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Li Y, Zhou G, Peng J, Liu L, Zhang F, Iturria-Medina Y, Yao D, Biswal BB, Wang P. White matter dysfunction in Alzheimer's disease is associated with disease-related transcriptomic signatures. Commun Biol 2025; 8:820. [PMID: 40437109 PMCID: PMC12120127 DOI: 10.1038/s42003-025-08177-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Accepted: 05/06/2025] [Indexed: 06/01/2025] Open
Abstract
While anatomical white matter (WM) alterations in Alzheimer's disease (AD) are well-established, functional WM dysregulation remains rarely investigated. The current study examines WM functional connectivity and network properties alterations in AD and mild cognitive impairment (MCI) and further describes their spatially correlated genes. AD and MCI shared decreased functional connectivity, clustering coefficient, and local efficiency within WM regions involved in impaired sensory-motor, visual-spatial, language, or memory functions. AD-specific dysfunction (i.e., AD vs. MCI and cognitively unimpaired participants) was predominantly located in WM, including anterior and posterior limb of internal capsule, corona radiata, and left tapetum. This WM dysfunction spatially correlates with specific genes, which are enriched in multiple biological processes related to synaptic function and development, and are mostly active in neurons and astrocytes. These findings may contribute to understanding molecular, cellular, and functional signatures associated with WM damage in AD.
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Affiliation(s)
- Yilu Li
- 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
| | - Guanyu Zhou
- 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
| | - Jinzhong Peng
- 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
| | - Lin Liu
- 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
| | - Fanyu Zhang
- 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
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
| | - Dezhong Yao
- 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
| | - 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, USA.
| | - 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.
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Zhao Z, Zhang B, Gan R, Xie H, Shao Y, Xu K, Jia Z. Causal relationships between white matter connectome and mental disorders: a large-scale genetic correlation study. J Affect Disord 2025; 386:119469. [PMID: 40419157 DOI: 10.1016/j.jad.2025.119469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2025] [Revised: 05/18/2025] [Accepted: 05/23/2025] [Indexed: 05/28/2025]
Abstract
BACKGROUND Abnormalities in white matter integrity in mental disorders have attracted widespread attention, yet the genetic correlations and causal effects between white matter structural connectome and various psychiatric conditions remain largely unexplored. METHODS In this study, we employed linkage disequilibrium score (LDSC) and high-definition likelihood (HDL) methods to analyze genetic correlations between white matter connectome and mental disorders, followed by bidirectional two-sample Mendelian randomization (MR) analysis to investigate causal relationships. We utilized 206 white matter connectome magnetic resonance imaging (MRI) phenotypes derived from the processed UK Biobank dataset (n = 26,333 individuals) and 12 mental disorders from the latest FinnGen database (n = 402,965 to 449,029 individuals). RESULTS Using both methods, we observed 26 pairs of brain white matter connectivity phenotypes and mental disorders showing significant correlations. Forward MR analysis identified two white matter structural connectome phenotypes causally associated with psychiatric disorder risk. Increased connectivity in left-hemisphere visual network(VIS) to right-hemisphere limbic network(LIM)white-matter structural connectivity was associated with increased risk of anxiety disorders. Additionally, decreased connectivity in left-hemisphere visual network to hippocampus white-matter structural connectivity was associated with reduced risk of post-traumatic stress disorder (PTSD). However, reverse MR analysis results did not survive multiple testing correction. CONCLUSION These findings provide crucial insights into the complex interplay between white matter structural connectivity and mental disorders, potentially offering new avenues for understanding the neurobiological underpinnings of psychiatric conditions and informing future diagnostic and therapeutic strategies.
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Affiliation(s)
- Ziru Zhao
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Baoshuai Zhang
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China; Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Ruoqiu Gan
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Hongsheng Xie
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Yingbo Shao
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Kun Xu
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Zhiyun Jia
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
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Wei J, Liu Z, Su H, She Y, Wang J, Liu Y, Zhong Y, Mo L, Tan C, Liu X, Chen L. Subregional alterations in corpus callosum is associated with different symptoms in early-stage parkinson's disease. Neurol Sci 2025; 46:2115-2127. [PMID: 39745586 DOI: 10.1007/s10072-024-07951-5] [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: 07/30/2024] [Accepted: 12/16/2024] [Indexed: 04/17/2025]
Abstract
OBJECTIVE Corpus callosum (CC) damage is the most consistent and typical change in early Parkinson's disease (PD), and is associated with various PD symptoms. However, the precise relationship between CC subregions and specific PD symptoms have not been identified comprehensively. In this study, we investigated the association between specific CC subregion alterations and PD symptoms using diffusion-weighted imaging. METHODS 70 PD patients in early-stage from the Parkinson's Progression Markers Initiative cohort were included. Fixel-based analysis (FBA) was used to calculate mean values of fiber density (FD), fiber cross-section (FC), and combined measure of FD and FC (FDC) for 7 CC subregions. Regression analyses between FBA metrics and PD symptom scores were performed to evaluate associations between CC subregion metrics and clinical symptom scores. Diffusion tensor imaging (DTI) metrics were also analyzed. RESULTS The score of akinetic rigid symptoms was negatively associated with FDC value of CC rostral body. The score of Activities of Daily Living was positively associated with FD value of CC anterior midbody. The score of gastrointestinal dysfunction was negatively associated with FDC value of CC rostrum. The severity of thermoregulatory dysfunction and cognitive decline was accompanied by an improvement in FBA metrics for several CC subregions. No significant associations were found using DTI metrics. CONCLUSIONS In early-stage of PD, motor, autonomic, and cognitive functions are associated with specific subregions of CC, and compensatory changes in CC may exist to maintain normal autonomic and cognitive functions.
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Affiliation(s)
- Jiahao Wei
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Zhihui Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Huahua Su
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Yuchen She
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Junyi Wang
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Ying Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Yuke Zhong
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Lijuan Mo
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Changhong Tan
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China
| | - Xi Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China.
| | - Lifen Chen
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China.
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Chu T, Si X, Song X, Che K, Dong F, Guo Y, Chen D, Yao W, Zhao F, Xie H, Shi Y, Ma H, Ming D, Mao N. Understanding structural-functional connectivity coupling in patients with major depressive disorder: A white matter perspective. J Affect Disord 2025; 373:219-226. [PMID: 39755127 DOI: 10.1016/j.jad.2024.12.082] [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: 10/06/2024] [Revised: 12/09/2024] [Accepted: 12/21/2024] [Indexed: 01/06/2025]
Abstract
PURPOSE To elucidate the structural-functional connectivity (SC-FC) coupling in white matter (WM) tracts in patients with major depressive disorder (MDD). METHODS A total of 178 individuals diagnosed with MDD and 173 healthy controls (HCs) were recruited for this study. The Euclidean distance was calculated to assess SC-FC coupling. The primary analyses focused on investigating alterations in SC-FC coupling in WM tracts of individuals with MDD. Additionally, we explored the association between coupling and clinical symptoms. Secondary analyses examined differences among three subgroups of MDD: those with suicidal ideation (SI), those with a history of suicidal attempts (SA), and those non-suicidal (NS). RESULTS The study revealed increased SC-FC coupling mainly in the middle cerebellar peduncle and bilateral corticospinal tract (PFDR < 0.05) in patients with MDD compared with HCs. Additionally, right cerebral peduncle coupling strength exhibited a significant positive correlation with Hamilton Anxiety Scale scores (r = 0.269, PFDR = 0.041), while right cingulum (hippocampus) coupling strength showed a significant negative correlation with Nurses' Global Assessment of Suicide Risk scores (r = -0.159, PFDR = 0.036). An increase in left anterior limb of internal capsule (PBonferroni < 0.01) and left corticospinal tract (PBonferroni < 0.05) coupling has been observed in MDD with SI. Additionally, a decrease in right posterior limb of internal capsule coupling has been found in MDD with SA (PBonferroni < 0.05). CONCLUSIONS This study emphasizes the variations in SC-FC coupling in WM tracts in individuals with MDD and its subgroups, highlighting the crucial role of WM networks in the pathophysiology of MDD.
