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Zhang X, Zeng Q, Wang Y, Jin Y, Qiu T, Li K, Luo X, Wang S, Xu X, Liu X, Zhao S, Li Z, Hong L, Li J, Zhong S, Zhang T, Huang P, Zhang B, Zhang M, Chen Y. Alteration of functional connectivity network in population of objectively-defined subtle cognitive decline. Brain Commun 2024; 6:fcae033. [PMID: 38425749 PMCID: PMC10903975 DOI: 10.1093/braincomms/fcae033] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 01/10/2024] [Accepted: 02/08/2024] [Indexed: 03/02/2024] Open
Abstract
The objectively-defined subtle cognitive decline individuals had higher progression rates of cognitive decline and pathological deposition than healthy elderly, indicating a higher risk of progressing to Alzheimer's disease. However, little is known about the brain functional alterations during this stage. Thus, we aimed to investigate the functional network patterns in objectively-defined subtle cognitive decline cohort. Forty-two cognitive normal, 29 objectively-defined subtle cognitive decline and 55 mild cognitive impairment subjects were included based on neuropsychological measures from the Alzheimer's disease Neuroimaging Initiative dataset. Thirty cognitive normal, 22 objectively-defined subtle cognitive declines and 48 mild cognitive impairment had longitudinal MRI data. The degree centrality and eigenvector centrality for each participant were calculated by using resting-state functional MRI. For cross-sectional data, analysis of covariance was performed to detect between-group differences in degree centrality and eigenvector centrality after controlling age, sex and education. For longitudinal data, repeated measurement analysis of covariance was used for comparing the alterations during follow-up period among three groups. In order to classify the clinical significance, we correlated degree centrality and eigenvector centrality values to Alzheimer's disease biomarkers and cognitive function. The results of analysis of covariance showed significant between-group differences in eigenvector centrality and degree centrality in left superior temporal gyrus and left precuneus, respectively. Across groups, the eigenvector centrality value of left superior temporal gyrus was positively related to recognition scores in auditory verbal learning test, whereas the degree centrality value of left precuneus was positively associated with mini-mental state examination total score. For longitudinal data, the results of repeated measurement analysis of covariance indicated objectively-defined subtle cognitive decline group had the highest declined rate of both eigenvector centrality and degree centrality values than other groups. Our study showed an increased brain functional connectivity in objectively-defined subtle cognitive decline individuals at both local and global level, which were associated with Alzheimer's disease pathology and neuropsychological assessment. Moreover, we also observed a faster declined rate of functional network matrix in objectively-defined subtle cognitive decline individuals during the follow-ups.
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Affiliation(s)
- Xinyi Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Yanbo Wang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Yu Jin
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Tiantian Qiu
- Department of Radiology, Linyi People’s Hospital, 276003, Linyi, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Shuai Zhao
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Zheyu Li
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Luwei Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Jixuan Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Siyan Zhong
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Tianyi Zhang
- Department of Neurology, The First Affiliated Hospital of Zhejiang University School of Medicine, 310003, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 310009, Hangzhou, China
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Invernizzi A, Renzetti S, van Thriel C, Rechtman E, Patrono A, Ambrosi C, Mascaro L, Cagna G, Gasparotti R, Reichenberg A, Tang CY, Lucchini RG, Wright RO, Placidi D, Horton MK. Covid-19 related cognitive, structural and functional brain changes among Italian adolescents and young adults: a multimodal longitudinal case-control study. medRxiv 2023:2023.07.19.23292909. [PMID: 37503251 PMCID: PMC10371098 DOI: 10.1101/2023.07.19.23292909] [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] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Coronavirus disease 2019 (COVID-19) has been associated with brain functional, structural, and cognitive changes that persist months after infection. Most studies of the neurologic outcomes related to COVID-19 focus on severe infection and aging populations. Here, we investigated the neural activities underlying COVID-19 related outcomes in a case-control study of mildly infected youth enrolled in a longitudinal study in Lombardy, Italy, a global hotspot of COVID-19. All participants (13 cases, 27 controls, mean age 24 years) completed resting state functional (fMRI), structural MRI, cognitive assessments (CANTAB spatial working memory) at baseline (pre-COVID) and follow-up (post-COVID). Using graph theory eigenvector centrality (EC) and data-driven statistical methods, we examined differences in ECdelta (i.e., the difference in EC values pre- and post-COVID-19) and volumetricdelta (i.e., the difference in cortical volume of cortical and subcortical areas pre- and post-COVID) between COVID-19 cases and controls. We found that ECdeltasignificantly between COVID-19 and healthy participants in five brain regions; right intracalcarine cortex, right lingual gyrus, left hippocampus, left amygdala, left frontal orbital cortex. The left hippocampus showed a significant decrease in volumetricdelta between groups (p=0.041). The reduced ECdelta in the right amygdala associated with COVID-19 status mediated the association between COVID-19 and disrupted spatial working memory. Our results show persistent structural, functional and cognitive brain changes in key brain areas associated with olfaction and cognition. These results may guide treatment efforts to assess the longevity, reversibility and impact of the observed brain and cognitive changes following COVID-19.
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Affiliation(s)
- Azzurra Invernizzi
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stefano Renzetti
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Christoph van Thriel
- Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Elza Rechtman
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alessandra Patrono
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Claudia Ambrosi
- Department of Neuroscience, Neuroradiology Unit, ASST Cremona
| | | | - Giuseppa Cagna
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Roberto Gasparotti
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Abraham Reichenberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Cheuk Y Tang
- Department of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Roberto G Lucchini
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
- Department of Environmental Health Sciences, Robert Stempel College of Public Health and Social Work, Florida International University, Miami, FL, United States
| | - Robert O Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Donatella Placidi
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Megan K Horton
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Ke M, Li H, Liu G. The Local Topological Reconfiguration in the Brain Network After Targeted Hub Dysfunction Attacks in Patients With Juvenile Myoclonic Epilepsy. Front Neurosci 2022; 16:864040. [PMID: 35495041 PMCID: PMC9047017 DOI: 10.3389/fnins.2022.864040] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 03/15/2022] [Indexed: 11/16/2022] Open
Abstract
The central brain regions of brain networks have been extensively studied in terms of their roles in various diseases. This study provides a direct measure of the brain's responses to targeted attacks on central regions, revealing the critical role these regions play in patients with juvenile myoclonic epilepsy (JME). The resting-state data of 37 patients with JME and 37 healthy subjects were collected, and brain functional networks were constructed for the two groups of data according to their Pearson correlation coefficients. The left middle cingulate gyrus was defined as the central brain region by the eigenvector centrality algorithm and was attacked by the CLM sequential failure model. The rich-club connection differences between the patients with JME and healthy controls before and after the attacks were compared according to graph theory indices and the number of rich-club connections. We found that the numbers of rich connections in the brain networks of the healthy control group and the group of patients with JME were significantly reduced [p < 0.05, false discovery rate (FDR) correction] before the CLM sequential failure attacks, and no significant differences were observed between the feeder connections and local connections. In the healthy control group, significant rich connection differences were obtained (p < 0.01, FDR correction), and no statistically significant differences were observed regarding the feeder connections and local connections in the brain network before and after CLM failure attacks on the central brain region. No significant differences were obtained between the rich connections, feeder connections, and local connections in patients with JME before and after CLM successive failure attacks on the central brain area. The rich connections, feeder connections, and local connections were not significantly different in the brain networks of the healthy control group and the group of patients with JME after CLM successive failure attacks on the central brain region. We concluded that the damage to the left middle cingulate gyrus is closely linked to various brain disorders, suggesting that this region is of great importance for understanding the pathophysiological basis of myoclonic seizures in patients with JME.
