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Waschkies KF, Soch J, Darna M, Richter A, Altenstein S, Beyle A, Brosseron F, Buchholz F, Butryn M, Dobisch L, Ewers M, Fliessbach K, Gabelin T, Glanz W, Goerss D, Gref D, Janowitz D, Kilimann I, Lohse A, Munk MH, Rauchmann BS, Rostamzadeh A, Roy N, Spruth EJ, Dechent P, Heneka MT, Hetzer S, Ramirez A, Scheffler K, Buerger K, Laske C, Perneczky R, Peters O, Priller J, Schneider A, Spottke A, Teipel S, Düzel E, Jessen F, Wiltfang J, Schott BH, Kizilirmak JM. Machine learning-based classification of Alzheimer's disease and its at-risk states using personality traits, anxiety, and depression. Int J Geriatr Psychiatry 2023; 38:e6007. [PMID: 37800601 DOI: 10.1002/gps.6007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 09/07/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is often preceded by stages of cognitive impairment, namely subjective cognitive decline (SCD) and mild cognitive impairment (MCI). While cerebrospinal fluid (CSF) biomarkers are established predictors of AD, other non-invasive candidate predictors include personality traits, anxiety, and depression, among others. These predictors offer non-invasive assessment and exhibit changes during AD development and preclinical stages. METHODS In a cross-sectional design, we comparatively evaluated the predictive value of personality traits (Big Five), geriatric anxiety and depression scores, resting-state functional magnetic resonance imaging activity of the default mode network, apoliprotein E (ApoE) genotype, and CSF biomarkers (tTau, pTau181, Aβ42/40 ratio) in a multi-class support vector machine classification. Participants included 189 healthy controls (HC), 338 individuals with SCD, 132 with amnestic MCI, and 74 with mild AD from the multicenter DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE). RESULTS Mean predictive accuracy across all participant groups was highest when utilizing a combination of personality, depression, and anxiety scores. HC were best predicted by a feature set comprised of depression and anxiety scores and participants with AD were best predicted by a feature set containing CSF biomarkers. Classification of participants with SCD or aMCI was near chance level for all assessed feature sets. CONCLUSION Our results demonstrate predictive value of personality trait and state scores for AD. Importantly, CSF biomarkers, personality, depression, anxiety, and ApoE genotype show complementary value for classification of AD and its at-risk stages.
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Affiliation(s)
- Konrad F Waschkies
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Joram Soch
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Margarita Darna
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Anni Richter
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- German Center for Mental Health (DZPG), Munich, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena-Magdeburg-Halle, Germany
| | - Slawek Altenstein
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Aline Beyle
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | | | - Friederike Buchholz
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité-Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Michaela Butryn
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- University of Bonn Medical Center, Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, Bonn, Germany
| | - Tatjana Gabelin
- Charité-Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Wenzel Glanz
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Doreen Goerss
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Daria Gref
- Charité-Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Andrea Lohse
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
- Department of Neuroradiology, University Hospital LMU, Munich, Germany
| | - Ayda Rostamzadeh
- Department of Psychiatry, University of Cologne, Medical Faculty, Cologne, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Eike Jakob Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Peter Dechent
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Goettingen, Göttingen, Germany
| | - Michael T Heneka
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Alfredo Ramirez
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- University of Bonn Medical Center, Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Psychiatry & Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, Texas, USA
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
- Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité-Universitätsmedizin Berlin, Freie Universität Berlin and Humboldt-Universität zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
- School of Medicine, Technical University of Munich, Department of Psychiatry and Psychotherapy, Munich, Germany
- University of Edinburgh and UK DRI, Edinburgh, UK
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- University of Bonn Medical Center, Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, Bonn, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry, University of Cologne, Medical Faculty, Cologne, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Björn H Schott
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Jasmin M Kizilirmak
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
- Neurodidactics and NeuroLab, Institute for Psychology, University of Hildesheim, Hildesheim, Germany
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Wheelock MD, Strain JF, Mansfield P, Tu JC, Tanenbaum A, Preische O, Chhatwal JP, Cash DM, Cruchaga C, Fagan AM, Fox NC, Graff-Radford NR, Hassenstab J, Jack CR, Karch CM, Levin J, McDade EM, Perrin RJ, Schofield PR, Xiong C, Morris JC, Bateman RJ, Jucker M, Benzinger TLS, Ances BM, Eggebrecht AT, Gordon BA, Allegri R, Araki A, Barthelemy N, Bateman R, Bechara J, Benzinger T, Berman S, Bodge C, Brandon S, Brooks W, Brosch J, Buck J, Buckles V, Carter K, Cash D, Cash L, Chen C, Chhatwal J, Chrem P, Chua J, Chui H, Cruchaga C, Day GS, De La Cruz C, Denner D, Diffenbacher A, Dincer A, Donahue T, Douglas J, Duong D, Egido N, Esposito B, Fagan A, Farlow M, Feldman B, Fitzpatrick C, Flores S, Fox N, Franklin E, Friedrichsen N, Fujii H, Gardener S, Ghetti B, Goate A, Goldberg S, Goldman J, Gonzalez A, Gordon B, Gräber-Sultan S, Graff-Radford N, Graham M, Gray J, Gremminger E, Grilo M, Groves A, Haass C, Häsler L, Hassenstab J, Hellm C, Herries E, Hoechst-Swisher L, Hofmann A, Holtzman D, Hornbeck R, Igor Y, Ihara R, Ikeuchi T, Ikonomovic S, Ishii K, Jack C, Jerome G, Johnson E, Jucker M, Karch C, Käser S, Kasuga K, Keefe S, Klunk W, Koeppe R, Koudelis D, Kuder-Buletta E, Laske C, Lee JH, Levey A, Levin J, Li Y, Lopez O, Marsh J, Martinez R, Martins R, Mason NS, Masters C, Mawuenyega K, McCullough A, McDade E, Mejia A, Morenas-Rodriguez E, Mori H, Morris J, Mountz J, Mummery C, Nadkami N, Nagamatsu A, Neimeyer K, Niimi Y, Noble J, Norton J, Nuscher B, O'Connor A, Obermüller U, Patira R, Perrin R, Ping L, Preische O, Renton A, Ringman J, Salloway S, Sanchez-Valle R, Schofield P, Senda M, Seyfried N, Shady K, Shimada H, Sigurdson W, Smith J, Smith L, Snitz B, Sohrabi H, Stephens S, Taddei K, Thompson S, Vöglein J, Wang P, Wang Q, Weamer E, Xiong C, Xu J, Xu X. Brain network decoupling with increased serum neurofilament and reduced cognitive function in Alzheimer's disease. Brain 2023; 146:2928-2943. [PMID: 36625756 PMCID: PMC10316768 DOI: 10.1093/brain/awac498] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 11/21/2022] [Accepted: 12/12/2022] [Indexed: 01/11/2023] Open
Abstract
Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer's disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer's disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer's disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer's disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer's disease.
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Affiliation(s)
- Muriah D Wheelock
- Department of Radiology, Washington University in St. Louis, MO, USA
| | - Jeremy F Strain
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | | | - Jiaxin Cindy Tu
- Department of Radiology, Washington University in St. Louis, MO, USA
| | - Aaron Tanenbaum
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Oliver Preische
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - David M Cash
- Dementia Research Center, UCL Queen Square, London, UK.,UK Dementia Research Institute, College London, London, UK
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University in St. Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Nick C Fox
- Dementia Research Center, UCL Queen Square, London, UK.,UK Dementia Research Institute, College London, London, UK
| | | | - Jason Hassenstab
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | | | - Celeste M Karch
- Department of Psychiatry, Washington University in St. Louis, MO, USA
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Eric M McDade
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Richard J Perrin
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA.,Department of Pathology & Immunology, Washington University in St. Louis, MO, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia.,School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Chengjie Xiong
- Division of Biostatistics, Washington University in St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Randal J Bateman
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Mathias Jucker
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Tammie L S Benzinger
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Beau M Ances
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Adam T Eggebrecht
- Department of Radiology, Washington University in St. Louis, MO, USA
| | - Brian A Gordon
- Department of Radiology, Washington University in St. Louis, MO, USA
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Gao Y, Lewis N, Calhoun VD, Miller RL. Interpretable LSTM model reveals transiently-realized patterns of dynamic brain connectivity that predict patient deterioration or recovery from very mild cognitive impairment. Comput Biol Med 2023; 161:107005. [PMID: 37211004 PMCID: PMC10365638 DOI: 10.1016/j.compbiomed.2023.107005] [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: 12/31/2022] [Revised: 04/09/2023] [Accepted: 05/02/2023] [Indexed: 05/23/2023]
Abstract
Alzheimer's Disease (AZD) is a neurodegenerative disease for which there is now no known effective treatment. Mild cognitive impairment (MCI) is considered a precursor to AZD and affects cognitive abilities. Patients with MCI have the potential to recover cognitive health, can remain mildly cognitively impaired indefinitely or eventually progress to AZD. Identifying imaging-based predictive biomarkers for disease progression in patients presenting with evidence of very mild/questionable MCI (qMCI) can play an important role in triggering early dementia intervention. Dynamic functional network connectivity (dFNC) estimated from resting-state functional magnetic resonance imaging (rs-fMRI) has been increasingly studied in brain disorder diseases. In this work, employing a recent developed a time-attention long short-term memory (TA-LSTM) network to classify multivariate time series data. A gradient-based interpretation framework, transiently-realized event classifier activation map (TEAM) is introduced to localize the group-defining "activated" time intervals over the full time series and generate the class difference map. To test the trustworthiness of TEAM, we did a simulation study to validate the model interpretative power of TEAM. We then applied this simulation-validated framework to a well-trained TA-LSTM model which predicts the progression or recovery from questionable/mild cognitive impairment (qMCI) subjects after three years from windowless wavelet-based dFNC (WWdFNC). The FNC class difference map points to potentially important predictive dynamic biomarkers. Moreover, the more highly time-solved dFNC (WWdFNC) achieves better performance in both TA-LSTM and a multivariate CNN model than dFNC based on windowed correlations between timeseries, suggesting that better temporally resolved measures can enhance the model's performance.
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Affiliation(s)
- Yutong Gao
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA; Department of Computer Science, Georgia State University, Atlanta, GA, USA.
| | - Noah Lewis
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA; School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Robyn L Miller
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
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Liebe T, Dordevic M, Kaufmann J, Avetisyan A, Skalej M, Müller N. Investigation of the functional pathogenesis of mild cognitive impairment by localisation-based locus coeruleus resting-state fMRI. Hum Brain Mapp 2022; 43:5630-5642. [PMID: 36441846 PMCID: PMC9704796 DOI: 10.1002/hbm.26039] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 06/27/2022] [Accepted: 07/25/2022] [Indexed: 01/15/2023] Open
Abstract
Dementia as one of the most prevalent diseases urges for a better understanding of the central mechanisms responsible for clinical symptoms, and necessitates improvement of actual diagnostic capabilities. The brainstem nucleus locus coeruleus (LC) is a promising target for early diagnosis because of its early structural alterations and its relationship to the functional disturbances in the patients. In this study, we applied our improved method of localisation-based LC resting-state fMRI to investigate the differences in central sensory signal processing when comparing functional connectivity (fc) of a patient group with mild cognitive impairment (MCI, n = 28) and an age-matched healthy control group (n = 29). MCI and control participants could be differentiated in their Mini-Mental-State-Examination (MMSE) scores (p < .001) and LC intensity ratio (p = .010). In the fMRI, LC fc to anterior cingulate cortex (FDR p < .001) and left anterior insula (FDR p = .012) was elevated, and LC fc to right temporoparietal junction (rTPJ, FDR p = .012) and posterior cingulate cortex (PCC, FDR p = .021) was decreased in the patient group. Importantly, LC to rTPJ connectivity was also positively correlated to MMSE scores in MCI patients (p = .017). Furthermore, we found a hyperactivation of the left-insula salience network in the MCI patients. Our results and our proposed disease model shed new light on the functional pathogenesis of MCI by directing to attentional network disturbances, which could aid new therapeutic strategies and provide a marker for diagnosis and prediction of disease progression.
