Calhoun
- Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University, Atlanta, GA, USA; Department of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA, USA; Tri-institutional Center for Translational Research in Neuroimaging and Data Science: Georgia State University, Georgia Institute of Technology, Emory University Atlanta, GA, USA; Georgia State University, Atlanta, GA, USA.
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4
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Spinelli G, Bakardjian H, Schwartz D, Potier MC, Habert MO, Levy M, Dubois B, George N. Theta Band-Power Shapes Amyloid-Driven Longitudinal EEG Changes in Elderly Subjective Memory Complainers At-Risk for Alzheimer's Disease. J Alzheimers Dis 2022; 90:69-84. [PMID: 36057818 DOI: 10.3233/jad-220204] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) includes progressive symptoms spread along a continuum of preclinical and clinical stages. Although numerous studies uncovered the neuro-cognitive changes of AD, very little is known on the natural history of brain lesions and modifications of brain networks in elderly cognitively-healthy memory complainers at risk of AD for carrying pathophysiological biomarkers (amyloidopathy and tauopathy). OBJECTIVE We analyzed resting-state electroencephalography (EEG) of 318 cognitively-healthy subjective memory complainers from the INSIGHT-preAD cohort at the time of their first visit (M0) and two-years later (M24). METHODS Using 18F-florbetapir PET-scanner, subjects were stratified between amyloid negative (A-; n = 230) and positive (A+; n = 88) groups. Differences between A+ and A-were estimated at source-level in each band-power of the EEG spectrum. RESULTS At M0, we found an increase of theta power in the mid-frontal cortex in A+ compared to A-. No significant association was found between mid-frontal theta and the individuals' cognitive performance. At M24, theta power increased in A+ relative to A-individuals in the posterior cingulate cortex and the pre-cuneus. Alpha band revealed a peculiar decremental trend in posterior brain regions in the A+ relative to the A-group only at M24. Theta power increase over the mid-frontal and mid-posterior cortices suggests an hypoactivation of the default-mode network in the A+ individuals and a non-linear longitudinal progression at M24. CONCLUSION We provide the first source-level longitudinal evidence on the impact of brain amyloidosis on the EEG dynamics of a large-scale, monocentric cohort of elderly individuals at-risk for AD.
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Affiliation(s)
- Giuseppe Spinelli
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Centre MEG-EEG, CENIR, Paris, France.,AP-HP, Hôpital de la Pitié-Salpêtrière, Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Paris, France
| | - Hovagim Bakardjian
- AP-HP, Hôpital de la Pitié-Salpêtrière, Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Paris, France
| | | | - Marie-Claude Potier
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Centre MEG-EEG, CENIR, Paris, France
| | - Marie-Odile Habert
- Sorbonne Université, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France.,AP-HP, Hôpital de la Pitié-Salpêtrière, Médecine Nucléaire, Paris, France.,Centre d'Acquisition et Traitement des Images (CATI), http://www.cati-neuroimaging.com
| | - Marcel Levy
- AP-HP, Hôpital de la Pitié-Salpêtrière, Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Paris, France
| | - Bruno Dubois
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Centre MEG-EEG, CENIR, Paris, France.,AP-HP, Hôpital de la Pitié-Salpêtrière, Institute of Memory and Alzheimer's Disease (IM2A), Department of Neurology, Paris, France
| | - Nathalie George
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Centre MEG-EEG, CENIR, Paris, France
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5
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He B, Gorijala P, Xie L, Cao S, Yan J. Gene co-expression changes underlying the functional connectomic alterations in Alzheimer's disease. BMC Med Genomics 2022; 15:92. [PMID: 35461274 PMCID: PMC9035246 DOI: 10.1186/s12920-022-01244-6] [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: 04/19/2022] [Accepted: 04/19/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND There is growing evidence indicating that a number of functional connectivity networks are disrupted at each stage of the full clinical Alzheimer's disease spectrum. Such differences are also detectable in cognitive normal (CN) carrying mutations of AD risk genes, suggesting a substantial relationship between genetics and AD-altered functional brain networks. However, direct genetic effect on functional connectivity networks has not been measured. METHODS Leveraging existing AD functional connectivity studies collected in NeuroSynth, we performed a meta-analysis to identify two sets of brain regions: ones with altered functional connectivity in resting state network and ones without. Then with the brain-wide gene expression data in the Allen Human Brain Atlas, we applied a new biclustering method to identify a set of genes with differential co-expression patterns between these two set of brain regions. RESULTS Differential co-expression analysis using biclustering method led to a subset of 38 genes which showed distinctive co-expression patterns between AD-related and non AD-related brain regions in default mode network. More specifically, we observed 4 sub-clusters with noticeable co-expression difference, where the difference in correlations is above 0.5 on average. CONCLUSIONS This work applies a new biclustering method to search for a subset of genes with altered co-expression patterns in AD-related default mode network regions. Compared with traditional differential expression analysis, differential co-expression analysis yielded many more significant hits with extra insights into the wiring mechanism between genes. Particularly, the differential co-expression pattern was observed between two sets of genes, suggesting potential upstream genetic regulators in AD development.
