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Schreiber CS, Wiesweg I, Stanelle-Bertram S, Beck S, Kouassi NM, Schaumburg B, Gabriel G, Richter F, Käufer C. Sex-specific biphasic alpha-synuclein response and alterations of interneurons in a COVID-19 hamster model. EBioMedicine 2024; 105:105191. [PMID: 38865747 PMCID: PMC11293593 DOI: 10.1016/j.ebiom.2024.105191] [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] [Received: 12/13/2023] [Revised: 05/02/2024] [Accepted: 05/25/2024] [Indexed: 06/14/2024] Open
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) frequently leads to neurological complications after recovery from acute infection, with higher prevalence in women. However, mechanisms by which SARS-CoV-2 disrupts brain function remain unclear and treatment strategies are lacking. We previously demonstrated neuroinflammation in the olfactory bulb of intranasally infected hamsters, followed by alpha-synuclein and tau accumulation in cortex, thus mirroring pathogenesis of neurodegenerative diseases such as Parkinson's or Alzheimer's disease. METHODS To uncover the sex-specific spatiotemporal profiles of neuroinflammation and neuronal dysfunction following intranasal SARS-CoV-2 infection, we quantified microglia cell density, alpha-synuclein immunoreactivity and inhibitory interneurons in cortical regions, limbic system and basal ganglia at acute and late post-recovery time points. FINDINGS Unexpectedly, microglia cell density and alpha-synuclein immunoreactivity decreased at 6 days post-infection, then rebounded to overt accumulation at 21 days post-infection. This biphasic response was most pronounced in amygdala and striatum, regions affected early in Parkinson's disease. Several brain regions showed altered densities of parvalbumin and calretinin interneurons which are involved in cognition and motor control. Of note, females appeared more affected. INTERPRETATION Our results demonstrate that SARS-CoV-2 profoundly disrupts brain homeostasis without neuroinvasion, via neuroinflammatory and protein regulation mechanisms that persist beyond viral clearance. The regional patterns and sex differences are in line with neurological deficits observed after SARS-CoV-2 infection. FUNDING Federal Ministry of Health, Germany (BMG; ZMV I 1-2520COR501 to G.G.), Federal Ministry of Education and Research, Germany (BMBF; 03COV06B to G.G.), Ministry of Science and Culture of Lower Saxony in Germany (14-76403-184, to G.G. and F.R.).
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Affiliation(s)
- Cara Sophie Schreiber
- Department of Pharmacology, Toxicology, and Pharmacy; University of Veterinary Medicine Hannover, Hannover, Germany; Center for Systems Neuroscience Hannover (ZSN), Germany
| | - Ivo Wiesweg
- Department of Pharmacology, Toxicology, and Pharmacy; University of Veterinary Medicine Hannover, Hannover, Germany
| | | | - Sebastian Beck
- Department for Viral Zoonoses-One Health, Leibniz Institute of Virology, Hamburg, Germany
| | - Nancy Mounogou Kouassi
- Department for Viral Zoonoses-One Health, Leibniz Institute of Virology, Hamburg, Germany
| | - Berfin Schaumburg
- Department for Viral Zoonoses-One Health, Leibniz Institute of Virology, Hamburg, Germany
| | - Gülsah Gabriel
- Department for Viral Zoonoses-One Health, Leibniz Institute of Virology, Hamburg, Germany; Institute of Virology, University of Veterinary Medicine Hannover, Hannover, Germany
| | - Franziska Richter
- Department of Pharmacology, Toxicology, and Pharmacy; University of Veterinary Medicine Hannover, Hannover, Germany; Center for Systems Neuroscience Hannover (ZSN), Germany.
| | - Christopher Käufer
- Department of Pharmacology, Toxicology, and Pharmacy; University of Veterinary Medicine Hannover, Hannover, Germany; Center for Systems Neuroscience Hannover (ZSN), Germany.