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Affiliation(s)
- Thomas Liebe
- Department of PsychiatryMedical University of ViennaViennaAustria
- Department of RadiologyUniversity Hospital JenaJenaGermany
- Department of PsychiatryUniversity Hospital JenaJenaGermany
- Clinical Affective Neuroimaging LaboratoryLeibniz Institute for NeurobiologyMagdeburgGermany
| | - Milos Dordevic
- Department of Degenerative and Chronic DiseasesUniversity PotsdamPotsdamGermany
| | - Jörn Kaufmann
- Department of NeurologyUniversity Hospital MagdeburgMagdeburgGermany
| | - Araks Avetisyan
- Neuroprotection LabGerman Center for Neurodegenerative Diseases (DZNE)MagdeburgGermany
| | - Martin Skalej
- Department of Neuroradiology, Clinic and Policlinic of RadiologyUniversity Hospital HalleHalleGermany
| | - Notger Müller
- Department of Degenerative and Chronic DiseasesUniversity PotsdamPotsdamGermany
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Yuan Q, Liang X, Xue C, Qi W, Chen S, Song Y, Wu H, Zhang X, Xiao C, Chen J. Altered anterior cingulate cortex subregional connectivity associated with cognitions for distinguishing the spectrum of pre-clinical Alzheimer's disease. Front Aging Neurosci 2022; 14:1035746. [PMID: 36570538 PMCID: PMC9768430 DOI: 10.3389/fnagi.2022.1035746] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Accepted: 11/14/2022] [Indexed: 12/12/2022] Open
Abstract
Background Subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are considered part of the early progression continuum of Alzheimer's disease (AD). The anterior cingulate cortex (ACC), a hub of information processing and regulation in the brain, plays an essential role in AD pathophysiology. In the present study, we aimed to systematically identify changes in the functional connectivity (FC) of ACC subregions in patients with SCD and aMCI and evaluate the association of these changes with cognition. Materials and methods Functional connectivity (FC) analysis of ACC sub-regions was performed among 66 patients with SCD, 71 patients with aMCI, and 78 healthy controls (HCs). Correlation analyses were performed to examine the relationship between FC of altered ACC subnetworks and cognition. Results Compared to HCs, SCD patients showed increased FC of the bilateral precuneus (PCUN) and caudal ACC, left superior frontal gyrus (SFG) and subgenual ACC, left inferior parietal lobule (IPL) and dorsal ACC, left middle occipital gyrus (MOG) and dorsal ACC, and left middle temporal gyrus (MTG) and subgenual ACC, while aMCI patients showed increased FC of the left inferior frontal gyrus (IFG) and dorsal ACC and left medial frontal gyrus (MFG) and subgenual ACC. Compared to patients with SCD, patients with aMCI showed increased FC of the right MFG and dorsal ACC and left ACC and subgenual ACC, while the left posterior cingulate cortex (PCC) showed decreased FC with the caudal ACC. Moreover, some FC values among the altered ACC subnetworks were significantly correlated with episodic memory and executive function. Conclusion SCD and aMCI, part of the spectrum of pre-clinical AD, share some convergent and divergent altered intrinsic connectivity of ACC subregions. These results may serve as neuroimaging biomarkers of the preclinical phase of AD and provide new insights into the design of preclinical interventions.
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Affiliation(s)
- Qianqian Yuan
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xuhong Liang
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chen Xue
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Wenzhang Qi
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Shanshan Chen
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yu Song
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Huimin Wu
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xulian Zhang
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chaoyong Xiao
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China,*Correspondence: Chaoyong Xiao,
| | - Jiu Chen
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China,Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China,Medical Imaging Center, The Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China,Jiu Chen,
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González-López M, Gonzalez-Moreira E, Areces-González A, Paz-Linares D, Fernández T. Who's driving? The default mode network in healthy elderly individuals at risk of cognitive decline. Front Neurol 2022; 13:1009574. [DOI: 10.3389/fneur.2022.1009574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 11/08/2022] [Indexed: 12/02/2022] Open
Abstract
IntroductionAge is the main risk factor for the development of neurocognitive disorders, with Alzheimer's disease being the most common. Its physiopathological features may develop decades before the onset of clinical symptoms. Quantitative electroencephalography (qEEG) is a promising and cost-effective tool for the prediction of cognitive decline in healthy older individuals that exhibit an excess of theta activity. The aim of the present study was to evaluate the feasibility of brain connectivity variable resolution electromagnetic tomography (BC-VARETA), a novel source localization algorithm, as a potential tool to assess brain connectivity with 19-channel recordings, which are common in clinical practice.MethodsWe explored differences in terms of functional connectivity among the nodes of the default mode network between two groups of healthy older participants, one of which exhibited an EEG marker of risk for cognitive decline.ResultsThe risk group exhibited increased levels of delta, theta, and beta functional connectivity among nodes of the default mode network, as well as reversed directionality patterns of connectivity among nodes in every frequency band when compared to the control group.DiscussionWe propose that an ongoing pathological process may be underway in healthy elderly individuals with excess theta activity in their EEGs, which is further evidenced by changes in their connectivity patterns. BC-VARETA implemented on 19-channels EEG recordings appears to be a promising tool to detect dysfunctions at the connectivity level in clinical settings.
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7
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Zhu JD, Huang CW, Chang HI, Tsai SJ, Huang SH, Hsu SW, Lee CC, Chen HJ, Chang CC, Yang AC. Functional MRI and ApoE4 genotype for predicting cognitive decline in amyloid-positive individuals. Ther Adv Neurol Disord 2022; 15:17562864221138154. [DOI: 10.1177/17562864221138154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 10/24/2022] [Indexed: 11/21/2022] Open
Abstract
Background: In light of advancements in machine learning techniques, many studies have implemented machine learning approaches combined with data measures to predict and classify Alzheimer’s disease. Studies that predicted cognitive status with longitudinal follow-up of amyloid-positive individuals remain scarce, however. Objective: We developed models based on voxel-wise functional connectivity (FC) density mapping and the presence of the ApoE4 genotype to predict whether amyloid-positive individuals would experience cognitive decline after 1 year. Methods: We divided 122 participants into cognitive decline and stable cognition groups based on the participants’ change rates in Mini-Mental State Examination scores. In addition, we included 68 participants from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database as an external validation data set. Subsequently, we developed two classification models: the first model included 99 voxels, and the second model included 99 voxels and the ApoE4 genotype as features to train the models by Wide Neural Network algorithm with fivefold cross-validation and to predict the classes in the hold-out test and ADNI data sets. Results: The results revealed that both models demonstrated high accuracy in classifying the two groups in the hold-out test data set. The model for FC demonstrated good performance, with a mean F1-score of 0.86. The model for FC combined with the ApoE4 genotype achieved superior performance, with a mean F1-score of 0.90. In the ADNI data set, the two models demonstrated stable performances, with mean F1-scores of 0.77 in the first and second models. Conclusion: Our findings suggest that the proposed models exhibited promising accuracy for predicting cognitive status after 1 year in amyloid-positive individuals. Notably, the combination of FC and the ApoE4 genotype increased prediction accuracy. These findings can assist clinicians in predicting changes in cognitive status in individuals with a high risk of Alzheimer’s disease and can assist future studies in developing precise treatment and prevention strategies.
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Affiliation(s)
- Jun-Ding Zhu
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chi-Wei Huang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Hsin-I Chang
- Department of Neurology, Cognition and Aging Center, Institute for Translational Research in Biomedicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Shih-Jen Tsai
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Division of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shu-Hua Huang
- Department of Nuclear Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Shih-Wei Hsu
- Department of NeuroRadiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chen-Chang Lee
- Department of NeuroRadiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Hong-Jie Chen
- Department of Nuclear Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chiung-Chih Chang
- Cognition and Aging Center, Institute for Translational Research in Biomedicine, Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, No. 123 Ta-Pei Road, Niau-Sung District, Kaohsiung 833, Taiwan
| | - Albert C. Yang
- Institute of Brain Science/Digital Medicine and Smart Healthcare Research Center, National Yang Ming Chiao Tung University, No. 155, Sec. 2, Linong Street, Beitou District, Taipei 112, Taiwan
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
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8
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Yuan Q, Qi W, Xue C, Ge H, Hu G, Chen S, Xu W, Song Y, Zhang X, Xiao C, Chen J. Convergent Functional Changes of Default Mode Network in Mild Cognitive Impairment Using Activation Likelihood Estimation. Front Aging Neurosci 2021; 13:708687. [PMID: 34675797 PMCID: PMC8525543 DOI: 10.3389/fnagi.2021.708687] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 08/30/2021] [Indexed: 12/13/2022] Open
Abstract
Background: Mild cognitive impairment (MCI) represents a transitional state between normal aging and dementia disorders, especially Alzheimer's disease (AD). The disruption of the default mode network (DMN) is often considered to be a potential biomarker for the progression from MCI to AD. The purpose of this study was to assess MRI-specific changes of DMN in MCI patients by elucidating the convergence of brain regions with abnormal DMN function. Methods: We systematically searched PubMed, Ovid, and Web of science for relevant articles. We identified neuroimaging studies by using amplitude of low frequency fluctuation /fractional amplitude of low frequency fluctuation (ALFF/fALFF), regional homogeneity (ReHo), and functional connectivity (FC) in MCI patients. Based on the activation likelihood estimation (ALE) algorithm, we carried out connectivity modeling of coordination-based meta-analysis and functional meta-analysis. Results: In total, this meta-analysis includes 39 articles on functional neuroimaging studies. Using computer software analysis, we discovered that DMN changes in patients with MCI mainly occur in bilateral inferior frontal lobe, right medial frontal lobe, left inferior parietal lobe, bilateral precuneus, bilateral temporal lobe, and parahippocampal gyrus (PHG). Conclusions: Herein, we confirmed the presence of DMN-specific damage in MCI, which is helpful in revealing pathology of MCI and further explore mechanisms of conversion from MCI to AD. Therefore, we provide a new specific target and direction for delaying conversion from MCI to AD.
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Affiliation(s)
- Qianqian Yuan
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Wenzhang Qi
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chen Xue
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Honglin Ge
- Department of Neurosurgery, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Guanjie Hu
- Department of Neurosurgery, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Shanshan Chen
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Wenwen Xu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yu Song
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - XuLian Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chaoyong Xiao
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Department of Neurosurgery, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China
| | - Jiu Chen
- Department of Neurosurgery, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China.,Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
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9
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Zhang J, Xu D, Cui H, Zhao T, Chu C, Wang J. Group-guided individual functional parcellation of the hippocampus and application to normal aging. Hum Brain Mapp 2021; 42:5973-5984. [PMID: 34529323 PMCID: PMC8596973 DOI: 10.1002/hbm.25662] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/18/2021] [Accepted: 09/04/2021] [Indexed: 02/01/2023] Open
Abstract
Aging is closely associated with cognitive decline affecting attention, memory and executive functions. The hippocampus is the core brain area for human memory, learning, and cognition processing. To delineate the individual functional patterns of hippocampus is pivotal to reveal the neural basis of aging. In this study, we developed a group‐guided individual parcellation approach based on semisupervised affinity propagation clustering using the resting‐state functional magnetic resonance imaging to identify individual functional subregions of hippocampus and to identify the functional patterns of each subregion during aging. A three‐way group parcellation was yielded and was taken as prior information to guide individual parcellation of hippocampus into head, body, and tail in each subject. The superiority of individual parcellation of hippocampus is validated by higher intraregional functional similarities by compared to group‐level parcellation results. The individual variations of hippocampus were associated with coactivation patterns of three typical functions of hippocampus. Moreover, the individual functional connectivities of hippocampus subregions with predefined target regions could better predict age than group‐level functional connectivities. Our study provides a novel framework for individual brain functional parcellations, which may facilitate the future individual researches for brain cognitions and brain disorders and directing accurate neuromodulation.
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Affiliation(s)
- Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Dundi Xu
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Hongjie Cui
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Tianyu Zhao
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Congying Chu
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
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10
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Michaelian JC, Duffy SL, Mowszowski L, Guastella AJ, McCade D, McKinnon AC, Naismith SL. Poorer Theory of Mind in Amnestic Mild Cognitive Impairment Is Associated with Decreased Functional Connectivity in the Default Mode Network. J Alzheimers Dis 2021; 81:1079-1091. [PMID: 33843670 DOI: 10.3233/jad-201284] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Older adults living with amnestic mild cognitive impairment (aMCI) not only demonstrate impairments in Theory of Mind (ToM), relative to adults with non-amnestic MCI (naMCI), but are also at a higher risk of developing dementia. OBJECTIVE Our primary objective was to ascertain whether default mode network (DMN) functional connectivity was differentially associated with ToM abilities between MCI subgroups. METHODS Using functional magnetic resonance imaging, we investigated alterations in resting-state functional connectivity within the brain's DMN in a sample of 43 older adults with aMCI (n = 19) and naMCI (n = 24), previously reported to demonstrate poorer ToM abilities. RESULTS Compared to naMCI, the aMCI subgroup revealed a significant association between poorer ToM performance and reduced functional connectivity between the bilateral temporal pole (TempP) and the left lateral temporal cortex (LTC) (LTC_L-TempP_L: b = -0.06, t(33) = -3.53, p = 0.02; LTC_L-TempP_R: b = -0.07,t(33) = -3.20, p = 0.03); between the right TempP and the dorsal medial prefrontal cortex (dMPFC) (b = -0.04, t(33) = -3.02, p = 0.03) and between the left and right TempP (b = -0.05, t(33) = -3.26, p = 0.03). In the naMCI subgroup, the opposite relationship was present between the bilateral TempP and the left LTC (Combined correlation: r = -0.47, p = 0.02), however, not between the right TempP and the dMPFC (r = -0.14, p = 0.51) or the left and right TempP (r = -0.31, p = 0.14). CONCLUSION Our findings suggest that alterations in functional connectivity within the DMN involving temporal and frontal lobe regions are associated with ToM deficits in aMCI.