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Affiliation(s)
- Bing He
- Department of BioHealth Informatics, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
| | - Priyanka Gorijala
- Department of BioHealth Informatics, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
| | - Linhui Xie
- Department of Electrical and Computer Engineering, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
| | - Sha Cao
- Department of Biostatistics and Health Data Sciences, School of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jingwen Yan
- Department of BioHealth Informatics, Indiana University Purdue University Indianapolis, Indianapolis, IN, USA
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6
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Zhao B, Li T, Smith SM, Xiong D, Wang X, Yang Y, Luo T, Zhu Z, Shan Y, Matoba N, Sun Q, Yang Y, Hauberg ME, Bendl J, Fullard JF, Roussos P, Lin W, Li Y, Stein JL, Zhu H. Common variants contribute to intrinsic human brain functional networks. Nat Genet 2022; 54:508-517. [PMID: 35393594 DOI: 10.1038/s41588-022-01039-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/28/2022] [Indexed: 01/01/2023]
Abstract
The human brain forms functional networks of correlated activity, which have been linked with both cognitive and clinical outcomes. However, the genetic variants affecting brain function are largely unknown. Here, we used resting-state functional magnetic resonance images from 47,276 individuals to discover and validate common genetic variants influencing intrinsic brain activity. We identified 45 new genetic regions associated with brain functional signatures (P < 2.8 × 10-11), including associations to the central executive, default mode, and salience networks involved in the triple-network model of psychopathology. A number of brain activity-associated loci colocalized with brain disorders (e.g., the APOE ε4 locus with Alzheimer's disease). Variation in brain function was genetically correlated with brain disorders, such as major depressive disorder and schizophrenia. Together, our study provides a step forward in understanding the genetic architecture of brain functional networks and their genetic links to brain-related complex traits and disorders.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics, Purdue University, West Lafayette, IN, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Di Xiong
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tianyou Luo
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ziliang Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Shan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nana Matoba
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yuchen Yang
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mads E Hauberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
| | - Jaroslav Bendl
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panagiotis Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark.,Department of Genetics and Genomic Science and Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Weili Lin
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Hongtu Zhu
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. .,Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. .,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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7
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Elsheikh SSM, Chimusa ER, Mulder NJ, Crimi A. Relating Global and Local Connectome Changes to Dementia and Targeted Gene Expression in Alzheimer's Disease. Front Hum Neurosci 2022; 15:761424. [PMID: 35002653 PMCID: PMC8734427 DOI: 10.3389/fnhum.2021.761424] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 11/25/2021] [Indexed: 01/01/2023] Open
Abstract
Networks are present in many aspects of our lives, and networks in neuroscience have recently gained much attention leading to novel representations of brain connectivity. The integration of neuroimaging characteristics and genetics data allows a better understanding of the effects of the gene expression on brain structural and functional connections. The current work uses whole-brain tractography in a longitudinal setting, and by measuring the brain structural connectivity changes studies the neurodegeneration of Alzheimer's disease. This is accomplished by examining the effect of targeted genetic risk factors on the most common local and global brain connectivity measures. Furthermore, we examined the extent to which Clinical Dementia Rating relates to brain connections longitudinally, as well as to gene expression. For instance, here we show that the expression of PLAU gene increases the change over time in betweenness centrality related to the fusiform gyrus. We also show that the betweenness centrality metric impact dementia-related changes in distinct brain regions. Our findings provide insights into the complex longitudinal interplay between genetics and brain characteristics and highlight the role of Alzheimer's genetic risk factors in the estimation of regional brain connectivity alterations.
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Affiliation(s)
- Samar S M Elsheikh
- Pharmacogenetic Research Clinic, Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada.,Computational Biology Division, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Emile R Chimusa
- Division of Human Genetics, Department of Pathology, Faculty of Health Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | | | - Nicola J Mulder
- Computational Biology Division, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Alessandro Crimi
- Computer Vision Group, Sano Centre for Computational Medicine, Kraków, Poland.,Institute for Neuropathology, University Hospital of Zurich, Zurich, Switzerland.,Department of Mathematics, African Institute for Mathematical Sciences, Cape Coast, Ghana
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8
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Pini L, Wennberg AM, Salvalaggio A, Vallesi A, Pievani M, Corbetta M. Breakdown of specific functional brain networks in clinical variants of Alzheimer's disease. Ageing Res Rev 2021; 72:101482. [PMID: 34606986 DOI: 10.1016/j.arr.2021.101482] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/24/2021] [Accepted: 09/29/2021] [Indexed: 02/07/2023]
Abstract
Alzheimer's disease (AD) is characterized by different clinical entities. Although AD phenotypes share a common molecular substrate (i.e., amyloid beta and tau accumulation), several clinicopathological differences exist. Brain functional networks might provide a macro-scale scaffolding to explain this heterogeneity. In this review, we summarize the evidence linking different large-scale functional network abnormalities to distinct AD phenotypes. Specifically, executive deficits in early-onset AD link with the dysfunction of networks that support sustained attention and executive functions. Posterior cortical atrophy relates to the breakdown of visual and dorsal attentional circuits, while the primary progressive aphasia variant of AD may be associated with the dysfunction of the left-lateralized language network. Additionally, network abnormalities might provide in vivo signatures for distinguishing proteinopathies that mimic AD, such as TAR DNA binding protein 43 related pathologies. These network differences vis-a-vis clinical syndromes are more evident in the earliest stage of AD. Finally, we discuss how these findings might pave the way for new tailored interventions targeting the most vulnerable brain circuit at the optimal time window to maximize clinical benefits.