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Affiliation(s)
- Ming Ke
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Huimin Li
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China
| | - Guangyao Liu
- Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China
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Chen B. A Preliminary Study of Abnormal Centrality of Cortical Regions and Subsystems in Whole Brain Functional Connectivity of Autism Spectrum Disorder Boys. Clin EEG Neurosci 2022; 53:3-11. [PMID: 34152841 DOI: 10.1177/15500594211026282] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The abnormal cortices of autism spectrum disorder (ASD) brains are uncertain. However, the pathological alterations of ASD brains are distributed throughout interconnected cortical systems. Functional connections (FCs) methodology identifies cooperation and separation characteristics of information process in macroscopic cortical activity patterns under the context of network neuroscience. Embracing the graph theory concepts, this paper introduces eigenvector centrality index (EC score) ground on the FCs, and further develops a new framework for researching the dysfunctional cortex of ASD in holism significance. The important process is to uncover noticeable regions and subsystems endowed with antagonistic stance in EC-scores of 26 ASD boys and 28 matched healthy controls (HCs). For whole brain regional EC scores of ASD boys, orbitofrontal superior medial cortex, insula R, posterior cingulate gyrus L, and cerebellum 9 L are endowed with different EC scores significantly. In the brain subsystems level, EC scores of DMN, prefrontal lobe, and cerebellum are aberrant in the ASD boys. Generally, the EC scores display widespread distribution of diseased regions in ASD brains. Meanwhile, the discovered regions and subsystems, such as MPFC, AMYG, INS, prefrontal lobe, and DMN, are engaged in social processing. Meanwhile, the CBCL externalizing problem scores are associated with EC scores.
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Affiliation(s)
- Bo Chen
- 12626Hangzhou Dianzi University, Hangzhou, Zhejiang, PR China
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5
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Luo X, Hong H, Wang S, Li K, Zeng Q, Hong L, Liu X, Li Z, Fu Y, Jiaerken Y, Xu X, Yu X, Huang P, Zhang M. Exploration of the Mechanism Underlying the Association of Incident Microinfarct and Motor Deficit: A Preliminary Functional MRI Study. J Alzheimers Dis 2021; 85:1545-1554. [PMID: 34958031 DOI: 10.3233/jad-215227] [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] [Indexed: 11/15/2022]
Abstract
BACKGROUND Cerebral microinfarcts (CMIs) might cause measurable disruption to brain connections and are associated with cognitive decline, but the association between CMIs and motor impairment is still unclear. OBJECTIVE To assess the CMIs effect on motor function in vivo and explore the potential neuropathological mechanism based on graph-based network method. METHODS We identified 133 non-demented middle-aged and elderly participants who underwent MRI scanning, cognitive, and motor assessment. The short physical performance battery (SPPB) assessed motor function, including balance, walking speed, and chair stand. We grouped participants into 34 incident CMIs carriers and 99 non-CMIs carriers as controls, depending on diffusion-weighted imaging. Then we assessed the independent CMIs effects on motor function and explored neural mechanisms of CMIs on motor impairment via mapping of degree centrality (DC) and eigenvector centrality (EC). RESULTS CMIs carriers had worse motor function than non-carriers. Linear regression analyses showed that CMIs independently contributed to motor function. CMIs carriers had decreased EC in the precuneus, while increased DC and EC in the middle temporal gyrus and increased DC in the inferior frontal gyrus compared to controls (p < 0.05, corrected). Correlation analyses showed that EC of precuneus was related to SPPB (r = 0.25) and balance (r = 0.27); however, DC (r = -0.25) and EC (r = -0.25) of middle temporal gyrus was related with SPPB in all participants (p < 0.05, corrected). CONCLUSION CMIs represent an independent risk factor for motor dysfunction. The relationship between CMIs and motor function may be attributed to suppression of functional hub region and compensatory activation of motor-related regions.
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Affiliation(s)
- Xiao Luo
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The 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, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Luwei Hong
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zheyu Li
- Department of Neurology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yanv Fu
- Department of Neurology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - XiaoPei Xu
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xinfeng Yu
- Department of Radiology, The 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, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Ingala S, Tomassen J, Collij LE, Prent N, van 't Ent D, Ten Kate M, Konijnenberg E, Yaqub M, Scheltens P, de Geus EJC, Teunissen CE, Tijms B, Wink AM, Barkhof F, van Berckel BNM, Visser PJ, den Braber A. Amyloid-driven disruption of default mode network connectivity in cognitively healthy individuals. Brain Commun 2021; 3:fcab201. [PMID: 34617016 PMCID: PMC8490784 DOI: 10.1093/braincomms/fcab201] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [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: 09/15/2020] [Revised: 04/06/2021] [Accepted: 05/03/2021] [Indexed: 12/03/2022] Open
Abstract
Cortical accumulation of amyloid beta is one of the first events of Alzheimer’s disease pathophysiology, and has been suggested to follow a consistent spatiotemporal ordering, starting in the posterior cingulate cortex, precuneus and medio-orbitofrontal cortex. These regions overlap with those of the default mode network, a brain network also involved in memory functions. Aberrant default mode network functional connectivity and higher network sparsity have been reported in prodromal and clinical Alzheimer’s disease. We investigated the association between amyloid burden and default mode network connectivity in the preclinical stage of Alzheimer’s disease and its association with longitudinal memory decline. We included 173 participants, in which amyloid burden was assessed both in CSF by the amyloid beta 42/40 ratio, capturing the soluble part of amyloid pathology, and in dynamic PET scans calculating the non-displaceable binding potential in early-stage regions. The default mode network was identified with resting-state functional MRI. Then, we calculated functional connectivity in the default mode network, derived from independent component analysis, and eigenvector centrality, a graph measure recursively defining important nodes on the base of their connection with other important nodes. Memory was tested at baseline, 2- and 4-year follow-up. We demonstrated that higher amyloid burden as measured by both CSF amyloid beta 42/40 ratio and non-displaceable binding potential in the posterior cingulate cortex was associated with lower functional connectivity in the default mode network. The association between amyloid burden (CSF and non-displaceable binding potential in the posterior cingulate cortex) and aberrant default mode network connectivity was confirmed at the voxel level with both functional connectivity and eigenvector centrality measures, and it was driven by voxel clusters localized in the precuneus, cingulate, angular and left middle temporal gyri. Moreover, we demonstrated that functional connectivity in the default mode network predicts longitudinal memory decline synergistically with regional amyloid burden, as measured by non-displaceable binding potential in the posterior cingulate cortex. Taken together, these results suggest that early amyloid beta deposition is associated with aberrant default mode network connectivity in cognitively healthy individuals and that default mode network connectivity markers can be used to identify subjects at risk of memory decline.