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Affiliation(s)
- Tongpeng Chu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, PR China; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, PR China; Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin 300072, PR China; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin 300392, PR China; Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, PR China; Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women's Diseases (Yantai Yuhuangding Hospital), Yantai, Shandong 264000, PR China; Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, PR China; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin 300072, PR China; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin 300392, PR China; Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, PR China.
| | - Xicheng Song
- Shandong Provincial Key Laboratory of Neuroimmune Interaction and Regulation, Yantai, Shandong 26400, PR China
| | - Kaili Che
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Fanghui Dong
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Yuting Guo
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong 264000, PR China
| | - Danni Chen
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong 264000, PR China
| | - Wei Yao
- Department of Neurology, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, Shandong 253000, PR China
| | - Feng Zhao
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, Shandong 264000, PR China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China.
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, PR China; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin 300072, PR China; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin 300392, PR China; Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, PR China.
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China; Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women's Diseases (Yantai Yuhuangding Hospital), Yantai, Shandong 264000, PR China; Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China.
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LinLi Z, Hu K, Guo Q, Guo S. Static and dynamic connectivity structure of white-matter functional networks across the adult lifespan. Prog Neuropsychopharmacol Biol Psychiatry 2025; 136:111252. [PMID: 39809409 DOI: 10.1016/j.pnpbp.2025.111252] [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: 10/02/2024] [Revised: 12/28/2024] [Accepted: 01/10/2025] [Indexed: 01/16/2025]
Abstract
Aging of the human brain involves intricate biological processes, resulting in complex changes in structure and function. While the effects of aging on gray matter (GM) connectivity are extensively studied, white matter (WM) functional changes have received comparatively less attention. This study examines age-related WM functional dynamics using resting-state fMRI across the adult lifespan. We identified GM and WM functional networks (FNs) using k-means clustering. Static and dynamic analyses of WM functional network connectivity (FNC) were performed to explore age effects on WM-FNs and recurrent patterns of dynamic FNC. We identified 9 WM and 12 GM FNs. Age-related effects on WM FNC strength and WM-GM FNC dynamics included linear positive and U-shaped age trajectories in static FNC strength, and linear negative and inverted U-shaped trajectories in FNC temporal variability. Three distinct brain states with significant age-related differences were identified and validated. These findings were largely replicated in the validation analysis. High integration and low temporal variability in WM-GM FNC may indicate reduced adaptability of the network system in older adults, offering insights into brain aging processes.
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Affiliation(s)
- Zeqiang LinLi
- School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou 510004, PR China; MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha 410006, PR China
| | - Kang Hu
- School of Information Engineering, Wuhan Business University, Wuhan 430056, PR China; MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha 410006, PR China
| | - Qingdong Guo
- School of Mathematical Sciences, Xiamen University, Xiamen 361005, PR China
| | - Shuixia Guo
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha 410006, PR China; Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha 410006, PR China.
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Chen C, Cao J, Zhang T, Zhang H, Shi Q, Li X, Wang L, Tian J, Huang G, Wang Y, Zhao L. Alterations in corpus callosum subregions morphology and functional connectivity in patients with adult-onset hypothyroidism. Brain Res 2024; 1840:149110. [PMID: 38964705 DOI: 10.1016/j.brainres.2024.149110] [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: 04/24/2024] [Revised: 06/16/2024] [Accepted: 07/02/2024] [Indexed: 07/06/2024]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) brain abnormalities have been reported in the corpus callosum (CC) of patients with adult-onset hypothyroidism. However, no study has directly compared CC-specific morphological or functional alterations among subclinical hypothyroidism (SCH), overt hypothyroidism (OH), and healthy controls (HC). Moreover, the association of CC alterations with cognition and emotion is not well understood. METHODS Demographic data, clinical variables, neuropsychological scores, and MRI data of 152 participants (60 SCH, 37 OH, and 55 HC) were collected. This study investigated the clinical performance, morphological and functional changes of CC subregions across three groups. Moreover, a correlation analysis was performed to explore potential relationships between these factors. RESULTS Compared to HC, SCH and OH groups exhibited lower cognitive scores and higher depressive/anxious scores. Notably, rostrum and rostral body volume of CC was larger in the SCH group. Functional connectivity between rostral body, anterior midbody and the right precentral and dorsolateral superior frontal gyrus were increased in the SCH group. In contrast, the SCH and OH groups exhibited a decline in functional connectivity between splenium and the right angular gyrus. Within the SCH group, rostrum volume demonstrated a negative correlation with Montreal Cognitive Assessment and visuospatial/executive scores, while displaying a positive correlation with 24-item Hamilton Depression Rating Scale scores. In the OH group, rostral body volume exhibited a negative correlation with serum thyroid stimulating hormone levels, while a positive correlation with serum total thyroxine and free thyroxine levels. CONCLUSIONS This study suggests that patients with different stages of adult-onset hypothyroidism may exhibit different patterns of CC abnormalities. These findings offer new insights into the neuropathophysiological mechanisms in hypothyroidism.
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Affiliation(s)
- Chen Chen
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China.
| | - Jiancang Cao
- Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China.
| | - Taotao Zhang
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China.
| | - Huiyan Zhang
- School of Clinical Medicine, Ningxia Medical University, Yinchuan 750000, China.
| | - Qian Shi
- The First Clinical Medical College, Gansu University of Chinese Medicine, Lanzhou 730000, China.
| | - Xiaotao Li
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China.
| | - Liting Wang
- The First Clinical Medical College, Gansu University of Chinese Medicine, Lanzhou 730000, China.
| | - Jinghe Tian
- The First Clinical Medical College, Gansu University of Chinese Medicine, Lanzhou 730000, China.
| | - Gang Huang
- Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China.
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510000, China.
| | - Lianping Zhao
- The First Clinical Medical College, Lanzhou University, Lanzhou 730000, China; Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China.
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Albadawi EA. Microstructural Changes in the Corpus Callosum in Neurodegenerative Diseases. Cureus 2024; 16:e67378. [PMID: 39310519 PMCID: PMC11413839 DOI: 10.7759/cureus.67378] [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] [Accepted: 08/21/2024] [Indexed: 09/25/2024] Open
Abstract
The corpus callosum, the largest white matter structure in the brain, plays a crucial role in interhemispheric communication and cognitive function. This review examines the microstructural changes observed in the corpus callosum across various neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis (ALS). New neuroimaging studies, mainly those that use diffusion tensor imaging (DTI) and advanced tractography methods, were put together to show how changes have happened in the organization of white matter and the connections between them. Some of the most common ways the corpus callosum breaks down are discussed, including less fractional anisotropy, higher mean diffusivity, and atrophy in certain regions. The relationship between these microstructural changes and cognitive decline, motor dysfunction, and disease progression is explored. Additionally, we consider the potential of corpus callosum imaging as a biomarker for early disease detection and monitoring. Studies show that people with these disorders have lower fractional anisotropy and higher mean diffusivity in the corpus callosum, often in ways that are specific to the disease. These changes often happen before gray matter atrophy and are linked to symptoms, which suggests that the corpus callosum could be used as an early sign of neurodegeneration. The review also highlights the implications of these findings for understanding disease mechanisms and developing therapeutic strategies. Future directions, including the application of advanced imaging techniques and longitudinal studies, are discussed to elucidate the role of corpus callosum degeneration in neurodegenerative processes. This review underscores the importance of the corpus callosum in understanding the pathophysiology of neurodegenerative diseases and its potential as a target for therapeutic interventions.
