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Wei Y, Zhang C, Peng Y, Chen C, Han S, Wang W, Zhang Y, Lu H, Cheng J. MRI Assessment of Intrinsic Neural Timescale and Gray Matter Volume in Parkinson's Disease. J Magn Reson Imaging 2024; 59:987-995. [PMID: 37318377 DOI: 10.1002/jmri.28864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 05/28/2023] [Accepted: 05/30/2023] [Indexed: 06/16/2023] Open
Abstract
BACKGROUND Numerous studies have indicated altered temporal features of the brain function in Parkinson's disease (PD), and the autocorrelation magnitude of intrinsic neural signals, called intrinsic neural timescales, were often applied to estimate how long neural information stored in local brain areas. However, it is unclear whether PD patients at different disease stages exhibit abnormal timescales accompanied with abnormal gray matter volume (GMV). PURPOSE To assess the intrinsic timescale and GMV in PD. STUDY TYPE Prospective. POPULATION 74 idiopathic PD patients (44 early stage (PD-ES) and 30 late stage (PD-LS), as determined by the Hoehn and Yahr (HY) severity classification scale), and 73 healthy controls (HC). FIELD STRENGTH/SEQUENCE 3.0 T MRI scanner; magnetization prepared rapid acquisition gradient echo and echo planar imaging sequences. ASSESSMENT The timescales were estimated by using the autocorrelation magnitude of neural signals. Voxel-based morphometry was performed to calculate GMV in the whole brain. Severity of motor symptoms and cognitive impairments were assessed using the unified PD rating scale, the HY scale, the Montreal cognitive assessment, and the mini-mental state examination. STATISTICAL TEST Analysis of variance; two-sample t-test; Spearman rank correlation analysis; Mann-Whitney U test; Kruskal-Wallis' H test. A P value <0.05 was considered statistically significant. RESULTS The PD group had significantly abnormal intrinsic timescales in the sensorimotor, visual, and cognitive-related areas, which correlated with the symptom severity (ρ = -0.265, P = 0.022) and GMV (ρ = 0.254, P = 0.029). Compared to the HC group, the PD-ES group had significantly longer timescales in anterior cortical regions, whereas the PD-LS group had significantly shorter timescales in posterior cortical regions. CONCLUSION This study suggested that PD patients have abnormal timescales in multisystem and distinct patterns of timescales and GMV in cerebral cortex at different disease stages. This may provide new insights for the neural substrate of PD. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Chunyan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yuanyuan Peng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Chen Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Hong Lu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
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Tan Z, Zeng Q, Hu X, Di D, Chen L, Lin Z, Cheng G. Altered dynamic functional network connectivity in drug-naïve Parkinson's disease patients with excessive daytime sleepiness. Front Aging Neurosci 2023; 15:1282962. [PMID: 38125809 PMCID: PMC10731041 DOI: 10.3389/fnagi.2023.1282962] [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: 08/25/2023] [Accepted: 11/23/2023] [Indexed: 12/23/2023] Open
Abstract
Background Excessive daytime sleepiness (EDS) is a frequent nonmotor symptoms of Parkinson's disease (PD), which seriously affects the quality of life of PD patients and exacerbates other nonmotor symptoms. Previous studies have used static analyses of these resting-state functional magnetic resonance imaging (rs-fMRI) data were measured under the assumption that the intrinsic fluctuations during MRI scans are stationary. However, dynamic functional network connectivity (dFNC) analysis captures time-varying connectivity over short time scales and may reveal complex functional tissues in the brain. Purpose To identify dynamic functional connectivity characteristics in PD-EDS patients in order to explain the underlying neuropathological mechanisms. Methods Based on rs-fMRI data from 16 PD patients with EDS and 41 PD patients without EDS, we applied the sliding window approach, k-means clustering and independent component analysis to estimate the inherent dynamic connectivity states associated with EDS in PD patients and investigated the differences between groups. Furthermore, to assess the correlations between the altered temporal properties and the Epworth sleepiness scale (ESS) scores. Results We found four distinct functional connectivity states in PD patients. The patients in the PD-EDS group showed increased fractional time and mean dwell time in state IV, which was characterized by strong connectivity in the sensorimotor (SMN) and visual (VIS) networks, and reduced fractional time in state I, which was characterized by strong positive connectivity intranetwork of the default mode network (DMN) and VIS, while negative connectivity internetwork between the DMN and VIS. Moreover, the ESS scores were positively correlated with fraction time in state IV. Conclusion Our results indicated that the strong connectivity within and between the SMN and VIS was characteristic of EDS in PD patients, which may be a potential marker of pathophysiological features related to EDS in PD patients.