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Galvez V, Romero-Rebollar C, Estudillo-Guerra MA, Fernandez-Ruiz J. Resting-state networks and their relationship with MoCA performance in PD patients. Brain Imaging Behav 2024; 18:612-621. [PMID: 38332386 DOI: 10.1007/s11682-024-00860-3] [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] [Accepted: 01/30/2024] [Indexed: 02/10/2024]
Abstract
Although mild cognitive impairment is a common non-motor symptom experienced by individuals with Parkinson's Disease, the changes in intrinsic resting-state networks associated with its onset in Parkinson's remain underexamined. To address the issue, our study sought to examine resting-state network alterations and their association with total performance in the Montreal Cognitive Assessment and its cognitive domains in Parkinson's by means of functional magnetic resonance imaging of 29 Parkinson's patients with normal cognition, 25 Parkinson's patients with mild cognitive impairment, and 13 healthy controls. To contrast the Parkinson's groups with each other and the controls, the images were used to estimate the Z-score coefficient between the regions of interest from the default mode network, the salience network and the central executive network. Our first finding was that default mode and salience network connectivity decreased significantly in Parkinson's patients regardless of their cognitive status. Additionally, default mode network nodes had a negative and salience network nodes a positive correlation with the global assessment in Parkinson's with normal cognition; this inverse relationship of both networks to total score was not found in the group with cognitive impairment. Finally, a positive correlation was found between executive scores and anterior and posterior cortical network connectivity and, in the group with cognitive impairment, between language scores and salience network connectivity. Our results suggest that specific resting-state networks of Parkinson's patients with cognitive impairment differ from those of Parkinson's patients with normal cognition, supporting the evidence that cognitive impairment in Parkinson's Disease displays a differentiated neurodegenerative pattern.
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Affiliation(s)
- Victor Galvez
- Laboratorio de Neurociencias Cognitivas y Desarrollo, Escuela de Psicología, Universidad Panamericana, Ciudad de México, México.
| | - César Romero-Rebollar
- Escuela de Pedagogía, Universidad Panamericana, Ciudad de México, México
- Universidad Tecnológica de México-UNITEC MÉXICO-Campus en línea, Ciudad de México, México
| | - M Anayali Estudillo-Guerra
- Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Juan Fernandez-Ruiz
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Ciudad de México, México
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Kiani MM, Heidari Beni MH, Aghajan H. Aberrations in temporal dynamics of cognitive processing induced by Parkinson's disease and Levodopa. Sci Rep 2023; 13:20195. [PMID: 37980451 PMCID: PMC10657430 DOI: 10.1038/s41598-023-47410-3] [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] [Received: 06/15/2023] [Accepted: 11/10/2023] [Indexed: 11/20/2023] Open
Abstract
The motor symptoms of Parkinson's disease (PD) have been shown to significantly improve by Levodopa. However, despite the widespread adoption of Levodopa as a standard pharmaceutical drug for the treatment of PD, cognitive impairments linked to PD do not show visible improvement with Levodopa treatment. Furthermore, the neuronal and network mechanisms behind the PD-induced cognitive impairments are not clearly understood. In this work, we aim to explain these cognitive impairments, as well as the ones exacerbated by Levodopa, through examining the differential dynamic patterns of the phase-amplitude coupling (PAC) during cognitive functions. EEG data recorded in an auditory oddball task performed by a cohort consisting of controls and a group of PD patients during both on and off periods of Levodopa treatment were analyzed to derive the temporal dynamics of the PAC across the brain. We observed distinguishing patterns in the PAC dynamics, as an indicator of information binding, which can explain the slower cognitive processing associated with PD in the form of a latency in the PAC peak time. Thus, considering the high-level connections between the hippocampus, the posterior and prefrontal cortices established through the dorsal and ventral striatum acting as a modulatory system, we posit that the primary issue with cognitive impairments of PD, as well as Levodopa's cognitive deficit side effects, can be attributed to the changes in temporal dynamics of dopamine release influencing the modulatory function of the striatum.
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Affiliation(s)
- Mohammad Mahdi Kiani
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | | | - Hamid Aghajan
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran.