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9
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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: 87] [Impact Index Per Article: 29.0] [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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10
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Kucikova L, Goerdten J, Dounavi ME, Mak E, Su L, Waldman AD, Danso S, Muniz-Terrera G, Ritchie CW. Resting-state brain connectivity in healthy young and middle-aged adults at risk of progressive Alzheimer's disease. Neurosci Biobehav Rev 2021; 129:142-153. [PMID: 34310975 DOI: 10.1016/j.neubiorev.2021.07.024] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 05/18/2021] [Accepted: 07/21/2021] [Indexed: 11/15/2022]
Abstract
Functional brain connectivity of the resting-state networks has gained recent attention as a possible biomarker of Alzheimer's Disease (AD). In this paper, we review the literature of functional connectivity differences in young adults and middle-aged cognitively intact individuals with non-modifiable risk factors of AD (n = 17). We focus on three main intrinsic resting-state networks: The Default Mode network, Executive network, and the Salience network. Overall, the evidence from the literature indicated early vulnerability of functional connectivity across different at-risk groups, particularly in the Default Mode Network. While there was little consensus on the interpretation on directionality, the topography of the findings showed frequent overlap across studies, especially in regions that are characteristic of AD (i.e., precuneus, posterior cingulate cortex, and medial prefrontal cortex areas). We conclude that while resting-state functional connectivity markers have great potential to identify at-risk individuals, implementing more data-driven approaches, further longitudinal and cross-validation studies, and the analysis of greater sample sizes are likely to be necessary to fully establish the effectivity and utility of resting-state network-based analyses.
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Affiliation(s)
- Ludmila Kucikova
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom.
| | - Jantje Goerdten
- Department of Epidemiological Methods and Etiological Research, Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Adam D Waldman
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Samuel Danso
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Graciela Muniz-Terrera
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Craig W Ritchie
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
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11
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Virtual Connectomic Datasets in Alzheimer's Disease and Aging Using Whole-Brain Network Dynamics Modelling. eNeuro 2021; 8:ENEURO.0475-20.2021. [PMID: 34045210 PMCID: PMC8260273 DOI: 10.1523/eneuro.0475-20.2021] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 03/08/2021] [Accepted: 04/12/2021] [Indexed: 12/18/2022] Open
Abstract
Large neuroimaging datasets, including information about structural connectivity (SC) and functional connectivity (FC), play an increasingly important role in clinical research, where they guide the design of algorithms for automated stratification, diagnosis or prediction. A major obstacle is, however, the problem of missing features [e.g., lack of concurrent DTI SC and resting-state functional magnetic resonance imaging (rsfMRI) FC measurements for many of the subjects]. We propose here to address the missing connectivity features problem by introducing strategies based on computational whole-brain network modeling. Using two datasets, the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset and a healthy aging dataset, for proof-of-concept, we demonstrate the feasibility of virtual data completion (i.e., inferring “virtual FC” from empirical SC or “virtual SC” from empirical FC), by using self-consistent simulations of linear and nonlinear brain network models. Furthermore, by performing machine learning classification (to separate age classes or control from patient subjects), we show that algorithms trained on virtual connectomes achieve discrimination performance comparable to when trained on actual empirical data; similarly, algorithms trained on virtual connectomes can be used to successfully classify novel empirical connectomes. Completion algorithms can be combined and reiterated to generate realistic surrogate connectivity matrices in arbitrarily large number, opening the way to the generation of virtual connectomic datasets with network connectivity information comparable to the one of the original data.
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12
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Figueroa-Jimenez MD, Cañete-Massé C, Carbó-Carreté M, Zarabozo-Hurtado D, Peró-Cebollero M, Salazar-Estrada JG, Guàrdia-Olmos J. Resting-state default mode network connectivity in young individuals with Down syndrome. Brain Behav 2021; 11:e01905. [PMID: 33179859 PMCID: PMC7821605 DOI: 10.1002/brb3.1905] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 09/24/2020] [Accepted: 10/02/2020] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Down syndrome (DS) is a chromosomal disorder that causes intellectual disability. Few studies have been conducted on functional connectivity using resting-state fMRI (functional magnetic resonance imaging) signals or more specifically, on the relevant structure and density of the default mode network (DMN). Although data on this issue have been reported in adult DS individuals (age: >45 years), the DMN properties in young DS individuals have not been studied. The aim of this study was to describe the density and structure of the DMN network from fMRI signals in young DS (age: <36 years). METHOD A sample of 22 young people with DS between the ages of 16 and 35 (M = 25.5 and SD = 5.1) was recruited in various centers for people with intellectual disability (ID). In addition to sociodemographic data, a six-minute fMRI session was recorded with a 3. T Philips Ingenia scanner. A control group of 22 young people, matched by age and gender, was obtained from the Human Connectome Project (to compare the networks properties between groups). RESULTS The values of the 48 ROIs that configured the DMN were obtained, and the connectivity graphs for each subject, the average connectivity graph for each group, the clustering and degree values for each ROI, and the average functional connectivity network were estimated. CONCLUSIONS A higher density of overactivation was identified in DS group in the ventral, sensorimotor, and visual DMN networks, although within a framework of a wide variability of connectivity patterns in comparison with the control group network. These results extend our understanding of the functional connectivity networks pattern and intrasubject variability in DS.