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Affiliation(s)
- Zhiyi Tan
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Qiaoling Zeng
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Xuehan Hu
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Duoduo Di
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Lele Chen
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Zhijian Lin
- Department of Neurology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Guanxun Cheng
- Department of Medical Imaging, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
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Wu N, Zhang L, Zhang X, Zhang Q, Liu J, Li Y, Yan XX, Liang Y, Zhang J, Cui M. Synthesis and Bioevaluation of 2-Styrylquinoxaline Derivatives as Tau-PET Tracers. Mol Pharm 2023; 20:5865-5876. [PMID: 37852240 DOI: 10.1021/acs.molpharmaceut.3c00717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2023]
Abstract
This study focused on designing and evaluating Tau-PET tracers for noninvasive positron emission computed tomography (PET) imaging of neurofibrillary tangles (NFTs), a hallmark pathology of Alzheimer's disease (AD). The tracers were synthesized with a 2-styrylquinoxaline scaffold and varying lengths of FPEG chains. The compound [18F]15, which had two ethoxy units, showed high affinity for recombinant K18-Tau aggregates (Ki = 41.48 nM) and the highest selectivity versus Aβ1-42 aggregates (8.83-fold). In vitro autoradiography and fluorescent staining profiles further validated the binding of [18F]15 or 15 toward NFTs in brain sections from AD patients and Tau-transgenic mice. In normal ICR mice, [18F]15 exhibited an ideal initial brain uptake (11.21% ID/g at 2 min) and moderate washout ratio (2.29), and micro-PET studies in rats confirmed its ability to penetrate the blood-brain barrier with the peak SUV value of 1.94 in the cortex. These results suggest that [18F]15 has the potential to be developed into a useful Tau-PET tracer for early AD diagnosis and evaluation of anti-Tau therapeutics.
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Affiliation(s)
- Nan Wu
- Key Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China
| | - Longfei Zhang
- Key Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China
| | - Xiaojun Zhang
- Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing 100853, China
| | - Qilei Zhang
- Department of Anatomy and Neurobiology, Xiangya School of Medicine, Central South University, Changsha 410013, China
| | - Jiaqi Liu
- Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Taikang Center for Life and Medical Science, Hubei Key Laboratory of Cell Homeostasis, Wuhan University, Wuhan 430072, China
| | - Yuying Li
- Key Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China
| | - Xiao-Xin Yan
- Department of Anatomy and Neurobiology, Xiangya School of Medicine, Central South University, Changsha 410013, China
| | - Yi Liang
- Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Taikang Center for Life and Medical Science, Hubei Key Laboratory of Cell Homeostasis, Wuhan University, Wuhan 430072, China
| | - Jinming Zhang
- Department of Nuclear Medicine, Chinese PLA General Hospital, Beijing 100853, China
| | - Mengchao Cui
- Key Laboratory of Radiopharmaceuticals, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China
- Center for Advanced Materials Research, Beijing Normal University, Zhuhai 519087, China
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Hensel L, Seger A, Farrher E, Bonkhoff AK, Shah NJ, Fink GR, Grefkes C, Sommerauer M, Doppler CEJ. Fronto-striatal dynamic connectivity is linked to dopaminergic motor response in Parkinson's disease. Parkinsonism Relat Disord 2023; 114:105777. [PMID: 37549587 DOI: 10.1016/j.parkreldis.2023.105777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 07/09/2023] [Accepted: 07/25/2023] [Indexed: 08/09/2023]
Abstract
INTRODUCTION Differences in dopaminergic motor response in Parkinson's disease (PD) patients can be related to PD subtypes, and previous fMRI studies associated dopaminergic motor response with corticostriatal functional connectivity. While traditional fMRI analyses have assessed the mean connectivity between regions of interest, an important aspect driving dopaminergic response might lie in the temporal dynamics in corticostriatal connections. METHODS This study aims to determine if altered resting-state dynamic functional network connectivity (DFC) is associated with dopaminergic motor response. To test this, static and DFC were assessed in 32 PD patients and 18 healthy controls (HC). Patients were grouped as low and high responders using a median split of their dopaminergic motor response. RESULTS Patients featuring a high dopaminergic motor response were observed to spend more time in a regionally integrated state compared to HC. Furthermore, DFC between the anterior midcingulate cortex/dorsal anterior cingulate cortex (aMCC/dACC) and putamen was lower in low responders during a more segregated state and correlated with dopaminergic motor response. CONCLUSION The findings of this study revealed that temporal dynamics of fronto-striatal connectivity are associated with clinically relevant information, which may be considered when assessing functional connectivity between regions involved in motor initiation.