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4
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Hu P, Wang P, Zhao R, Yang H, Biswal BB. Characterizing the spatiotemporal features of functional connectivity across the white matter and gray matter during the naturalistic condition. Front Neurosci 2023; 17:1248610. [PMID: 38027509 PMCID: PMC10665512 DOI: 10.3389/fnins.2023.1248610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/25/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction The naturalistic stimuli due to its ease of operability has attracted many researchers in recent years. However, the influence of the naturalistic stimuli for whole-brain functions compared with the resting state is still unclear. Methods In this study, we clustered gray matter (GM) and white matter (WM) masks both at the ROI- and network-levels. Functional connectivity (FC) and inter-subject functional connectivity (ISFC) were calculated in GM, WM, and between GM and WM under the movie-watching and the resting-state conditions. Furthermore, intra-class correlation coefficients (ICC) of FC and ISFC were estimated on different runs of fMRI data to denote the reliability of them during the two conditions. In addition, static and dynamic connectivity indices were calculated with Pearson correlation coefficient to demonstrate the associations between the movie-watching and the resting-state. Results As the results, we found that the movie-watching significantly affected FC in whole-brain compared with the resting-state, but ISFC did not show significant connectivity induced by the naturalistic condition. ICC of FC and ISFC was generally higher during movie-watching compared with the resting-state, demonstrating that naturalistic stimuli could promote the reliability of connectivity. The associations between static and dynamic ISFC were weakly negative correlations in the naturalistic stimuli while there is no correlation between them under resting-state condition. Discussion Our findings confirmed that compared to resting-state condition, the connectivity indices under the naturalistic stimuli were more reliable and stable to investigate the normal functional activities of the human brain, and might promote the applications of FC in the cerebral dysfunction in various mental disorders.
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Affiliation(s)
- Peng Hu
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Pan Wang
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Rong Zhao
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hang Yang
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Chinese Institute for Brain Research, Beijing, China
| | - Bharat B. Biswal
- MOE Key Laboratory for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
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Ling Q, Liu A, Li Y, Mi T, Chan P, Liu Y, Chen X. Homogeneous-Multiset-CCA-Based Brain Covariation and Contravariance Connectivity Network Modeling. IEEE Trans Neural Syst Rehabil Eng 2023; 31:3556-3565. [PMID: 37682656 DOI: 10.1109/tnsre.2023.3310340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/10/2023]
Abstract
Brain connectivity networks based on functional magnetic resonance imaging (fMRI) have expanded our understanding of brain functions in both healthy and diseased states. However, most current studies construct connectivity networks using averaged regional time courses with the strong assumption that the activities of voxels contained in each brain region are similar, ignoring their possible variations. Additionally, pairwise correlation analysis is often adopted with more attention to positive relationships, while joint interactions at the network level as well as anti-correlations are less investigated. In this paper, to provide a new strategy for regional activity representation and brain connectivity modeling, a novel homogeneous multiset canonical correlation analysis (HMCCA) model is proposed, which enforces sign constraints on the weights of voxels to guarantee homogeneity within each brain region. It is capable of obtaining regional representative signals and constructing covariation and contravariance networks simultaneously, at both group and subject levels. Validations on two sessions of fMRI data verified its reproducibility and reliability when dealing with brain connectivity networks. Further experiments on subjects with and without Parkinson's disease (PD) revealed significant alterations in brain connectivity patterns, which were further associated with clinical scores and demonstrated superior prediction ability, indicating its potential in clinical practice.
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Ryan SK, Zelic M, Han Y, Teeple E, Chen L, Sadeghi M, Shankara S, Guo L, Li C, Pontarelli F, Jensen EH, Comer AL, Kumar D, Zhang M, Gans J, Zhang B, Proto JD, Saleh J, Dodge JC, Savova V, Rajpal D, Ofengeim D, Hammond TR. Microglia ferroptosis is regulated by SEC24B and contributes to neurodegeneration. Nat Neurosci 2023; 26:12-26. [PMID: 36536241 PMCID: PMC9829540 DOI: 10.1038/s41593-022-01221-3] [Citation(s) in RCA: 100] [Impact Index Per Article: 100.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 10/28/2022] [Indexed: 12/24/2022]
Abstract
Iron dysregulation has been implicated in multiple neurodegenerative diseases, including Parkinson's disease (PD). Iron-loaded microglia are frequently found in affected brain regions, but how iron accumulation influences microglia physiology and contributes to neurodegeneration is poorly understood. Here we show that human induced pluripotent stem cell-derived microglia grown in a tri-culture system are highly responsive to iron and susceptible to ferroptosis, an iron-dependent form of cell death. Furthermore, iron overload causes a marked shift in the microglial transcriptional state that overlaps with a transcriptomic signature found in PD postmortem brain microglia. Our data also show that this microglial response contributes to neurodegeneration, as removal of microglia from the tri-culture system substantially delayed iron-induced neurotoxicity. To elucidate the mechanisms regulating iron response in microglia, we performed a genome-wide CRISPR screen and identified novel regulators of ferroptosis, including the vesicle trafficking gene SEC24B. These data suggest a critical role for microglia iron overload and ferroptosis in neurodegeneration.