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Affiliation(s)
- Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Naomi Prent
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Faculty of Behavioral and Movement Sciences, Section Clinical Neuropsychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.,Vesalius, Centre for Neuropsychiatry, GGZ Altrecht, 3447 GM Woerden, The Netherlands
| | - Dennis van 't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Mara Ten Kate
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Elles Konijnenberg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, Neurochemistry Laboratory, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
| | - Betty Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Institute of Neurology and Healthcare Engineering, University College London, WC1E 6BT London, UK
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
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7
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Zalmijn E, Heskes T, Claassen T. Spectral Ranking of Causal Influence in Complex Systems. Entropy (Basel) 2021; 23:369. [PMID: 33804599 DOI: 10.3390/e23030369] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 03/09/2021] [Accepted: 03/16/2021] [Indexed: 11/23/2022]
Abstract
Similar to natural complex systems, such as the Earth’s climate or a living cell, semiconductor lithography systems are characterized by nonlinear dynamics across more than a dozen orders of magnitude in space and time. Thousands of sensors measure relevant process variables at appropriate sampling rates, to provide time series as primary sources for system diagnostics. However, high-dimensionality, non-linearity and non-stationarity of the data are major challenges to efficiently, yet accurately, diagnose rare or new system issues by merely using model-based approaches. To reliably narrow down the causal search space, we validate a ranking algorithm that applies transfer entropy for bivariate interaction analysis of a system’s multivariate time series to obtain a weighted directed graph, and graph eigenvector centrality to identify the system’s most important sources of original information or causal influence. The results suggest that this approach robustly identifies the true drivers or causes of a complex system’s deviant behavior, even when its reconstructed information transfer network includes redundant edges.
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Abstract
SARS-CoV-2 main protease is one of the major targets in drug development efforts against Covid-19. Even though several structures were reported to date, its dynamics is not understood well. In particular, impact of dimerization and ligand binding on the dynamics is an important issue to investigate. In this study, we performed molecular dynamics simulations of SARS-CoV and SARS-CoV-2 main proteases to investigate influence of dimerization on the dynamics by modeling monomeric and dimeric apo and holo forms. The dimerization causes an organization of the interdomain dynamics as well as some local structural changes. Moreover, we investigated impact of a peptide mimetic (N3) on the dynamics of SARS-CoV and SARS-CoV-2 Mpro. The ligand binding to the dimeric forms causes some key local changes at the dimer interface and it causes an allosteric interaction between the active sites of two protomers. Our results support the idea that only one protomer is active on SARS-CoV-2 due to this allosteric interaction. Additionally, we analyzed the molecular dynamics trajectories from graph theoretical perspective and found that the most influential residues – as measured by eigenvector centrality – are a group of residues in active site and dimeric interface of the protease. This study may form a bridge between what we know about the dynamics of SARS-CoV and SARS-CoV-2 Mpro. We think that enlightening allosteric communication of the active sites and the role of dimerization in SARS-CoV-2 Mpro can contribute to development of novel drugs against this global health problem as well as other similar proteases. Communicated by Ramaswamy H. Sarma
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Affiliation(s)
- Mustafa Tekpinar
- Unit of Structural Dynamics of Biological Macromolecules, Pasteur Institute, UMR 3528 CNRS, Paris, France
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9
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Cao F, Guan X, Ma Y, Shao Y, Zhong J. Altered Functional Network Associated With Cognitive Performance in Early Parkinson Disease Measured by Eigenvector Centrality Mapping. Front Aging Neurosci 2020; 12:554660. [PMID: 33178007 PMCID: PMC7596167 DOI: 10.3389/fnagi.2020.554660] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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: 04/22/2020] [Accepted: 09/11/2020] [Indexed: 02/01/2023] Open
Abstract
Objective: To investigate relationships between whole-brain functional changes and the performance of multiple cognitive functions in early Parkinson’s disease (PD). Methods: In the current study, we evaluated resting-state functional MRI (rsfMRI) data and neuropsychological assessments for various cognitive functions in a cohort with 84 early PD patients from the Parkinson’s Progression Markers Initiative (PPMI). Eigenvector centrality (EC) mapping based on rsfMRI was used to identify the functional connectivity of brain areas correlated with different neuropsychological scores at a whole-brain level. Results: Our study demonstrated that in the early PD patients, scores of Letter Number Sequencing (LNS) were positively correlated with EC in the left inferior occipital gyrus (IOG) and lingual gyrus. The immediate recall scores of Hopkins Verbal Learning Test-Revised (HVLT-R) were positively correlated with EC in the left superior frontal gyrus. No correlation was found between the EC and other cognitive performance scores. Conclusions: Functional alternations in the left occipital lobe (inferior occipital and lingual gyrus) and left superior frontal gyrus may account for the performance of working memory and immediate recall memory, respectively in early PD. These results may broaden the understanding of the potential mechanism of cognitive impairments in early PD.
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Affiliation(s)
- Fang Cao
- Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Xiaojun Guan
- Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yanqing Ma
- Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Yuan Shao
- Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Jianguo Zhong
- Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
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Athira K, Gopakumar G. An integrated method for identifying essential proteins from multiplex network model of protein-protein interactions. J Bioinform Comput Biol 2020; 18:2050020. [PMID: 32795133 DOI: 10.1142/s0219720020500201] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [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: 12/12/2022]
Abstract
Cell survival requires the presence of essential proteins. Detection of essential proteins is relevant not only because of the critical biological functions they perform but also the role played by them as a drug target against pathogens. Several computational techniques are in place to identify essential proteins based on protein-protein interaction (PPI) network. Essential protein detection using only physical interaction data of proteins is challenging due to its inherent uncertainty. Hence, in this work, we propose a multiplex network-based framework that incorporates multiple protein interaction data from their physical, coexpression and phylogenetic profiles. An extended version termed as multiplex eigenvector centrality (MEC) is used to identify essential proteins from this network. The methodology integrates the score obtained from the multiplex analysis with subcellular localization and Gene Ontology information and is implemented using Saccharomyces cerevisiae datasets. The proposed method outperformed many recent essential protein prediction techniques in the literature.
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Affiliation(s)
- K Athira
- Department of Computer Science and Engineering, National Institute of Technology Calicut, Kozhikkode, Kerala 673601, India
| | - G Gopakumar
- Department of Computer Science and Engineering, National Institute of Technology Calicut, Kozhikkode, Kerala 673601, India
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11
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Wu M, He S, Zhang Y, Chen J, Sun Y, Liu YY, Zhang J, Poor HV. A tensor-based framework for studying eigenvector multicentrality in multilayer networks. Proc Natl Acad Sci U S A 2019; 116:15407-15413. [PMID: 31315978 PMCID: PMC6681706 DOI: 10.1073/pnas.1801378116] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [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: 11/18/2022] Open
Abstract
Centrality is widely recognized as one of the most critical measures to provide insight into the structure and function of complex networks. While various centrality measures have been proposed for single-layer networks, a general framework for studying centrality in multilayer networks (i.e., multicentrality) is still lacking. In this study, a tensor-based framework is introduced to study eigenvector multicentrality, which enables the quantification of the impact of interlayer influence on multicentrality, providing a systematic way to describe how multicentrality propagates across different layers. This framework can leverage prior knowledge about the interplay among layers to better characterize multicentrality for varying scenarios. Two interesting cases are presented to illustrate how to model multilayer influence by choosing appropriate functions of interlayer influence and design algorithms to calculate eigenvector multicentrality. This framework is applied to analyze several empirical multilayer networks, and the results corroborate that it can quantify the influence among layers and multicentrality of nodes effectively.