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Affiliation(s)
- Johannes C Michaelian
- School of Psychology, University of Sydney, Sydney, Australia.,Healthy Brain Ageing Program, Brain and Mind Centre, University of Sydney, Sydney, Australia.,Brain and Mind Centre, University of Sydney, Sydney, Australia.,Charles Perkins Centre, University of Sydney, Sydney, Australia
| | - Shantel L Duffy
- Healthy Brain Ageing Program, Brain and Mind Centre, University of Sydney, Sydney, Australia.,Charles Perkins Centre, University of Sydney, Sydney, Australia.,School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Loren Mowszowski
- School of Psychology, University of Sydney, Sydney, Australia.,Healthy Brain Ageing Program, Brain and Mind Centre, University of Sydney, Sydney, Australia.,Brain and Mind Centre, University of Sydney, Sydney, Australia.,Charles Perkins Centre, University of Sydney, Sydney, Australia
| | - Adam J Guastella
- Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Donna McCade
- Healthy Brain Ageing Program, Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Andrew C McKinnon
- School of Psychology, University of Sydney, Sydney, Australia.,Healthy Brain Ageing Program, Brain and Mind Centre, University of Sydney, Sydney, Australia.,Brain and Mind Centre, University of Sydney, Sydney, Australia.,Charles Perkins Centre, University of Sydney, Sydney, Australia
| | - Sharon L Naismith
- School of Psychology, University of Sydney, Sydney, Australia.,Healthy Brain Ageing Program, Brain and Mind Centre, University of Sydney, Sydney, Australia.,Brain and Mind Centre, University of Sydney, Sydney, Australia.,Charles Perkins Centre, University of Sydney, Sydney, Australia
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11
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Ibrahim B, Suppiah S, Ibrahim N, Mohamad M, Hassan HA, Nasser NS, Saripan MI. Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review. Hum Brain Mapp 2021; 42:2941-2968. [PMID: 33942449 PMCID: PMC8127155 DOI: 10.1002/hbm.25369] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 12/20/2022] Open
Abstract
Resting‐state fMRI (rs‐fMRI) detects functional connectivity (FC) abnormalities that occur in the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC of the default mode network (DMN) is commonly impaired in AD and MCI. We conducted a systematic review aimed at determining the diagnostic power of rs‐fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. Multiple kernel approach can be utilized to aid in the classification by incorporating various discriminating features, such as FC graphs based on “nodes” and “edges” together with structural MRI‐based regional cortical thickness and gray matter volume. Other multimodal features include neuropsychiatric testing scores, DTI features, and regional cerebral blood flow. Among AD patients, the posterior cingulate cortex (PCC)/Precuneus was noted to be a highly affected hub of the DMN that demonstrated overall reduced FC. Whereas reduced DMN FC between the PCC and anterior cingulate cortex (ACC) was observed in MCI patients. Evidence indicates that the nodes of the DMN can offer moderate to high diagnostic power to distinguish AD and MCI patients. Nevertheless, various concerns over the homogeneity of data based on patient selection, scanner effects, and the variable usage of classifiers and algorithms pose a challenge for ML‐based image interpretation of rs‐fMRI datasets to become a mainstream option for diagnosing AD and predicting the conversion of HC/MCI to AD.
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Affiliation(s)
- Buhari Ibrahim
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.,Department of Physiology, Faculty of Basic Medical Sciences, Bauchi State University Gadau, Gadau, Nigeria
| | - Subapriya Suppiah
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Normala Ibrahim
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Mazlyfarina Mohamad
- Centre for Diagnostic and Applied Health Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Hasyma Abu Hassan
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Nisha Syed Nasser
- Department of Radiology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - M Iqbal Saripan
- Department of Computer and Communication System Engineering, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
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12
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Zhou J, Li K, Luo X, Zeng Q, Jiaerken Y, Wang S, Xu X, Liu X, Li Z, Zhang T, Fu Y, Zhao S, Huang P, Zhang M. Distinct impaired patterns of intrinsic functional network centrality in patients with early- and late-onset Alzheimer's disease. Brain Imaging Behav 2021; 15:2661-2670. [PMID: 33844192 DOI: 10.1007/s11682-021-00470-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 03/04/2021] [Indexed: 10/21/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) involves multiple cognitive domains and shows more rapid progression than late-onset Alzheimer's disease (LOAD). However, the difference in pathogenesis between EOAD and LOAD is still unclear. Accordingly, we applied intrinsic network analysis to explore the potential neuropathological mechanism underlying distinct clinical phenotypes. According to the cut-off age of 65, we included 20 EOAD patients, 20 LOAD patients, and 36 age-matched controls (19 young and 17 old controls). We employed resting-state functional MRI and network centrality analysis to explore the local (degree centrality (DC)) and global (eigenvector centrality (EC)) functional integrity. Two-sample t-test analysis was performed, with gray matter volume, age, gender, and education as covariates. Furthermore, we performed a correlation analysis between network metrics and cognition. Compared to young controls, EOAD patients exhibited lower DC in the middle temporal gyrus (MTG), parahippocampal gyrus (PHG), superior temporal gyrus (STG), and lower EC in the MTG, PHG, and postcentral gyrus. In contrast, LOAD patients exhibited lower DC in the STG and anterior cingulum gyrus and higher DC in the middle frontal gyrus compared to old controls. No significant difference in EC was observed in LOAD patients. Furthermore, both DC and EC correlated with cognitive performance. Our study demonstrated divergent functional network impairments in EOAD and LOAD patients. EOAD patients showed more complex network damage involving both local and global centrality properties, while LOAD patients mainly featured local functional connectivity changes. Such centrality impairments are related to poor cognition, especially regarding memory performance.
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Affiliation(s)
- Jiong Zhou
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Xiao Luo
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Qingze Zeng
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Yerfan Jiaerken
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Shuyue Wang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Xiaopei Xu
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Xiaocao Liu
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China
| | - Zheyu Li
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Tianyi Zhang
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yanv Fu
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuai Zhao
- Department of Neurology, 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China.
| | - Minming Zhang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, No.88 Jie-fang Road, Shang-cheng District, Hangzhou, 310009, China.
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13
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Cao Y, Yang H, Zhou Z, Cheng Z, Zhao X. Abnormal Default-Mode Network Homogeneity in Patients With Mild Cognitive Impairment in Chinese Communities. Front Neurol 2021; 11:569806. [PMID: 33643176 PMCID: PMC7905225 DOI: 10.3389/fneur.2020.569806] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 12/23/2020] [Indexed: 11/15/2022] Open
Abstract
Background and Objective: Current evidence suggests that abnormalities within the default-mode network (DMN) play a key role in the broad-scale cognitive problems that characterize mild cognitive impairment (MCI). However, little is known about the alterations of DMN network homogeneity (NH) in MCI. Methods: Resting-state functional magnetic resonance imaging scans (rs-fMRI) were collected from 38 MCI patients and 69 healthy controls matched for age, gender, and education. NH approach was employed to analyze the imaging dataset. Cognitive performance was measured with the Chinese version of Alzheimer's disease assessment scale-Cognitive subscale (ADAS-Cog). Results: Two groups have no significant differences between demographic factors. And mean ADAS-Cog score in MCI was 12.02. MCI patients had significantly lower NH values than controls in the right anterior cingulate cortex and significantly higher NH values in the ventral medial prefrontal cortex(vmPFC) than those in healthy controls. No significant correlations were found between abnormal NH values and ADAS-Cog in the patients. Conclusions: These findings provide further evidence that abnormal NH of the DMN exists in MCI, and highlight the significance of DMN in the pathophysiology of cognitive problems occurring in MCI.
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Affiliation(s)
- Yuping Cao
- Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders, Changsha, China.,China National Technology Institute on Mental Disorders, Changsha, China.,Hunan Technology Institute of Psychiatry, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Huan Yang
- Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders, Changsha, China.,China National Technology Institute on Mental Disorders, Changsha, China.,Hunan Technology Institute of Psychiatry, Changsha, China.,Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zhenhe Zhou
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Zaohuo Cheng
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Xingfu Zhao
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
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14
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Abnormal cortical regions and subsystems in whole brain functional connectivity of mild cognitive impairment and Alzheimer's disease: a preliminary study. Aging Clin Exp Res 2021; 33:367-381. [PMID: 32277436 DOI: 10.1007/s40520-020-01539-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Accepted: 03/24/2020] [Indexed: 12/12/2022]
Abstract
The disease roots of Alzheimer's disease (AD) are unknown. Functional connection (FC) methodology based on functional MRI data is an effective lever to investigate macroscopic neural activity patterns. However, regional properties of brain architecture have been less investigated by special markers of graph indexes in general mental disorders. In terms of the set of the abnormal edges in the FCs matrix, this paper introduces the strength index (S-scores) of region centrality on the principle of holism. Then, the important process is to investigate the S-scores of regions and subsystems in 36 healthy controls, 38 mild cognitive impairment (MCI) patients and 34 AD patients. At the edge level, abnormal FCs is numerically increasing progressively from MCI to AD brains. At the region level, the CUN.L, PAL.R, THA.L, and TPOsup.R regions are highlighted with abnormal S-scores in MCI patients. By comparison, more regions are abnormal in AD patients, which are PreCG.L, INS.R, DCG.L, AMYG.R, IOG.R, FFG.L, PoCG.L, PCUN.R, TPOsup.L, MTG.L, and TPOmid.L. Importantly, the regions in DMN have abnormal S-scores in AD groups. At the module level, the S-scores of frontal, parietal, occipital lobe, and cerebellum are found in MCI and AD patients. Meanwhile, the abnormal lateralization is inferred because of the S-scores of left and top hemisphere in the AD group. Though this is strictly a contrastive study, the S-score may be a meaningful imaging marker for excavating AD psychopathology.
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15
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Ruden JB, Dugan LL, Konradi C. Parvalbumin interneuron vulnerability and brain disorders. Neuropsychopharmacology 2021; 46:279-287. [PMID: 32722660 PMCID: PMC7852528 DOI: 10.1038/s41386-020-0778-9] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 07/02/2020] [Accepted: 07/21/2020] [Indexed: 12/31/2022]
Abstract
Parvalbumin-expressing interneurons (PV-INs) are highly vulnerable to stressors and have been implicated in many neuro-psychiatric diseases such as schizophrenia, Alzheimer's disease, autism spectrum disorder, and bipolar disorder. We examined the literature about the current knowledge of the physiological properties of PV-INs and gathered results from diverse research areas to provide insight into their vulnerability to stressors. Among the factors that confer heightened vulnerability are the substantial energy requirements, a strong excitatory drive, and a unique developmental trajectory. Understanding these stressors and elaborating on their impact on PV-IN health is a step toward developing therapies to protect these neurons in various disease states and to retain critical brain functions.
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Affiliation(s)
- Jacob B Ruden
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Laura L Dugan
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Division of Geriatric Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christine Konradi
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA.
- Department of Pharmacology, Vanderbilt University, Nashville, TN, USA.
- Department of Psychiatry, Vanderbilt University, Nashville, TN, USA.
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Wang L, Feng Q, Wang M, Zhu T, Yu E, Niu J, Ge X, Mao D, Lv Y, Ding Z. An Effective Brain Imaging Biomarker for AD and aMCI: ALFF in Slow-5 Frequency Band. Curr Alzheimer Res 2021; 18:45-55. [PMID: 33761855 DOI: 10.2174/1567205018666210324130502] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 01/13/2021] [Accepted: 03/17/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND As a potential brain imaging biomarker, amplitude of low frequency fluctuation (ALFF) has been used as a feature to distinguish patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) from normal controls (NC). However, it remains unclear whether the frequency-dependent pattern of ALFF alterations can effectively distinguish the different phases of the disease. METHODS In the present study, 52 AD and 50 aMCI patients were enrolled together with 43 NC in total. The ALFF values were calculated in the following three frequency bands: classical (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) for the three different groups. Subsequently, the local functional abnormalities were employed as features to examine the effect of classification among AD, aMCI and NC using a support vector machine (SVM). RESULTS We found that the among-group differences of ALFF in the different frequency bands were mainly located in the left hippocampus (HP), right HP, bilateral posterior cingulate cortex (PCC) and bilateral precuneus (PCu), left angular gyrus (AG) and left medial prefrontal cortex (mPFC). When the local functional abnormalities were employed as features, we identified that the ALFF in the slow-5 frequency band showed the highest accuracy to distinguish among the three groups. CONCLUSION These findings may deepen our understanding of the pathogenesis of AD and suggest that slow-5 frequency band may be helpful to explore the pathogenesis and distinguish the phases of this disease.