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Affiliation(s)
- Sean K Ryan
- Sanofi, Rare and Neurologic Diseases, Cambridge, MA, USA
| | - Matija Zelic
- Sanofi, Rare and Neurologic Diseases, Cambridge, MA, USA
| | - Yingnan Han
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Erin Teeple
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Luoman Chen
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Mahdiar Sadeghi
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Srinivas Shankara
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Lilu Guo
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Cong Li
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | | | | | - Ashley L Comer
- Sanofi, Rare and Neurologic Diseases, Cambridge, MA, USA
| | - Dinesh Kumar
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Mindy Zhang
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Joseph Gans
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Bailin Zhang
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | | | | | - James C Dodge
- Sanofi, Rare and Neurologic Diseases, Cambridge, MA, USA
| | - Virginia Savova
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
| | - Deepak Rajpal
- Sanofi, Precision Medicine and Computational Biology, Cambridge, MA, USA
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Wen J, Guo T, Wu J, Bai X, Zhou C, Wu H, Liu X, Chen J, Cao Z, Gu L, Pu J, Zhang B, Zhang M, Guan X, Xu X. Nigral Iron Deposition Influences Disease Severity by Modulating the Effect of Parkinson's Disease on Brain Networks. JOURNAL OF PARKINSON'S DISEASE 2022; 12:2479-2492. [PMID: 36336939 PMCID: PMC9837680 DOI: 10.3233/jpd-223372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND In Parkinson's disease (PD), excessive iron deposition in the substantia nigra may exacerbate α-synuclein aggregation, facilitating the degeneration of dopaminergic neurons and their neural projection. OBJECTIVE To investigate the interaction effect between nigral iron deposition and PD status on brain networks. METHODS Eighty-five PD patients and 140 normal controls (NC) were included. Network function and nigral iron were measured using multi-modality magnetic resonance imaging. According to the median of nigral magnetic susceptibility of NC (0.095 ppm), PD and NC were respectively divided into high and low nigral iron group. The main and interaction effects were investigated by mixed effect analysis. RESULTS The main effect of disease was observed in basal ganglia network (BGN) and visual network (VN). The interaction effect between nigral iron and PD status was observed in left inferior frontal gyrus and left insular lobe in BGN, as well as right middle occipital gyrus, right superior temporal gyrus, and bilateral cuneus in VN. Furthermore, multiple mediation analysis revealed that the functional connectivity of interaction effect clusters in BGN and medial VN partially mediated the relationship between nigral iron and Unified Parkinson's Disease Rating Scale II score. CONCLUSION Our study demonstrates an interaction of nigral iron deposition and PD status on brain networks, that is, nigral iron deposition is associated with the change of brain network configuration exclusively when in PD. We identified a potential causal mediation pathway for iron to affect disease severity that was mediated by both BGN dysfunction and VN hyperfunction in PD.