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Affiliation(s)
| | - Cristina Cañete-Massé
- Department of Social Psychology & Quantitative Psychology, Faculty of Psychology, University of Barcelona, Barcelona, Spain.,UB Institute of Complex Systems, University of Barcelona, Barcelona, Spain
| | - María Carbó-Carreté
- Institute of Neuroscience, University of Barcelona, Barcelona, Spain.,Department of Cognition, Developmental Psychology and Education, Faculty of Psychology, University of Barcelona, Barcelona, Spain
| | - Daniel Zarabozo-Hurtado
- RIO Group Clinical Laboratory, Center for Research in Advanced Functional Neuro-Diagnosis CINDFA, Guadalajara, México
| | - Maribel Peró-Cebollero
- Department of Social Psychology & Quantitative Psychology, Faculty of Psychology, University of Barcelona, Barcelona, Spain.,UB Institute of Complex Systems, University of Barcelona, Barcelona, Spain.,Institute of Neuroscience, University of Barcelona, Barcelona, Spain
| | | | - Joan Guàrdia-Olmos
- Department of Social Psychology & Quantitative Psychology, Faculty of Psychology, University of Barcelona, Barcelona, Spain.,UB Institute of Complex Systems, University of Barcelona, Barcelona, Spain.,Institute of Neuroscience, University of Barcelona, Barcelona, Spain
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13
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Avila J, Perry G. A Multilevel View of the Development of Alzheimer's Disease. Neuroscience 2020; 457:283-293. [PMID: 33246061 DOI: 10.1016/j.neuroscience.2020.11.015] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 10/28/2020] [Accepted: 11/10/2020] [Indexed: 12/12/2022]
Abstract
Every year the Alzheimer's Association publishes a report that provides facts and figures indicating the public health, social and economic impact of Alzheimer's disease (AD). In addition, there are a number of reviews on the disease for general readers. Also, at congresses, AD is analyzed at different but not always related levels, leading to an "elephant as seen by blind men situation" for many of the participants. The review presented herein seeks to provide readers with a holistic view of how AD develops from various perspectives: the whole human organism, brain, circuits, neurons, cellular hallmarks, and molecular level.
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Affiliation(s)
- Jesús Avila
- Centro de Biología Molecular Severo Ochoa (CSIC-UAM), 28049 Madrid, Spain; Network Centre for Biomedical Research in Neurodegenerative Diseases (CIBERNED), 28031 Madrid, Spain.
| | - George Perry
- College of Sciences, University of Texas at San Antonio, San Antonio, TX, USA.
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14
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Kuang L, Jia J, Zhao D, Xiong F, Han X, Wang Y. Default Mode Network Analysis of APOE Genotype in Cognitively Unimpaired Subjects Based on Persistent Homology. Front Aging Neurosci 2020; 12:188. [PMID: 32733231 PMCID: PMC7358981 DOI: 10.3389/fnagi.2020.00188] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 06/02/2020] [Indexed: 12/22/2022] Open
Abstract
Current researches on default mode network (DMN) in normal elderly have mainly focused on finding some dysfunctional areas with decreased or increased connectivity. The global network dynamics of apolipoprotein E (APOE) e4 allele group is rarely studied. In our previous brain network study, we have demonstrated the advantage of persistent homology. It can distinguish robust and noisy topological features over multiscale nested networks, and the derived properties are more stable. In this study, for the first time we applied persistent homology to analyze APOE-related effects on whole-brain functional network. In our experiments, the risk allele group exhibited lower network radius and modularity in whole brain DMN based on graph theory, suggesting the abnormal organization structure. Moreover, two suggested measures from persistent homology detected significant differences between groups within the left hemisphere and in the whole brain in two datasets. They were more statistically sensitive to APOE genotypic differences than standard graph-based measures. In summary, we provide evidence that the e4 genotype leads to distinct DMN functional alterations in the early phases of Alzheimer's disease using persistent homology approach. Our study offers a novel insight to explore potential biomarkers in healthy elderly populations carrying APOE e4 allele.
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Affiliation(s)
- Liqun Kuang
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Jiaying Jia
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Deyu Zhao
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Fengguang Xiong
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Xie Han
- School of Data Science and Technology, North University of China, Taiyuan, China
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, United States
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15
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Chiesa PA, Houot M, Vergallo A, Cavedo E, Lista S, Potier MC, Zetterberg H, Blennow K, Vanmechelen E, De Vos A, Dubois B, Hampel H. Association of brain network dynamics with plasma biomarkers in subjective memory complainers. Neurobiol Aging 2020; 88:83-90. [DOI: 10.1016/j.neurobiolaging.2019.12.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 12/15/2019] [Accepted: 12/16/2019] [Indexed: 11/16/2022]
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16
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Genetic influence on ageing-related changes in resting-state brain functional networks in healthy adults: A systematic review. Neurosci Biobehav Rev 2020; 113:98-110. [PMID: 32169413 DOI: 10.1016/j.neubiorev.2020.03.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 02/08/2020] [Accepted: 03/09/2020] [Indexed: 11/21/2022]
Abstract
This systematic review examines the genetic and epigenetic factors associated with resting-state functional connectivity (RSFC) in healthy human adult brains across the lifespan, with a focus on genes associated with Alzheimer's disease (AD). There were 58 studies included. The key findings are: (i) genetic factors have a low to moderate contribution; (ii) the apolipoprotein E ε2/3/4 polymorphism was the most studied genetic variant, with the APOE-ε4 allele most consistently associated with deficits of the default mode network, but there were insufficient studies to determine the relationships with other AD candidate risk genes; (iii) a single genome-wide association study identified several variants related to RSFC; (iv) two epigenetic independent studies showed a positive relationship between blood DNA methylation of the SLC6A4 promoter and RSFC measures. Thus, there is emerging evidence that genetic and epigenetic variation influence the brain's functional organisation and connectivity over the adult lifespan. However, more studies are required to elucidate the roles genetic and epigenetic factors play in RSFC measures across the adult lifespan.