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Affiliation(s)
- Emad A Albadawi
- Department of Basic Medical Sciences, College of Medicine, Taibah Univeristy, Madinah, SAU
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Eugenia Caligiuri M, Quattrone A, Giovanna Bianco M, Riccardo Aquila V, Celeste Bonacci M, Calomino C, Camastra C, Buonocore J, Augimeri A, Morelli M, Quattrone A. Corpus callosum damage in PSP and unsteady PD patients: A multimodal MRI study. Neuroimage Clin 2024; 43:103642. [PMID: 39029159 PMCID: PMC11315164 DOI: 10.1016/j.nicl.2024.103642] [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: 03/14/2024] [Revised: 06/24/2024] [Accepted: 07/13/2024] [Indexed: 07/21/2024]
Abstract
INTRODUCTION Postural instability (PI) is a common disabling symptom in Parkinson's disease (PD) patients, but the brain alterations underlying this sign are not fully understood yet. This study aimed to investigate the association between PI and callosal damage in PD and progressive supranuclear palsy (PSP) patients, using multimodal MR imaging. METHODS One-hundred and two PD patients stratified according to the presence/absence of PI (PD-steady N=58; PD-unsteady N=44), 69 PSP patients, and 38 healthy controls (HC) underwent structural and diffusion 3T brain MRI. Thickness, fractional anisotropy (FA) and mean diffusivity (MD) were calculated over 50 equidistant points covering the whole midsagittal profile of the corpus callosum (CC) and compared among groups. Associations between imaging metrics and postural instability score were investigated using linear regression. RESULTS Both PSP and PD-unsteady patient groups showed CC involvement in comparison with HC, while no difference was found between PD-steady patients and controls. The CC damage was more severe and widespread in PSP than in PD patients. The CC genu was the regions most damaged in PD-unsteady patients compared with PD-steady patients, showing significant microstructural alterations of MD and FA metrics. Linear regression analysis pointed at the MD in the CC genu as the main contributor to PI among the considered MRI metrics. CONCLUSION This study identified callosal microstructural alterations associated with PI in unsteady PD and PSP patients, which provide new insights on PI pathophysiology and might serve as imaging biomarkers for assessing postural instability progression and treatment response.
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Affiliation(s)
- Maria Eugenia Caligiuri
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Andrea Quattrone
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy; Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy.
| | - Maria Giovanna Bianco
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Valerio Riccardo Aquila
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Maria Celeste Bonacci
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Camilla Calomino
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Chiara Camastra
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy
| | - Jolanda Buonocore
- Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy
| | | | - Maurizio Morelli
- Institute of Neurology, Department of Medical and Surgical Sciences, Magna Graecia University, Catanzaro, Italy
| | - Aldo Quattrone
- Neuroscience Research Center, Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy
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Li Y, Peng J, Yang Z, Zhang F, Liu L, Wang P, Biswal BB. Altered white matter functional pathways in Alzheimer's disease. Cereb Cortex 2024; 34:bhad505. [PMID: 38436465 DOI: 10.1093/cercor/bhad505] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 10/13/2023] [Accepted: 12/03/2023] [Indexed: 03/05/2024] Open
Abstract
Alzheimer's disease (AD) is associated with functional disruption in gray matter (GM) and structural damage to white matter (WM), but the relationship to functional signal in WM is unknown. We performed the functional connectivity (FC) and graph theory analysis to investigate abnormalities of WM and GM functional networks and corpus callosum among different stages of AD from a publicly available dataset. Compared to the controls, AD group showed significantly decreased FC between the deep WM functional network (WM-FN) and the splenium of corpus callosum, between the sensorimotor/occipital WM-FN and GM visual network, but increased FC between the deep WM-FN and the GM sensorimotor network. In the clinical groups, the global assortativity, modular interaction between occipital WM-FN and visual network, nodal betweenness centrality, degree centrality, and nodal clustering coefficient in WM- and GM-FNs were reduced. However, modular interaction between deep WM-FN and sensorimotor network, and participation coefficients of deep WM-FN and splenium of corpus callosum were increased. These findings revealed the abnormal integration of functional networks in different stages of AD from a novel WM-FNs perspective. The abnormalities of WM functional pathways connect downward to the corpus callosum and upward to the GM are correlated with AD.
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Affiliation(s)
- Yilu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Jinzhong Peng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Zhenzhen Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Fanyu Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Lin Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, NO. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, China
- Department of Biomedical Engineering, New Jersey Institute of Technology, 154 Summit Street, Newark 07102, NJ, United States
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10
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Najafzadeh M, Mohammadian F, Mirabian S, Ganji Z, Akbari H, Rezaie M, Ranjbar E, Zare H, Nasseri S, Ferini‐Strambi L. Rapid eye movement sleep behavior disorder and its relation to Parkinson's disease: The potential of graph measures as brain biomarkers to identify the underlying physiopathology of the disorder. Brain Behav 2024; 14:e3460. [PMID: 38494747 PMCID: PMC10945078 DOI: 10.1002/brb3.3460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 03/19/2024] Open
Abstract
Rapid eye movement behavior disorder (RBD) is a parasomnia characterized by the loss of skeletal muscle atonia during the rapid eye movement (REM) sleep phase. On the other hand, idiopathic RDB (iRBD) is considered the prelude of the various α-synucleinopathies, including Parkinson's disease (PD), dementia with Lewy bodies and multiple system atrophy. Consequently, over 40% of patients eventually develop PD. Recent neuroimaging studies utilizing structural magnetic resonance imaging (s-MRI), diffusion-weighted imaging (DWI), and functional magnetic resonance imaging (fMRI) with graph theoretical analysis have demonstrated that patients with iRBD and Parkinson's disease have extensive brain abnormalities. Thus, it is crucial to identify new biomarkers that aid in determining the underlying physiopathology of iRBD group. This review was conducted systematically on the included full-text articles of s-MRI, DWI, and fMRI studies using graph theoretical analysis on patients with iRBD, per the procedures recommended by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The literature search was conducted through the PubMed and Google scholar databases concentrating on studies from September to January 2022. Based on the three perspectives of integration, segregation, and centrality, the reviewed articles demonstrated that iRBD is associated with segregation disorders in frontal and limbic brain regions. Moreover, this study highlighted the need for additional longitudinal and multicenter studies to better understand the potential of graph metrics as brain biomarkers for identifying the underlying physiopathology of iRBD group.
