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Khokhar SK, Kumar M, Kumar S, Manae T, Thanissery N, Ramakrishnan S, Arshad F, Nagaraj C, Mangalore S, Alladi S, Gandhi TK, Bharath RD. Alzheimer's Disease Is Associated with Increased Network Assortativity: Evidence from Metabolic Connectivity. Brain Connect 2023; 13:610-620. [PMID: 37930734 DOI: 10.1089/brain.2023.0024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023] Open
Abstract
Introduction: Unraveling the network pathobiology in neurodegenerative disorders is a popular and promising field in research. We use a relatively newer network measure of assortativity in metabolic connectivity to understand network differences in patients with Alzheimer's Disease (AD), compared with those with mild cognitive impairment (MCI). Methods: Eighty-three demographically matched patients with dementia (56 AD and 27 MCI) who underwent positron emission tomography-magnetic resonance imaging (PET-MRI) study were recruited for this exploratory study. Global and nodal network measures obtained using the BRain Analysis using graPH theory toolbox were used to derive group-level differences (corrected p < 0.05). The methods were validated in age, and gender-matched 23 cognitively normal, 25 MCI, and 53 AD patients from the publicly available Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Regions that revealed significant differences were correlated with the Addenbrooke's Cognitive Examination-III (ACE-III) scores. Results: Patients with AD revealed significantly increased global assortativity compared with the MCI group. In addition, they also revealed increased modularity and decreased participation coefficient. These findings were validated in the ADNI data. We also found that the regional standard uptake values of the right superior parietal and left superior temporal lobes were proportional to the ACE-III memory subdomain scores. Conclusion: Global errors associated with network assortativity are found in patients with AD, making the networks more regular and less resilient. Since the regional measures of these network errors were proportional to memory deficits, these measures could be useful in understanding the network pathobiology in AD.
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Affiliation(s)
- Sunil Kumar Khokhar
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Manoj Kumar
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Sandeep Kumar
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Tejaswini Manae
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Nithin Thanissery
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Subasree Ramakrishnan
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Faheem Arshad
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Chandana Nagaraj
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Sandhya Mangalore
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Suvarna Alladi
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Tapan K Gandhi
- Department of Electrical Engineering, Indian Institute of Technology (IIT) Delhi, New Delhi, Delhi, India
| | - Rose Dawn Bharath
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
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2
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Li YL, Zheng MX, Hua XY, Gao X, Wu JJ, Shan CL, Zhang JP, Wei D, Xu JG. Cross-modality comparison between structural and metabolic networks in individual brain based on the Jensen-Shannon divergence method: a healthy Chinese population study. Brain Struct Funct 2023; 228:761-773. [PMID: 36749387 DOI: 10.1007/s00429-023-02616-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 01/25/2023] [Indexed: 02/08/2023]
Abstract
The study aimed to investigate the consistency and diversity between metabolic and structural brain networks at individual level constructed with divergence-based method in healthy Chinese population. The 18F-FDG PET and T1-weighted images of brain were collected from 209 healthy participants. The Jensen-Shannon divergence (JSD) was used to calculate metabolic or structural connectivities between any pair of brain regions and then individual brain networks were constructed. The global and regional topological properties of both networks were analyzed with graph theoretical analysis. Regional properties including nodal efficiency, degree, and betweenness centrality were used to define hub regions of networks. Cross-modality similarity of brain connectivity was analyzed with differential power (DP) analysis. The default mode network (DMN) had the largest number of brain connectivities with high DP values. The small-worldness indexes of metabolic and structural networks in all participants were greater than 1. The structural network showed higher assortativity and local efficiency than metabolic network, while hierarchy and global efficiency were greater in the metabolic network (all P < 0.001). Most of hubs in both networks were symmetrically spatial distributed in the regions of the DMN and subcortical nuclei including thalamus and amygdala, etc. The human brain presented small-world architecture both in perspective of individual metabolic and structural networks. There was a structural substrate that supported the brain to globally and efficiently integrate and process metabolic interaction across brain regions. The cross-modality cooperation or specialization in both networks might imply mechanisms of achieving higher-order brain functions.
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Affiliation(s)
- Yu-Lin Li
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, No.1200 Cailun Road, Shanghai, China
| | - Mou-Xiong Zheng
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xu-Yun Hua
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xin Gao
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China
| | - Jia-Jia Wu
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chun-Lei Shan
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, No.1200 Cailun Road, Shanghai, China.,Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
| | - Jun-Peng Zhang
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, No.1200 Cailun Road, Shanghai, China
| | - Dong Wei
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, No.1200 Cailun Road, Shanghai, China
| | - Jian-Guang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, No.1200 Cailun Road, Shanghai, China. .,Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
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3
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Perovnik M, Rus T, Schindlbeck KA, Eidelberg D. Functional brain networks in the evaluation of patients with neurodegenerative disorders. Nat Rev Neurol 2023; 19:73-90. [PMID: 36539533 DOI: 10.1038/s41582-022-00753-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/21/2022] [Indexed: 12/24/2022]
Abstract
Network analytical tools are increasingly being applied to brain imaging maps of resting metabolic activity (PET) or blood oxygenation-dependent signals (functional MRI) to characterize the abnormal neural circuitry that underlies brain diseases. This approach is particularly valuable for the study of neurodegenerative disorders, which are characterized by stereotyped spread of pathology along discrete neural pathways. Identification and validation of disease-specific brain networks facilitate the quantitative assessment of pathway changes over time and during the course of treatment. Network abnormalities can often be identified before symptom onset and can be used to track disease progression even in the preclinical period. Likewise, network activity can be modulated by treatment and might therefore be used as a marker of efficacy in clinical trials. Finally, early differential diagnosis can be achieved by simultaneously measuring the activity levels of multiple disease networks in an individual patient's scans. Although these techniques were originally developed for PET, over the past several years analogous methods have been introduced for functional MRI, a more accessible non-invasive imaging modality. This advance is expected to broaden the application of network tools to large and diverse patient populations.