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17
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Quan M, Zhao T, Tang Y, Luo P, Wang W, Qin Q, Li T, Wang Q, Fang J, Jia J. Effects of gene mutation and disease progression on representative neural circuits in familial Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2020; 12:14. [PMID: 31937364 PMCID: PMC6961388 DOI: 10.1186/s13195-019-0572-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 12/23/2019] [Indexed: 02/08/2023]
Abstract
Background Although structural and functional changes of the striatum and hippocampus are present in familial Alzheimer’s disease, little is known about the effects of specific gene mutation or disease progression on their related neural circuits. This study was to evaluate the effects of known pathogenic gene mutation and disease progression on the striatum- and hippocampus-related neural circuits, including frontostriatal and hippocampus-posterior cingulate cortex (PCC) pathways. Methods A total of 102 healthy mutation non-carriers, 40 presymptomatic mutation carriers (PMC), and 30 symptomatic mutation carriers (SMC) of amyloid precursor protein (APP), presenilin 1 (PS1), or presenilin 2 gene, with T1 structural MRI, diffusion tensor imaging, and resting-state functional MRI were included. Representative neural circuits and their key nodes were obtained, including bilateral caudate-rostral middle frontal gyrus (rMFG), putamen-rMFG, and hippocampus-PCC. Volumes, diffusion indices, and functional connectivity of circuits were compared between groups and correlated with neuropsychological and clinical measures. Results In PMC, APP gene mutation carriers showed impaired diffusion indices of caudate-rMFG and putamen-rMFG circuits; PS1 gene mutation carriers showed increased fiber numbers of putamen-rMFG circuit. SMC showed increased diffusivity of the left hippocampus-PCC circuit and volume reduction of all regions as compared with PMC. Imaging measures especially axial diffusivity of the representative circuits were correlated with neuropsychological measures. Conclusions APP and PS1 gene mutations affect frontostriatal circuits in a different manner in familial Alzheimer’s disease; disease progression primarily affects the structure of hippocampus-PCC circuit. The structural connectivity of both frontostriatal and hippocampus-PCC circuits is associated with general cognitive function. Such findings may provide further information about the imaging biomarkers for early identification and prognosis of familial Alzheimer’s disease, and pave the way for early diagnosis, gene- or circuit-targeted treatment, and even prevention. Electronic supplementary material The online version of this article (10.1186/s13195-019-0572-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Meina Quan
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Tan Zhao
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Yi Tang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Ping Luo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Wei Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Qi Qin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Tingting Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Qigeng Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China.,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China
| | - Jiliang Fang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, People's Republic of China. .,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, People's Republic of China. .,Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing, People's Republic of China. .,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, People's Republic of China.
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18
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Chiesa PA, Cavedo E, Vergallo A, Lista S, Potier M, Habert M, Dubois B, Thiebaut de Schotten M, Hampel H. Differential default mode network trajectories in asymptomatic individuals at risk for Alzheimer's disease. Alzheimers Dement 2019; 15:940-950. [DOI: 10.1016/j.jalz.2019.03.006] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 01/25/2019] [Accepted: 03/04/2019] [Indexed: 11/16/2022]
Affiliation(s)
- Patrizia A. Chiesa
- Sorbonne University, GRC no 21Alzheimer Precision Medicine (APM), AP‐HPPitié‐Salpêtrière HospitalBoulevard de l'hôpitalParisFrance
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225Boulevard de l'hôpitalParisFrance
- Department of NeurologyInstitute of Memory and Alzheimer's Disease (IM2A)Pitié‐Salpêtrière Hospital, AP‐HPBoulevard de l'hôpitalParisFrance
| | - Enrica Cavedo
- Sorbonne University, GRC no 21Alzheimer Precision Medicine (APM), AP‐HPPitié‐Salpêtrière HospitalBoulevard de l'hôpitalParisFrance
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225Boulevard de l'hôpitalParisFrance
- Department of NeurologyInstitute of Memory and Alzheimer's Disease (IM2A)Pitié‐Salpêtrière Hospital, AP‐HPBoulevard de l'hôpitalParisFrance
| | - Andrea Vergallo
- Sorbonne University, GRC no 21Alzheimer Precision Medicine (APM), AP‐HPPitié‐Salpêtrière HospitalBoulevard de l'hôpitalParisFrance
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225Boulevard de l'hôpitalParisFrance
- Department of NeurologyInstitute of Memory and Alzheimer's Disease (IM2A)Pitié‐Salpêtrière Hospital, AP‐HPBoulevard de l'hôpitalParisFrance
| | - Simone Lista
- Sorbonne University, GRC no 21Alzheimer Precision Medicine (APM), AP‐HPPitié‐Salpêtrière HospitalBoulevard de l'hôpitalParisFrance
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225Boulevard de l'hôpitalParisFrance
- Department of NeurologyInstitute of Memory and Alzheimer's Disease (IM2A)Pitié‐Salpêtrière Hospital, AP‐HPBoulevard de l'hôpitalParisFrance
| | - Marie‐Claude Potier
- ICM Institut du Cerveau et de la Moelleépinière, CNRS UMR7225, INSERM U1127, UPMCHôpital de la Pitié‐Salpêtrière, 47 Bd de l'HôpitalParisFrance
| | - Marie‐Odile Habert
- Laboratoire d'Imagerie BiomédicaleSorbonne Université, INSERM U 1146, CNRS UMRParisFrance
- Department of Nuclear Medicine, AP‐HPHôpitalPitié‐SalpêtrièreParisFrance
- Centre Acquisition et Traitement des Images (CATI)ParisFrance
| | - Bruno Dubois
- Sorbonne University, GRC no 21Alzheimer Precision Medicine (APM), AP‐HPPitié‐Salpêtrière HospitalBoulevard de l'hôpitalParisFrance
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225Boulevard de l'hôpitalParisFrance