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Affiliation(s)
- Mincheng Wu
- State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, Zhejiang, China
| | - Shibo He
- State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, Zhejiang, China;
| | - Yongtao Zhang
- State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, Zhejiang, China
| | - Jiming Chen
- State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, Zhejiang, China
| | - Youxian Sun
- State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, Zhejiang, China
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115
- Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA 02115
| | - Junshan Zhang
- School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287
| | - H Vincent Poor
- Department of Electrical Engineering, Princeton University, Princeton, NJ 08544
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12
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Negre CFA, Morzan UN, Hendrickson HP, Pal R, Lisi GP, Loria JP, Rivalta I, Ho J, Batista VS. Eigenvector centrality for characterization of protein allosteric pathways. Proc Natl Acad Sci U S A 2018; 115:E12201-8. [PMID: 30530700 DOI: 10.1073/pnas.1810452115] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Determining the principal energy-transfer pathways responsible for allosteric communication in biomolecules remains challenging, partially due to the intrinsic complexity of the systems and the lack of effective characterization methods. In this work, we introduce the eigenvector centrality metric based on mutual information to elucidate allosteric mechanisms that regulate enzymatic activity. Moreover, we propose a strategy to characterize the range of correlations that underlie the allosteric processes. We use the V-type allosteric enzyme imidazole glycerol phosphate synthase (IGPS) to test the proposed methodology. The eigenvector centrality method identifies key amino acid residues of IGPS with high susceptibility to effector binding. The findings are validated by solution NMR measurements yielding important biological insights, including direct experimental evidence for interdomain motion, the central role played by helix h[Formula: see text], and the short-range nature of correlations responsible for the allosteric mechanism. Beyond insights on IGPS allosteric pathways and the nature of residues that could be targeted by therapeutic drugs or site-directed mutagenesis, the reported findings demonstrate the eigenvector centrality analysis as a general cost-effective methodology to gain fundamental understanding of allosteric mechanisms at the molecular level.
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13
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Abstract
Objectives:Schizophrenia is a predominant product of pathological alterations distributed throughout interconnected neural systems. Functional connections (FCs) methodology is an effective lever to investigate macroscopic neural activity patterns underlying critical aspects of cognition and behaviour. However, region properties of brain architecture have been less investigated by special markers of dynamical graph in general mental disorders. Methods:Embracing the eigenvector centrality in holism significance, our important process is to uncover noticeable edges and regions with antagonistic stance between morbid and normal FCs of 67 healthy controls (HCs) and 53 chronic schizophrenia patients (SZs). Results: Results suggest that, there are 12 abnormal edges with significant p value of FCs weight, such as lingual gyrus L versus cuneus L, thalamus L versus middle frontal gyrus R, superior temporal gyrus R versus thalamus R. Importantly, SZs' superior temporal gyrus R, parahippocampal gyrus L and parahippocampal gyrus R are endowed with different eigenvector centrality scores. Conclusion: Consistent with SZs' positive symptoms of hallucinations, and negative symptoms of thinking impairment, it can be infer that the functional separation and integration are destroyed in schizophrenia. Thought the strict contrastive study, it is worth stressing that eigenvector centrality is a meaningful biological marker to excavating schizophrenic psychopathology.
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Affiliation(s)
- Bo Chen
- a School of Science , Hangzhou Dianzi University , Hangzhou , PR China
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14
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Wink AM, Tijms BM, Ten Kate M, Raspor E, de Munck JC, Altena E, Ecay-Torres M, Clerigue M, Estanga A, Garcia-Sebastian M, Izagirre A, Martinez-Lage Alvarez P, Villanua J, Barkhof F, Sanz-Arigita E. Functional brain network centrality is related to APOE genotype in cognitively normal elderly. Brain Behav 2018; 8:e01080. [PMID: 30136422 PMCID: PMC6160659 DOI: 10.1002/brb3.1080] [Citation(s) in RCA: 12] [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: 01/11/2018] [Revised: 06/20/2018] [Accepted: 06/25/2018] [Indexed: 01/19/2023] Open
Abstract
INTRODUCTION Amyloid plaque deposition in the brain is an early pathological change in Alzheimer's disease (AD), causing disrupted synaptic connections. Brain network disruptions in AD have been demonstrated with eigenvector centrality (EC), a measure that identifies central regions within networks. Carrying an apolipoprotein (APOE)-ε4 allele is a genetic risk for AD, associated with increased amyloid deposition. We studied whether APOE-ε4 carriership is associated with EC disruptions in cognitively normal individuals. METHODS A total of 261 healthy middle-aged to older adults (mean age 56.6 years) were divided into high-risk (APOE-ε4 carriers) and low-risk (noncarriers) groups. EC was computed from resting-state functional MRI data. Clusters of between-group differences were assessed with a permutation-based method. Correlations between cluster mean EC with brain volume, CSF biomarkers, and psychological test scores were assessed. RESULTS Decreased EC in the visual cortex was associated with APOE-ε4 carriership, a genetic risk factor for AD. EC differences were correlated with age, CSF amyloid levels, and scores on the trail-making and 15-object recognition tests. CONCLUSION Our findings suggest that the APOE-ε4 genotype affects brain connectivity in regions previously found to be abnormal in AD as a sign of very early disease-related pathology. These differences were too subtle in healthy elderly to use EC for single-subject prediction of APOE genotype.