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Affiliation(s)
- Jiaqi Wen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Guo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingjing Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xueqin Bai
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haoting Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jingwen Chen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhengye Cao
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Luyan Gu
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jiali Pu
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China,Correspondence to: Xiaojun Xu, MD, Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 310009, China. Tel.: +86 0571 87315255; Fax: +86 0571 87315255; E-mail: and Xiaojun Guan, PhD, Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Shangcheng District, Hangzhou 310009, China. Tel.: +86 0571 87315255; Fax: +86 0571 87315255;
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China,Correspondence to: Xiaojun Xu, MD, Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 310009, China. Tel.: +86 0571 87315255; Fax: +86 0571 87315255; E-mail: and Xiaojun Guan, PhD, Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No. 88 Jiefang Road, Shangcheng District, Hangzhou 310009, China. Tel.: +86 0571 87315255; Fax: +86 0571 87315255;
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Jeong SH, Lee EC, Chung SJ, Lee HS, Jung JH, Sohn YH, Seong JK, Lee PH. Local striatal volume and motor reserve in drug-naïve Parkinson's disease. NPJ Parkinsons Dis 2022; 8:168. [PMID: 36470876 PMCID: PMC9722895 DOI: 10.1038/s41531-022-00429-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 11/11/2022] [Indexed: 12/12/2022] Open
Abstract
Motor reserve (MR) may explain why individuals with similar pathological changes show marked differences in motor deficits in Parkinson's disease (PD). In this study, we investigated whether estimated individual MR was linked to local striatal volume (LSV) in PD. We analyzed data obtained from 333 patients with drug naïve PD who underwent dopamine transporter scans and high-resolution 3-tesla T1-weighted structural magnetic resonance images. Using a residual model, we estimated individual MRs on the basis of initial UPDRS-III score and striatal dopamine depletion. We performed a correlation analysis between MR estimates and LSV. Furthermore, we assessed the effect of LSV, which is correlated with MR estimates, on the longitudinal increase in the levodopa-equivalent dose (LED) during the 4-year follow-up period using a linear mixed model. After controlling for intracranial volume, there was a significant positive correlation between LSV and MR estimates in the bilateral caudate, anterior putamen, and ventro-posterior putamen. The linear mixed model showed that the large local volume of anterior and ventro-posterior putamen was associated with the low requirement of LED initially and accelerated LED increment thereafter. The present study demonstrated that LSV is crucial to MR in early-stage PD, suggesting LSV as a neural correlate of MR in PD.
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Affiliation(s)
- Seong Ho Jeong
- grid.15444.300000 0004 0470 5454Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea ,grid.411627.70000 0004 0647 4151Department of Neurology, Inje University Sanggye Paik Hospital, Seoul, South Korea
| | - Eun-Chong Lee
- grid.222754.40000 0001 0840 2678School of Biomedical Engineering, Korea University, Seoul, South Korea
| | - Seok Jong Chung
- grid.15444.300000 0004 0470 5454Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea ,grid.413046.40000 0004 0439 4086Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
| | - Hye Sun Lee
- grid.15444.300000 0004 0470 5454Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea
| | - Jin Ho Jung
- grid.411625.50000 0004 0647 1102Department of Neurology, Inje University Busan Paik Hospital, Seoul, South Korea
| | - Young H. Sohn
- grid.15444.300000 0004 0470 5454Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Joon-Kyung Seong
- grid.222754.40000 0001 0840 2678School of Biomedical Engineering, Korea University, Seoul, South Korea ,grid.222754.40000 0001 0840 2678Department of Artificial Intelligence, Korea University, Seoul, South Korea
| | - Phil Hyu Lee
- grid.15444.300000 0004 0470 5454Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea ,grid.15444.300000 0004 0470 5454Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea
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Imaging the Limbic System in Parkinson's Disease-A Review of Limbic Pathology and Clinical Symptoms. Brain Sci 2022; 12:brainsci12091248. [PMID: 36138984 PMCID: PMC9496800 DOI: 10.3390/brainsci12091248] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/05/2022] [Accepted: 09/13/2022] [Indexed: 01/09/2023] Open
Abstract
The limbic system describes a complex of brain structures central for memory, learning, as well as goal directed and emotional behavior. In addition to pathological studies, recent findings using in vivo structural and functional imaging of the brain pinpoint the vulnerability of limbic structures to neurodegeneration in Parkinson's disease (PD) throughout the disease course. Accordingly, dysfunction of the limbic system is critically related to the symptom complex which characterizes PD, including neuropsychiatric, vegetative, and motor symptoms, and their heterogeneity in patients with PD. The aim of this systematic review was to put the spotlight on neuroimaging of the limbic system in PD and to give an overview of the most important structures affected by the disease, their function, disease related alterations, and corresponding clinical manifestations. PubMed was searched in order to identify the most recent studies that investigate the limbic system in PD with the help of neuroimaging methods. First, PD related neuropathological changes and corresponding clinical symptoms of each limbic system region are reviewed, and, finally, a network integration of the limbic system within the complex of PD pathology is discussed.