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Affiliation(s)
- Milad Najafzadeh
- Department of Medical Physics, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Fatemeh Mohammadian
- Department of Medical Physics, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Sara Mirabian
- Department of Medical Physics, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Zohre Ganji
- Department of Medical Physics, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Hossein Akbari
- Department of Medical Physics, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Masoud Rezaie
- Department of Medical Physics, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Esmaeil Ranjbar
- Department of Anatomy and Cell Biology, School of MedicineMashhad University of Medical SciencesMashhadIran
| | - Hoda Zare
- Department of Medical Physics, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
- Medical Physics Research CenterMashhad University of Medical SciencesMashhadIran
| | - Shahrokh Nasseri
- Department of Medical Physics, Faculty of MedicineMashhad University of Medical SciencesMashhadIran
- Medical Physics Research CenterMashhad University of Medical SciencesMashhadIran
| | - Luigi Ferini‐Strambi
- Vita‐Salute San Raffaele UniversityMilanItaly
- Division of Neuroscience, Sleep Disorders CenterSan Raffaele Scientific InstituteMilanItaly
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11
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Wang P, Jiang Y, Biswal BB. Aberrant interhemispheric structural and functional connectivity within whole brain in schizophrenia. Schizophr Res 2024; 264:336-344. [PMID: 38218019 DOI: 10.1016/j.schres.2023.12.033] [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: 09/19/2022] [Revised: 11/27/2023] [Accepted: 12/26/2023] [Indexed: 01/15/2024]
Abstract
OBJECTIVE Schizophrenia is a serious mental disorder whose etiology remains unclear. Although numerous studies have analyzed the abnormal gray matter functional activity and whole-brain anatomical changes in schizophrenia, fMRI signal fluctuations from white matter have usually been ignored and rarely reported in the literature. METHODS We employed 45 schizophrenia subjects and 75 healthy controls (HCs) from a publicly available fMRI dataset. By combining the voxel-mirrored homotopic connectivity (VMHC) measure and fiber tracking method, we investigated the interhemispheric functional and structural connectivity within whole brain in schizophrenia. RESULTS Compared to HCs, patients with schizophrenia exhibited significantly reduced VMHC in the bilateral middle occipital gyrus, precentral gyrus, postcentral gyrus and corpus callosum. Fiber tracking results showed the changes in structural connectivity for the bilateral precentral gyrus, and the bilateral corpus callosum, and the fiber bundles connecting bilateral precentral gyrus and connecting the bilateral corpus callosum passed through the posterior midbody, isthmus and splenium of mid-sagittal corpus callosum, which closely related to the interhemispheric integration of visual and auditory information. More importantly, we observed a negative correlation between averaged VMHC values in the postcentral gyrus and SAPS scores, and a positive correlation between the fractional anisotropy of fiber bundle connecting the bilateral precentral gyrus and Matrix Reasoning scores in schizophrenia. CONCLUSION Our findings provide a novel perspective of white matter functional images on understanding abnormal interhemispheric visual and auditory information transfer in schizophrenia.
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Affiliation(s)
- Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuan Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, 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 07102, USA.
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12
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Chen K, Zhuang W, Zhang Y, Yin S, Liu Y, Chen Y, Kang X, Ma H, Zhang T. Alteration of the large-scale white-matter functional networks in autism spectrum disorder. Cereb Cortex 2023; 33:11582-11593. [PMID: 37851712 DOI: 10.1093/cercor/bhad392] [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: 09/07/2023] [Revised: 10/02/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023] Open
Abstract
Autism spectrum disorder is a neurodevelopmental disorder whose core deficit is social dysfunction. Previous studies have indicated that structural changes in white matter are associated with autism spectrum disorder. However, few studies have explored the alteration of the large-scale white-matter functional networks in autism spectrum disorder. Here, we identified ten white-matter functional networks on resting-state functional magnetic resonance imaging data using the K-means clustering algorithm. Compared with the white matter and white-matter functional network connectivity of the healthy controls group, we found significantly decreased white matter and white-matter functional network connectivity mainly located within the Occipital network, Middle temporo-frontal network, and Deep network in autism spectrum disorder. Compared with healthy controls, findings from white-matter gray-matter functional network connectivity showed the decreased white-matter gray-matter functional network connectivity mainly distributing in the Occipital network and Deep network. Moreover, we compared the spontaneous activity of white-matter functional networks between the two groups. We found that the spontaneous activity of Middle temporo-frontal and Deep network was significantly decreased in autism spectrum disorder. Finally, the correlation analysis showed that the white matter and white-matter functional network connectivity between the Middle temporo-frontal network and others networks and the spontaneous activity of the Deep network were significantly correlated with the Social Responsiveness Scale scores of autism spectrum disorder. Together, our findings indicate that changes in the white-matter functional networks are associated behavioral deficits in autism spectrum disorder.
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Affiliation(s)
- Kai Chen
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Wenwen Zhuang
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Yanfang Zhang
- Department of Ultrasonic Medicine, Baiyun Branch, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Baiyun District, Guangzhou City, Guangdong Province, China
| | - Shunjie Yin
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Yinghua Liu
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Yuan Chen
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
| | - Xiaodong Kang
- The Department of Sichuan 81 Rehabilitation Center, Chengdu University of TCM, No. 81 Bayi Road, Yongning Street, Wenjiang District, Chengdu City 610075, China
| | - Hailin Ma
- Plateau Brain Science Research Center, Tibet University, 10 Zangda East Road, Lhasa City 510631, China
| | - Tao Zhang
- Mental Health Education Center and School of Big Health Management, Xihua University, Jinniu District, Chengdu, Sichuan, China
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13
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Wang P, Jiang Y, Hoptman MJ, Li Y, Cao Q, Shah P, Klugah-Brown B, Biswal BB. Structural-functional connectivity deficits of callosal-white matter-cortical circuits in schizophrenia. Psychiatry Res 2023; 330:115559. [PMID: 37931478 DOI: 10.1016/j.psychres.2023.115559] [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: 08/24/2023] [Revised: 10/18/2023] [Accepted: 10/21/2023] [Indexed: 11/08/2023]
Abstract
Schizophrenia is increasingly recognized as a disorder with altered integration between large-scale functional networks and cortical-subcortical pathways. This spatial long-distance information communication must be associated with white matter (WM) fiber bundles. With accumulating evidence that WM functional signals reflect the intrinsic neural activities, how the deep callosal organization modulates cortical functional activities through WM remains unclear in schizophrenia. Using a data-driven method, we identified nine WM and gray matter (GM) functional networks, and then parcellated corpus callosum into distinct sub-regions. Combining functional connectivity and fiber tracking analysis, we estimated the structural and functional connectivity changes of callosal-WM-cortical circuits in schizophrenia. We observed higher structural and functional connectivity between corpus callosum, WM and GM functional networks involving visual network (visual processing), executive control network (executive controls), ventral attention network (processing of salience), and limbic network (emotion processing) in schizophrenia compared to healthy controls. We also found nine abnormal pathways of callosal-WM-cortical circuits involving the above networks and default mode network (self-related thought). These results highlight the role of connectivity deficits in callosal-WM-cortical circuits may play in understanding the delusions, hallucinations and cognitive impairment of schizophrenia.