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Affiliation(s)
- Luoyu Wang
- Centre for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang,China
| | - Qi Feng
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang,China
| | - Mei Wang
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang,China
| | - Tingting Zhu
- Centre for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang,China
| | - Enyan Yu
- Cancer Hospital of the University of Chinese Academy of Sciences, Hangzhou, Zhejiang,China
| | - Jialing Niu
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang,China
| | - Xiuhong Ge
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang,China
| | - Dewang Mao
- Department of Radiology, Zhejiang Provincial People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang,China
| | - Yating Lv
- Centre for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang,China
| | - Zhongxiang Ding
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang,China
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17
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Eyler LT, Elman JA, Hatton SN, Gough S, Mischel AK, Hagler DJ, Franz CE, Docherty A, Fennema-Notestine C, Gillespie N, Gustavson D, Lyons MJ, Neale MC, Panizzon MS, Dale AM, Kremen WS. Resting State Abnormalities of the Default Mode Network in Mild Cognitive Impairment: A Systematic Review and Meta-Analysis. J Alzheimers Dis 2020; 70:107-120. [PMID: 31177210 DOI: 10.3233/jad-180847] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Large-scale brain networks such as the default mode network (DMN) are often disrupted in Alzheimer's disease (AD). Numerous studies have examined DMN functional connectivity in those with mild cognitive impairment (MCI), a presumed AD precursor, to discover a biomarker of AD risk. Prior reviews were qualitative or limited in scope or approach. OBJECTIVE We aimed to systematically and quantitatively review DMN resting state fMRI studies comparing MCI and healthy comparison (HC) groups. METHODS PubMed was searched for relevant articles. Study characteristics were abstracted and the number of studies showing no group difference or hyper- versus hypo-connnectivity in MCI was tallied. A voxel-wise (ES-SDM) meta-analysis was conducted to identify regional group differences. RESULTS Qualitatively, our review of 57 MCI versus HC comparisons suggests substantial inconsistency; 9 showed no group difference, 8 showed MCI > HC and 22 showed HC > MCI across the brain, and 18 showed regionally-mixed directions of effect. The meta-analysis of 31 studies revealed areas of significant hypo- and hyper-connectivity in MCI, including hypoconnectivity in the posterior cingulate cortex/precuneus (z = -3.1, p < 0.0001). Very few individual studies, however, showed patterns resembling the meta-analytic results. Methodological differences did not appear to explain inconsistencies. CONCLUSIONS The pattern of altered resting DMN function or connectivity in MCI is complex and variable across studies. To date, no index of DMN connectivity qualifies as a useful biomarker of MCI or risk for AD. Refinements to MCI diagnosis, including other biological markers, or longitudinal studies of progression to AD, might identify DMN alterations predictive of AD risk.
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Affiliation(s)
- Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA.,Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Sean N Hatton
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA.,Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - Sarah Gough
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Anna K Mischel
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Anna Docherty
- Departments of Psychiatry & Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA.,Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Nathan Gillespie
- Departments of Psychiatry and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Daniel Gustavson
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Michael J Lyons
- Department of Psychology, Boston University, Boston, MA, USA
| | - Michael C Neale
- Departments of Psychiatry and Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Anders M Dale
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA.,Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA.,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
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18
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Intrinsic functional connectivity, CSF biomarker profiles and their relation to cognitive function in mild cognitive impairment. Acta Neuropsychiatr 2020; 32:206-213. [PMID: 31801648 DOI: 10.1017/neu.2019.49] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Mild cognitive impairment (MCI) often precedes Alzheimer's Dementia (AD), and in a high proportion of individuals affected by MCI, there are already neuropathological processes ongoing that become more evident when patients progress to AD. Accordingly, there is a need for reliable biomarkers to distinguish between normal aging and incipient AD. Recent research suggests that, in addition to established biomarkers such as CSF Aß42, total tau and hyperphosphorylated tau, resting state connectivity established by functional magnetic resonance imaging might also be a feasible biomarker for prodromal stages of AD. In order to explore this possibility, we investigated resting state functional connectivity as well as cerebrospinal fluid (CSF) biomarker profiles in patients with MCI (n = 30; age 66.43 ± 7.06 years) and cognitively healthy controls (n = 38; age 66.89 ± 7.12 years). CSF Aß42, total tau and hyperphosphorylated tau concentrations were correlated with measures of cognitive performance (immediate and delayed recall, global cognition, processing speed). Moreover, MCI-related alterations in intrinsic functional connectivity within the default mode network were investigated using functional resting state MRI. As expected, MCI patients showed decreased CSF Aß42 and increased total tau concentrations. These alterations were associated with cognitive performance. However, there were no differences between MCI patients and cognitively healthy controls regarding intrinsic functional connectivity. In conclusion, our results indicate that CSF protein profiles seem to be more closely related to cognitive decline than alterations in resting state activity. Thus, resting state connectivity might not be a reliable biomarker for early stages of AD.
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19
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Liu T, Bai Y, Ma L, Ma X, Wei W, Zhang J, Roberts N, Wang M. Altered Effective Connectivity of Bilateral Hippocampus in Type 2 Diabetes Mellitus. Front Neurosci 2020; 14:657. [PMID: 32655364 PMCID: PMC7325692 DOI: 10.3389/fnins.2020.00657] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 05/27/2020] [Indexed: 02/05/2023] Open
Abstract
Patients with type 2 diabetes mellitus (T2DM) experience cognitive deficits but the underlying pathophysiologic mechanisms are not known. We therefore applied Granger causality analysis of resting-state functional magnetic resonance imaging to study the effective connectivity (EC) of the hippocampus in patients with T2DM. Eighty six patients with T2DM and 84 matched healthy controls (HC) were recruited. The directional EC between anatomically defined seeds in left hippocampus (LHIP) and right hippocampus (RHIP) and other brain regions was compared between T2DM and HC and Pearson correlation analysis was performed to determine whether alterations in EC were related to clinical characteristics of diabetes. Compared with HC, patients with T2DM had altered EC between LHIP and RHIP and the default mode network (DMN), occipital cortex and cerebellum. In addition, for LHIP only duration of diabetes positively correlated with decreased inflow from right postcentral gyrus and right parietal lobe, glycosylated hemoglobin (HbA1c) negatively correlated with decreased inflow from right thalamus (r = -0.255, p = 0.018) and Montreal Cognitive Assessment (MoCA) negatively correlated with decreased inflow from left inferior parietal lobe (r = -0.206, p = 0.05). The altered EC between hippocampus and DMN is interpreted to be related to cognitive deficits in patients with T2DM particularly affecting memory and learning.
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Affiliation(s)
- Taiyuan Liu
- Henan Key Laboratory of Neurological Imaging, Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Yan Bai
- Henan Key Laboratory of Neurological Imaging, Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Lun Ma
- Henan Key Laboratory of Neurological Imaging, Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Xiaoyue Ma
- Henan Key Laboratory of Neurological Imaging, Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Wei Wei
- Henan Key Laboratory of Neurological Imaging, Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Junran Zhang
- Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Neil Roberts
- The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Meiyun Wang
- Henan Key Laboratory of Neurological Imaging, Department of Medical Imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
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20
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Cai C, Huang C, Yang C, Lu H, Hong X, Ren F, Hong D, Ng E. Altered Patterns of Functional Connectivity and Causal Connectivity in Salience Subnetwork of Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment. Front Neurosci 2020; 14:288. [PMID: 32390791 PMCID: PMC7189119 DOI: 10.3389/fnins.2020.00288] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/12/2020] [Indexed: 12/22/2022] Open
Abstract
The subjective cognitive decline (SCD) may last for decades prior to the onset of dementia and has been proposed as a risk population for development to amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD). Disruptions of functional connectivity and causal connectivity (CC) in the salience network (SN) are generally perceived as prominent hallmarks of the preclinical AD. Nevertheless, the alterations in anterior SN (aSN), and posterior SN (pSN) remain unclear. Here, we hypothesized that both the functional connectivity (FC) and CC of the SN subnetworks, comprising aSN and pSN, were distinct disruptive in the SCD and aMCI. We utilized resting-state functional magnetic resonance imaging to investigate the altered FC and CC of the SN subnetworks in 28 healthy controls, 23 SCD subjects, and 29 aMCI subjects. In terms of altered patterns of FC in SN subnetworks, aSN connected to the whole brain was significantly increased in the left orbital superior frontal gyrus, left insula lobule, right caudate lobule, and left rolandic operculum gyrus (ROG), whereas decreased FC was found in the left cerebellum superior lobule and left middle temporal gyrus when compared with the HC group. Notably, no prominent statistical differences were obtained in pSN. For altered patterns of CC in SN subnetworks, compared to the HC group, the aberrant connections in aMCI group were separately involved in the right cerebellum inferior lobule (CIL), right supplementary motor area (SMA), and left ROG, whereas the SCD group exhibited more regions of aberrant connection, comprising the right superior parietal lobule, right CIL, left inferior parietal lobule, left post-central gyrus (PG), and right angular gyrus. Especially, SCD group showed increased CC in the right CIL and left PG, whereas the aMCI group showed decreased CC in the left pre-cuneus, corpus callosum, and right SMA when compared to the SCD group. Collectively, our results suggest that analyzing the altered FC and CC observed in SN subnetworks, served as impressible neuroimaging biomarkers, may supply novel insights for designing preclinical interventions in the preclinical stages of AD.
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Affiliation(s)
- Chunting Cai
- School of Informatics, Xiamen University, Xiamen, China
| | - Chenxi Huang
- School of Informatics, Xiamen University, Xiamen, China
| | - Chenhui Yang
- School of Informatics, Xiamen University, Xiamen, China
| | - Haijie Lu
- Department of Radiation Oncology, Zhongshan Hospital of Xiamen University, Xiamen, China
| | - Xin Hong
- School of Informatics, Xiamen University, Xiamen, China.,College of Computer Science and Technology, Huaqiao University, Xiamen, China
| | - Fujia Ren
- School of Informatics, Xiamen University, Xiamen, China
| | - Dan Hong
- School of Informatics, Xiamen University, Xiamen, China
| | - Eyk Ng
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore
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21
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The Long-Term Effects of Acupuncture on Hippocampal Functional Connectivity in aMCI with Hippocampal Atrophy: A Randomized Longitudinal fMRI Study. Neural Plast 2020. [DOI: 10.1155/2020/6389368] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Background. Acupuncture has been used to treat amnestic mild cognitive impairment (aMCI) for many years in China. However, the long-term effects of continuous acupuncture treatment remained unclear. Objective. We aimed to explore the long-term effects of continuous acupuncture treatment on hippocampal functional connectivity (FC) in aMCI. Methods. Fifty healthy control (HC) participants and 28 aMCI patients were recruited for resting-state functional magnetic resonance imaging (fMRI) at baseline. The 28 aMCI patients were then divided into the aMCI acupuncture group, which received acupuncture treatment for 6 months, and the aMCI control group, which received no intervention. All aMCI patients completed the second resting-state fMRI scanning after 6 months of acupuncture treatment. Analysis based on the region of interest and two-way analysis of covariance were both used to explore the long-term effects of acupuncture on cognition change and hippocampal FC in aMCI. Results. Compared to HC, aMCI showed decreased right hippocampal FC with the right inferior/middle temporal gyrus (ITG/MTG), left amygdala, and the right fusiform and increased FC with bilateral caudates at baseline. After acupuncture treatment, the right hippocampal FC with right ITG/MTG enhanced significantly in the aMCI acupuncture group, but continued to decrease in the aMCI control group. Whole brain FC analysis showed enhanced right hippocampal FC with the right ITG and the left MTG in the aMCI acupuncture group relative to the aMCI control group. Furthermore, FC strength of the right hippocampus with right ITG at baseline was negatively correlated with the changes in memory scores of aMCI acupuncture patients. Conclusion. Acupuncture treatment could alleviate the progression of cognitive decline and could enhance hippocampal FC with ITG and MTG in aMCI that may be associated with resilience to resistant against neurodegeneration. The findings provided a better understanding of the long-term effects of acupuncture treatment and confirmed the therapeutic role of acupuncture in aMCI.