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Affiliation(s)
- Alle Meije Wink
- Department of Radiology, Nuclear Medicine and PET Research, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Betty M Tijms
- Department of Neurology, Alzheimer Centre, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Mara Ten Kate
- Department of Neurology, Alzheimer Centre, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Eva Raspor
- Department of Radiology, Nuclear Medicine and PET Research, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Jan C de Munck
- Department of Physics and Medical Technology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Ellemarije Altena
- Université Bordeaux, Bordeaux, France.,CNRS, SANPSY, USR 3413, Bordeaux, France
| | - Mirian Ecay-Torres
- CITA Alzheimer Foundation, Donostia University Hospital, San Sebastian, Spain
| | - Montserrat Clerigue
- CITA Alzheimer Foundation, Donostia University Hospital, San Sebastian, Spain
| | - Ainara Estanga
- CITA Alzheimer Foundation, Donostia University Hospital, San Sebastian, Spain
| | | | - Andrea Izagirre
- CITA Alzheimer Foundation, Donostia University Hospital, San Sebastian, Spain
| | | | - Jorge Villanua
- CITA Alzheimer Foundation, Donostia University Hospital, San Sebastian, Spain.,Donostia Unit, Osatek, Donostia University Hospital, San Sebastian, Spain
| | - Frederik Barkhof
- Department of Radiology, Nuclear Medicine and PET Research, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Ernesto Sanz-Arigita
- Department of Radiology, Nuclear Medicine and PET Research, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands.,Université Bordeaux, Bordeaux, France
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Pawar S, Ashraf MI, Mujawar S, Mishra R, Lahiri C. In silico Identification of the Indispensable Quorum Sensing Proteins of Multidrug Resistant Proteus mirabilis. Front Cell Infect Microbiol 2018; 8:269. [PMID: 30131943 PMCID: PMC6090301 DOI: 10.3389/fcimb.2018.00269] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [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: 03/01/2018] [Accepted: 07/17/2018] [Indexed: 11/13/2022] Open
Abstract
Catheter-associated urinary tract infections (CAUTI) is an alarming hospital based disease with the increase of multidrug resistance (MDR) strains of Proteus mirabilis. Cases of long term hospitalized patients with multiple episodes of antibiotic treatments along with urinary tract obstruction and/or undergoing catheterization have been reported to be associated with CAUTI. The cases are complicated due to the opportunist approach of the pathogen having robust swimming and swarming capability. The latter giving rise to biofilms and probably inducible through autoinducers make the scenario quite complex. High prevalence of long-term hospital based CAUTI for patients along with moderate percentage of morbidity, cropping from ignorance about drug usage and failure to cure due to MDR, necessitates an immediate intervention strategy effective enough to combat the deadly disease. Several reports and reviews focus on revealing the important genes and proteins, essential to tackle CAUTI caused by P. mirabilis. Despite longitudinal countrywide studies and methodical strategies to circumvent the issues, effective means of unearthing the most indispensable proteins to target for therapeutic uses have been meager. Here, we report a strategic approach for identifying the most indispensable proteins from the genome of P. mirabilis strain HI4320, besides comparing the interactomes comprising the autoinducer-2 (AI-2) biosynthetic pathway along with other proteins involved in biofilm formation and responsible for virulence. Essentially, we have adopted a theoretical network model based approach to construct a set of small protein interaction networks (SPINs) along with the whole genome (GPIN) to computationally identify the crucial proteins involved in the phenomenon of quorum sensing (QS) and biofilm formation and thus, could be therapeutically targeted to fight out the MDR threats to antibiotics of P. mirabilis. Our approach utilizes the functional modularity coupled with k-core analysis and centrality scores of eigenvector as a measure to address the pressing issues.
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Affiliation(s)
- Shrikant Pawar
- Department of Computer Science, Georgia State University, Atlanta, GA, United States.,Department of Biology, Georgia State University, Atlanta, GA, United States
| | - Md Izhar Ashraf
- Department of Computer Applications, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India.,Theoretical Physics, The Institute of Mathematical Sciences, Chennai, India
| | - Shama Mujawar
- Department of Biological Sciences, Sunway University, Petaling Jaya, Malaysia
| | - Rohit Mishra
- Department of Bioinformatics, G.N. Khalsa College, University of Mumbai, Mumbai, India
| | - Chandrajit Lahiri
- Department of Biological Sciences, Sunway University, Petaling Jaya, Malaysia
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16
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Kolskår KK, Alnæs D, Kaufmann T, Richard G, Sanders AM, Ulrichsen KM, Moberget T, Andreassen OA, Nordvik JE, Westlye LT. Key Brain Network Nodes Show Differential Cognitive Relevance and Developmental Trajectories during Childhood and Adolescence. eNeuro 2018; 5:ENEURO. [PMID: 30073200 DOI: 10.1523/ENEURO.0092-18.2018] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 05/14/2018] [Accepted: 05/31/2018] [Indexed: 11/21/2022] Open
Abstract
Human adolescence is a period of rapid changes in cognition and goal-directed behavior, and it constitutes a major transitional phase towards adulthood. One of the mechanisms suggested to underlie the protracted maturation of functional brain networks, is the increased network integration and segregation enhancing neural efficiency. Importantly, the increasing coordinated network interplay throughout development is mediated through functional hubs, which are highly connected brain areas suggested to be pivotal nodes for the regulation of neural activity. To elucidate brain hub development during childhood and adolescence, we estimated voxel-wise eigenvector centrality (EC) using functional magnetic resonance imaging (fMRI) data from two different psychological contexts (resting state and a working memory task), in a large cross-sectional sample (n = 754) spanning the age from 8 to 22 years, and decomposed the maps using independent component analysis (ICA). Our results reveal significant age-related centrality differences in cingulo-opercular, visual, and sensorimotor network nodes during both rest and task performance, suggesting that common neurodevelopmental processes manifest across different mental states. Supporting the functional significance of these developmental patterns, the centrality of the cingulo-opercular node was positively associated with task performance. These findings provide evidence for protracted maturation of hub properties in specific nodes of the brain connectome during the course of childhood and adolescence and suggest that cingulo-opercular centrality is a key factor supporting neurocognitive development.
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17
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Lou W, Shi L, Wong A, Chu WCW, Mok VCT, Wang D. Changes of Cerebral Perfusion and Functional Brain Network Organization in Patients with Mild Cognitive Impairment. J Alzheimers Dis 2018; 54:397-409. [PMID: 27567823 DOI: 10.3233/jad-160201] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [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: 12/15/2022]
Abstract
Disruptions of the functional brain network and cerebral blood flow (CBF) have been revealed in patients with mild cognitive impairment (MCI). However, the neurophysiological mechanism of hypoperfusion as well as the reorganization of the intrinsic whole brain network due to the neuropathology of MCI are still unclear. In this study, we aimed to investigate the changes of CBF and the whole brain network organization in MCI by using a multimodal MRI approach. Resting state ASL MRI and BOLD MRI were used to evaluate disruptions of CBF and underlying functional connectivity in 27 patients with MCI and 35 cognitive normal controls (NC). The eigenvector centrality mapping (ECM) was used to assess the whole brain network reorganization in MCI, and a seed-based ECM approach was proposed to reveal the contributions of the whole brain network on the ECM alterations. Significantly decreased perfusion in the posterior parietal cortex as well as its connectivity within the default mode network and occipital cortex were found in the MCI group compared to the NC group. The ECM analysis revealed decreased EC in the middle cingulate cortex, parahippocampal gyrus, medial frontal gyrus, and increased EC in the right calcarine sulcus, superior temporal gyrus, and supplementary motor area in the MCI group. The results of this study indicate that there are deficits in cerebral blood flow and functional connectivity in the default mode network, and that sensory-processing networks might play a compensatory role to make up for the decreased connections in MCI.