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Affiliation(s)
- Pan Wang
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.
| | - Yuan Jiang
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Matthew J Hoptman
- Division of Clinical Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA; Department of Psychiatry, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Yilu Li
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Qingquan Cao
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Pushti Shah
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
| | - Benjamin Klugah-Brown
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.
| | - Bharat B Biswal
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China; Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
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14
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Videtta G, Squarcina L, Rossetti MG, Brambilla P, Delvecchio G, Bellani M. White matter modifications of corpus callosum in bipolar disorder: A DTI tractography review. J Affect Disord 2023; 338:220-227. [PMID: 37301293 DOI: 10.1016/j.jad.2023.06.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 05/08/2023] [Accepted: 06/04/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND The recent widespread use of diffusion tensor imaging (DTI) tractography allowed researchers to investigate the diffusivity modifications and neuroanatomical changes of white matter (WM) fascicles in major psychiatric disorders, including bipolar disorder (BD). In BD, corpus callosum (CC) seems to have a crucial role in explaining the pathophysiology and cognitive impairment of this psychiatric disorder. This review aims to provide an overview on the latest results emerging from studies that investigated neuroanatomical changes of CC in BD using DTI tractography. METHODS Bibliographic research was conducted on PubMed, Scopus and Web of Science datasets until March 2022. Ten studies fulfilled our inclusion criteria. RESULTS From the reviewed DTI tractography studies a significant decrease of fractional anisotropy emerged in the genu, body and splenium of CC of BD patients compared to controls. This finding is coupled with reduction of fiber density and modification in fiber tract length. Finally, an increase of radial and mean diffusivity in forceps minor and in the entire CC was also reported. LIMITATIONS Small sample size, heterogeneity in terms of methodological (diffusion gradient) and clinical (lifetime comorbidity, BD status, pharmacological treatments) characteristics. CONCLUSIONS Overall, these findings suggest the presence of structural modifications in CC in BD patients, which may in turn explain the cognitive impairments often observed in this psychiatric disorder, especially in executive processing, motor control and visual memory. Finally, structural modifications may suggest an impairment in the amount of functional information and a morphological impact within those brain regions connected by CC.
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Affiliation(s)
- Giovanni Videtta
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy
| | - Letizia Squarcina
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Maria Gloria Rossetti
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy.
| | - Marcella Bellani
- Section of Psychiatry, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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15
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Duque ACM, Cuesta TAC, Melo ADS, Maldonado IL. Right hemisphere and metaphor comprehension: A connectionist perspective. Neuropsychologia 2023; 187:108618. [PMID: 37321404 DOI: 10.1016/j.neuropsychologia.2023.108618] [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: 09/26/2022] [Revised: 04/11/2023] [Accepted: 06/10/2023] [Indexed: 06/17/2023]
Abstract
Metaphor comprehension is a cognitively complex task, with evidence pointing to the engagement of multiple cerebral areas. In addition, the involvement of the right hemisphere appears to vary with cognitive effort. Therefore, the interconnecting pathways of such distributed cortical centers should be taken into account when studying this topic. Despite this, the potential contribution of white matter fasciculi has received very little attention in the literature to date and is not mentioned in most metaphor comprehension studies. To highlight the probable implications of the right inferior fronto-occipital fasciculus, right superior longitudinal system, and callosal radiations, we bring together findings from different research fields. The aim is to describe important insights enabled by the cross-fertilization of functional neuroimaging, clinical findings, and structural connectivity.
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Affiliation(s)
- Anna Clara Mota Duque
- Programa de Pós-Graduação em Medicina e Saúde, Universidade Federal da Bahia, Salvador, Brazil; Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Brazil
| | - Taryn Ariadna Castro Cuesta
- Programa de Pós-Graduação em Medicina e Saúde, Universidade Federal da Bahia, Salvador, Brazil; Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Brazil
| | - Ailton de Souza Melo
- Programa de Pós-Graduação em Medicina e Saúde, Universidade Federal da Bahia, Salvador, Brazil; Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Brazil
| | - Igor Lima Maldonado
- Programa de Pós-Graduação em Medicina e Saúde, Universidade Federal da Bahia, Salvador, Brazil; Dep. Biomorfologia, Instituto de Ciências da Saúde, Universidade Federal da Bahia, Salvador, Brazil; UMR 1253, iBrain, Université de Tours, Inserm, Tours, France.
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16
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Zhao R, Wang P, Liu L, Zhang F, Hu P, Wen J, Li H, Biswal BB. Whole-brain structure-function coupling abnormalities in mild cognitive impairment: a study combining amplitude of low-frequency fluctuations and voxel-based morphometry. Front Neurosci 2023; 17:1236221. [PMID: 37583417 PMCID: PMC10424122 DOI: 10.3389/fnins.2023.1236221] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 07/12/2023] [Indexed: 08/17/2023] Open
Abstract
Alzheimer's disease (AD), one of the leading diseases of the nervous system, is accompanied by symptoms such as loss of memory, thinking and language skills. Both mild cognitive impairment (MCI) and very mild cognitive impairment (VMCI) are the transitional pathological stages between normal aging and AD. While the changes in whole-brain structural and functional information have been extensively investigated in AD, The impaired structure-function coupling remains unknown. The current study employed the OASIS-3 dataset, which includes 53 MCI, 90 VMCI, and 100 Age-, gender-, and education-matched normal controls (NC). Several structural and functional parameters, such as the amplitude of low-frequency fluctuations (ALFF), voxel-based morphometry (VBM), and The ALFF/VBM ratio, were used To estimate The whole-brain neuroimaging changes In MCI, VMCI, and NC. As disease symptoms became more severe, these regions, distributed in the frontal-inf-orb, putamen, and paracentral lobule in the white matter (WM), exhibited progressively increasing ALFF (ALFFNC < ALFFVMCI < ALFFMCI), which was similar to the tendency for The cerebellum and putamen in the gray matter (GM). Additionally, as symptoms worsened in AD, the cuneus/frontal lobe in the WM and the parahippocampal gyrus/hippocampus in the GM showed progressively decreasing structure-function coupling. As the typical focal areas in AD, The parahippocampal gyrus and hippocampus showed significant positive correlations with the severity of cognitive impairment, suggesting the important applications of the ALFF/VBM ratio in brain disorders. On the other hand, these findings from WM functional signals provided a novel perspective for understanding the pathophysiological mechanisms involved In cognitive decline in AD.
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Affiliation(s)
- Rong Zhao
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Pan Wang
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Lin Liu
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Fanyu Zhang
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Peng Hu
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Jiaping Wen
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongyi Li
- The Fourth People’s Hospital of Chengdu, Chengdu, China
| | - Bharat B. Biswal
- MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, The Clinical Hospital of Chengdu Brain Science Institute, 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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17
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Nozais V, Forkel SJ, Petit L, Talozzi L, Corbetta M, Thiebaut de Schotten M, Joliot M. Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain. Commun Biol 2023; 6:726. [PMID: 37452124 PMCID: PMC10349117 DOI: 10.1038/s42003-023-05107-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 07/06/2023] [Indexed: 07/18/2023] Open
Abstract
Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.
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Affiliation(s)
- Victor Nozais
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France.
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France.
| | - Stephanie J Forkel
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Donders Institute for Brain Cognition Behaviour, Radboud University, Nijmegen, the Netherlands
- Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Departments of Neurosurgery, Technical University of Munich School of Medicine, Munich, Germany
| | - Laurent Petit
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France
| | - Lia Talozzi
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Maurizio Corbetta
- Department of Neuroscience, Venetian Institute of Molecular Medicine and Padova Neuroscience Center, University of Padua, Padova, PD, 32122, Italy
| | - Michel Thiebaut de Schotten
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
| | - Marc Joliot
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France.
