1
|
Liu SW, Ma XT, Yu S, Weng XF, Li M, Zhu J, Liu CF, Hu H. Bridging Reduced Grip Strength and Altered Executive Function: Specific Brain White Matter Structural Changes in Patients with Alzheimer's Disease. Clin Interv Aging 2024; 19:93-107. [PMID: 38250174 PMCID: PMC10799618 DOI: 10.2147/cia.s438782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 01/09/2024] [Indexed: 01/23/2024] Open
Abstract
Objective To investigate the correlation between specific fiber tracts and grip strength and cognitive function in patients with Alzheimer's disease (AD) by fixel-based analysis (FBA). Methods AD patients were divided into AD with low grip strength (AD-LGS, n=29) and AD without low grip strength (AD-nLGS, n=25), along with 31 normal controls (NC). General data, neuropsychological tests, grip strength and cranial magnetic resonance imaging (MRI) scans were collected. FBA evaluated white matter (WM) fiber metrics, including fiber density (FD), fiber cross-sectional (FC), and fiber density and cross-sectional area (FDC). The mean fiber indicators of the fiber tracts of interest (TOI) were extracted in cerebral region of significant statistical differences in FBA to further compare the differences between groups and analyze the correlation between fiber properties and neuropsychological test scores. Results Compared to AD-nLGS group, AD-LGS group showed significant reductions in FDC in several cerebral regions. In AD patients, FDC values of bilateral uncinate fasciculus and left superior longitudinal fasciculus were positively correlated with Clock Drawing Test scores, while FDC of splenium of corpus callosum, bilateral anterior cingulate tracts, forceps major, and bilateral inferior longitudinal fasciculus were positively correlated with the Executive Factor Score of Memory and Executive Screening scale scores. Conclusion Reduced grip strength in AD patients is associated with extensive impairment of WM structural integrity. Changes in FDC of specific WM fiber tracts related to executive function play a significant mediating role in the reduction of grip strength in AD patients.
Collapse
Affiliation(s)
- Shan-Wen Liu
- Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Xiao-Ting Ma
- Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Shuai Yu
- Department of Neurology, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, 215000, People’s Republic of China
| | - Xiao-Fen Weng
- Department of Geriatric Medicine, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, 215000, People’s Republic of China
| | - Meng Li
- Department of Imaging, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Jiangtao Zhu
- Department of Imaging, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Chun-Feng Liu
- Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Hua Hu
- Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| |
Collapse
|
2
|
Lv Y, Zhang JJ, Wang K, Ju L, Zhang H, Zhao Y, Pan Y, Gong J, Wang X, Fong KNK. Determining the Optimal Stimulation Sessions for TMS-Induced Recovery of Upper Extremity Motor Function Post Stroke: A Randomized Controlled Trial. Brain Sci 2023; 13:1662. [PMID: 38137110 PMCID: PMC10741851 DOI: 10.3390/brainsci13121662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 11/23/2023] [Accepted: 11/28/2023] [Indexed: 12/24/2023] Open
Abstract
To find out the optimal treatment sessions of repetitive transcranial magnetic stimulation (TMS) over the primary motor cortex (M1) for upper extremity dysfunction after stroke during the 6-week treatment and to explore its mechanism using motor-evoked potentials (MEPs) and resting-state functional magnetic resonance imaging (rs-fMRI), 72 participants with upper extremity motor dysfunction after ischemic stroke were randomly divided into the control group, 10-session, 20-session, and 30-session rTMS groups. Low-frequency (1 Hz) rTMS over the contralesional M1 was applied in all rTMS groups. The motor function of the upper extremity was assessed before and after treatment. In addition, MEPs and rs-fMRI data were analyzed to detect its effect on brain reorganization. After 6 weeks of treatment, there were significant differences in the Fugl-Meyer Assessment of the upper extremity and the Wolf Motor Function Test scores between the 10-session group and the 30-session group and between the 20- and 30-session groups and the control group, while there was no significant difference between the 20-session group and the 30-session group. Meanwhile, no significant difference was found between the 10-session group and the control group. The 20-session group of rTMS decreased the excitability of the contralesional corticospinal tract represented by the amplitudes of MEPs and enhanced the functional connectivity of the ipsilesional M1 or premotor cortex with the the precentral gyrus, postcentral gyrus, and cingulate gyrus, etc. In conclusion, the 20-session of rTMS protocol is the optimal treatment sessions of TMS for upper extremity dysfunction after stroke during the 6-week treatment. The potential mechanism is related to its influence on the excitability of the corticospinal tract and the remodeling of corticomotor functional networks.