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Affiliation(s)
- Lukas Hensel
- University of Cologne, University Hospital Cologne, Department of Neurology, 50937, Köln, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich, 52425, Jülich, Germany.
| | - Aline Seger
- University of Cologne, University Hospital Cologne, Department of Neurology, 50937, Köln, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich, 52425, Jülich, Germany
| | - Ezequiel Farrher
- Institute of Neuroscience and Medicine 4 and Molecular Neuroscience and Neuroimaging (INM-4 / INM-11), Forschungszentrum Jülich, 52425, Jülich, Germany
| | - Anna K Bonkhoff
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - N Jon Shah
- Institute of Neuroscience and Medicine 4 and Molecular Neuroscience and Neuroimaging (INM-4 / INM-11), Forschungszentrum Jülich, 52425, Jülich, Germany; JARA - BRAIN - Translational Medicine, 52056, Aachen, Germany; RWTH Aachen University, Department of Neurology, 52056, Aachen, Germany
| | - Gereon R Fink
- University of Cologne, University Hospital Cologne, Department of Neurology, 50937, Köln, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich, 52425, Jülich, Germany
| | - Christian Grefkes
- University Hospital Frankfurt, Goethe University, Department of Neurology, Frankfurt am Main, Germany
| | - Michael Sommerauer
- University of Cologne, University Hospital Cologne, Department of Neurology, 50937, Köln, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich, 52425, Jülich, Germany
| | - Christopher E J Doppler
- University of Cologne, University Hospital Cologne, Department of Neurology, 50937, Köln, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich, 52425, Jülich, Germany.
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Li Z, Wang Z, Cao D, You R, Hu J. Altered dynamic functional network connectivity states in patients with acute basal ganglia ischemic stroke. Brain Res 2023:148406. [PMID: 37201623 DOI: 10.1016/j.brainres.2023.148406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 05/04/2023] [Accepted: 05/08/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Dynamic functional network connectivity (dFNC) patterns are successfully able to capture the time-varying features of intrinsic fluctuations throughout a scan. We explored dFNC alterations across the entire brain in patients with acute ischemic stroke (AIS) of the basal ganglia (BG). METHOD Resting-state functional magnetic resonance imaging data were acquired from 26 patients with first-ever AIS in the BG and 26 healthy controls (HCs). Independent component analysis, the sliding window method, and the K-means clustering method were used to obtain reoccurring dynamic network connectivity patterns. Moreover, temporal features across diverse dFNC states were compared between the two groups, and the local and global efficiencies across states were analyzed to explore the characteristics of the topological networks among states. RESULTS Four dFNC states were characterized for comparison of dynamic brain network connectivity patterns. In contrast to the HC group, the AIS group spent a significantly higher fraction of time in State 1, which is characterized by a relatively weaker brain network connectome. Conversely, compared with HC, patients with AIS showed a lower mean dwell time in State 2, which was characterized by a relatively stronger brain network connectome. Additionally, functional networks exhibited variable efficiency of information transfer across 4 states. CONCLUSIONS AIS not only altered the interaction between the different dynamic networks but also promoted characteristic alterations in the temporal and topological features of large-scale dynamic network connectivity.