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18
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Jelisejevs I, Upite J, Kalnins S, Jansone B. An Improved Surgical Approach for Complete Interhemispheric Corpus Callosotomy Combined with Extended Frontoparietal Craniotomy in Mice. Biomedicines 2023; 11:1782. [PMID: 37509422 PMCID: PMC10376606 DOI: 10.3390/biomedicines11071782] [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: 04/20/2023] [Revised: 06/19/2023] [Accepted: 06/20/2023] [Indexed: 07/30/2023] Open
Abstract
Callosotomy is an invasive method that is used to study the role of interhemispheric functional connectivity in the brain. This surgical approach is technically demanding to perform in small laboratory animals, such as rodents, due to several methodological challenges. To date, there exist two main approaches for transecting the corpus callosum (CC) in rodents: trephine hole(s) or unilateral craniotomy, which cause damage to the cerebral cortex or the injury of large vessels, and may lead to intracranial hemorrhage and animal death. This study presents an improved surgical approach for complete corpus callosotomy in mice using an interhemispheric approach combined with bilateral and extended craniotomy across the midline. This study demonstrated that bilateral and extended craniotomy provided the visual space required for hemisphere and sinus retraction, thus keeping large blood vessels and surrounding brain structures intact under the surgical microscope using standardized surgical instruments. We also emphasized the importance of good post-operative care leading to an increase in overall animal survival following experimentation. This optimized surgical approach avoids extracallosal tissue and medium- to large-sized cerebral blood vessel damage in mice, which can provide higher study reproducibility/validity among animals when revealing the role of the CC in various neurological pathologies.
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Affiliation(s)
| | | | | | - Baiba Jansone
- Department of Pharmacology, Faculty of Medicine, University of Latvia, LV-1586 Riga, Latvia; (I.J.); (J.U.); (S.K.)
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19
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Chen SJ, Wu BS, Ge YJ, Chen SD, Ou YN, Dong Q, Feng J, Cheng W, Yu JT. The genetic architecture of the corpus callosum and its genetic overlap with common neuropsychiatric diseases. J Affect Disord 2023; 335:418-430. [PMID: 37164063 DOI: 10.1016/j.jad.2023.05.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 04/25/2023] [Accepted: 05/02/2023] [Indexed: 05/12/2023]
Abstract
BACKGROUND The corpus callosum (CC) is the main structure transferring information between the cerebral hemispheres. Although previous large-scale genome-wide association study (GWAS) has illustrated the genetic architecture of white matter integrity of CC, CC volume is less stressed. METHODS Using MRI data from 33,861 individuals in UK Biobank, we conducted univariate and multivariate GWAS for CC fractional anisotropy (FA) and volume with PLINK 2.0 and MOSTest. All discovered SNPs in the multivariate framework were functionally annotated in FUMA v1.3.8. In the meanwhile, a series of gene property analyses was conducted simultaneously. In addition, we estimated genetic relationship between CC metrics and other neuropsychiatric traits and diseases. RESULTS We identified a total of 36 and 82 significant genomic loci for CC FA and volume (P < 5 × 10-8). And 53 and 27 genes were respectively mapped by four mapping strategies. For CC volume, gene-set analysis revealed pathways mainly relating to cell migration; cell-type analysis found the top enrichment in neuroglia while for CC FA in GABAergic neurons. Furthermore, we found a lot of genetic overlap and shared loci between CC FA and volume and common neuropsychiatric diseases. DISCUSSION Collectively, this study helps to better understand the genetic architecture of whole CC and CC subregions. However, the way to divide CC FA and volume in our study restricts the interpretations of our results. Future work will be needed to pay attention to the genetic structure of white matter volume, and an appropriate division of CC may help to better understand CC structure.
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Affiliation(s)
- Si-Jia Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi-Jun Ge
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
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20
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Klugah-Brown B, Wang P, Jiang Y, Becker B, Hu P, Uddin LQ, Biswal B. Structural-functional connectivity mapping of the insular cortex: a combined data-driven and meta-analytic topic mapping. Cereb Cortex 2023; 33:1726-1738. [PMID: 35511500 DOI: 10.1093/cercor/bhac168] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 04/06/2022] [Accepted: 04/07/2022] [Indexed: 11/15/2022] Open
Abstract
In this study, we examined structural and functional profiles of the insular cortex and mapped associations with well-described functional networks throughout the brain using diffusion tensor imaging (DTI) and resting-state functional connectivity (RSFC) data. We used a data-driven method to independently estimate the structural-functional connectivity of the insular cortex. Data were obtained from the Human Connectome Project comprising 108 adult participants. Overall, we observed moderate to high associations between the structural and functional mapping scores of 3 different insular subregions: the posterior insula (associated with the sensorimotor network: RSFC, DTI = 50% and 72%, respectively), dorsal anterior insula (associated with ventral attention: RSFC, DTI = 83% and 83%, respectively), and ventral anterior insula (associated with the frontoparietal: RSFC, DTI = 42% and 89%, respectively). Further analyses utilized meta-analytic decoding maps to demonstrate specific cognitive and affective as well as gene expression profiles of the 3 subregions reflecting the core properties of the insular cortex. In summary, given the central role of the insular in the human brain, our results revealing correspondence between DTI and RSFC mappings provide a complementary approach and insight for clinical researchers to identify dysfunctional brain organization in various neurological disorders associated with insular pathology.
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Affiliation(s)
- Benjamin Klugah-Brown
- 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, No. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731 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, No. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731 Chengdu, China
| | - Yuan Jiang
- 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, No. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731 Chengdu, China
| | - Benjamin Becker
- 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, No. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731 Chengdu, China
| | - 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, No. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731 Chengdu, China
| | - Lucina Q Uddin
- Department of Biomedical Engineering, New Jersey Institute of Technology, 323 Dr Martin Luther King Jr Blvd, Newark, NJ 07102, United States
| | - Bharat 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, No. 2006, Xiyuan Ave, West Hi-Tech Zone, 611731 Chengdu, China.,Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90095, United States
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21
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Du J, Zhou X, Liang Y, Zhao L, Dai C, Zhong Y, Liu H, Liu G, Mo L, Tan C, Liu X, Chen L. Levodopa responsiveness and white matter alterations in Parkinson's disease: A DTI-based study and brain network analysis: A cross-sectional study. Brain Behav 2022; 12:e2825. [PMID: 36423257 PMCID: PMC9759147 DOI: 10.1002/brb3.2825] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 09/24/2022] [Accepted: 11/01/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Patients with Parkinson's disease (PD) present various responsiveness to levodopa, but the cause of such differences in levodopa responsiveness is unclear. Previous studies related the damage of brain white matter (WM) to levodopa responsiveness in PD patients, but no study investigated the relationship between the structural brain network change in PD patients and their levodopa responsiveness. METHODS PD patients were recruited and evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS). Each patient received a diffusion tensor imaging (DTI) scan and an acute levodopa challenge test. The improvement rate of UPDRS-III was calculated. PD patients were grouped into irresponsive group (improvement rate < 30%) and responsive group (improvement rate ≥ 30%). Tract-based spatial statistics (TBSS), deterministic tracing (DT), region of interest (ROI) analysis, and automatic fiber identification (AFQ) analyses were performed. The structural brain network was also constructed and the topological parameters were calculated. RESULTS Fifty-four PD patients were included. TBSS identified significant differences in fractional anisotropy (FA) values in the corpus callosum and other regions of the brain. DT and ROI analysis of the corpus callosum found a significant difference in FA between the two groups. Graph theory analysis showed statistical differences in global efficiency, local efficiency, and characteristic path length. CONCLUSION PD patients with poor responsiveness to levodopa had WM damage in multiple brain areas, especially the corpus callosum, which might cause disruption of information integration of the structural brain network.