Collapse
Affiliation(s)
- Yichen Lv
- School of Rehabilitation Medicine, Binzhou Medical University, Yantai 264000, China
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Jack Jiaqi Zhang
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Kui Wang
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Leilei Ju
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Hongying Zhang
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Yuehan Zhao
- School of Rehabilitation Medicine, Binzhou Medical University, Yantai 264000, China
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Yao Pan
- School of Rehabilitation Medicine, Binzhou Medical University, Yantai 264000, China
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Jianwei Gong
- School of Rehabilitation Medicine, Binzhou Medical University, Yantai 264000, China
| | - Xin Wang
- Department of Rehabilitation Medicine, Clinical Medical College, Yangzhou University, Yangzhou 225001, China
| | - Kenneth N. K. Fong
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| |
Collapse
|
3
|
Zhang X, Lu B, Chen C, Yang L, Chen W, Yao D, Hou J, Qiu J, Li F, Xu P. The correlation between upper body grip strength and resting-state EEG network. Med Biol Eng Comput 2023:10.1007/s11517-023-02865-4. [PMID: 37338738 DOI: 10.1007/s11517-023-02865-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 06/07/2023] [Indexed: 06/21/2023]
Abstract
Current research in the field of neuroscience primarily focuses on the analysis of electroencephalogram (EEG) activities associated with movement within the central nervous system. However, there is a dearth of studies investigating the impact of prolonged individual strength training on the resting state of the brain. Therefore, it is crucial to examine the correlation between upper body grip strength and resting-state EEG networks. In this study, coherence analysis was utilized to construct resting-state EEG networks using the available datasets. A multiple linear regression model was established to examine the correlation between the brain network properties of individuals and their maximum voluntary contraction (MVC) during gripping tasks. The model was used to predict individual MVC. The beta and gamma frequency bands showed significant correlation between RSN connectivity and MVC (p < 0.05), particularly in left hemisphere frontoparietal and fronto-occipital connectivity. RSN properties were consistently correlated with MVC in both bands, with correlation coefficients greater than 0.60 (p < 0.01). Additionally, predicted MVC positively correlated with actual MVC, with a coefficient of 0.70 and root mean square error of 5.67 (p < 0.01). The results show that the resting-state EEG network is closely related to upper body grip strength, which can indirectly reflect an individual's muscle strength through the resting brain network.
Collapse
Affiliation(s)
- Xiabing Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Bin Lu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Chunli Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Lei Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Wanjun Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, 611731, China
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, China
| | - Jingming Hou
- Department of Rehabilitation, Southwest Hospital, Army Medical University, Chongqing, 400038, China
| | - Jing Qiu
- Robotics Research Center, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China.
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China.
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, 611731, China.
| | - Peng Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China.
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China.
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, 611731, China.
- Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, 610041, China.