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Affiliation(s)
- Wutao Lou
- Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR
| | - Lin Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR.,Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Adrian Wong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR
| | - Winnie C W Chu
- Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR.,Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
| | - Vincent C T Mok
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR.,Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Defeng Wang
- Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR.,Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
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18
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Youssofzadeh V, Williamson BJ, Kadis DS. Mapping Critical Language Sites in Children Performing Verb Generation: Whole-Brain Connectivity and Graph Theoretical Analysis in MEG. Front Hum Neurosci 2017; 11:173. [PMID: 28424604 PMCID: PMC5380724 DOI: 10.3389/fnhum.2017.00173] [Citation(s) in RCA: 17] [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: 01/31/2017] [Accepted: 03/22/2017] [Indexed: 11/13/2022] Open
Abstract
A classic left frontal-temporal brain network is known to support language processes. However, the level of participation of constituent regions, and the contribution of extra-canonical areas, is not fully understood; this is particularly true in children, and in individuals who have experienced early neurological insult. In the present work, we propose whole-brain connectivity and graph-theoretical analysis of magnetoencephalography (MEG) source estimates to provide robust maps of the pediatric expressive language network. We examined neuromagnetic data from a group of typically-developing young children (n = 15, ages 4–6 years) and adolescents (n = 14, 16–18 years) completing an auditory verb generation task in MEG. All source analyses were carried out using a linearly-constrained minimum-variance (LCMV) beamformer. Conventional differential analyses revealed significant (p < 0.05, corrected) low-beta (13–23 Hz) event related desynchrony (ERD) focused in the left inferior frontal region (Broca’s area) in both groups, consistent with previous studies. Connectivity analyses were carried out in broadband (3–30 Hz) on time-course estimates obtained at the voxel level. Patterns of connectivity were characterized by phase locking value (PLV), and network hubs identified through eigenvector centrality (EVC). Hub analysis revealed the importance of left perisylvian sites, i.e., Broca’s and Wernicke’s areas, across groups. The hemispheric distribution of frontal and temporal lobe EVC values was asymmetrical in most subjects; left dominant EVC was observed in 20% of young children, and 71% of adolescents. Interestingly, the adolescent group demonstrated increased critical sites in the right cerebellum, left inferior frontal gyrus (IFG) and left putamen. Here, we show that whole brain connectivity and network analysis can be used to map critical language sites in typical development; these methods may be useful for defining the margins of eloquent tissue in neurosurgical candidates.
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Affiliation(s)
- Vahab Youssofzadeh
- Pediatric Neuroimaging Research Consortium (PNRC), Cincinnati Children's Hospital Medical CenterCincinnati, OH, USA.,Division of Neurology, Cincinnati Children's Hospital Medical CenterCincinnati, OH, USA
| | - Brady J Williamson
- Pediatric Neuroimaging Research Consortium (PNRC), Cincinnati Children's Hospital Medical CenterCincinnati, OH, USA.,Department of Psychology, University of CincinnatiCincinnati, OH, USA
| | - Darren S Kadis
- Pediatric Neuroimaging Research Consortium (PNRC), Cincinnati Children's Hospital Medical CenterCincinnati, OH, USA.,Division of Neurology, Cincinnati Children's Hospital Medical CenterCincinnati, OH, USA.,College of Medicine, Department of Pediatrics, University of CincinnatiCincinnati, OH, USA
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Punzi M, Gili T, Petrosini L, Caltagirone C, Spalletta G, Sensi SL. Modafinil-Induced Changes in Functional Connectivity in the Cortex and Cerebellum of Healthy Elderly Subjects. Front Aging Neurosci 2017; 9:85. [PMID: 28424611 PMCID: PMC5371677 DOI: 10.3389/fnagi.2017.00085] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Accepted: 03/20/2017] [Indexed: 11/25/2022] Open
Abstract
In the past few years, cognitive enhancing drugs (CEDs) have gained growing interest and the focus of investigations aimed at exploring their use to potentiate the cognitive performances of healthy individuals. Most of this exploratory CED-related research has been performed on young adults. However, CEDs may also help to maintain optimal brain functioning or compensate for subtle and or subclinical deficits associated with brain aging or early-stage dementia. In this study, we assessed effects on resting state brain activity in a group of healthy elderly subjects undergoing acute administration of modafinil, a wakefulness-promoting agent. To that aim, participants (n = 24) were investigated with resting state functional Magnetic Resonance Imaging (rs-fMRI) before and after the administration of a single dose (100 mg) of modafinil. Effects were compared to age and size-matched placebo group. Rs-fMRI effects were assessed, employing a graph-based approach and Eigenvector Centrality (EC) analysis, by taking in account topological changes occurring in functional brain networks. The main finding of the study is that modafinil promotes enhanced centrality, a measure of the importance of nodes within functional networks, of the bilateral primary visual (V1) cortex. EC analysis also revealed that modafinil-treated subjects show increased functional connectivity between the V1 and specific cerebellar (Crus I, Crus II, VIIIa lobule) and frontal (right inferior frontal sulcus and left middle frontal gyrus) regions. Present findings provide functional data supporting the hypothesis that modafinil can modulate the cortico-cerebellar connectivity of the aging brain.
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Affiliation(s)
- Miriam Punzi
- Department of Neurosciences, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-PescaraChieti, Italy.,Molecular Neurology Unit, Center of Excellence on Aging and Translational Medicine (Ce.S.I.-Me.T.), "G. d'Annunzio" University of Chieti-PescaraChieti, Italy
| | - Tommaso Gili
- Museo Storico della Fisica e Centro Studi e Ricerche Enrico FermiRome, Italy.,Santa Lucia FoundationRome, Italy
| | - Laura Petrosini
- Santa Lucia FoundationRome, Italy.,Department of Psychology, Section of Neuroscience and "Daniel Bovet" Neurobiology Research Center, Sapienza University of RomeRome, Italy
| | - Carlo Caltagirone
- Santa Lucia FoundationRome, Italy.,Department of Medicine of Systems, University of Rome Tor VergataRome, Italy
| | | | - Stefano L Sensi
- Department of Neurosciences, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-PescaraChieti, Italy.,Molecular Neurology Unit, Center of Excellence on Aging and Translational Medicine (Ce.S.I.-Me.T.), "G. d'Annunzio" University of Chieti-PescaraChieti, Italy.,Departments of Neurology and Pharmacology, Institute for Mind Impairments and Neurological Disorders, University of California, Irvine, IrvineCA, USA
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20
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Hove MJ, Stelzer J, Nierhaus T, Thiel SD, Gundlach C, Margulies DS, Van Dijk KRA, Turner R, Keller PE, Merker B. Brain Network Reconfiguration and Perceptual Decoupling During an Absorptive State of Consciousness. Cereb Cortex 2015; 26:3116-24. [PMID: 26108612 DOI: 10.1093/cercor/bhv137] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [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: 11/13/2022] Open
Abstract
Trance is an absorptive state of consciousness characterized by narrowed awareness of external surroundings and has long been used-for example, by shamans-to gain insight. Shamans across cultures often induce trance by listening to rhythmic drumming. Using functional magnetic resonance imaging (fMRI), we examined the brain-network configuration associated with trance. Experienced shamanic practitioners (n = 15) listened to rhythmic drumming, and either entered a trance state or remained in a nontrance state during 8-min scans. We analyzed changes in network connectivity. Trance was associated with higher eigenvector centrality (i.e., stronger hubs) in 3 regions: posterior cingulate cortex (PCC), dorsal anterior cingulate cortex (dACC), and left insula/operculum. Seed-based analysis revealed increased coactivation of the PCC (a default network hub involved in internally oriented cognitive states) with the dACC and insula (control-network regions involved in maintaining relevant neural streams). This coactivation suggests that an internally oriented neural stream was amplified by the modulatory control network. Additionally, during trance, seeds within the auditory pathway were less connected, possibly indicating perceptual decoupling and suppression of the repetitive auditory stimuli. In sum, trance involved coactive default and control networks, and decoupled sensory processing. This network reconfiguration may promote an extended internal train of thought wherein integration and insight can occur.