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Affiliation(s)
- Juncong Du
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Xuan Zhou
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Yi Liang
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Lili Zhao
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Chengcheng Dai
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Yuke Zhong
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Hang Liu
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Guohui Liu
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Lijuan Mo
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Changhong Tan
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Xi Liu
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
| | - Lifen Chen
- Department of NeurologyThe Second Affiliated Hospital of Chongqing Medical UniversityChongqingPeople's Republic of China
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22
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Zhang P, He Z, Mao Y, Sun R, Qu Y, Chen L, Ma P, Yin S, Yin T, Zeng F. Aberrant resting-state functional connectivity and topological properties of the subcortical network in functional dyspepsia patients. Front Mol Neurosci 2022; 15:1001557. [PMCID: PMC9606653 DOI: 10.3389/fnmol.2022.1001557] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
Functional dyspepsia (FD) is a disorder of gut-brain interaction. Previous studies have demonstrated a wide range of abnormalities in functional brain activity and connectivity patterns in FD. However, the connectivity pattern of the subcortical network (SCN), which is a hub of visceral information transmission and processing, remains unclear in FD patients. The study compared the resting-state functional connectivity (rsFC) and the global and nodal topological properties of SCN between 109 FD patients and 98 healthy controls, and then explored the correlations between the connectivity metrics and clinical symptoms in FD patients. The results demonstrated that FD patients manifested the increased rsFC in seventeen edges among the SCN, decreased small-worldness and local efficiency in SCN, as well as increased nodal efficiency and nodal degree centrality in the anterior thalamus than healthy controls (p < 0.05, false discovery rate corrected). Moreover, the rsFC of the right anterior thalamus-left nucleus accumbens edge was significantly correlated with the NDSI scores (r = 0.255, p = 0.008, uncorrected) and NDLQI scores (r = −0.241, p = 0.013, uncorrected), the nodal efficiency of right anterior thalamus was significantly correlated with NDLQI scores (r = 0.204, p = 0.036, uncorrected) in FD patients. This study indicated the abnormal rsFC pattern, as well as global and nodal topological properties of the SCN, especially the bilateral anterior thalamus in FD patients, which enhanced our understanding of the central pathophysiology of FD and will lay the foundation for the objective diagnosis of FD and the development of new therapies.
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Affiliation(s)
- Pan Zhang
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Zhaoxuan He
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yangke Mao
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Ruirui Sun
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yuzhu Qu
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Li Chen
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Peihong Ma
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China
| | - Shuai Yin
- First Affiliated Hospital, Henan University of Traditional Chinese Medicine, Zhengzhou, Henan, China
| | - Tao Yin
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- *Correspondence: Tao Yin,
| | - Fang Zeng
- Acupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Fang Zeng,
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Jiang Y, Wang P, Wen J, Wang J, Li H, Biswal BB. Hippocampus-based static functional connectivity mapping within white matter in mild cognitive impairment. Brain Struct Funct 2022; 227:2285-2297. [PMID: 35864361 DOI: 10.1007/s00429-022-02521-x] [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: 11/23/2021] [Accepted: 06/04/2022] [Indexed: 11/28/2022]
Abstract
Mild cognitive impairment (MCI) is clinically characterized by memory loss and cognitive impairment closely associated with the hippocampal atrophy. Accumulating studies have confirmed the presence of neural signal changes within white matter (WM) in resting-state functional magnetic resonance imaging (fMRI). However, it remains unclear how abnormal hippocampus activity affects the WM regions in MCI. The current study employs 43 MCI, 71 very MCI (VMCI) and 87 age-, gender-, and education-matched healthy controls (HCs) from the public OASIS-3 dataset. Using the left and right hippocampus as seed points, we obtained the whole-brain functional connectivity (FC) maps for each subject. We then perform one-way ANOVA analysis to investigate the abnormal FC regions among HCs, VMCI, and MCI. We further performed probabilistic tracking to estimate whether the abnormal FC correspond to structural connectivity disruptions. Compared to HCs, MCI and VMCI groups exhibited reduced FC in the right middle temporal gyrus within gray matter, and right temporal pole, right inferior frontal gyrus within white matter. Specific dysconnectivity is shown in the cerebellum Crus II, left inferior temporal gyrus within gray matter, and right frontal gyrus within white matter. In addition, the fiber bundles connecting the left hippocampus and right temporal pole within white matter show abnormally increased mean diffusivity in MCI. The current study proposes a new functional imaging direction for exploring the mechanism of memory decline and pathophysiological mechanisms in different stages of Alzheimer's disease.
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Affiliation(s)
- Yuan Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
| | - Jiaping Wen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jianlin Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongyi Li
- The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, 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, 07102, USA.
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24
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Palmisciano P, Ferini G, Watanabe G, Ogasawara C, Lesha E, Bin-Alamer O, Umana GE, Yu K, Cohen-Gadol AA, El Ahmadieh TY, Haider AS. Gliomas Infiltrating the Corpus Callosum: A Systematic Review of the Literature. Cancers (Basel) 2022; 14:2507. [PMID: 35626112 PMCID: PMC9139932 DOI: 10.3390/cancers14102507] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/01/2022] [Accepted: 05/18/2022] [Indexed: 12/10/2022] Open
Abstract
Background: Gliomas infiltrating the corpus callosum (G-I-CC) majorly impact patient quality-of-life, but maximally safe tumor resection is challenging. We systematically reviewed the literature on G-I-CC. Methods: PubMed, EMBASE, Scopus, Web of Science, and Cochrane were searched following the PRISMA guidelines to include studies of patients with G-I-CC. Clinicopathological features, treatments, and outcomes were analyzed. Results: We included 52 studies comprising 683 patients. Most patients experienced headache (33%), cognitive decline (18.7%), and seizures (17.7%). Tumors mostly infiltrated the corpus callosum genu (44.2%) with bilateral extension (85.4%) into frontal (68.3%) or parietal (8.9%) lobes. Most G-I-CC were glioblastomas (84.5%) with IDH-wildtype (84.9%) and unmethylated MGMT promoter (53.5%). Resection (76.7%) was preferred over biopsy (23.3%), mostly gross-total (33.8%) and subtotal (32.5%). The tumor-infiltrated corpus callosum was resected in 57.8% of cases. Radiation was delivered in 65.8% of patients and temozolomide in 68.3%. Median follow-up was 12 months (range, 0.1−116). In total, 142 patients (31.8%) experienced post-surgical complications, including transient supplementary motor area syndrome (5.1%) and persistent motor deficits (4.3%) or abulia (2.5%). Post-treatment symptom improvement was reported in 42.9% of patients. No differences in rates of complications (p = 0.231) and symptom improvement (p = 0.375) were found in cases with resected versus preserved corpus callosum. Recurrences occurred in 40.9% of cases, with median progression-free survival of 9 months (0.1−72). Median overall survival was 10.7 months (range, 0.1−116), significantly longer in low-grade tumors (p = 0.013) and after resection (p < 0.001), especially gross-total (p = 0.041) in patients with high-grade tumors. Conclusions: G-I-CC show clinicopathological patterns comparable to other more frequent gliomas. Maximally safe resection significantly improves survival with low rates of persistent complications.
