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Qiu T, Liu ZQ, Rheault F, Legarreta JH, Valcourt Caron A, St-Onge F, Strikwerda-Brown C, Metz A, Dadar M, Soucy JP, Pichet Binette A, Spreng RN, Descoteaux M, Villeneuve S. Structural white matter properties and cognitive resilience to tau pathology. Alzheimers Dement 2024. [PMID: 38561254 DOI: 10.1002/alz.13776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 01/11/2024] [Accepted: 02/07/2024] [Indexed: 04/04/2024]
Abstract
INTRODUCTION We assessed whether macro- and/or micro-structural white matter properties are associated with cognitive resilience to Alzheimer's disease pathology years prior to clinical onset. METHODS We examined whether global efficiency, an indicator of communication efficiency in brain networks, and diffusion measurements within the limbic network and default mode network moderate the association between amyloid-β/tau pathology and cognitive decline. We also investigated whether demographic and health/risk factors are associated with white matter properties. RESULTS Higher global efficiency of the limbic network, as well as free-water corrected diffusion measures within the tracts of both networks, attenuated the impact of tau pathology on memory decline. Education, age, sex, white matter hyperintensities, and vascular risk factors were associated with white matter properties of both networks. DISCUSSION White matter can influence cognitive resilience against tau pathology, and promoting education and vascular health may enhance optimal white matter properties. HIGHLIGHTS Aβ and tau were associated with longitudinal memory change over ∼7.5 years. White matter properties attenuated the impact of tau pathology on memory change. Health/risk factors were associated with white matter properties.
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Affiliation(s)
- Ting Qiu
- Douglas Mental Health University Institute, Montreal, Canada
| | - Zhen-Qi Liu
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - François Rheault
- Medical Imaging and NeuroInformatics Lab, Université de Sherbrooke, Sherbrooke, Canada
| | - Jon Haitz Legarreta
- Department of Radiology, Brigham and Women's Hospital, Mass General Brigham/Harvard Medical School, Boston, Massachusetts, USA
| | - Alex Valcourt Caron
- Sherbrooke Connectivity Imaging Laboratory, Université de Sherbrooke, Sherbrooke, Canada
| | | | - Cherie Strikwerda-Brown
- Douglas Mental Health University Institute, Montreal, Canada
- School of Psychological Science, The University of Western Australia, Perth, Australia
| | - Amelie Metz
- Douglas Mental Health University Institute, Montreal, Canada
| | - Mahsa Dadar
- Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Jean-Paul Soucy
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - R Nathan Spreng
- Douglas Mental Health University Institute, Montreal, Canada
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory, Université de Sherbrooke, Sherbrooke, Canada
| | - Sylvia Villeneuve
- Douglas Mental Health University Institute, Montreal, Canada
- Department of Psychiatry, McGill University, Montreal, Canada
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Eldaief MC, Brickhouse M, Katsumi Y, Rosen H, Carvalho N, Touroutoglou A, Dickerson BC. Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks. Brain 2023; 146:4476-4485. [PMID: 37201288 PMCID: PMC10629759 DOI: 10.1093/brain/awad167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 04/10/2023] [Accepted: 04/16/2023] [Indexed: 05/20/2023] Open
Abstract
The identification of a neurodegenerative disorder's distributed pattern of atrophy-or atrophy 'signature'-can lend insights into the cortical networks that degenerate in individuals with specific constellations of symptoms. In addition, this signature can be used as a biomarker to support early diagnoses and to potentially reveal pathological changes associated with said disorder. Here, we characterized the cortical atrophy signature of behavioural variant frontotemporal dementia (bvFTD). We used a data-driven approach to estimate cortical thickness using surface-based analyses in two independent, sporadic bvFTD samples (n = 30 and n = 71, total n = 101), using age- and gender-matched cognitively and behaviourally normal individuals. We found highly similar patterns of cortical atrophy across the two independent samples, supporting the reliability of our bvFTD signature. Next, we investigated whether our bvFTD signature targets specific large-scale cortical networks, as is the case for other neurodegenerative disorders. We specifically asked whether the bvFTD signature topographically overlaps with the salience network, as previous reports have suggested. We hypothesized that because phenotypic presentations of bvFTD are diverse, this would not be the case, and that the signature would cross canonical network boundaries. Consistent with our hypothesis, the bvFTD signature spanned rostral portions of multiple networks, including the default mode, limbic, frontoparietal control and salience networks. We then tested whether the signature comprised multiple anatomical subtypes, which themselves overlapped with specific networks. To explore this, we performed a hierarchical clustering analysis. This yielded three clusters, only one of which extensively overlapped with a canonical network (the limbic network). Taken together, these findings argue against the hypothesis that the salience network is preferentially affected in bvFTD, but rather suggest that-at least in patients who meet diagnostic criteria for the full-blown syndrome-neurodegeneration in bvFTD encompasses a distributed set of prefrontal, insular and anterior temporal nodes of multiple large-scale brain networks, in keeping with the phenotypic diversity of this disorder.