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22
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Xue C, Yuan B, Yue Y, Xu J, Wang S, Wu M, Ji N, Zhou X, Zhao Y, Rao J, Yang W, Xiao C, Chen J. Distinct Disruptive Patterns of Default Mode Subnetwork Connectivity Across the Spectrum of Preclinical Alzheimer's Disease. Front Aging Neurosci 2019; 11:307. [PMID: 31798440 PMCID: PMC6863958 DOI: 10.3389/fnagi.2019.00307] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 10/25/2019] [Indexed: 12/28/2022] Open
Abstract
Background: The early progression continuum of Alzheimer’s disease (AD) has been considered to advance through subjective cognitive decline (SCD), non-amnestic mild cognitive impairment (naMCI), and amnestic mild cognitive impairment (aMCI). Altered functional connectivity (FC) in the default mode network (DMN) is regarded as a hallmark of AD. Furthermore, the DMN can be divided into two subnetworks, the anterior and posterior subnetworks. However, little is known about distinct disruptive patterns in the subsystems of the DMN across the preclinical AD spectrum. This study investigated the connectivity patterns of anterior DMN (aDMN) and posterior DMN (pDMN) across the preclinical AD spectrum. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the FC in the DMN subnetworks in 20 healthy controls (HC), eight SCD, 11 naMCI, and 28 aMCI patients. Moreover, a correlation analysis was used to examine associations between the altered connectivity of the DMN subnetworks and the neurocognitive performance. Results: Compared to the HC, SCD patients showed increased FC in the bilateral superior frontal gyrus (SFG), naMCI patients showed increased FC in the left inferior parietal lobule (IPL), and aMCI patients showed increased FC in the bilateral IPL in the aDMN; while SCD patients showed decreased FC in the precuneus, naMCI patients showed increased FC in the left middle temporal gyrus (MTG), and aMCI patients also showed increased FC in the right middle frontal gyrus (MFG) in the pDMN. Notably, the FC between the ventromedial prefrontal cortex (vmPFC) and the left MFG and the IPL in the aDMN was associated with episodic memory in the SCD and aMCI groups. Interestingly, the FC between the posterior cingulated cortex (PCC) and several regions in the pDMN was associated with other cognitive functions in the SCD and naMCI groups. Conclusions: This study demonstrates that the three preclinical stages of AD exhibit distinct FC alternations in the DMN subnetworks. Furthermore, the patient group data showed that the altered FC involves cognitive function. These findings can provide novel insights for tailored clinical intervention across the preclinical AD spectrum.
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Affiliation(s)
- Chen Xue
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Baoyu Yuan
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yingying Yue
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Jiani Xu
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Siyu Wang
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Meilin Wu
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Nanxi Ji
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Xingzhi Zhou
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Yilin Zhao
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China
| | - Jiang Rao
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Wenjie Yang
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Chaoyong Xiao
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Jiu Chen
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, China.,Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
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23
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De Marco M, Ourselin S, Venneri A. Age and hippocampal volume predict distinct parts of default mode network activity. Sci Rep 2019; 9:16075. [PMID: 31690806 PMCID: PMC6831650 DOI: 10.1038/s41598-019-52488-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 10/08/2019] [Indexed: 01/20/2023] Open
Abstract
Group comparison studies have established that activity in the posterior part of the default-mode network (DMN) is down-regulated by both normal ageing and Alzheimer’s disease (AD). In this study linear regression models were used to disentangle distinctive DMN activity patterns that are more profoundly associated with either normal ageing or a structural marker of neurodegeneration. 312 datasets inclusive of healthy adults and patients were analysed. Days of life at scan (DOL) and hippocampal volume were used as predictors. Group comparisons confirmed a significant association between functional connectivity in the posterior cingulate/retrosplenial cortex and precuneus and both ageing and AD. Fully-corrected regression models revealed that DOL significantly predicted DMN strength in these regions. No such effect, however, was predicted by hippocampal volume. A significant positive association was found between hippocampal volumes and DMN connectivity in the right temporo-parietal junction (TPJ). These results indicate that postero-medial DMN down-regulation may not be specific to neurodegenerative processes but may be more an indication of brain vulnerability to degeneration. The DMN-TPJ disconnection is instead linked to the volumetric properties of the hippocampus, may reflect early-stage regional accumulation of pathology and might be of aid in the clinical detection of abnormal ageing.
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Affiliation(s)
- Matteo De Marco
- Department of Neuroscience, Medical School, University of Sheffield, Royal Hallamshire Hospital, Beech Hill Road, S10 2RX, Sheffield, UK
| | - Sebastien Ourselin
- Department of Imaging and Biomedical Engineering, King's College London, Strand, London, UK
| | - Annalena Venneri
- Department of Neuroscience, Medical School, University of Sheffield, Royal Hallamshire Hospital, Beech Hill Road, S10 2RX, Sheffield, UK.
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24
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McDermott K, Ren P, Lin F. The mediating role of hippocampal networks on stress regulation in amnestic mild cognitive impairment. Neurobiol Stress 2019; 10:100162. [PMID: 31193516 PMCID: PMC6535625 DOI: 10.1016/j.ynstr.2019.100162] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 01/18/2019] [Accepted: 04/03/2019] [Indexed: 12/27/2022] Open
Abstract
Objectives To examine the role of the hippocampus in stress regulation in older adults with amnestic mild cognitive impairment (aMCI). Methods This study combined resting-state functional MRI, structural MRI, self-reported chronic stress exposure, and an electrocardiography-based acute stress protocol to compare aMCI group (n = 17) to their cognitively healthy counterparts (HC, n = 22). Results For the entire sample, there was a positive correlation between chronic stress exposure and acute stress regulation. The aMCI group showed significantly smaller volumes in the right hippocampus than HC. The two groups did not differ in chronic stress exposure or acute stress regulation. In the HC group, the left hippocampal connectivity with inferior parietal lobe was significantly correlated with both the chronic stress and acute stress. In the aMCI group, the left hippocampal connectivity with both the right insula and the left precentral gyrus was significantly correlated to chronic stress exposure and acute stress regulation. Additionally, the left hippocampal connectivity with right insula significantly mediated the relationship between chronic stress exposure and acute stress regulation in aMCI group. Conclusions Extra hippocampal networks may be recruited as compensation to attend the maintenance of relatively normal stress regulation in aMCI by alleviating the detrimental effects of chronic stress exposure on acute stress regulation.
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Key Words
- AD, Alzheimer's Disease
- ANS, Autonomic Nervous System
- Acute stress regulation
- Chronic stress exposure
- FC, functional connectivity
- GDS, Geriatric Depression Scale
- GLM, General Linear Model
- HC, healthy control
- HF-HRV, high frequency heart rate variability
- HPA, Hypothalamic Pituitary Adrenal
- Hippocampus
- LHIP, left hippocampus
- LIPL, left inferior parietal lobe
- LPG, left precentral gyrus
- MOCA, Montreal Cognitive Assessment
- Mild cognitive impairment
- PSS, Perceived stress scale
- RAVLT, Rey's Auditory Verbal Learning Test
- RHIP, right hippocampus
- Resting-state functional connectivity
- Rinsula, right insula
- aMCI, amnestic Mild Cognitive Impairment
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Affiliation(s)
- Kelsey McDermott
- School of Nursing, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Ping Ren
- School of Nursing, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Feng Lin
- School of Nursing, University of Rochester Medical Center, Rochester, NY, 14642, USA
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, 14642, USA
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, 14642, USA
- Department of Neurology, University of Rochester Medical Center, Rochester, NY, 14642, USA
- Department of Brain and Cognitive Science, University of Rochester, Rochester, NY, 14627, USA
- Corresponding author. 601 Elmwood Ave, Rochester, NY, 14642
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25
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Anthony M, Lin F. A Systematic Review for Functional Neuroimaging Studies of Cognitive Reserve Across the Cognitive Aging Spectrum. Arch Clin Neuropsychol 2019; 33:937-948. [PMID: 29244054 DOI: 10.1093/arclin/acx125] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 11/27/2017] [Indexed: 12/29/2022] Open
Abstract
Objective Cognitive reserve has been proposed to explain the discrepancy between clinical symptoms and the effects of aging or Alzheimer's pathology. Functional magnetic resonance imaging (fMRI) may help elucidate how neural reserve and compensation delay cognitive decline and identify brain regions associated with cognitive reserve. This systematic review evaluated neural correlates of cognitive reserve via fMRI (resting-state and task-related) studies across the cognitive aging spectrum (i.e., normal cognition, mild cognitive impairment, and Alzheimer's disease). Method This review examined published articles up to March 2017. There were 13 cross-sectional observational studies that met the inclusion criteria, including relevance to cognitive reserve, subjects 60 years or older with normal cognition, mild cognitive impairment, and/or Alzheimer's disease, at least one quantitative measure of cognitive reserve, and fMRI as the imaging modality. Quality assessment of included studies was conducted using the Newcastle-Ottawa Scale adapted for cross-sectional studies. Results Across the cognitive aging spectrum, medial temporal regions and an anterior or posterior cingulate cortex-seeded default mode network were associated with neural reserve. Frontal regions and the dorsal attentional network were related to neural compensation. Compared to neural reserve, neural compensation was more common in mild cognitive impairment and Alzheimer's disease. Conclusions Neural reserve and compensation both support cognitive reserve, with compensation more common in later stages of the cognitive aging spectrum. Longitudinal and intervention studies are needed to investigate changes between neural reserve and compensation during the transition between clinical stages, and to explore the causal relationship between cognitive reserve and potential neural substrates.
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Affiliation(s)
- Mia Anthony
- School of Nursing, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Feng Lin
- School of Nursing, University of Rochester Medical Center, Rochester, NY 14642, USA.,Department of Psychiatry, University of Rochester Medical Center, Rochester, NY 14642, USA.,Department of Brain and Cognitive Science, University of Rochester, Rochester, NY 14642, USA.,Department of Neuroscience, University of Rochester Medical Center, Rochester, NY 14642, USA.,Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA
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26
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Li H, Jia X, Qi Z, Fan X, Ma T, Pang R, Ni H, Li CSR, Lu J, Li K. Disrupted Functional Connectivity of Cornu Ammonis Subregions in Amnestic Mild Cognitive Impairment: A Longitudinal Resting-State fMRI Study. Front Hum Neurosci 2018; 12:413. [PMID: 30420801 PMCID: PMC6216144 DOI: 10.3389/fnhum.2018.00413] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 09/24/2018] [Indexed: 12/16/2022] Open
Abstract
Background: The cornu ammonis (CA), as part of the hippocampal formation, represents a primary target region of neural degeneration in amnestic mild cognitive impairment (aMCI). Previous studies have revealed subtle structural deficits of the CA subregions (CA1-CA3, bilateral) in aMCI; however, it is not clear how the network function is impacted by aMCI. The present study examined longitudinal changes in resting state functional connectivity (FC) of each CA subregion and how these changes relate to neuropsychological profiles in aMCI. Methods: Twenty aMCI and 20 healthy control (HC) participants underwent longitudinal cognitive assessment and resting state functional MRI scans at baseline and 15 months afterward. Imaging data were processed with published routines in SPM8 and CONN software. Two-way analysis of covariance was performed with covariates of age, gender, education level, follow up interval, gray matter volume, mean FD, as well as global correlation (GCOR). Pearson’s correlation was conducted to evaluate the relationship between the longitudinal changes in CA subregional FC and neuropsychological performance in aMCI subjects. Results: Resting state FC between the right CA1 and right middle temporal gyrus (MTG) as well as between the left CA2 and bilateral cuneal cortex (CC) were decreased in aMCI subjects as compared to HC. Longitudinal decrease in FC between the right CA1 and right MTG was correlated with reduced capacity of episodic memory in aMCI subjects. Conclusion: The current findings suggest functional alterations in the CA subregions. CA1 connectivity with the middle temporal cortex may represent an important neural marker of memory dysfunction in aMCI.
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Affiliation(s)
- Hui Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China
| | - Xiuqin Jia
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.,Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Zhigang Qi
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China
| | - Xiang Fan
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tian Ma
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Ran Pang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Hong Ni
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale School of Medicine, Yale University, New Haven, CT, United States.,Department of Neuroscience, Yale School of Medicine, Yale University, New Haven, CT, United States.,Beijing Huilongguan Hospital, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of MRI and Brain Informatics, Beijing, China
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27
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Grieder M, Wang DJJ, Dierks T, Wahlund LO, Jann K. Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer's Disease. Front Neurosci 2018; 12:770. [PMID: 30405347 PMCID: PMC6206840 DOI: 10.3389/fnins.2018.00770] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Accepted: 10/03/2018] [Indexed: 01/11/2023] Open
Abstract
The human resting-state is characterized by spatially coherent brain activity at a low temporal frequency. The default mode network (DMN), one of so-called resting-state networks, has been associated with cognitive processes that are directed toward the self, such as introspection and autobiographic memory. The DMN's integrity appears to be crucial for mental health. For example, patients with Alzheimer's disease or other psychiatric conditions show disruptions of functional connectivity within the brain regions of the DMN. However, in prodromal or early stages of Alzheimer's disease, physiological alterations are sometimes elusive, despite manifested cognitive impairment. While functional connectivity assesses the signal correlation between brain areas, multi-scale entropy (MSE) measures the complexity of the blood-oxygen level dependent signal within an area and thus might show local changes before connectivity is affected. Hence, we investigated alterations of functional connectivity and MSE within the DMN in fifteen mild Alzheimer's disease patients as compared to fourteen controls. Potential associations of MSE with functional connectivity and cognitive abilities [i.e., mini-mental state examination (MMSE)] were assessed. A moderate decrease of DMN functional connectivity between posterior cingulate cortex and right hippocampus in Alzheimer's disease was found, whereas no differences were evident for whole-network functional connectivity. In contrast, the Alzheimer's disease group yielded lower global DMN-MSE than the control group. The most pronounced regional effects were localized in left and right hippocampi, and this was true for most scales. Moreover, MSE significantly correlated with functional connectivity, and DMN-MSE correlated positively with the MMSE in Alzheimer's disease. Most interestingly, the right hippocampal MSE was positively associated with semantic memory performance. Thus, our results suggested that cognitive decline in Alzheimer's disease is reflected by decreased signal complexity in DMN nodes, which might further lead to disrupted DMN functional connectivity. Additionally, altered entropy in Alzheimer's disease found in the majority of the scales indicated a disturbance of both local information processing and information transfer between distal areas. Conclusively, a loss of nodal signal complexity potentially impairs synchronization across nodes and thus preempts functional connectivity changes. MSE presents a putative functional marker for cognitive decline that might be more sensitive than functional connectivity alone.