| |
Collapse
|
4
|
Santos AN, Kherif F, Melie-Garcia L, Lutti A, Chiappini A, Rauschenbach L, Dinger TF, Riess C, El Rahal A, Darkwah Oppong M, Sure U, Dammann P, Draganski B. Parkinson's disease may disrupt overlapping subthalamic nucleus and pallidal motor networks. Neuroimage Clin 2023; 38:103432. [PMID: 37210889 PMCID: PMC10213095 DOI: 10.1016/j.nicl.2023.103432] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 04/13/2023] [Accepted: 05/07/2023] [Indexed: 05/23/2023]
Abstract
There is an ongoing debate about differential clinical outcome and associated adverse effects of deep brain stimulation (DBS) in Parkinson's disease (PD) targeting the subthalamic nucleus (STN) or the globus pallidus pars interna (GPi). Given that functional connectivity profiles suggest beneficial DBS effects within a common network, the empirical evidence about the underlying anatomical circuitry is still scarce. Therefore, we investigate the STN and GPi-associated structural covariance brain patterns in PD patients and healthy controls. We estimate GPi's and STN's whole-brain structural covariance from magnetic resonance imaging (MRI) in a normative mid- to old-age community-dwelling cohort (n = 1184) across maps of grey matter volume, magnetization transfer (MT) saturation, longitudinal relaxation rate (R1), effective transversal relaxation rate (R2*) and effective proton density (PD*). We compare these with the structural covariance estimates in patients with idiopathic PD (n = 32) followed by validation using a reduced size controls' cohort (n = 32). In the normative data set, we observed overlapping spatially distributed cortical and subcortical covariance patterns across maps confined to basal ganglia, thalamus, motor, and premotor cortical areas. Only the subcortical and midline motor cortical areas were confirmed in the reduced size cohort. These findings contrasted with the absence of structural covariance with cortical areas in the PD cohort. We interpret with caution the differential covariance maps of overlapping STN and GPi networks in patients with PD and healthy controls as correlates of motor network disruption. Our study provides face validity to the proposed extension of the currently existing structural covariance methods based on morphometry features to multiparameter MRI sensitive to brain tissue microstructure.
Collapse
Affiliation(s)
- Alejandro N Santos
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Ferath Kherif
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Lester Melie-Garcia
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Antoine Lutti
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Alessio Chiappini
- Department of Neurosurgery, University Hospital Basel, Basel, Switzerland
| | - Laurèl Rauschenbach
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Thiemo F Dinger
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Christoph Riess
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Amir El Rahal
- Department of Neurosurgery, University Hospital Freiburg, Freiburg im Breisgau, Germany
| | - Marvin Darkwah Oppong
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Ulrich Sure
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Philipp Dammann
- Department of Neurosurgery, University Hospital Essen, Essen, Germany; Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg, Essen, Germany
| | - Bogdan Draganski
- Laboratory of Research in Neuroimaging (LREN) -Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| |
Collapse
|
5
|
Jiang R, Westwater ML, Noble S, Rosenblatt M, Dai W, Qi S, Sui J, Calhoun VD, Scheinost D. Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank. BMC Med 2022; 20:286. [PMID: 36076200 PMCID: PMC9461129 DOI: 10.1186/s12916-022-02490-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/20/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Grip strength is a widely used and well-validated measure of overall health that is increasingly understood to index risk for psychiatric illness and neurodegeneration in older adults. However, existing work has not examined how grip strength relates to a comprehensive set of mental health outcomes, which can detect early signs of cognitive decline. Furthermore, whether brain structure mediates associations between grip strength and cognition remains unknown. METHODS Based on cross-sectional and longitudinal data from over 40,000 participants in the UK Biobank, this study investigated the behavioral and neural correlates of handgrip strength using a linear mixed effect model and mediation analysis. RESULTS In cross-sectional analysis, we found that greater grip strength was associated with better cognitive functioning, higher life satisfaction, greater subjective well-being, and reduced depression and anxiety symptoms while controlling for numerous demographic, anthropometric, and socioeconomic confounders. Further, grip strength of females showed stronger associations with most behavioral outcomes than males. In longitudinal analysis, baseline grip strength was related to cognitive performance at ~9 years follow-up, while the reverse effect was much weaker. Further, baseline neuroticism, health, and financial satisfaction were longitudinally associated with subsequent grip strength. The results revealed widespread associations between stronger grip strength and increased grey matter volume, especially in subcortical regions and temporal cortices. Moreover, grey matter volume of these regions also correlated with better mental health and considerably mediated their relationship with grip strength. CONCLUSIONS Overall, using the largest population-scale neuroimaging dataset currently available, our findings provide the most well-powered characterization of interplay between grip strength, mental health, and brain structure, which may facilitate the discovery of possible interventions to mitigate cognitive decline during aging.
Collapse
Affiliation(s)
- Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA.
| | - Margaret L Westwater
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Matthew Rosenblatt
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Wei Dai
- Department of Biostatistics, Yale University, New Haven, CT, 06520, USA
| | - Shile Qi
- 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
| | - Jing Sui
- 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
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA.
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, 06520, USA.
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA.
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA.
| |
Collapse
|