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Affiliation(s)
- Mark C Eldaief
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Michael Brickhouse
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Yuta Katsumi
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Howard Rosen
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Nicole Carvalho
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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3
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Ren Y, Liu Y, Zhao X, Hu W, Wei Z, Tang Z, Luo J, Li M, Guo K, Wu Y, Yang J. Hair Cortisone Predicts Lower Stress-induced Salivary Cortisol Response: Resting-state Functional Connectivity Between Salience and Limbic Networks. Neuroscience 2023; 517:61-69. [PMID: 36924986 DOI: 10.1016/j.neuroscience.2023.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 03/04/2023] [Accepted: 03/08/2023] [Indexed: 03/15/2023]
Abstract
Previous studies revealed that high long-term hypothalamic-pituitaryadrenal (HPA) axis activity measured by the hair cortisol concentrations predicts lower acute stress cortisol response and reported the influences of hair cortisol on brain activity during acute stress exposure. However, considering that long-term HPA axis activity has a close relationship with the brain's resting-state functional connectivity (RSFC), the current study aimed to explore the role of RSFC between limbic and salience network in this relationship. Seventy-seven healthy participants underwent resting-state imaging scans before performing the acute ScanSTRESS task. Saliva samples were collected to assess the levels of acute stress salivary cortisol. Hair samples were also collected, and the corticosteroid concentration extracted from these samples were used as a biomarker of long-term HPA axis activity. High hair cortisone (HairE) levels predicted lower acute stress cortisol response. Moreover, high HairE levels were significantly correlated with enhanced RSFC between limbic and salience networks, while RSFC was negatively associated with acute stress cortisol response. Importantly, the RSFC between left insula and left parahippocampus mediated the association between HairE and acute cortisol stress response. Taken together, this study uncovers the important role of RSFC between salience and limbic networks in the long-term relationship between HairE and acute cortisol response and contributes to a deeper understanding of the individual differences in acute stress response.
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Affiliation(s)
- Yipeng Ren
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Yadong Liu
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Xiaolin Zhao
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Weiyu Hu
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Zhenni Wei
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Zihan Tang
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Jiahao Luo
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Mengyi Li
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Kaige Guo
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China
| | - Yan Wu
- Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing, China
| | - Juan Yang
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Southwest University, Chongqing, China.
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Baker AE, Tashjian SM, Goldenberg D, Galván A. Sleep variability over a 2-week period is associated with restfulness and intrinsic limbic network connectivity in adolescents. Sleep 2023; 46:zsac248. [PMID: 36223429 PMCID: PMC9905777 DOI: 10.1093/sleep/zsac248] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 09/20/2022] [Indexed: 11/05/2022] Open
Abstract
STUDY OBJECTIVES Sleep duration and intraindividual variability in sleep duration undergo substantial changes in adolescence and impact brain and behavioral functioning. Although experimental work has linked acute sleep deprivation to heightened limbic responding and reduced regulatory control, there is limited understanding of how variability in sleep patterns might interact with sleep duration to influence adolescent functioning. This is important for optimal balancing of length and consistency of sleep. Here, we investigated how objective indices of sleep duration and variability relate to stress, restfulness, and intrinsic limbic network functioning in adolescents. METHODS A sample of 101 adolescents ages 14-18 reported their stressors, after which they wore wrist actigraph watches to monitor their sleep and rated their restfulness every morning over a 2-week period. They also completed a resting-state fMRI scan. RESULTS Adolescents reporting more stress experienced shorter sleep duration and greater sleep variability over the 2-week period. Longer nightly sleep duration was linked to feeling more rested the next morning, but this effect was reduced in adolescents with high cumulative sleep variability. Sleep variability showed both linear and quadratic effects on limbic connectivity: adolescents with high sleep variability exhibited more connectivity within the limbic network and less connectivity between the limbic and frontoparietal networks than their peers, effects which became stronger once variability exceeded an hour. CONCLUSIONS Results suggest that cumulative sleep variability is related to stress and limbic network connectivity and shows interactive effects with sleep duration, highlighting the importance of balancing length and consistency of sleep for optimal functioning in adolescence.