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Affiliation(s)
- Michael J Hove
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Johannes Stelzer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Till Nierhaus
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany Neurocomputation and Neuroimaging Unit, Freie Universität Berlin, Berlin, Germany
| | - Sabrina D Thiel
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | - Daniel S Margulies
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | - Robert Turner
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Peter E Keller
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany The MARCS Institute, University of Western Sydney, Australia
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21
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Burns SP, Santaniello S, Yaffe RB, Jouny CC, Crone NE, Bergey GK, Anderson WS, Sarma SV. Network dynamics of the brain and influence of the epileptic seizure onset zone. Proc Natl Acad Sci U S A 2014; 111:E5321-30. [PMID: 25404339 DOI: 10.1073/pnas.1401752111] [Citation(s) in RCA: 176] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The human brain is a dynamic networked system. Patients with partial epileptic seizures have focal regions that periodically diverge from normal brain network dynamics during seizures. We studied the evolution of brain connectivity before, during, and after seizures with graph-theoretic techniques on continuous electrocorticographic (ECoG) recordings (5.4 ± 1.7 d per patient, mean ± SD) from 12 patients with temporal, occipital, or frontal lobe partial onset seizures. Each electrode was considered a node in a graph, and edges between pairs of nodes were weighted by their coherence within a frequency band. The leading eigenvector of the connectivity matrix, which captures network structure, was tracked over time and clustered to uncover a finite set of brain network states. Across patients, we found that (i) the network connectivity is structured and defines a finite set of brain states, (ii) seizures are characterized by a consistent sequence of states, (iii) a subset of nodes is isolated from the network at seizure onset and becomes more connected with the network toward seizure termination, and (iv) the isolated nodes may identify the seizure onset zone with high specificity and sensitivity. To localize a seizure, clinicians visually inspect seizures recorded from multiple intracranial electrode contacts, a time-consuming process that may not always result in definitive localization. We show that network metrics computed from all ECoG channels capture the dynamics of the seizure onset zone as it diverges from normal overall network structure. This suggests that a state space model can be used to help localize the seizure onset zone in ECoG recordings.
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Geerligs L, Saliasi E, Renken RJ, Maurits NM, Lorist MM. Flexible connectivity in the aging brain revealed by task modulations. Hum Brain Mapp 2014; 35:3788-804. [PMID: 24382835 PMCID: PMC6869581 DOI: 10.1002/hbm.22437] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2013] [Revised: 10/18/2013] [Accepted: 11/11/2013] [Indexed: 11/09/2022] Open
Abstract
Recent studies have shown that aging has a large impact on connectivity within and between functional networks. An open question is whether elderly still have the flexibility to adapt functional network connectivity (FNC) to the demands of the task at hand. To study this, we collected fMRI data in younger and older participants during resting state, a selective attention (SA) task and an n-back working memory task with varying levels of difficulty. Spatial independent component (IC) analysis was used to identify functional networks over all participants and all conditions. Dual regression was used to obtain participant and task specific time-courses per IC. Subsequently, functional connectivity was computed between all ICs in each of the tasks. Based on these functional connectivity matrices, a scaled version of the eigenvector centrality (SEC) was used to measure the total influence of each IC in the complete graph of ICs. The results demonstrated that elderly remain able to adapt FNC to task demands. However, there was an age-related shift in the impetus for FNC change. Older participants showed the maximal change in SEC patterns between resting state and the SA task. Young participants, showed the largest shift in SEC patterns between the less demanding SA task and the more demanding 2-back task. Our results suggest that increased FNC changes from resting state to low demanding tasks in elderly reflect recruitment of additional resources, compared with young adults. The lack of change between the low and high demanding tasks suggests that elderly reach a resource ceiling.
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Affiliation(s)
- Linda Geerligs
- Department of Experimental Psychology, Faculty of Behavioural and Social Sciences, University of Groningen, The Netherlands; Neuroimaging Center, University Medical Center Groningen, University of Groningen, The Netherlands
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Schmidt BT, Ghuman AS, Huppert TJ. Whole brain functional connectivity using phase locking measures of resting state magnetoencephalography. Front Neurosci 2014; 8:141. [PMID: 25018690 PMCID: PMC4071638 DOI: 10.3389/fnins.2014.00141] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [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: 10/30/2013] [Accepted: 05/20/2014] [Indexed: 01/11/2023] Open
Abstract
The analysis of spontaneous functional connectivity (sFC) reveals the statistical connections between regions of the brain consistent with underlying functional communication networks within the brain. In this work, we describe the implementation of a complete all-to-all network analysis of resting state neuronal activity from magnetoencephalography (MEG). Using graph theory to define networks at the dipole level, we established functionally defined regions by k-means clustering cortical surface locations using Eigenvector centrality (EVC) scores from the all-to-all adjacency model. Permutation testing was used to estimate regions with statistically significant connections compared to empty room data, which adjusts for spatial dependencies introduced by the MEG inverse problem. In order to test this model, we performed a series of numerical simulations investigating the effects of the MEG reconstruction on connectivity estimates. We subsequently applied the approach to subject data to investigate the effectiveness of our method in obtaining whole brain networks. Our findings indicated that our model provides statistically robust estimates of functional region networks. Application of our phase locking network methodology to real data produced networks with similar connectivity to previously published findings, specifically, we found connections between contralateral areas of the arcuate fasciculus that have been previously investigated. The use of data-driven methods for neuroscientific investigations provides a new tool for researchers in identifying and characterizing whole brain functional connectivity networks.