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Affiliation(s)
- Matej Perovnik
- Department of Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia.,Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Tomaž Rus
- Department of Neurology, University Medical Center Ljubljana, Ljubljana, Slovenia.,Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | | | - David Eidelberg
- Center for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY, USA.
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4
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Habich A, Wahlund LO, Westman E, Dierks T, Ferreira D. (Dis-)Connected Dots in Dementia with Lewy Bodies-A Systematic Review of Connectivity Studies. Mov Disord 2023; 38:4-15. [PMID: 36253921 PMCID: PMC10092805 DOI: 10.1002/mds.29248] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/04/2022] [Accepted: 09/12/2022] [Indexed: 01/21/2023] Open
Abstract
Studies on dementia with Lewy bodies (DLB) have mainly focused on the degeneration of distinct cortical and subcortical regions related to the deposition of Lewy bodies. In view of the proposed trans-synaptic spread of the α-synuclein pathology, investigating the disease only in this segregated fashion would be detrimental to our understanding of its progression. In this systematic review, we summarize findings on structural and functional brain connectivity in DLB, as connectivity measures may offer better insights on how the brain is affected by the spread of the pathology. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Web of Science, PubMed, and SCOPUS for relevant articles published up to November 1, 2021. Of 1215 identified records, we selected and systematically reviewed 53 articles that compared connectivity features between patients with DLB and healthy controls. Structural and functional magnetic resonance imaging, positron emission tomography, single-positron emission computer tomography, and electroencephalography assessments of patients revealed widespread abnormalities within and across brain networks in DLB. Frontoparietal, default mode, and visual networks and their connections to other brain regions featured the most consistent disruptions, which were also associated with core clinical features and cognitive impairments. Furthermore, graph theoretical measures revealed disease-related decreases in local and global network efficiency. This systematic review shows that structural and functional connectivity characteristics in DLB may be particularly valuable at early stages, before overt brain atrophy can be observed. This knowledge may help improve the diagnosis and prognosis in DLB as well as pinpoint targets for future disease-modifying treatments. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Annegret Habich
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Lars-Olof Wahlund
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Thomas Dierks
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
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5
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Li YL, Wu JJ, Ma J, Li SS, Xue X, Wei D, Shan CL, Hua XY, Zheng MX, Xu JG. Alteration of the Individual Metabolic Network of the Brain Based on Jensen-Shannon Divergence Similarity Estimation in Elderly Patients With Type 2 Diabetes Mellitus. Diabetes 2022; 71:894-905. [PMID: 35133397 DOI: 10.2337/db21-0600] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 02/03/2022] [Indexed: 11/13/2022]
Abstract
The aim of this study was to investigate the interactive effect between aging and type 2 diabetes mellitus (T2DM) on brain glucose metabolism, individual metabolic connectivity, and network properties. Using a 2 × 2 factorial design, 83 patients with T2DM (40 elderly and 43 middle-aged) and 69 sex-matched healthy control subjects (HCs) (34 elderly and 35 middle-aged) underwent 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance scanning. Jensen-Shannon divergence was applied to construct individual metabolic connectivity and networks. The topological properties of the networks were quantified using graph theoretical analysis. The general linear model was used to mainly estimate the interaction effect between aging and T2DM on glucose metabolism, metabolic connectivity, and network. There was an interaction effect between aging and T2DM on glucose metabolism, metabolic connectivity, and regional metabolic network properties (all P < 0.05). The post hoc analyses showed that compared with elderly HCs and middle-aged patients with T2DM, elderly patients with T2DM had decreased glucose metabolism, increased metabolic connectivity, and regional metabolic network properties in cognition-related brain regions (all P < 0.05). Age and fasting plasma glucose had negative correlations with glucose metabolism and positive correlations with metabolic connectivity. Elderly patients with T2DM had glucose hypometabolism, strengthened functional integration, and increased efficiency of information communication mainly located in cognition-related brain regions. Metabolic connectivity pattern changes might be compensatory changes for glucose hypometabolism.