- Department of NeurologyInstitute of Memory and Alzheimer's Disease (IM2A)Pitié‐Salpêtrière Hospital, AP‐HPBoulevard de l'hôpitalParisFrance
| | - Michel Thiebaut de Schotten
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225Boulevard de l'hôpitalParisFrance
- Laboratory of Alzheimer's Neuroimaging and EpidemiologyIRCCS Centro San Giovanni di Dio FatebenefratelliBresciaItaly
- Brain Connectivity Behaviour LaboratorySorbonne UniversitiesParisFrance
- Groupe d'Imagerie NeurofonctionnelleInstitut des Maladies Neurodégénératives‐UMR 5293CNRSCEA University of BordeauxBordeauxFrance
| | - Harald Hampel
- Sorbonne University, GRC no 21Alzheimer Precision Medicine (APM), AP‐HPPitié‐Salpêtrière HospitalBoulevard de l'hôpitalParisFrance
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Hampel H, Vergallo A, Perry G, Lista S. The Alzheimer Precision Medicine Initiative. J Alzheimers Dis 2019; 68:1-24. [DOI: 10.3233/jad-181121] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Harald Hampel
- AXA Research Fund & Sorbonne University Chair, Paris, France
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l’hôpital, Paris, France
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Paris, France
- Institute of Memory and Alzheimer’s Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l’hôpital, Paris, France
| | - Andrea Vergallo
- AXA Research Fund & Sorbonne University Chair, Paris, France
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l’hôpital, Paris, France
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Paris, France
- Institute of Memory and Alzheimer’s Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l’hôpital, Paris, France
| | - George Perry
- College of Sciences, One UTSA Circle, The University of Texas at San Antonio, San Antonio, TX, USA
| | - Simone Lista
- AXA Research Fund & Sorbonne University Chair, Paris, France
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l’hôpital, Paris, France
- Brain & Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Paris, France
- Institute of Memory and Alzheimer’s Disease (IM2A), Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l’hôpital, Paris, France
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Chiesa PA, Cavedo E, Grothe MJ, Houot M, Teipel SJ, Potier MC, Habert MO, Lista S, Dubois B, Hampel H. Relationship between Basal Forebrain Resting-State Functional Connectivity and Brain Amyloid-β Deposition in Cognitively Intact Older Adults with Subjective Memory Complaints. Radiology 2018; 290:167-176. [PMID: 30351255 DOI: 10.1148/radiol.2018180268] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Purpose To evaluate the association between the global fibrillary amyloid-β pathology and the basal forebrain connectivity at rest in cognitively intact older adults at risk for Alzheimer disease. Materials and Methods This retrospective study was approved by the local ethics committee and written informed consent was obtained from all participants. Resting-state functional connectivity (RSFC) of anterior and posterior basal forebrain seeds was investigated, as well as PET-measured global amyloid-β load by using standardized uptake value ratio (SUVR) in 267 older cognitively intact individuals with subjective memory complaints (age range, 70-85 years; overall mean age, 75.8 years; 167 women [mean age, 75.9 years] and 100 men [mean age, 75.8 years]). The participants were from the Investigation of Alzheimer's Predictors in Subjective Memory Complainers (INSIGHT-preAD) cohort (date range, 2013-present). The relationship between SUVR and the basal forebrain RSFC was assessed, followed by the effects of apolipoprotein E (APOE) genotype and sex on the basal forebrain RSFC. Results Higher SUVR values correlated with lower posterior basal forebrain RSFC in the hippocampus and the thalamus (Pearson r =-0.23; P <.001 corrected for familywise error [FWE]). Both sex and APOE genotype impacted the associations between basal forebrain RSFC and the global amyloid deposition (t values >3.59; P <.05 corrected for FWE). Conclusion Data indicate a distinct in vivo association between posterior basal forebrain dynamics and global fibrillary amyloid-β pathology in cognitively intact older adults with subjective memory complaints; both apolipoprotein E and sex moderate such association. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Caspers in this issue.
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Affiliation(s)
- Patrizia A Chiesa
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Enrica Cavedo
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Michel J Grothe
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Marion Houot
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Stefan J Teipel
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Marie-Claude Potier
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Marie-Odile Habert
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Simone Lista
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Bruno Dubois
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
| | - Harald Hampel
- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
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- From the AXA Research Fund & UPMC Chair, Paris, France (P.A.C., E.C., S.L., H.H.); Sorbonne Université, GRC n° 21, Alzheimer Precision Medicine, AP-HP, Hôpital de la Pitié-Salpêtrière, Boulevard de l'hôpital, F-75013, Paris, France (P.A.C., E.C., M.H., S.L., B.D., H.H.); Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225 (P.A.C., E.C., S.L., B.D., H.H.); Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Department of Neurology, Hôpital de la Pitié-Salpêtrière (P.A.C., E.C., M.H., S.L., B.D., H.H.); Istituto Centro San Giovanni di Dio-Fatebenefratelli, Italy (E.C.); German Center for Neurodegenerative Diseases - Rostock/Greifswald, Rostock, Germany (M.J.G., S.J.T.); Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany (S.J.T.); ICM, CNRS UMR7225, INSERM U1127, UPMC, Hôpital de la Pitié-Salpêtrière, Paris, France (M.C.P.); Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, Paris, France (M.O.H.); Centre pour l'Acquisition et le Traitement des Images, Paris, France (M.O.H.); AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France (M.O.H.). Centre of Excellence of Neurodegenerative Disease, Department of Neurology, Hôpital de la Pitié-Salpêtrière (M.H., B.D.); Center for Clinical Investigation Neurosciences, ICM (M.H.)