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Affiliation(s)
- Matthias Grieder
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Danny J J Wang
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Thomas Dierks
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Lars-Olof Wahlund
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, NVS, Karolinska Institute, Stockholm, Sweden
| | - Kay Jann
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
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28
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Conwell K, von Reutern B, Richter N, Kukolja J, Fink GR, Onur OA. Test-retest variability of resting-state networks in healthy aging and prodromal Alzheimer's disease. NEUROIMAGE-CLINICAL 2018; 19:948-962. [PMID: 30003032 PMCID: PMC6039839 DOI: 10.1016/j.nicl.2018.06.016] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Revised: 06/11/2018] [Accepted: 06/13/2018] [Indexed: 12/03/2022]
Abstract
In recent years, changes in resting-state networks (RSN), identified by functional magnetic resonance imaging (fMRI), have gained increasing attention as potential biomarkers and trackers of neurological disorders such as Alzheimer's disease (AD). Intersession reliability of RSN is fundamental to this approach. In this study, we investigated the test-retest reliability of three memory related RSN (i.e., the default mode, salience, and executive control network) in 15 young, 15 healthy seniors (HS), and 15 subjects affected by mild cognitive impairment (MCI) with positive biomarkers suggestive of incipient AD (6 females each). FMRI was conducted on three separate occasions. Independent Component Analysis decomposed the resting-state data into RSNs. Comparisons of variation in functional connectivity between groups were made applying different thresholds in an explorative approach. Intersession test-retest reliability was evaluated by intraclass correlation coefficient (ICC) comparisons. To assess the effect of gray matter volume loss, motion, cerebrospinal fluid based biomarkers and the time gap between sessions on intersession variation, the former four were correlated separately with the latter. Data showed that i) young subjects ICCs (relative to HS/MCI-subjects) had higher intersession reliability, ii) stringent statistical thresholds need to be applied to prevent false-positives, iii) both HS and MCI-subjects (relative to young) showed significantly more clusters of intersession variation in all three RSN, iv) while intersession variation was highly correlated with head motion, it was also correlated with biomarkers (especially phospho-tau), the time gap between sessions and local GMV. Results indicate that time gaps between sessions should be kept constant and that head motion must be taken into account when using RSN to assess aging and neurodegeneration. In patients with prodromal AD, re-test reliability may be increased by accouting for overall disease burden by including biomarkers of neuronal injury (especially phospho-tau) in statistical analyses. Local atrophy however, does not seem to play a major role in regards to reliability, but should be used as covariate depending on the research question. Intersession reliability of resting state networks is highest in young subjects. Test-Retest Variability increases with aging and in MCI. Motion and csf-biomarkers correlate with increased variability. Motion and biomarkers should be included as confounders in the statistical models. Stringent statistical thresholds should be applied to prevent type I-errors.
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Affiliation(s)
- K Conwell
- Department of Neurology, University Hospital of Cologne, Cologne 50937, Germany; Department of General, Abdominal, Endocrine and Minimally Invasive Surgery, Academic Hospital Bogenhausen, 81925 Munich, Germany
| | - B von Reutern
- Department of Neurology, University Hospital of Cologne, Cologne 50937, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre, Jülich 52428, Germany
| | - N Richter
- Department of Neurology, University Hospital of Cologne, Cologne 50937, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre, Jülich 52428, Germany
| | - J Kukolja
- Department of Neurology, University Hospital of Cologne, Cologne 50937, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre, Jülich 52428, Germany
| | - G R Fink
- Department of Neurology, University Hospital of Cologne, Cologne 50937, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre, Jülich 52428, Germany
| | - O A Onur
- Department of Neurology, University Hospital of Cologne, Cologne 50937, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre, Jülich 52428, Germany.
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29
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Ma HR, Sheng LQ, Pan PL, Wang GD, Luo R, Shi HC, Dai ZY, Zhong JG. Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer's dementia: a meta-analysis. Transl Neurodegener 2018; 7:9. [PMID: 29713467 PMCID: PMC5911957 DOI: 10.1186/s40035-018-0114-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 04/03/2018] [Indexed: 12/14/2022] Open
Abstract
Brain 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) has been utilized to monitor disease conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer’s dementia (AD). However, the conversion patterns of FDG-PET metabolism across studies are not conclusive. We conducted a voxel-wise meta-analysis using Seed-based d Mapping that included 10 baseline voxel-wise FDG-PET comparisons between 93 aMCI converters and 129 aMCI non-converters from nine longitudinal studies. The most robust and reliable metabolic alterations that predicted conversion from aMCI to AD were localized in the left posterior cingulate cortex (PCC)/precuneus. Furthermore, meta-regression analyses indicated that baseline mean age and severity of cognitive impairment, and follow-up duration were significant moderators for metabolic alterations in aMCI converters. Our study revealed hypometabolism in the left PCC/precuneus as an early feature in the development of AD. This finding has important implications in understanding the neural substrates for AD conversion and could serve as a potential imaging biomarker for early detection of AD as well as for tracking disease progression at the predementia stage.
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Affiliation(s)
- Hai Rong Ma
- 1Department of Neurology, Traditional Chinese Medicine Hospital of Kunshan, Kunshan, People's Republic of China
| | - Li Qin Sheng
- 1Department of Neurology, Traditional Chinese Medicine Hospital of Kunshan, Kunshan, People's Republic of China
| | - Ping Lei Pan
- 2Department of Neurology, School of Medicine, Affiliated Yancheng Hospital, Southeast University, West Xindu Road 2#, Yancheng, Jiangsu Province 224001 People's Republic of China
| | - Gen Di Wang
- 2Department of Neurology, School of Medicine, Affiliated Yancheng Hospital, Southeast University, West Xindu Road 2#, Yancheng, Jiangsu Province 224001 People's Republic of China
| | - Rong Luo
- 2Department of Neurology, School of Medicine, Affiliated Yancheng Hospital, Southeast University, West Xindu Road 2#, Yancheng, Jiangsu Province 224001 People's Republic of China
| | - Hai Cun Shi
- 2Department of Neurology, School of Medicine, Affiliated Yancheng Hospital, Southeast University, West Xindu Road 2#, Yancheng, Jiangsu Province 224001 People's Republic of China
| | - Zhen Yu Dai
- 3Department of Radiology, School of Medicine, Affiliated Yancheng Hospital, Southeast University, West Xindu Road 2#, Yancheng, Jiangsu Province 224001 People's Republic of China
| | - Jian Guo Zhong
- 2Department of Neurology, School of Medicine, Affiliated Yancheng Hospital, Southeast University, West Xindu Road 2#, Yancheng, Jiangsu Province 224001 People's Republic of China
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30
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Wang C, Pan Y, Liu Y, Xu K, Hao L, Huang F, Ke J, Sheng L, Ma H, Guo W. Aberrant default mode network in amnestic mild cognitive impairment: a meta-analysis of independent component analysis studies. Neurol Sci 2018; 39:919-931. [DOI: 10.1007/s10072-018-3306-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 02/23/2018] [Indexed: 12/24/2022]
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31
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Zhao Q, Lu H, Metmer H, Li WX, Lu J. Evaluating functional connectivity of executive control network and frontoparietal network in Alzheimer’s disease. Brain Res 2018; 1678:262-272. [DOI: 10.1016/j.brainres.2017.10.025] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 10/21/2017] [Accepted: 10/23/2017] [Indexed: 12/30/2022]
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32
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de Flores R, Mutlu J, Bejanin A, Gonneaud J, Landeau B, Tomadesso C, Mézenge F, de La Sayette V, Eustache F, Chételat G. Intrinsic connectivity of hippocampal subfields in normal elderly and mild cognitive impairment patients. Hum Brain Mapp 2017; 38:4922-4932. [PMID: 28653793 DOI: 10.1002/hbm.23704] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2017] [Revised: 06/14/2017] [Accepted: 06/15/2017] [Indexed: 12/11/2022] Open
Abstract
Hippocampal connectivity has been widely described but connectivity specificities of hippocampal subfields and their changes in early AD are poorly known. The aim of this study was to highlight hippocampal subfield networks in healthy elderly (HE) and their changes in amnestic patients with mild cognitive impairment (aMCI). Thirty-six HE and 27 aMCI patients underwent resting-state functional MRI scans. Specific intrinsic connectivity of bilateral CA1, SUB (subiculum), and CA2/3/4/DG was identified in HE (using seeds derived from manually delineation on high-resolution scans) and compared between HE and aMCI. Compared to the other subfields, CA1 was more strongly connected to the amygdala and occipital regions, CA2/3/4/DG to the left anterior cingulate cortex, temporal, and occipital regions, and SUB to the angular, precuneus, putamen, posterior cingulate, and frontal regions. aMCI patients showed reduced connectivity within the SUB network (with frontal and posterior cingulate regions). Our study highlighted for the first time three specific and distinct hippocampal subfield functional networks in HE, and their alterations in aMCI. These findings are important to understand AD specificities in both cognitive deficits and lesion topography, given the role of functional connectivity in these processes. Hum Brain Mapp 38:4922-4932, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Robin de Flores
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
| | - Justine Mutlu
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
| | - Alexandre Bejanin
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
| | - Julie Gonneaud
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
| | - Brigitte Landeau
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
| | - Clémence Tomadesso
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
| | - Florence Mézenge
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
| | - Vincent de La Sayette
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Service de Neurologie, Caen, France
| | - Francis Eustache
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
| | - Gaël Chételat
- INSERM, Caen, U1077, France.,Université de Caen Normandie, UMR-S1077, Caen, France.,Ecole Pratique des Hautes Etudes, UMR-S1077, Caen, France.,CHU de Caen, Caen, U1077, France
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33
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Sun DM, Chen HF, Zuo QL, Su F, Bai F, Liu CF. Effect of PICALM rs3851179 polymorphism on the default mode network function in mild cognitive impairment. Behav Brain Res 2017; 331:225-232. [PMID: 28549650 DOI: 10.1016/j.bbr.2017.05.043] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 05/12/2017] [Accepted: 05/17/2017] [Indexed: 01/17/2023]
Abstract
Alterations in default mode network (DMN) functional connectivity (FC) might accompany the dysfunction of Alzheimer's disease (AD). Indeed, episodic memory impairment is a hallmark of AD, and mild cognitive impairment (MCI) has been associated with a high risk for AD. Phosphatidylinositol-binding clathrin assembly protein (PICALM) (rs3851179) has been associated with AD; in particular, the A allele may serve a protective role, while the G allele serves as a strong genetic risk factor. Therefore, the identification of genetic polymorphisms associated with the DMN is required in MCI subjects. In all, 32 MCI subjects and 32 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) and a genetic imaging approach. Subjects were divided into four groups according to the diagnosis (i.e., MCI and HCs) and the PICALM rs3851179 polymorphism (i.e., AA/AG genotype and GG genotype). The differences in FC within the DMN between the four subgroups were explored. Furthermore, we examined the relationship between our neuroimaging measures and cognitive performance. The regions associated with the genotype-by-disease interaction were in the left middle temporal gyrus (LMTG) and left middle frontal gyrus (LMFG). These changes in LMFG FC were generally manifested as an "inverse U-shaped curve", while a "U-shaped curve" was associated with the LMTG FC between these four subgroups (all P<0.05). Furthermore, higher FC within the LMFG was related to better episodic memory performance (i.e., AVLT 20min DR, rho=0.72, P=0.044) for the MCI subgroups with the GG genotype. The PICALM rs3851179 polymorphism significantly affects the DMN network in MCI. The LMFG and LMTG may be associated with opposite patterns. However, the altered LMFG FC in MCI patients with the GG genotype was more sensitive to episodic memory impairment, which is more likely to lead to a high risk of AD.
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Affiliation(s)
- Ding-Ming Sun
- Department of Neurology, Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China; Department of Neurology, Fourth Affiliated Yancheng Hospital of Nantong University, Yancheng 224001, China
| | - Hai-Feng Chen
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, and The Institute of Neuropsychiatry of Southeast University, Nanjing 210009, China
| | - Qi-Long Zuo
- Department of Neurology, Fourth Affiliated Yancheng Hospital of Nantong University, Yancheng 224001, China
| | - Fan Su
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, and The Institute of Neuropsychiatry of Southeast University, Nanjing 210009, China
| | - Feng Bai
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, and The Institute of Neuropsychiatry of Southeast University, Nanjing 210009, China
| | - Chun-Feng Liu
- Department of Neurology, Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China.