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Affiliation(s)
- Zhongming Li
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
| | - Zhimin Wang
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Dairong Cao
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Ruixiong You
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Jianping Hu
- Department of Imaging, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
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Alaçam D, Miller R, Agcaoglu O, Preda A, Ford J, Calhoun V. A method for capturing dynamic spectral coupling in resting fMRI reveals domain-specific patterns in schizophrenia. Front Neurosci 2023; 17:1078995. [PMID: 37179560 PMCID: PMC10174238 DOI: 10.3389/fnins.2023.1078995] [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: 10/24/2022] [Accepted: 04/03/2023] [Indexed: 05/15/2023] Open
Abstract
Introduction Resting-state functional magnetic resonance imaging (rs-fMRI) is a powerful tool for assessing functional brain connectivity. Recent studies have focused on shorter-term connectivity and dynamics in the resting state. However, most of the prior work evaluates changes in time-series correlations. In this study, we propose a framework that focuses on time-resolved spectral coupling (assessed via the correlation between power spectra of the windowed time courses) among different brain circuits determined via independent component analysis (ICA). Methods Motivated by earlier work suggesting significant spectral differences in people with schizophrenia, we developed an approach to evaluate time-resolved spectral coupling (trSC). To do this, we first calculated the correlation between the power spectra of windowed time-courses pairs of brain components. Then, we subgrouped each correlation map into four subgroups based on the connectivity strength utilizing quartiles and clustering techniques. Lastly, we examined clinical group differences by regression analysis for each averaged count and average cluster size matrices in each quartile. We evaluated the method by applying it to resting-state data collected from 151 (114 males, 37 females) people with schizophrenia (SZ) and 163 (117 males, 46 females) healthy controls (HC). Results Our proposed approach enables us to observe the change of connectivity strength within each quartile for different subgroups. People with schizophrenia showed highly modularized and significant differences in multiple network domains, whereas males and females showed less modular differences. Both cell count and average cluster size analysis for subgroups indicate a higher connectivity rate in the fourth quartile for the visual network in the control group. This indicates increased trSC in visual networks in the controls. In other words, this shows that the visual networks in people with schizophrenia have less mutually consistent spectra. It is also the case that the visual networks are less spectrally correlated on short timescales with networks of all other functional domains. Conclusions The results of this study reveal significant differences in the degree to which spectral power profiles are coupled over time. Importantly, there are significant but distinct differences both between males and females and between people with schizophrenia and controls. We observed a more significant coupling rate in the visual network for the healthy controls and males in the upper quartile. Fluctuations over time are complex, and focusing on only time-resolved coupling among time-courses is likely to miss important information. Also, people with schizophrenia are known to have impairments in visual processing but the underlying reasons for the impairment are still unknown. Therefore, the trSC approach can be a useful tool to explore the reasons for the impairments.
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Affiliation(s)
- Deniz Alaçam
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
- Department of Mathematics, Bursa Uludag University, Bursa, Türkiye
- *Correspondence: Deniz Alaçam
| | - Robyn Miller
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Oktay Agcaoglu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States
| | - Judith Ford
- San Francisco VA Medical Center, University of California, San Francisco, San Francisco, CA, United States
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
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Jellinger KA. The pathobiological basis of depression in Parkinson disease: challenges and outlooks. J Neural Transm (Vienna) 2022; 129:1397-1418. [PMID: 36322206 PMCID: PMC9628588 DOI: 10.1007/s00702-022-02559-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/20/2022] [Indexed: 11/06/2022]
Abstract
Depression, with an estimated prevalence of about 40% is a most common neuropsychiatric disorder in Parkinson disease (PD), with a negative impact on quality of life, cognitive impairment and functional disability, yet the underlying neurobiology is poorly understood. Depression in PD (DPD), one of its most common non-motor symptoms, can precede the onset of motor symptoms but can occur at any stage of the disease. Although its diagnosis is based on standard criteria, due to overlap with other symptoms related to PD or to side effects of treatment, depression is frequently underdiagnosed and undertreated. DPD has been related to a variety of pathogenic mechanisms associated with the underlying neurodegenerative process, in particular dysfunction of neurotransmitter systems (dopaminergic, serotonergic and noradrenergic), as well as to disturbances of cortico-limbic, striato-thalamic-prefrontal, mediotemporal-limbic networks, with disruption in the topological organization of functional mood-related, motor and other essential brain network connections due to alterations in the blood-oxygen-level-dependent (BOLD) fluctuations in multiple brain areas. Other hypothetic mechanisms involve neuroinflammation, neuroimmune dysregulation, stress hormones, neurotrophic, toxic or metabolic factors. The pathophysiology and pathogenesis of DPD are multifactorial and complex, and its interactions with genetic factors, age-related changes, cognitive disposition and other co-morbidities awaits further elucidation.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, 1150, Vienna, Austria.
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