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Affiliation(s)
- Amanda E Baker
- Department of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90095, USA
| | - Sarah M Tashjian
- Department of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90095, USA
| | - Diane Goldenberg
- Department of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90095, USA
| | - Adriana Galván
- Department of Psychology, University of California, Los Angeles, 502 Portola Plaza, Los Angeles, CA 90095, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA 90095, USA
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5
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Zhang T, Xie X, Li Q, Zhang L, Chen Y, Ji GJ, Hou Q, Li T, Zhu C, Tian Y, Wang K. Hypogyrification in Generalized Anxiety Disorder and Associated with Insomnia Symptoms. Nat Sci Sleep 2022; 14:1009-1019. [PMID: 35642211 PMCID: PMC9148579 DOI: 10.2147/nss.s358763] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 05/03/2022] [Indexed: 01/04/2023] Open
Abstract
PURPOSE Insomnia is a recognized feature of generalized anxiety disorder (GAD). The underlying neural substrate of insomnia in GAD is still unclear. Cortical folding is a reliable index and possibly an endophenotype of psychiatric disease. The aim of this study was to explore whether the aberrant cortical morphology was associated with insomnia in GAD. PATIENTS AND METHODS We enrolled 73 patients with GAD and 74 matched healthy controls (HCs) to undergo neuropsychiatric assessment and 3.0 T magnetic resonance imaging scanning. Neuropsychiatric batteries included the 14-item Hamilton Anxiety Rating Scale (HAMA) and the Insomnia Severity Index (ISI). Using FreeSurfer7.1.1, we calculated local gyrification index, cortical thickness and surface area and identified group differences in these parameters. Then, we calculated the functional connectivity of these identified regions and determined functional alterations. The relationship between these neuroimaging indicators and clinical measurement was explored. RESULTS Compared with HCs, the LGI in the bilateral orbitofrontal cortex (OFC), bilateral insula, left middle frontal gyrus, left temporal pole, and left fusiform area was significantly decreased in GAD. GAD patients had concurrent decreased surface area in the left OFC and thicker right OFC. GAD patients also exhibited increased functional connectivity between the left insula and frontoparietal control network. In addition, a negative relationship was observed between decreased LGI in these limbic regions and ISI score. CONCLUSION GAD patients presented aberrant cortical folding in limbic network. Cortical morphology is a potential endophenotype in GAD, corresponding to an insomnia phenotype.
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Affiliation(s)
- Ting Zhang
- Department of Psychiatry, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, People's Republic of China
| | - Xiaohui Xie
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, People's Republic of China.,Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China
| | - Qianqian Li
- Department of Psychiatry, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, People's Republic of China
| | - Lei Zhang
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, People's Republic of China.,School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province, People's Republic of China.,Department of Psychiatry, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China
| | - Yue Chen
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China
| | - Gong-Jun Ji
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, People's Republic of China.,School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province, People's Republic of China
| | - Qiangqiang Hou
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, People's Republic of China.,Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China
| | - Tianxia Li
- Anhui Mental Health Center, Hefei, Anhui Province, People's Republic of China
| | - Chunyan Zhu
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, People's Republic of China.,School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province, People's Republic of China.,Department of Psychiatry, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China
| | - Yanghua Tian
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China.,Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, People's Republic of China
| | - Kai Wang
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, Anhui Province, People's Republic of China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, People's Republic of China.,Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui Province, People's Republic of China.,School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui Province, People's Republic of China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, People's Republic of China
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6