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Rodríguez-Rojo IC, Cuesta P, López ME, de Frutos-Lucas J, Bruña R, Pereda E, Barabash A, Montejo P, Montenegro-Peña M, Marcos A, López-Higes R, Fernández A, Maestú F. BDNF Val66Met Polymorphism and Gamma Band Disruption in Resting State Brain Functional Connectivity: A Magnetoencephalography Study in Cognitively Intact Older Females. Front Neurosci 2018; 12:684. [PMID: 30333719 PMCID: PMC6176075 DOI: 10.3389/fnins.2018.00684] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Accepted: 09/11/2018] [Indexed: 11/13/2022] Open
Abstract
The pathophysiological processes undermining brain functioning decades before the onset of the clinical symptoms associated with dementia are still not well understood. Several heritability studies have reported that the Brain Derived Neurotrophic Factor (BDNF) Val66Met genetic polymorphism could contribute to the acceleration of cognitive decline in aging. This mutation may affect brain functional connectivity (FC), especially in those who are carriers of the BDNF Met allele. The aim of this work was to explore the influence of the BDNF Val66Met polymorphism in whole brain eyes-closed, resting-state magnetoencephalography (MEG) FC in a sample of 36 cognitively intact (CI) older females. All of them were ε3ε3 homozygotes for the apolipoprotein E (APOE) gene and were divided into two subgroups according to the presence of the Met allele: Val/Met group (n = 16) and Val/Val group (n = 20). They did not differ in age, years of education, Mini-Mental State Examination scores, or normalized hippocampal volumes. Our results showed reduced antero-posterior gamma band FC within the Val/Met genetic risk group, which may be caused by a GABAergic network impairment. Despite the lack of cognitive decline, these results might suggest a selective brain network vulnerability due to the carriage of the BDNF Met allele, which is linked to a potential progression to dementia. This neurophysiological signature, as tracked with MEG FC, indicates that age-related brain functioning changes could be mediated by the influence of particular genetic risk factors.
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Affiliation(s)
- Inmaculada C Rodríguez-Rojo
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain.,Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Pablo Cuesta
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain.,Electrical Engineering and Bioengineering Lab, Department of Industrial Engineering and IUNE, Universidad de La Laguna, Tenerife, Spain
| | - María Eugenia López
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain.,Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Jaisalmer de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain.,Biological and Health Psychology Department, Universidad Autónoma de Madrid, Madrid, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain.,Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain.,Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Ernesto Pereda
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain.,Electrical Engineering and Bioengineering Lab, Department of Industrial Engineering and IUNE, Universidad de La Laguna, Tenerife, Spain
| | - Ana Barabash
- Laboratory of Psychoneuroendocrinology and Genetics, Hospital Clínico San Carlos, Madrid, Spain.,Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Pedro Montejo
- Center for the Prevention of Cognitive Impairment, Public Health Institute, Madrid-Salud, Madrid, Spain
| | - Mercedes Montenegro-Peña
- Center for the Prevention of Cognitive Impairment, Public Health Institute, Madrid-Salud, Madrid, Spain
| | - Alberto Marcos
- Neurology Department, Hospital Clínico San Carlos, Madrid, Spain
| | - Ramón López-Higes
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain.,Department of Legal Medicine, Psychiatry, and Pathology, Universidad Complutense de Madrid, Madrid, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain.,Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain.,Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
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22
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Gong CX, Liu F, Iqbal K. Multifactorial Hypothesis and Multi-Targets for Alzheimer’s Disease. J Alzheimers Dis 2018; 64:S107-S117. [DOI: 10.3233/jad-179921] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Cheng-Xin Gong
- Department of Neurochemistry, Inge Grundke-Iqbal Research Floor, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY, USA
| | - Fei Liu
- Department of Neurochemistry, Inge Grundke-Iqbal Research Floor, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY, USA
| | - Khalid Iqbal
- Department of Neurochemistry, Inge Grundke-Iqbal Research Floor, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY, USA
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23
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Hampel H, Toschi N, Babiloni C, Baldacci F, Black KL, Bokde AL, Bun RS, Cacciola F, Cavedo E, Chiesa PA, Colliot O, Coman CM, Dubois B, Duggento A, Durrleman S, Ferretti MT, George N, Genthon R, Habert MO, Herholz K, Koronyo Y, Koronyo-Hamaoui M, Lamari F, Langevin T, Lehéricy S, Lorenceau J, Neri C, Nisticò R, Nyasse-Messene F, Ritchie C, Rossi S, Santarnecchi E, Sporns O, Verdooner SR, Vergallo A, Villain N, Younesi E, Garaci F, Lista S. Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology. J Alzheimers Dis 2018; 64:S47-S105. [PMID: 29562524 PMCID: PMC6008221 DOI: 10.3233/jad-179932] [Citation(s) in RCA: 95] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.