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Affiliation(s)
- Yu-Lin Li
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jia-Jia Wu
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jie Ma
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Si-Si Li
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xin Xue
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Dong Wei
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chun-Lei Shan
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
| | - Xu-Yun Hua
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Mou-Xiong Zheng
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jian-Guang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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6
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Chen KT, Ho TY, Siow TY, Yeh YC, Huang SY. OUP accepted manuscript. Cereb Cortex Commun 2022; 3:tgac008. [PMID: 35281215 PMCID: PMC8914218 DOI: 10.1093/texcom/tgac008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 02/08/2022] [Indexed: 11/12/2022] Open
Affiliation(s)
- Ko-Ting Chen
- Department of Neurosurgery, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
- School of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
| | - Tsung-Ying Ho
- Department of Nuclear Medicine and Molecular Imaging Center, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan 333, Taiwan
| | - Tiing-Yee Siow
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
| | - Yu-Chiang Yeh
- Department of Neurosurgery, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
| | - Sheng-Yao Huang
- Corresponding author: Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan.
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7
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Soni N, Ora M, Bathla G, Nagaraj C, Boles Ponto LL, Graham MM, Saini J, Menda Y. Multiparametric magnetic resonance imaging and positron emission tomography findings in neurodegenerative diseases: Current status and future directions. Neuroradiol J 2021; 34:263-288. [PMID: 33666110 PMCID: PMC8447818 DOI: 10.1177/1971400921998968] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Neurodegenerative diseases (NDDs) are characterized by progressive neuronal loss, leading to dementia and movement disorders. NDDs broadly include Alzheimer's disease, frontotemporal lobar degeneration, parkinsonian syndromes, and prion diseases. There is an ever-increasing prevalence of mild cognitive impairment and dementia, with an accompanying immense economic impact, prompting efforts aimed at early identification and effective interventions. Neuroimaging is an essential tool for the early diagnosis of NDDs in both clinical and research settings. Structural, functional, and metabolic imaging modalities, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are widely available. They show encouraging results for diagnosis, monitoring, and treatment response evaluation. The current review focuses on the complementary role of various imaging modalities in relation to NDDs, the qualitative and quantitative utility of newer MRI techniques, novel radiopharmaceuticals, and integrated PET/MRI in the setting of NDDs.
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Affiliation(s)
- Neetu Soni
- University of Iowa Hospitals and Clinics, USA
| | - Manish Ora
- Department of Nuclear Medicine, SGPGIMS, India
| | - Girish Bathla
- Neuroradiology Department, University of Iowa Hospitals and
Clinics, USA
| | - Chandana Nagaraj
- Department of Neuro Imaging and Interventional Radiology,
NIMHANS, India
| | | | - Michael M Graham
- Division of Nuclear Medicine, University of Iowa Hospitals and
Clinics, USA
| | - Jitender Saini
- Department of Neuro Imaging and Interventional Radiology,
NIMHANS, India
| | - Yusuf Menda
- University of Iowa Hospitals and Clinics, USA
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8
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Carli G, Tondo G, Boccalini C, Perani D. Brain Molecular Connectivity in Neurodegenerative Conditions. Brain Sci 2021; 11:brainsci11040433. [PMID: 33800680 PMCID: PMC8067093 DOI: 10.3390/brainsci11040433] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 03/15/2021] [Accepted: 03/23/2021] [Indexed: 12/28/2022] Open
Abstract
Positron emission tomography (PET) allows for the in vivo assessment of early brain functional and molecular changes in neurodegenerative conditions, representing a unique tool in the diagnostic workup. The increased use of multivariate PET imaging analysis approaches has provided the chance to investigate regional molecular processes and long-distance brain circuit functional interactions in the last decade. PET metabolic and neurotransmission connectome can reveal brain region interactions. This review is an overview of concepts and methods for PET molecular and metabolic covariance assessment with evidence in neurodegenerative conditions, including Alzheimer’s disease and Lewy bodies disease spectrum. We highlight the effects of environmental and biological factors on brain network organization. All of the above might contribute to innovative diagnostic tools and potential disease-modifying interventions.
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Affiliation(s)
- Giulia Carli
- School of Psychology, Vita-Salute San Raffaele University, 20121 Milan, Italy; (G.C.); (G.T.); (C.B.)
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20121 Milan, Italy
| | - Giacomo Tondo
- School of Psychology, Vita-Salute San Raffaele University, 20121 Milan, Italy; (G.C.); (G.T.); (C.B.)
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20121 Milan, Italy
| | - Cecilia Boccalini
- School of Psychology, Vita-Salute San Raffaele University, 20121 Milan, Italy; (G.C.); (G.T.); (C.B.)
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20121 Milan, Italy
| | - Daniela Perani
- School of Psychology, Vita-Salute San Raffaele University, 20121 Milan, Italy; (G.C.); (G.T.); (C.B.)
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20121 Milan, Italy
- Nuclear Medicine Unit, San Raffaele Hospital, 20121 Milan, Italy
- Correspondence: ; Tel.: +39-02-26432224
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9
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Role of [18F]-FDG PET in patients with atypical parkinsonism associated with dementia. Clin Transl Imaging 2020. [DOI: 10.1007/s40336-020-00360-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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