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Quattrini G, Marizzoni M, Pizzini FB, Galazzo IB, Aiello M, Didic M, Soricelli A, Albani D, Romano M, Blin O, Forloni G, Golay X, Jovicich J, Nathan PJ, Richardson JC, Salvatore M, Frisoni GB, Pievani M. Convergent and Discriminant Validity of Default Mode Network and Limbic Network Perfusion in Amnestic Mild Cognitive Impairment Patients. J Alzheimers Dis 2021; 82:1797-1808. [PMID: 34219733 DOI: 10.3233/jad-210531] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Previous studies reported default mode network (DMN) and limbic network (LIN) brain perfusion deficits in patients with amnestic mild cognitive impairment (aMCI), frequently a prodromal stage of Alzheimer's disease (AD). However, the validity of these measures as AD markers has not yet been tested using MRI arterial spin labeling (ASL). OBJECTIVE To investigate the convergent and discriminant validity of DMN and LIN perfusion in aMCI. METHODS We collected core AD markers (amyloid-β 42 [Aβ42], phosphorylated tau 181 levels in cerebrospinal fluid [CSF]), neurodegenerative (hippocampal volumes and CSF total tau), vascular (white matter hyperintensities), genetic (apolipoprotein E [APOE] status), and cognitive features (memory functioning on Paired Associate Learning test [PAL]) in 14 aMCI patients. Cerebral blood flow (CBF) was extracted from DMN and LIN using ASL and correlated with AD features to assess convergent validity. Discriminant validity was assessed carrying out the same analysis with AD-unrelated features, i.e., somatomotor and visual networks' perfusion, cerebellar volume, and processing speed. RESULTS Perfusion was reduced in the DMN (F = 5.486, p = 0.039) and LIN (F = 12.678, p = 0.004) in APOE ɛ4 carriers compared to non-carriers. LIN perfusion correlated with CSF Aβ42 levels (r = 0.678, p = 0.022) and memory impairment (PAL, number of errors, r = -0.779, p = 0.002). No significant correlation was detected with tau, neurodegeneration, and vascular features, nor with AD-unrelated features. CONCLUSION Our results support the validity of DMN and LIN ASL perfusion as AD markers in aMCI, indicating a significant correlation between CBF and amyloidosis, APOE ɛ4, and memory impairment.
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Affiliation(s)
- Giulia Quattrini
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Laboratory of Biological Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Francesca B Pizzini
- Radiology, Department of Diagnostic and Public Health, University of Verona, Verona, Italy
| | | | | | - Mira Didic
- Aix-Marseille Univ, INSERM, INS, Instit Neurosci des Syst, Marseille, France.,APHM, Timone, Service de Neurologie et Neuropsychologie, Hôpital Timone Adultes, Marseille, France
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Sport Sciences, University of Naples Parthenope, Naples, Italy
| | - Diego Albani
- Neuroscience Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Melissa Romano
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Olivier Blin
- Aix-Marseille Univ, INSERM, INS, Instit Neurosci des Syst, DHUNE, Ap-Hm, Marseille, France
| | - Gianluigi Forloni
- Neuroscience Department, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jorge Jovicich
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Pradeep J Nathan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Jill C Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Gunnels Wood Road, Stevenage, United Kingdom
| | | | - Giovanni B Frisoni
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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7
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Sunaga M, Takei Y, Kato Y, Tagawa M, Suto T, Hironaga N, Ohki T, Takahashi Y, Fujihara K, Sakurai N, Ujita K, Tsushima Y, Fukuda M. Frequency-Specific Resting Connectome in Bipolar Disorder: An MEG Study. Front Psychiatry 2020; 11:597. [PMID: 32670117 PMCID: PMC7330711 DOI: 10.3389/fpsyt.2020.00597] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 06/09/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Bipolar disorder (BD) is a serious psychiatric disorder that is associated with a high suicide rate, and for which no clinical biomarker has yet been identified. To address this issue, we investigated the use of magnetoencephalography (MEG) as a new prospective tool. MEG has been used to evaluate frequency-specific connectivity between brain regions; however, no previous study has investigated the frequency-specific resting-state connectome in patients with BD. This resting-state MEG study explored the oscillatory representations of clinical symptoms of BD via graph analysis. METHODS In this prospective case-control study, 17 patients with BD and 22 healthy controls (HCs) underwent resting-state MEG and evaluations for depressive and manic symptoms. After estimating the source current distribution, orthogonalized envelope correlations between multiple brain regions were evaluated for each frequency band. We separated regions-of-interest into seven left and right network modules, including the frontoparietal network (FPN), limbic network (LM), salience network (SAL), and default mode network (DMN), to compare the intra- and inter-community edges between the two groups. RESULTS In the BD group, we found significantly increased inter-community edges of the right LM-right DMN at the gamma band, and decreased inter-community edges of the right SAL-right FPN at the delta band and the left SAL-right SAL at the theta band. Intra-community edges in the left LM at the high beta band were significantly higher in the BD group than in the HC group. The number of connections in the left LM at the high beta band showed positive correlations with the subjective and objective depressive symptoms in the BD group. CONCLUSION We introduced graph theory into resting-state MEG studies to investigate the functional connectivity in patients with BD. To the best of our knowledge, this is a novel approach that may be beneficial in the diagnosis of BD. This study describes the spontaneous oscillatory brain networks that compensate for the time-domain issues associated with functional magnetic resonance imaging. These findings suggest that the connectivity of the LM at the beta band may be a good objective biological biomarker of the depressive symptoms associated with BD.