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Affiliation(s)
- Harald Hampel
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
- Department of Radiology, “Athinoula A. Martinos” Center for Biomedical Imaging, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Claudio Babiloni
- Department of Physiology and Pharmacology “Vittorio Erspamer”, University of Rome “La Sapienza”, Rome, Italy
- Institute for Research and Medical Care, IRCCS “San Raffaele Pisana”, Rome, Italy
| | - Filippo Baldacci
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Keith L. Black
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Arun L.W. Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience (TCIN), Trinity College Dublin, Dublin, Ireland
| | - René S. Bun
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Francesco Cacciola
- Unit of Neurosurgery, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - Enrica Cavedo
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
- IRCCS “San Giovanni di Dio-Fatebenefratelli”, Brescia, Italy
| | - Patrizia A. Chiesa
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Olivier Colliot
- Inserm, U1127, Paris, France; CNRS, UMR 7225 ICM, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR S 1127, Paris, France; Institut du Cerveau et de la Moelle Épinière (ICM) Paris, France; Inria, Aramis project-team, Centre de Recherche de Paris, France; Department of Neuroradiology, AP-HP, Hôpital de la Pitié-Salpêtrière, Paris, France; Department of Neurology, AP-HP, Hôpital de la Pitié-Salpêtrière, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Paris, France
| | - Cristina-Maria Coman
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Bruno Dubois
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
| | - Andrea Duggento
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
| | - Stanley Durrleman
- Inserm, U1127, Paris, France; CNRS, UMR 7225 ICM, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR S 1127, Paris, France; Institut du Cerveau et de la Moelle Épinière (ICM) Paris, France; Inria, Aramis project-team, Centre de Recherche de Paris, France
| | - Maria-Teresa Ferretti
- IREM, Institute for Regenerative Medicine, University of Zurich, Zürich, Switzerland
- ZNZ Neuroscience Center Zurich, Zürich, Switzerland
| | - Nathalie George
- Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Inserm U 1127, CNRS UMR 7225, Institut du Cerveau et de la Moelle Épinière, ICM, Ecole Normale Supérieure, ENS, Centre MEG-EEG, F-75013, Paris, France
| | - Remy Genthon
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
| | - Marie-Odile Habert
- Département de Médecine Nucléaire, Hôpital de la Pitié-Salpêtrière, AP-HP, Paris, France
- Laboratoire d’Imagerie Biomédicale, Sorbonne Universités, UPMC Univ Paris 06, Inserm U 1146, CNRS UMR 7371, Paris, France
| | - Karl Herholz
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
- Division of Informatics, Imaging and Data Sciences, University of Manchester, Wolfson Molecular Imaging Centre, Manchester, UK
| | - Yosef Koronyo
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Maya Koronyo-Hamaoui
- Department of Neurosurgery, Maxine Dunitz Neurosurgical Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Foudil Lamari
- AP-HP, UF Biochimie des Maladies Neuro-métaboliques, Service de Biochimie Métabolique, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | | | - Stéphane Lehéricy
- Centre de NeuroImagerie de Recherche - CENIR, Institut du Cerveau et de la Moelle Épinière - ICM, F-75013, Paris, France
- Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Inserm U 1127, CNRS UMR 7225, ICM, F-75013, Paris, France
| | - Jean Lorenceau
- Institut de la Vision, INSERM, Sorbonne Universités, UPMC Univ Paris 06, UMR_S968, CNRS UMR7210, Paris, France
| | - Christian Neri
- Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, CNRS UMR 8256, Institut de Biologie Paris-Seine (IBPS), Place Jussieu, F-75005, Paris, France
| | - Robert Nisticò
- Department of Biology, University of Rome “Tor Vergata” & Pharmacology of Synaptic Disease Lab, European Brain Research Institute (E.B.R.I.), Rome, Italy
| | - Francis Nyasse-Messene
- Sorbonne Université, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
| | - Craig Ritchie
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Simone Rossi
- Department of Medicine, Surgery and Neurosciences, Unit of Neurology and Clinical Neurophysiology, Brain Investigation & Neuromodulation Lab. (Si-BIN Lab.), University of Siena, Siena, Italy
- Department of Medicine, Surgery and Neurosciences, Section of Human Physiology University of Siena, Siena, Italy
| | - Emiliano Santarnecchi
- Department of Medicine, Surgery and Neurosciences, Unit of Neurology and Clinical Neurophysiology, Brain Investigation & Neuromodulation Lab. (Si-BIN Lab.), University of Siena, Siena, Italy
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- IU Network Science Institute, Indiana University, Bloomington, IN, USA
| | | | - Andrea Vergallo
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | - Nicolas Villain
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
| | | | - Francesco Garaci
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
- Casa di Cura “San Raffaele Cassino”, Cassino, Italy
| | - Simone Lista
- AXA Research Fund & Sorbonne Université Chair, Paris, France
- Sorbonne Université, AP-HP, GRC n° 21, Alzheimer Precision Medicine (APM), Hôpital de la Pitié-Salpêtrière, Boulevard de l’hôpital, F-75013, Paris, France
- Institut du Cerveau et de la Moelle Épinière (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l’hôpital, F-75013, Paris, France
- Institut de la Mémoire et de la Maladie d’Alzheimer (IM2A), Département de Neurologie, Hôpital de la Pitié-Salpêtrière, AP-HP, Boulevard de l’hôpital, F-75013, Paris, France
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