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34
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Pievani M, Pini L, Ferrari C, Pizzini FB, Boscolo Galazzo I, Cobelli C, Cotelli M, Manenti R, Frisoni GB. Coordinate-Based Meta-Analysis of the Default Mode and Salience Network for Target Identification in Non-Invasive Brain Stimulation of Alzheimer’s Disease and Behavioral Variant Frontotemporal Dementia Networks. J Alzheimers Dis 2017; 57:825-843. [DOI: 10.3233/jad-161105] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Michela Pievani
- Laboratory Alzheimer’s Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio – Fatebenefratelli, Brescia, Italy
| | - Lorenzo Pini
- Laboratory Alzheimer’s Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio – Fatebenefratelli, Brescia, Italy
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Clarissa Ferrari
- Statistics Service, IRCCS Centro San Giovanni di Dio – Fatebenefratelli, Brescia, Italy
| | - Francesca B. Pizzini
- Neuroradiology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
| | | | - Chiara Cobelli
- Neuropsychology Unit, IRCCS Centro San Giovanni di Dio – Fatebenefratelli, Brescia, Italy
| | - Maria Cotelli
- Neuropsychology Unit, IRCCS Centro San Giovanni di Dio – Fatebenefratelli, Brescia, Italy
| | - Rosa Manenti
- Neuropsychology Unit, IRCCS Centro San Giovanni di Dio – Fatebenefratelli, Brescia, Italy
| | - Giovanni B. Frisoni
- Laboratory Alzheimer’s Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio – Fatebenefratelli, Brescia, Italy
- University Hospitals and University of Geneva, Geneva, Switzerland
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35
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Yang H, Wang C, Zhang Y, Xia L, Feng Z, Li D, Xu S, Xie H, Chen F, Shi Y, Wang J. Disrupted Causal Connectivity Anchored in the Posterior Cingulate Cortex in Amnestic Mild Cognitive Impairment. Front Neurol 2017; 8:10. [PMID: 28167926 PMCID: PMC5256067 DOI: 10.3389/fneur.2017.00010] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2016] [Accepted: 01/09/2017] [Indexed: 12/13/2022] Open
Abstract
Amnestic mild cognitive impairment (aMCI) is a transitional stage between normal cognitive aging and Alzheimer’s disease. Previous studies have found that neuronal activity and functional connectivity impaired in many functional networks, especially in the default mode network (DMN), which is related to significantly impaired cognitive and memory functions in aMCI patients. However, few studies have focused on the effective connectivity of the DMN and its subsystems in aMCI patients. The posterior cingulate cortex (PCC) is considered a crucial region in connectivity of the DMN and its key subsystem. In this study, using the coefficient Granger causality analysis approach and using the PCC as the region of interest, we explored changes in the DMN and its subsystems in effective connectivity with other brain regions as well as in correlations among them in 16 aMCI patients and 15 age-matched cognitively normal elderly. Results showed decreased effective connectivity from PCC to whole brain in the left prefrontal cortex, the left medial temporal lobe (MTL), the left fusiform gyrus (FG), and the left cerebellar hemisphere, meanwhile, right temporal lobe showed increased effective connectivity from PCC to the whole brain in aMCI patients compared with normal control. In addition, compared with the normal controls, increased effective connectivity of the whole brain to the PCC in aMCI patients was found in the right thalamus, left medial temporal lobe, left FG, and left cerebellar hemisphere. Compared with the normal controls, no reduced effective connectivity was found in any brain regions from the whole brain to the PCC in aMCI patients. The reduced effective connectivity of the PCC to left MTL showed negative correlation trend with neuropsychological tests (Auditory Verbal Learning Test-immediate recall and clock drawing test) in aMCI patients. Our study shows that aMCI patients have abnormalities in effective connectivity within the PCC-centered DMN network and its posterior subsystems as well as in the cerebellar hemisphere and thalamus. Abnormal integration of networks may be related to cognitive and memory impairment and compensation mechanisms in aMCI patients.
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Affiliation(s)
- Hong Yang
- Department of Radiology, The First Affiliated Hospital of College of Medicine, Zhejiang University , Hangzhou , China
| | - Chengwei Wang
- Department of CT/MRI, The First Affiliated Hospital of the Medical College, Shihezi University, Shihezi, China; Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yumei Zhang
- Department of Radiology, The First Affiliated Hospital of College of Medicine, Zhejiang University, Hangzhou, China; Department of CT/MRI, The First Affiliated Hospital of the Medical College, Shihezi University, Shihezi, China
| | - Liming Xia
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology , Wuhan, Hubei , China
| | - Zhan Feng
- Department of Radiology, The First Affiliated Hospital of College of Medicine, Zhejiang University , Hangzhou , China
| | - Deqiang Li
- Department of Neurology, The First Affiliated Hospital of College of Medicine, Zhejiang University , Hangzhou , China
| | - Shunliang Xu
- Department of Radiology, The First Affiliated Hospital of College of Medicine, Zhejiang University , Hangzhou , China
| | - Haiyan Xie
- Department of Psychiatry, The Fourth Affiliated Hospital Zhejiang University School of Medicine , Yiwu , China
| | - Feng Chen
- Department of Radiology, The First Affiliated Hospital of College of Medicine, Zhejiang University , Hangzhou , China
| | - Yushu Shi
- Department of Radiology, The First Affiliated Hospital of College of Medicine, Zhejiang University , Hangzhou , China
| | - Jue Wang
- Center for Cognition and Brain Disorders, Affiliated Hospital, Hangzhou Normal University , Hangzhou , China
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Default Mode Network Functional Connectivity in Early and Late Mild Cognitive Impairment. Alzheimer Dis Assoc Disord 2016; 30:289-296. [DOI: 10.1097/wad.0000000000000143] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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Deng Y, Liu K, Shi L, Lei Y, Liang P, Li K, Chu WCW, Wang D. Identifying the Alteration Patterns of Brain Functional Connectivity in Progressive Mild Cognitive Impairment Patients: A Longitudinal Whole-Brain Voxel-Wise Degree Analysis. Front Aging Neurosci 2016; 8:195. [PMID: 27582703 PMCID: PMC4987370 DOI: 10.3389/fnagi.2016.00195] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Accepted: 08/02/2016] [Indexed: 11/21/2022] Open
Abstract
Patients with mild cognitive impairment (MCI) are at high risk for developing Alzheimer’s disease (AD), while some of them may remain stable over decades. The underlying mechanism is still not fully understood. In this study, we aimed to explore the connectivity differences between progressive MCI (PMCI) and stable MCI (SMCI) individuals on a whole-brain scale and on a voxel-wise basis, and we also aimed to reveal the differential dynamic alteration patterns between these two disease subtypes. The resting-state functional magnetic resonance images of PMCI and SMCI patients at baseline and year-one were obtained from the Alzheimer’s Disease Neuroimaging Initiative dataset, and the progression was determined based on a 3-year follow-up. A whole-brain voxel-wise degree map that was calculated based on graph-theory was constructed for each subject, and then the cross-sectional and longitudinal analyses on the degree maps were performed between PMCI and SMCI patients. In longitudinal analyses, compared with SMCI group, PMCI group showed decreased long-range degree in the left middle occipital/supramarginal gyrus, while the short-range degree was increased in the left supplementary motor area and middle frontal gyrus and decreased in the right middle temporal pole. A significant longitudinal alteration of decreased short-range degree in the right middle occipital was found in PMCI group. Taken together with previous evidence, our current findings may suggest that PMCI, compared with SMCI, might be a “severe” presentation of disease along the AD continuum, and the rapidly reduced degree in the right middle occipital gyrus may have indicative value for the disease progression. Moreover, the cross-sectional comparison results and corresponding receiver-operator characteristic-curves analyses may indicate that the baseline degree difference is not a good predictor of disease progression in MCI patients. Overall, these findings may provide objective evidence and an indicator to characterize the progression-related brain connectivity changes in MCI patients.
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Affiliation(s)
- Yanjia Deng
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong Shatin, Hong Kong
| | - Kai Liu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong Shatin, Hong Kong
| | - Lin Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong KongShatin, Hong Kong; Chow Yuk Ho Center of Innovative Technology for Medicine, The Chinese University of Hong KongShatin, Hong Kong
| | - Yi Lei
- Department of Radiology, The Second People's Hospital of Shenzhen Shenzhen, China
| | - Peipeng Liang
- Department of Radiology, Xuanwu Hospital, Capital Medical University Beijing, China
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University Beijing, China
| | - Winnie C W Chu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong KongShatin, Hong Kong; Shenzhen Research Institute, The Chinese University of Hong KongShenzhen, China
| | - Defeng Wang
- Department of Imaging and Interventional Radiology, The Chinese University of Hong KongShatin, Hong Kong; Shenzhen Research Institute, The Chinese University of Hong KongShenzhen, China
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Zhang J, Liu Z, Zhang H, Yang C, Li H, Li X, Chen K, Zhang Z. A Two-Year Treatment of Amnestic Mild Cognitive Impairment using a Compound Chinese Medicine: A Placebo Controlled Randomized Trial. Sci Rep 2016; 6:28982. [PMID: 27373556 PMCID: PMC4931444 DOI: 10.1038/srep28982] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Accepted: 06/13/2016] [Indexed: 12/18/2022] Open
Abstract
We aimed to investigate the long-term therapeutic effects of a compound Chinese medicine, the Bushen capsule, on cognition and brain connectivity in patients with amnestic mild cognitive impairment (aMCI). Thus, sixty aMCI participants were recruited to this 24-month study and were randomly divided into treatment (30 with a Bushen capsule) and placebo (30 with a placebo capsule) groups. Neuropsychological tests with MMSE and episodic memory as the primary outcomes and resting-state functional magnetic resonance imaging (fMRI) were analyzed before and after the treatment over 24 month period. In contrast to the placebo group, the drug group presented improved or stable general cognitive function, memory, language and executive function especially the primary outcomes MMSE and episodic memory with Bushen capsule treatment. FMRI results showed increased connectivity in the right precuneus and the global connectivity indexed with goodness of fit (GOF) of the default mode network (DMN) in the drug group and decreased GOF in the placebo group. More importantly, we found the GOF change was positively correlated with changes in MMSE and memory scores after 24 months in the drug group. Over 24 months, treatment with the compound Chinese medicine Bushen capsule can improve multiple domains of cognition and increase the functional local (right precuneus) and global connectivity within the DMN, which are associated with better performance.
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Affiliation(s)
- Junying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, P. R. China
- BABRI Centre, Beijing Normal University, Beijing 100875, P. R. China
| | - Zhen Liu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, P. R. China
- BABRI Centre, Beijing Normal University, Beijing 100875, P. R. China
| | - Huamin Zhang
- BABRI Centre, Beijing Normal University, Beijing 100875, P. R. China
- Institute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, P. R. China
| | - Caishui Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, P. R. China
- BABRI Centre, Beijing Normal University, Beijing 100875, P. R. China
| | - He Li
- BABRI Centre, Beijing Normal University, Beijing 100875, P. R. China
- Institute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, P. R. China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, P. R. China
- BABRI Centre, Beijing Normal University, Beijing 100875, P. R. China
| | - Kewei Chen
- BABRI Centre, Beijing Normal University, Beijing 100875, P. R. China
- Banner Alzheimer’s Institute, Phoenix, AZ 85006, USA
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, P. R. China
- BABRI Centre, Beijing Normal University, Beijing 100875, P. R. China
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The Significance of the Default Mode Network (DMN) in Neurological and Neuropsychiatric Disorders: A Review. THE YALE JOURNAL OF BIOLOGY AND MEDICINE 2016; 89:49-57. [PMID: 27505016 PMCID: PMC4797836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
The relationship of cortical structure and specific neuronal circuitry to global brain function, particularly its perturbations related to the development and progression of neuropathology, is an area of great interest in neurobehavioral science. Disruption of these neural networks can be associated with a wide range of neurological and neuropsychiatric disorders. Herein we review activity of the Default Mode Network (DMN) in neurological and neuropsychiatric disorders, including Alzheimer's disease, Parkinson's disease, Epilepsy (Temporal Lobe Epilepsy - TLE), attention deficit hyperactivity disorder (ADHD), and mood disorders. We discuss the implications of DMN disruptions and their relationship to the neurocognitive model of each disease entity, the utility of DMN assessment in clinical evaluation, and the changes of the DMN following treatment.