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Affiliation(s)
- Masakazu Sunaga
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yuichi Takei
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yutaka Kato
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan.,Tsutsuji Mental Hospital, Tatebayashi, Japan
| | - Minami Tagawa
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan.,Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
| | - Tomohiro Suto
- Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
| | - Naruhito Hironaga
- Brain Center, Faculty of Medicine, Kyushu University, Fukuoka, Japan
| | - Takefumi Ohki
- Department of Neurosurgery, Osaka University Medical School, Suita, Japan
| | - Yumiko Takahashi
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kazuyuki Fujihara
- Department of Genetic and Behavioral Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Noriko Sakurai
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Koichi Ujita
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yoshito Tsushima
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Masato Fukuda
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
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Qi Z, An Y, Zhang M, Li HJ, Lu J. Altered Cerebro-Cerebellar Limbic Network in AD Spectrum: A Resting-State fMRI Study. Front Neural Circuits 2019; 13:72. [PMID: 31780903 PMCID: PMC6851020 DOI: 10.3389/fncir.2019.00072] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 10/17/2019] [Indexed: 12/05/2022] Open
Abstract
Recent evidence suggests that the cerebellum is related to motor and non-motor cognitive functions, and that several coupled cerebro-cerebellar networks exist, including links with the limbic network. Since several limbic structures are affected by Alzheimer pathology, even in the preclinical stages of Alzheimer’s disease (AD), we aimed to investigate the cerebral limbic network activity from the perspective of the cerebellum. Twenty patients with mild cognitive impairment (MCI), 18 patients with AD, and 26 healthy controls (HC) were recruited to acquire Resting-state functional MRI (rs-fMRI). We used seed-based approach to construct the cerebro-cerebellar limbic network. Two-sample t-tests were carried out to explore the differences of the cerebellar limbic network connectivity. The first result, a sub-scale network including the bilateral posterior part of the orbitofrontal cortex (POFC) extending to the anterior insular cortex (AIC) and left inferior parietal lobule (L-IPL), showed greater functional connectivity in MCI than in HC and less functional connectivity in AD than in MCI. The location of this sub-scale network was in accordance with components of the ventral attention network. Second, there was decreased functional connectivity to the right mid-cingulate cortex (MCC) in the AD and MCI patient groups relative to the HC group. As the cerebellum is not compromised by Alzheimer pathology in the prodromal stage of AD, this pattern indicates that the sub-scale ventral attention network may play a pivotal role in functional compensation through the coupled cerebro-cerebellar limbic network in MCI, and the cerebellum may be a key node in the modulation of social cognition.