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Affiliation(s)
- Benjamin T Schmidt
- Department of Bioengineering, University of Pittsburgh Pittsburgh, PA, USA
| | - Avniel S Ghuman
- Departments of Neurosurgery and Neurobiology, University of Pittsburgh Pittsburgh, PA, USA
| | - Theodore J Huppert
- Department of Bioengineering, University of Pittsburgh Pittsburgh, PA, USA ; Department of Radiology, University of Pittsburgh Pittsburgh, PA, USA
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24
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Sargent J, Bedford A. Evaluating Australian football league player contributions using interactive network simulation. J Sports Sci Med 2013; 12:116-121. [PMID: 24149734 PMCID: PMC3761758] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2012] [Accepted: 01/10/2013] [Indexed: 06/02/2023]
Abstract
This paper focuses on the contribution of Australian Football League (AFL) players to their team's on-field network by simulating player interactions within a chosen team list and estimating the net effect on final score margin. A Visual Basic computer program was written, firstly, to isolate the effective interactions between players from a particular team in all 2011 season matches and, secondly, to generate a symmetric interaction matrix for each match. Negative binomial distributions were fitted to each player pairing in the Geelong Football Club for the 2011 season, enabling an interactive match simulation model given the 22 chosen players. Dynamic player ratings were calculated from the simulated network using eigenvector centrality, a method that recognises and rewards interactions with more prominent players in the team network. The centrality ratings were recorded after every network simulation and then applied in final score margin predictions so that each player's match contribution-and, hence, an optimal team-could be estimated. The paper ultimately demonstrates that the presence of highly rated players, such as Geelong's Jimmy Bartel, provides the most utility within a simulated team network. It is anticipated that these findings will facilitate optimal AFL team selection and player substitutions, which are key areas of interest to coaches. Network simulations are also attractive for use within betting markets, specifically to provide information on the likelihood of a chosen AFL team list "covering the line ". Key pointsA simulated interaction matrix for Australian Rules football players is proposedThe simulations were carried out by fitting unique negative binomial distributions to each player pairing in a sideEigenvector centrality was calculated for each player in a simulated matrix, then for the teamThe team centrality measure adequately predicted the team's winning marginA player's net effect on margin could hence be estimated by replacing him in the simulated side with another player.
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Affiliation(s)
- Jonathan Sargent
- School of Mathematical & Geospatial Sciences, RMIT University , Australia
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25
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Pandey A, Davis NA, White BC, Pajewski NM, Savitz J, Drevets WC, McKinney BA. Epistasis network centrality analysis yields pathway replication across two GWAS cohorts for bipolar disorder. Transl Psychiatry 2012; 2:e154. [PMID: 22892719 PMCID: PMC3432194 DOI: 10.1038/tp.2012.80] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [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: 12/11/2022] Open
Abstract
Most pathway and gene-set enrichment methods prioritize genes by their main effect and do not account for variation due to interactions in the pathway. A portion of the presumed missing heritability in genome-wide association studies (GWAS) may be accounted for through gene-gene interactions and additive genetic variability. In this study, we prioritize genes for pathway enrichment in GWAS of bipolar disorder (BD) by aggregating gene-gene interaction information with main effect associations through a machine learning (evaporative cooling) feature selection and epistasis network centrality analysis. We validate this approach in a two-stage (discovery/replication) pathway analysis of GWAS of BD. The discovery cohort comes from the Wellcome Trust Case Control Consortium (WTCCC) GWAS of BD, and the replication cohort comes from the National Institute of Mental Health (NIMH) GWAS of BD in European Ancestry individuals. Epistasis network centrality yields replicated enrichment of Cadherin signaling pathway, whose genes have been hypothesized to have an important role in BD pathophysiology but have not demonstrated enrichment in previous analysis. Other enriched pathways include Wnt signaling, circadian rhythm pathway, axon guidance and neuroactive ligand-receptor interaction. In addition to pathway enrichment, the collective network approach elevates the importance of ANK3, DGKH and ODZ4 for BD susceptibility in the WTCCC GWAS, despite their weak single-locus effect in the data. These results provide evidence that numerous small interactions among common alleles may contribute to the diathesis for BD and demonstrate the importance of including information from the network of gene-gene interactions as well as main effects when prioritizing genes for pathway analysis.
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Affiliation(s)
- A Pandey
- Tandy School of Computer Science, Department of Mathematics, University of Tulsa, Tulsa, OK, USA
| | - N A Davis
- Tandy School of Computer Science, Department of Mathematics, University of Tulsa, Tulsa, OK, USA
| | - B C White
- Tandy School of Computer Science, Department of Mathematics, University of Tulsa, Tulsa, OK, USA
| | - N M Pajewski
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - J Savitz
- Laureate Institute for Brain Research, Tulsa, OK, USA,Department of Medicine, Tulsa School of Community Medicine, University of Tulsa, Tulsa, OK, USA
| | - W C Drevets
- Laureate Institute for Brain Research, Tulsa, OK, USA,Department of Psychiatry, University of Oklahoma College of Medicine Tulsa, Tulsa, OK, USA
| | - B A McKinney
- Tandy School of Computer Science, Department of Mathematics, University of Tulsa, Tulsa, OK, USA,Laureate Institute for Brain Research, Tulsa, OK, USA,Tandy School of Computer Science, Department of Mathematics, University of Tulsa, Rayzor Hall, 800 South Tucker Drive, Tulsa, OK 74104, USA. E-mail:
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Bilal E, Alexe G, Yao M, Cong L, Kulkarni A, Ginjala V, Toppmeyer D, Ganesan S, Bhanot G. Identification of the YES1 Kinase as a Therapeutic Target in Basal-Like Breast Cancers. Genes Cancer 2010; 1:1063-73. [PMID: 21779430 PMCID: PMC3092264 DOI: 10.1177/1947601910395583] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.5] [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: 08/26/2010] [Revised: 11/22/2010] [Accepted: 11/29/2010] [Indexed: 01/01/2023] Open
Abstract
Normal cellular behavior can be described as a complex, regulated network of interaction between genes and proteins. Targeted cancer therapies aim to neutralize specific proteins that are necessary for the cancer cell to remain viable in vivo. Ideally, the proteins targeted should be such that their downregulation has a major impact on the survival/fitness of the tumor cells and, at the same time, has a smaller effect on normal cells. It is difficult to use standard analysis methods on gene or protein expression levels to identify these targets because the level thresholds for tumorigenic behavior are different for different genes/proteins. We have developed a novel methodology to identify therapeutic targets by using a new paradigm called "gene centrality." The main idea is that, in addition to being overexpressed, good therapeutic targets should have a high degree of connectivity in the tumor network because one expects that suppression of its expression would affect many other genes. We propose a mathematical quantity called "centrality," which measures the degree of connectivity of genes in a network in which each edge is weighted by the expression level of the target gene. Using our method, we found that several SRC proto-oncogenes LYN, YES1, HCK, FYN, and LCK have high centrality in identifiable subsets of basal-like and HER2+ breast cancers. To experimentally validate the clinical value of this finding, we evaluated the effect of YES1 knockdown in basal-like breast cancer cell lines that overexpress this gene. We found that YES1 downregulation has a significant effect on the survival of these cell lines. Our results identify YES1 as a target for therapeutics in a subset of basal-like breast cancers.
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Affiliation(s)
- Erhan Bilal
- Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- University of Medicine and Dentistry of New Jersey and Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Gabriela Alexe
- Dana-Farber Institute, Harvard Medical School and Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ming Yao
- University of Medicine and Dentistry of New Jersey and Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Lei Cong
- University of Medicine and Dentistry of New Jersey and Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Atul Kulkarni
- University of Medicine and Dentistry of New Jersey and Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Vasudeva Ginjala
- University of Medicine and Dentistry of New Jersey and Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Deborah Toppmeyer
- University of Medicine and Dentistry of New Jersey and Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Shridar Ganesan
- University of Medicine and Dentistry of New Jersey and Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Gyan Bhanot
- Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- University of Medicine and Dentistry of New Jersey and Cancer Institute of New Jersey, New Brunswick, NJ, USA
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