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Abnormal Resting-State Functional Connectivity Strength in Mild Cognitive Impairment and Its Conversion to Alzheimer's Disease. Neural Plast 2015; 2016:4680972. [PMID: 26843991 PMCID: PMC4710946 DOI: 10.1155/2016/4680972] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2015] [Accepted: 10/04/2015] [Indexed: 01/25/2023] Open
Abstract
Individuals diagnosed with mild cognitive impairment (MCI) are at high risk of transition to Alzheimer's disease (AD). However, little is known about functional characteristics of the conversion from MCI to AD. Resting-state functional magnetic resonance imaging was performed in 25 AD patients, 31 MCI patients, and 42 well-matched normal controls at baseline. Twenty-one of the 31 MCI patients converted to AD at approximately 24 months of follow-up. Functional connectivity strength (FCS) and seed-based functional connectivity analyses were used to assess the functional differences among the groups. Compared to controls, subjects with MCI and AD showed decreased FCS in the default-mode network and the occipital cortex. Importantly, the FCS of the left angular gyrus and middle occipital gyrus was significantly lower in MCI-converters as compared with MCI-nonconverters. Significantly decreased functional connectivity was found in MCI-converters compared to nonconverters between the left angular gyrus and bilateral inferior parietal lobules, dorsolateral prefrontal and lateral temporal cortices, and the left middle occipital gyrus and right middle occipital gyri. We demonstrated gradual but progressive functional changes during a median 2-year interval in patients converting from MCI to AD, which might serve as early indicators for the dysfunction and progression in the early stage of AD.
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Chen Y, Liu Z, Zhang J, Tian G, Li L, Zhang S, Li X, Chen K, Zhang Z. Selectively Disrupted Functional Connectivity Networks in Type 2 Diabetes Mellitus. Front Aging Neurosci 2015; 7:233. [PMID: 26696885 PMCID: PMC4675853 DOI: 10.3389/fnagi.2015.00233] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2015] [Accepted: 11/27/2015] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND The high prevalence of type 2 diabetes mellitus (T2DM) in individuals over 65 years old and cognitive deficits caused by T2DM have attracted broad attention. The pathophysiological mechanism of T2DM-induced cognitive impairments, however, remains poorly understood. Previous studies have suggested that the cognitive impairments can be attributed not only to local functional and structural abnormalities but also to specific brain networks. Thus, our aim is to investigate the changes of global networks selectively affected by T2DM. METHODS A resting state functional network analysis was conducted to investigate the intrinsic functional connectivity in 37 patients with diabetes and 40 healthy controls who were recruited from local communities in Beijing, China. RESULTS We found that patients with T2DM exhibited cognitive function declines and functional connectivity disruptions within the default mode network, left frontal parietal network, and sensorimotor network. More importantly, the fasting glucose level was correlated with abnormal functional connectivity. CONCLUSION These findings could help to understand the neural mechanisms of cognitive impairments in T2DM and provide potential neuroimaging biomarkers that may be used for early diagnosis and intervention in cognitive decline.
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Affiliation(s)
- Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University , Beijing , China ; BABRI Centre, Beijing Normal University , Beijing , China
| | - Zhen Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University , Beijing , China ; BABRI Centre, Beijing Normal University , Beijing , China
| | - Junying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University , Beijing , China ; BABRI Centre, Beijing Normal University , Beijing , China
| | - Guihua Tian
- Dongzhimen Hospital, Beijing University of Chinese Medicine , Beijing , China
| | - Linzi Li
- School of Life Sciences, Fudan University , Shanghai , China
| | - Sisi Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University , Beijing , China ; BABRI Centre, Beijing Normal University , Beijing , China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University , Beijing , China ; BABRI Centre, Beijing Normal University , Beijing , China
| | - Kewei Chen
- BABRI Centre, Beijing Normal University , Beijing , China ; Banner Alzheimer's Institute , Phoenix, AZ , USA
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University , Beijing , China ; BABRI Centre, Beijing Normal University , Beijing , China
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Griffanti L, Dipasquale O, Laganà MM, Nemni R, Clerici M, Smith SM, Baselli G, Baglio F. Effective artifact removal in resting state fMRI data improves detection of DMN functional connectivity alteration in Alzheimer's disease. Front Hum Neurosci 2015; 9:449. [PMID: 26321937 PMCID: PMC4531245 DOI: 10.3389/fnhum.2015.00449] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Accepted: 07/28/2015] [Indexed: 01/01/2023] Open
Abstract
Artifact removal from resting state fMRI data is an essential step for a better identification of the resting state networks and the evaluation of their functional connectivity (FC), especially in pathological conditions. There is growing interest in the development of cleaning procedures, especially those not requiring external recordings (data-driven), which are able to remove multiple sources of artifacts. It is important that only inter-subject variability due to the artifacts is removed, preserving the between-subject variability of interest—crucial in clinical applications using clinical scanners to discriminate different pathologies and monitor their staging. In Alzheimer's disease (AD) patients, decreased FC is usually observed in the posterior cingulate cortex within the default mode network (DMN), and this is becoming a possible biomarker for AD. The aim of this study was to compare four different data-driven cleaning procedures (regression of motion parameters; regression of motion parameters, mean white matter and cerebrospinal fluid signal; FMRIB's ICA-based Xnoiseifier—FIX—cleanup with soft and aggressive options) on data acquired at 1.5 T. The approaches were compared using data from 20 elderly healthy subjects and 21 AD patients in a mild stage, in terms of their impact on within-group consistency in FC and ability to detect the typical FC alteration of the DMN in AD patients. Despite an increased within-group consistency across subjects after applying any of the cleaning approaches, only after cleaning with FIX the expected DMN FC alteration in AD was detectable. Our study validates the efficacy of artifact removal even in a relatively small clinical population, and supports the importance of cleaning fMRI data for sensitive detection of FC alterations in a clinical environment.
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Affiliation(s)
- Ludovica Griffanti
- IRCCS, Fondazione Don Carlo GnocchiMilan, Italy
- Department of Electronics, Information and Bioengineering, Politecnico di MilanoMilan, Italy
- Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional MRI of the Brain, University of OxfordOxford, UK
- *Correspondence: Ludovica Griffanti, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional MRI of the Brain, John Radcliffe Hospital, University of Oxford, Headley Way, Oxford, OX3 9DU, UK
| | - Ottavia Dipasquale
- IRCCS, Fondazione Don Carlo GnocchiMilan, Italy
- Department of Electronics, Information and Bioengineering, Politecnico di MilanoMilan, Italy
| | | | - Raffaello Nemni
- IRCCS, Fondazione Don Carlo GnocchiMilan, Italy
- Physiopatholgy Department, Università degli Studi di MilanoMilan, Italy
| | - Mario Clerici
- IRCCS, Fondazione Don Carlo GnocchiMilan, Italy
- Physiopatholgy Department, Università degli Studi di MilanoMilan, Italy
| | - Stephen M. Smith
- Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional MRI of the Brain, University of OxfordOxford, UK
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering, Politecnico di MilanoMilan, Italy
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Assessment of Functional Characteristics of Amnestic Mild Cognitive Impairment and Alzheimer's Disease Using Various Methods of Resting-State FMRI Analysis. BIOMED RESEARCH INTERNATIONAL 2015; 2015:907464. [PMID: 26180816 PMCID: PMC4477185 DOI: 10.1155/2015/907464] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2014] [Revised: 10/09/2014] [Accepted: 10/27/2014] [Indexed: 12/03/2022]
Abstract
Resting-state functional magnetic resonance imaging (RS FMRI) has been widely used to analyze functional alterations in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) patients. Although many clinical studies of aMCI and AD patients using RS FMRI have been undertaken, conducting a meta-analysis has not been easy because of seed selection bias by the investigators. The purpose of our study was to investigate the functional differences in aMCI and AD patients compared with healthy subjects in a meta-analysis. Thus, a multimethod approach using regional homogeneity, amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and global brain connectivity was used to investigate differences between three groups based on previously published data. According to the choice of RS FMRI approach used, the patterns of functional alteration were slightly different. Nevertheless, patients with aMCI and AD displayed consistently decreased functional characteristics with all approaches. All approaches showed that the functional characteristics in the left parahippocampal gyrus were decreased in AD patients compared with healthy subjects. Although some regions were slightly different according to the different RS FMRI approaches, patients with aMCI and AD showed a consistent pattern of decreased functional characteristics with all approaches.
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45
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Li HJ, Hou XH, Liu HH, Yue CL, He Y, Zuo XN. Toward systems neuroscience in mild cognitive impairment and Alzheimer's disease: a meta-analysis of 75 fMRI studies. Hum Brain Mapp 2014; 36:1217-32. [PMID: 25411150 DOI: 10.1002/hbm.22689] [Citation(s) in RCA: 136] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2014] [Revised: 10/03/2014] [Accepted: 11/03/2014] [Indexed: 11/11/2022] Open
Abstract
Most of the previous task functional magnetic resonance imaging (fMRI) studies found abnormalities in distributed brain regions in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and few studies investigated the brain network dysfunction from the system level. In this meta-analysis, we aimed to examine brain network dysfunction in MCI and AD. We systematically searched task-based fMRI studies in MCI and AD published between January 1990 and January 2014. Activation likelihood estimation meta-analyses were conducted to compare the significant group differences in brain activation, the significant voxels were overlaid onto seven referenced neuronal cortical networks derived from the resting-state fMRI data of 1,000 healthy participants. Thirty-nine task-based fMRI studies (697 MCI patients and 628 healthy controls) were included in MCI-related meta-analysis while 36 task-based fMRI studies (421 AD patients and 512 healthy controls) were included in AD-related meta-analysis. The meta-analytic results revealed that MCI and AD showed abnormal regional brain activation as well as large-scale brain networks. MCI patients showed hypoactivation in default, frontoparietal, and visual networks relative to healthy controls, whereas AD-related hypoactivation mainly located in visual, default, and ventral attention networks relative to healthy controls. Both MCI-related and AD-related hyperactivation fell in frontoparietal, ventral attention, default, and somatomotor networks relative to healthy controls. MCI and AD presented different pathological while shared similar compensatory large-scale networks in fulfilling the cognitive tasks. These system-level findings are helpful to link the fundamental declines of cognitive tasks to brain networks in MCI and AD.
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Affiliation(s)
- Hui-Jie Li
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
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Disruption of Resting Functional Connectivity in Alzheimer’s Patients and At-Risk Subjects. Curr Neurol Neurosci Rep 2014; 14:491. [DOI: 10.1007/s11910-014-0491-3] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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47
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Shi L, Wang D, Chu WCW, Liu S, Xiong Y, Wang Y, Wang Y, Wong LKS, Mok VCT. Abnormal organization of white matter network in patients with no dementia after ischemic stroke. PLoS One 2013; 8:e81388. [PMID: 24349063 PMCID: PMC3862493 DOI: 10.1371/journal.pone.0081388] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2013] [Accepted: 10/12/2013] [Indexed: 01/07/2023] Open
Abstract
Structural changes after ischemic stroke could affect information communication extensively in the brain network. It is likely that the defects in the white matter (WM) network play a key role in information interchange. In this study, we used graph theoretical analysis to examine potential organization alteration in the WM network architecture derived from diffusion tensor images from subjects with no dementia and experienced stroke in the past 5.4-14.8 months (N = 47, Mini-Mental Screening Examination, MMSE range 18-30), compared with a normal control group with 44 age and gender-matched healthy volunteers (MMSE range 26-30). Region-wise connectivity was derived from fiber connection density of 90 different cortical and subcortical parcellations across the whole brain. Both normal controls and patients with chronic stroke exhibited efficient small-world properties in their WM structural networks. Compared with normal controls, topological efficiency was basically unaltered in the patients with chronic stroke, as reflected by unchanged local and global clustering coefficient, characteristic path length, and regional efficiency. No significant difference in hub distribution was found between normal control and patient groups. Patients with chronic stroke, however, were found to have reduced betweenness centrality and predominantly located in the orbitofrontal cortex, whereas increased betweenness centrality and vulnerability were observed in parietal-occipital cortex. The National Institutes of Health Stroke Scale (NIHSS) score of patient is correlated with the betweenness centrality of right pallidum and local clustering coefficient of left superior occipital gyrus. Our findings suggest that patients with chronic stroke still exhibit efficient small-world organization and unaltered topological efficiency, with altered topology at orbitofrontal cortex and parietal-occipital cortex in the overall structural network. Findings from this study could help in understanding the mechanism of cognitive impairment and functional compensation occurred in patients with chronic stroke.
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Affiliation(s)
- Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Defeng Wang
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- CUHK Shenzhen Research Institute, Shenzhen, China
- * E-mail: (DW); (VCTM)
| | - Winnie C. W. Chu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Shangping Liu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Yunyun Xiong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lawrence K. S. Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
| | - Vincent C. T. Mok
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China
- * E-mail: (DW); (VCTM)
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Sandrone S. A DMN-based functional taxonomy of the resting human brain: Is essential really invisible to the eye? Brain Res Bull 2013; 99:A1-3. [DOI: 10.1016/j.brainresbull.2013.06.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2013] [Revised: 06/21/2013] [Accepted: 06/30/2013] [Indexed: 12/13/2022]
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