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Affiliation(s)
- Paolo Palmisciano
- Department of Neurosurgery, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA
| | - Gianluca Ferini
- Department of Radiation Oncology, REM Radioterapia srl, 95029 Viagrande, Italy;
| | - Gina Watanabe
- John A. Burns School of Medicine, University of Hawai’i, Honolulu, HI 96813, USA; (G.W.); (C.O.)
| | - Christian Ogasawara
- John A. Burns School of Medicine, University of Hawai’i, Honolulu, HI 96813, USA; (G.W.); (C.O.)
| | - Emal Lesha
- Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, TN 38163, USA;
| | - Othman Bin-Alamer
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA;
| | - Giuseppe E. Umana
- Department of Neurosurgery, Trauma Center, Gamma Knife Center, Cannizzaro Hospital, 95126 Catania, Italy;
| | - Kenny Yu
- Department of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (K.Y.); (T.Y.E.A.)
| | - Aaron A. Cohen-Gadol
- Department of Neurological Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
| | - Tarek Y. El Ahmadieh
- Department of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (K.Y.); (T.Y.E.A.)
| | - Ali S. Haider
- Department of Neurosurgery, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA;
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25
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Wang J, Wang P, Jiang Y, Wang Z, Zhang H, Li H, Biswal BB. Hippocampus-Based Dynamic Functional Connectivity Mapping in the Early Stages of Alzheimer's Disease. J Alzheimers Dis 2021; 85:1795-1806. [PMID: 34958033 DOI: 10.3233/jad-215239] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The hippocampus with varying degrees of atrophy was a crucial neuroimaging feature resulting in the declining memory and cognitive function in Alzheimer's disease (AD). However, the abnormal dynamic functional connectivity (DFC) in both white matter (WM) and gray matter (GM) from the left and right hippocampus remains unclear. OBJECTIVE To explore the abnormal DFC within WM and GM from the left and right hippocampus across the different stages of AD. METHODS Current study employed the OASIS-3 dataset including 43 mild cognitive impairment (MCI), 71 pre-mild cognitive impairment (pre-MCI), and matched 87 normal cognitive (NC). Adopting the FMRIB's Integrated Registration and Segmentation Tool, we obtained the left and right hippocampus mask. Based on above hippocampus mask as seed point, we calculated the DFC between left/right hippocampus and all voxel time series within whole brain. One-way ANOVA analysis was performed to estimate the abnormal DFC among MCI, pre-MCI, and NC groups. RESULTS We found that MCI and pre-MCI groups showed the common abnormalities of DFC in the Temporal_Mid_L, Cingulum_Mid_L, and Thalamus_L. Specific abnormalities were found in the Cerebelum_9_L and Precuneus of MCI group and Vermis_8 and Caudate_L of pre-MCI group. In addition, we found that DFC within WM regions also showed the common low DFC for the Cerebellum anterior lobe-WM, Corpus callosum, and Frontal lobe-WM in MCI and pre-MCI group. CONCLUSION Our findings provided a novel information for discover the pathophysiological mechanisms of AD and indicate WM lesions were also an important cause of cognitive decline in AD.
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Affiliation(s)
- Jianlin Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuan Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Zedong Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hong Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongyi Li
- The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, 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, USA
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26
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Wang P, Wang J, Michael A, Wang Z, Klugah-Brown B, Meng C, Biswal BB. White Matter Functional Connectivity in Resting-State fMRI: Robustness, Reliability, and Relationships to Gray Matter. Cereb Cortex 2021; 32:1547-1559. [PMID: 34753176 DOI: 10.1093/cercor/bhab181] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 04/05/2021] [Accepted: 04/09/2021] [Indexed: 01/21/2023] Open
Abstract
A comprehensive characterization of the spatiotemporal organization in the whole brain is critical to understand both the function and dysfunction of the human brain. Resting-state functional connectivity (FC) of gray matter (GM) has helped in uncovering the inherent baseline networks of brain. However, the white matter (WM), which composes almost half of brain, has been largely ignored in this characterization despite studies indicating that FC in WM does change during task and rest functional magnetic resonance imaging (fMRI). In this study, we identify 9 white matter functional networks (WM-FNs) and 9 gray matter functional networks (GM-FNs) of resting fMRI. Intraclass correlation coefficient (ICC) was calculated on multirun fMRI data to estimate the reliability of static functional connectivity (SFC) and dynamic functional connectivity (DFC). Associations between SFC, DFC, and their respective ICCs are estimated for GM-FNs, WM-FNs, and GM-WM-FNs. SFC of GM-FNs were stronger than that of WM-FNs, but the corresponding DFC of GM-FNs was lower, indicating that WM-FNs were more dynamic. Associations between SFC, DFC, and their ICCs were similar in both GM- and WM-FNs. These findings suggest that WM fMRI signal contains rich spatiotemporal information similar to that of GM and may hold important cues to better establish the functional organization of the whole brain.
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Affiliation(s)
- Pan Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Jianlin Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Andrew Michael
- Duke Institute for Brain Sciences, Duke University, Durham, NC 27708, USA
| | - Zedong Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Benjamin Klugah-Brown
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Chun Meng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
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Wang P, Wang Z, Wang J, Jiang Y, Zhang H, Li H, Biswal BB. Altered Homotopic Functional Connectivity Within White Matter in the Early Stages of Alzheimer's Disease. Front Neurosci 2021; 15:697493. [PMID: 34630008 PMCID: PMC8492970 DOI: 10.3389/fnins.2021.697493] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 08/13/2021] [Indexed: 11/13/2022] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder with memory loss and cognitive impairment. The white matter (WM) BOLD signal has recently been shown to provide an important role in understanding the intrinsic cerebral activity. Although the altered homotopic functional connectivity within gray matter (GM-HFC) has been examined in AD, the abnormal HFC to WM remains unknown. The present study sought to identify changes in the WM-HFC and anatomic characteristics by combining functional magnetic resonance imaging with diffusion tensor imaging (DTI). Resting-state and DTI magnetic resonance images were collected from the OASIS-3 dataset and consisted of 53 mild cognitive impairment (MCI) patients, 90 very MCI (VMCI), and 100 normal cognitive (NC) subjects. Voxel-mirrored HFC was adopted to examine whether WM-HFC was disrupted in VMCI and MCI participants. Moreover, the DTI technique was used to investigate whether specific alterations of WM-HFC were associated with anatomic characteristics. Support vector machine analyses were used to identify the MCI and VMCI participants using the abnormal WM-HFC as the features. Compared with NC, MCI, and VMCI participants showed significantly decreased GM-HFC in the middle occipital gyrus and inferior parietal gyrus and decreased WM-HFC in the bilateral middle occipital and parietal lobe-WM. In addition, specific WM-functional network alteration for the bilateral sub-lobar-WM was found in MCI subjects. MCI subjects showed abnormal anatomic characteristics for bilateral sub-lobar and parietal lobe-WM. Results of GM-HFC mainly showed common neuroimaging features for VMCI and MCI subjects, whereas analysis of WM-HFC showed specific clinical neuromarkers and effectively compensated for the lack of GM-HFC to distinguish NC, VMCI, and MCI subjects.
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Affiliation(s)
- Pan Wang
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Zedong Wang
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Jianlin Wang
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuan Jiang
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Hong Zhang
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongyi Li
- The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Bharat B Biswal
- Ministry of Education (MOE) Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Sciences and Technology, The Clinical Hospital of Chengdu Brain Science Institute, 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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