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Divergent time-varying connectivity of thalamic sub-regions characterizes clinical phenotypes and cognitive status in multiple sclerosis. Mol Psychiatry 2022; 27:1765-1773. [PMID: 34992237 DOI: 10.1038/s41380-021-01401-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 11/17/2021] [Accepted: 11/23/2021] [Indexed: 12/17/2022]
Abstract
We aimed to investigate abnormal time-varying functional connectivity (FC) for thalamic sub-regions in multiple sclerosis (MS) and their clinical, cognitive and MRI correlates. Eighty-nine MS patients (49 relapsing-remitting [RR] MS; 40 progressive [P] MS) and 53 matched healthy controls underwent neurological, neuropsychological and resting state fMRI assessment. Time-varying connectivity (TVC) was quantified using sliding-window seed-voxel correlation analysis. Standard deviation of FC across windows was taken as measure of TVC, while mean connectivity across windows expressed static FC. MS patients showed reduced TVC vs controls between most of thalamic sub-regions and fronto-temporo-occipital regions. At the same time, they showed increased static FC between all thalamic sub-regions and structurally connected cortico-subcortical regions. TVC reduction was mainly driven by RRMS; while PMS exhibited a variable pattern of TVC abnormalities, characterized by reduced TVC between frontal/motor thalamic seeds and default-mode network areas and increased TVC vs controls/RRMS between posterior thalamic sub-regions and occipito-temporo-insular cortices, associated with severity of clinical disability. Compared with controls, both cognitively preserved and impaired patients showed reduced TVC between anterior thalamic sub-regions and frontal cortex. Cognitively impaired patients also showed increased TVC of the right postcentral thalamic sub-region with the cingulate cortex and postcentral gyrus vs both controls and cognitively preserved patients. Divergent patterns of TVC thalamic abnormalities were found between RRMS and PMS patients. TVC reduction in RRMS may represent the attempt of thalamic network to keep with stable connections. Conversely, increased TVC of posterior thalamic sub-regions characterized PMS and cognitively impaired MS, possibly reflecting maladaptive mechanisms.
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Li Y, Liu A, Mi T, Yang R, Chan P, McKeown MJ, Chen X, Wu F. Striatal Subdivisions Estimated via Deep Embedded Clustering With Application to Parkinson's Disease. IEEE J Biomed Health Inform 2021; 25:3564-3575. [PMID: 34038373 DOI: 10.1109/jbhi.2021.3083879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Recent fMRI connectivity-based parcellation (CBP) methods have been developed to obtain homogeneous and functionally coherent brain parcels. However, most of these studies utilize traditional clustering methods that neglect hidden nonlinear features. To enhance parcellation performance, here we propose a deep embedded connectivity-based parcellation (DECBP) framework and apply it to determine functional subdivisions of the striatum in public resting state fMRI data sets. This framework integrates fMRI connectivity features into deep embedded clustering (DEC), a deep neural network based on a stacked autoencoder. Compared to three prevalent clustering methods and their combinations with principal component analysis (PCA), the DECBP exhibited a significantly higher similarity between scans, individuals, and groups, indicating enhanced reproducibility. The generated reliable parcellations were also largely consistent with other public atlases. We further explored the functional subunits in the striatum in a data set from 23 Parkinson's disease (PD) subjects and 27 age-matched healthy controls (HC). All putaminal subregions of PD demonstrated lower interhemispheric connectivity than those of HC, which might reflect imbalance in the pathological progression of PD. Such hypo-connectivity was also observed between putaminal subregions and other brain regions, reflecting neuroimaging manifestations of the altered cortico-striato-thalamo-cortical circuit. These observed weaker couplings were associated with PD severity and duration. Our results support the utilization of the DECBP framework and suggest that abnormal connectivity in putaminal subregions may be a potential indicator of PD.