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Affiliation(s)
- Zhigang Qi
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yanhong An
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Mo Zhang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Hui-Jie Li
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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Kim SM, Park SY, Kim YI, Son YD, Chung US, Min KJ, Han DH. Affective network and default mode network in depressive adolescents with disruptive behaviors. Neuropsychiatr Dis Treat 2016; 12:49-56. [PMID: 26770059 PMCID: PMC4706123 DOI: 10.2147/ndt.s95541] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
AIM Disruptive behaviors are thought to affect the progress of major depressive disorder (MDD) in adolescents. In resting-state functional connectivity (RSFC) studies of MDD, the affective network (limbic network) and the default mode network (DMN) have garnered a great deal of interest. We aimed to investigate RSFC in a sample of treatment-naïve adolescents with MDD and disruptive behaviors. METHODS Twenty-two adolescents with MDD and disruptive behaviors (disrup-MDD) and 20 age- and sex-matched healthy control (HC) participants underwent resting-state functional magnetic resonance imaging (fMRI). We used a seed-based correlation approach concerning two brain circuits including the affective network and the DMN, with two seed regions including the bilateral amygdala for the limbic network and the bilateral posterior cingulate cortex (PCC) for the DMN. We also observed a correlation between RSFC and severity of depressive symptoms and disruptive behaviors. RESULTS The disrup-MDD participants showed lower RSFC from the amygdala to the orbitofrontal cortex and parahippocampal gyrus compared to HC participants. Depression scores in disrup-MDD participants were negatively correlated with RSFC from the amygdala to the right orbitofrontal cortex. The disrup-MDD participants had higher PCC RSFC compared to HC participants in a cluster that included the left precentral gyrus, left insula, and left parietal lobe. Disruptive behavior scores in disrup-MDD patients were positively correlated with RSFC from the PCC to the left insular cortex. CONCLUSION Depressive mood might be correlated with the affective network, and disruptive behavior might be correlated with the DMN in adolescent depression.
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Affiliation(s)
- Sun Mi Kim
- Department of Psychiatry, School of Medicine, Chung-Ang University, Seoul, South Korea
| | - Sung Yong Park
- Department of Psychiatry, School of Medicine, Chung-Ang University, Seoul, South Korea
| | - Young In Kim
- Department of Psychiatry, School of Medicine, Chung-Ang University, Seoul, South Korea
| | - Young Don Son
- Department of Biomedical Engineering, Gachon University of Medicine and Science, Incheon, South Korea
| | - Un-Sun Chung
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, South Korea; School Mental Health Resources and Research Center, Kyungpook National University Children's Hospital, Daegu, South Korea
| | - Kyung Joon Min
- Department of Psychiatry, School of Medicine, Chung-Ang University, Seoul, South Korea
| | - Doug Hyun Han
- Department of Psychiatry, School of Medicine, Chung-Ang University, Seoul, South Korea
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Chou YH, You H, Wang H, Zhao YP, Hou B, Chen NK, Feng F. Effect of Repetitive Transcranial Magnetic Stimulation on fMRI Resting-State Connectivity in Multiple System Atrophy. Brain Connect 2015; 5:451-9. [PMID: 25786196 PMCID: PMC4575511 DOI: 10.1089/brain.2014.0325] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique that has been used to treat neurological and psychiatric conditions. Although results of rTMS intervention are promising, so far, little is known about the rTMS effect on brain functional networks in clinical populations. In this study, we used a whole-brain connectivity analysis of resting-state functional magnetic resonance imaging data to uncover changes in functional connectivity following rTMS intervention and their association with motor symptoms in patients with multiple system atrophy (MSA). Patients were randomized to active rTMS or sham rTMS groups and completed a 10-session 5-Hz rTMS treatment over the left primary motor area. The results showed significant rTMS-related changes in motor symptoms and functional connectivity. Specifically, (1) significant improvement of motor symptoms was observed in the active rTMS group, but not in the sham rTMS group; and (2) several functional links involving the default mode, cerebellar, and limbic networks exhibited positive changes in functional connectivity in the active rTMS group. Moreover, the positive changes in functional connectivity were associated with improvement in motor symptoms for the active rTMS group. The present findings suggest that rTMS may improve motor symptoms by modulating functional links connecting to the default mode, cerebellar, and limbic networks, inferring a future therapeutic candidate for patients with MSA.
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Affiliation(s)
- Ying-hui Chou
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, North Carolina
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, North Carolina
| | - Hui You
- Department of Radiology, Peking Union Medical College Hospital, Beijing, China
| | - Han Wang
- Department of Neurology, Peking Union Medical College Hospital, Beijing, China
| | - Yan-Ping Zhao
- Department of Radiology, Peking Union Medical College Hospital, Beijing, China
| | - Bo Hou
- Department of Radiology, Peking Union Medical College Hospital, Beijing, China
| | - Nan-kuei Chen
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, North Carolina
- Department of Radiology, Duke University Medical Center, Durham, North Carolina
| | - Feng Feng
- Department of Radiology, Peking Union Medical College Hospital, Beijing, China
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