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Iraji A, Faghiri A, Lewis N, Fu Z, Rachakonda S, Calhoun VD. Tools of the trade: estimating time-varying connectivity patterns from fMRI data. Soc Cogn Affect Neurosci 2020; 16:849-874. [PMID: 32785604 PMCID: PMC8343585 DOI: 10.1093/scan/nsaa114] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 06/24/2020] [Accepted: 08/05/2020] [Indexed: 01/04/2023] Open
Abstract
Given the dynamic nature of the brain, there has always been a motivation to move beyond 'static' functional connectivity, which characterizes functional interactions over an extended period of time. Progress in data acquisition and advances in analytical neuroimaging methods now allow us to assess the whole brain's dynamic functional connectivity (dFC) and its network-based analog, dynamic functional network connectivity at the macroscale (mm) using fMRI. This has resulted in the rapid growth of analytical approaches, some of which are very complex, requiring technical expertise that could daunt researchers and neuroscientists. Meanwhile, making real progress toward understanding the association between brain dynamism and brain disorders can only be achieved through research conducted by domain experts, such as neuroscientists and psychiatrists. This article aims to provide a gentle introduction to the application of dFC. We first explain what dFC is and the circumstances under which it can be used. Next, we review two major categories of analytical approaches to capture dFC. We discuss caveats and considerations in dFC analysis. Finally, we walk readers through an openly accessible toolbox to capture dFC properties and briefly review some of the dynamic metrics calculated using this toolbox.
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Affiliation(s)
- Armin Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Ashkan Faghiri
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Noah Lewis
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Srinivas Rachakonda
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
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Mao Q, Wang X, Chen B, Fan L, Wang S, Zhang Y, Lin X, Cao Y, Wu YC, Ji J, Xu J, Zheng J, Zhang H, Zheng C, Chen W, Cheng W, Luo X, Wang K, Zuo L, Kang L, Li CSR, Luo X. KTN1 Variants Underlying Putamen Gray Matter Volumes and Parkinson's Disease. Front Neurosci 2020; 14:651. [PMID: 32655362 PMCID: PMC7324786 DOI: 10.3389/fnins.2020.00651] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 05/26/2020] [Indexed: 11/13/2022] Open
Abstract
Background Selective loss of dopaminergic neurons and diminished putamen gray matter volume (GMV) represents a central feature of Parkinson’s disease (PD). Recent studies have reported specific effects of kinectin 1 gene (KTN1) variants on the putamen GMV. Objective To examine the relationship of KTN1 variants, KTN1 mRNA expression in the putamen and substantia nigra pars compacta (SNc), putamen GMV, and PD. Methods We examined the associations between PD and a total of 1847 imputed KTN1 single nucleotide polymorphisms (SNPs) in one discovery sample [2,000 subjects with PD vs. 1,986 healthy controls (HC)], and confirmed the nominally significant associations (p < 0.05) in two replication samples (900 PD vs. 867 HC, and 940 PD vs. 801 HC, respectively). The regulatory effects of risk variants on the KTN1 mRNA expression in putamen and SNc and the putamen GMV were tested. We also quantified the expression levels of KTN1 mRNA in the putamen and/or SNc for comparison between PD and HC in five independent cohorts. Results Six replicable and two non-replicable KTN1-PD associations were identified (0.009 ≤ p ≤ 0.049). The major alleles of five SNPs, including rs12880292, rs8017172, rs17253792, rs945270, and rs4144657, significantly increased risk for PD (0.020 ≤ p ≤ 0.049) and putamen GMVs (19.08 ≤ β ≤ 60.38; 2.82 ≤ Z ≤ 15.03; 5.0 × 10–51 ≤ p ≤ 0.018). The risk alleles of five SNPs, including rs8017172, rs17253792, rs945270, rs4144657, and rs1188184 also significantly increased the KTN1 mRNA expression in the putamen or SNc (0.021 ≤ p ≤ 0.046). The KTN1 mRNA was abundant in the putamen and/or SNc across five independent cohorts and differentially expressed in the SNc between PD and HC in one cohort (p = 0.047). Conclusion There was a consistent, significant, replicable, and robust positive relationship among the KTN1 variants, PD risk, KTN1 mRNA expression in putamen, and putamen volumes, and a modest relation between PD risk and KTN1 mRNA expression in SNc, suggesting that KTN1 may play a functional role in the development of PD.
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Affiliation(s)
- Qiao Mao
- Department of Psychosomatic Medicine, People's Hospital of Deyang, Deyang, China
| | - Xiaoping Wang
- Department of Neurology, Shanghai Tongren Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Bin Chen
- Department of Cardiovascular Medicine, Fujian Provincial Hospital, Fuzhou, China
| | - Longhua Fan
- Qingpu Branch, Department of Vascular Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shuhong Wang
- Department of Neurology, Shanghai Tongren Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yong Zhang
- Tianjin Mental Health Center, Tianjin, China
| | - Xiandong Lin
- Laboratory of Radiation Oncology and Radiobiology, Fujian Provincial Cancer Hospital, Teaching Hospital of Fujian Medical University, Fuzhou, China
| | - Yuping Cao
- Department of Psychiatry, Second Xiangya Hospital, Central South University, Changsha, China
| | - Yun-Cheng Wu
- Department of Neurology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiawu Ji
- Department of Psychiatry, Fuzhou Neuropsychiatric Hospital, Fujian Medical University, Fuzhou, China
| | - Jianying Xu
- Zhuhai Municipal Maternal and Children's Health Hospital, Zhuhai, China
| | - Jianming Zheng
- Huashan Hospital, Fudan University School of Medicine, Shanghai, China
| | - Huihao Zhang
- The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | | | - Wenzhong Chen
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai, China
| | - Wenhong Cheng
- Department of Psychiatry, Shanghai Mental Health Center, Shanghai, China
| | - Xingqun Luo
- Department of Clinical Medicine, College of Integrated Traditional Chinese and Western Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China
| | - Kesheng Wang
- Department of Family and Community Health, School of Nursing, Health Sciences Center, West Virginia University, Morgantown, WV, United States
| | - Lingjun Zuo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Longli Kang
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research on High Altitude Diseases of Tibet Autonomous Region, Xizang Minzu University School of Medicine, Xiangyang, China
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Xingguang Luo
- Biological Psychiatry Research Center, Beijing Huilongguan Hospital, Beijing, China
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Valsasina P, Hidalgo de la Cruz M, Filippi M, Rocca MA. Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis. Front Neurosci 2019; 13:618. [PMID: 31354402 PMCID: PMC6636554 DOI: 10.3389/fnins.2019.00618] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 05/29/2019] [Indexed: 01/27/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called “sliding windows,” in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.
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Affiliation(s)
- Paola Valsasina
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Milagros Hidalgo de la Cruz
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
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Filippi M, Spinelli EG, Cividini C, Agosta F. Resting State Dynamic Functional Connectivity in Neurodegenerative Conditions: A Review of Magnetic Resonance Imaging Findings. Front Neurosci 2019; 13:657. [PMID: 31281241 PMCID: PMC6596427 DOI: 10.3389/fnins.2019.00657] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Accepted: 06/07/2019] [Indexed: 12/12/2022] Open
Abstract
In the last few decades, brain functional connectivity (FC) has been extensively assessed using resting-state functional magnetic resonance imaging (RS-fMRI), which is able to identify temporally correlated brain regions known as RS functional networks. Fundamental insights into the pathophysiology of several neurodegenerative conditions have been provided by studies in this field. However, most of these studies are based on the assumption of temporal stationarity of RS functional networks, despite recent evidence suggests that the spatial patterns of RS networks may change periodically over the time of an fMRI scan acquisition. For this reason, dynamic functional connectivity (dFC) analysis has been recently implemented and proposed in order to consider the temporal fluctuations of FC. These approaches hold promise to provide fundamental information for the identification of pathophysiological and diagnostic markers in the vast field of neurodegenerative diseases. This review summarizes the main currently available approaches for dFC analysis and reports their recent applications for the assessment of the most common neurodegenerative conditions, including Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, and frontotemporal dementia. Critical state-of-the-art findings, limitations, and future perspectives regarding the analysis of dFC in these diseases are provided from both a clinical and a technical point of view.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Edoardo G Spinelli
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
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