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Li K, Wang S, Luo X, Zeng Q, Liu X, Hong L, Li J, Hong H, Xu X, Zhang Y, Jiaerken Y, Zhang R, Xie L, Xu S, Zhang X, Chen Y, Liu Z, Zhang M, Huang P. Associations of Alzheimer's Disease Pathology and Small Vessel Disease With Cerebral White Matter Degeneration: A Tract-Based MR Diffusion Imaging Study. J Magn Reson Imaging 2024; 60:268-278. [PMID: 37737474 DOI: 10.1002/jmri.29022] [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: 06/04/2023] [Revised: 09/02/2023] [Accepted: 09/05/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND White matter (WM) degeneration is a key feature of Alzheimer's disease (AD). However, the underlying mechanism remains unclear. PURPOSE To investigate how amyloid-β (Aβ), tau, and small vascular disease (SVD) jointly affect WM degeneration in subjects along AD continuum. STUDY TYPE Retrospective. SUBJECTS 152 non-demented participants (age: 55.8-91.6, male/female: 66/86) from the ADNI database were included, classified into three groups using the A (Aβ)/T (tau)/N pathological scheme (Group 1: A-T-; Group 2: A+T-; Group 3: A+T+) based on positron emission tomography data. FIELD STRENGTH/SEQUENCE 3T; T1-weighted images, T2-weighted fluid-attenuated inversion recovery images, T2*-weighted images, diffusion-weighted spin-echo echo-planar imaging sequence (54 diffusion directions). ASSESSMENT Free-water diffusion model (generated parameters: free water, FW; tissue fractional anisotropy, FAt; tissue mean diffusivity, MDt); SVD total score; Neuropsychological tests. STATISTICAL TESTS Linear regression analysis was performed to investigate the independent contribution of AD (Aβ and tau) and SVD pathologies to diffusion parameters in each fiber tract, first in the entire population and then in each subgroup. We also investigated associations between diffusion parameters and cognitive functions. The level of statistical significance was set at p < 0.05 (false discovery rate corrected). RESULTS In the entire population, we found that: 1) Increased FW was significantly associated with SVD and tau, while FAt and MDt were significantly associated with Aβ and tau; 2) The spatial pattern of fiber tracts related to a certain pathological marker is consistent with the known distribution of that pathology; 3) Subgroup analysis showed that Group 2 and 3 had more alterations of FAt and MDt associated with Aβ and tau; 4) Diffusion imaging indices showed significant associations with cognitive score in all domains except memory. DATA CONCLUSION WM microstructural injury was associated with both AD and SVD pathologies, showing compartment-specific, tract-specific, and stage-specific WM patterns. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Luwei Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jixuan Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yao Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Linyun Xie
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Shan Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xinyi Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhirong Liu
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Sakaie K, Koenig K, Lerner A, Appleby B, Ogrocki P, Pillai JA, Rao S, Leverenz JB, Lowe MJ. Multi-shell diffusion MRI of the fornix as a biomarker for cognition in Alzheimer's disease. Magn Reson Imaging 2024; 109:221-226. [PMID: 38521367 DOI: 10.1016/j.mri.2024.03.030] [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: 07/25/2023] [Revised: 03/05/2024] [Accepted: 03/19/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND AND PURPOSE A substantial fraction of those who had Alzheimer's Disease (AD) pathology on autopsy did not have dementia in life. While biomarkers for AD pathology are well-developed, biomarkers specific to cognitive domains affected by early AD are lagging. Diffusion MRI (dMRI) of the fornix is a candidate biomarker for early AD-related cognitive changes but is susceptible to bias due to partial volume averaging (PVA) with cerebrospinal fluid. The purpose of this work is to leverage multi-shell dMRI to correct for PVA and to evaluate PVA-corrected dMRI measures in fornix as a biomarker for cognition in AD. METHODS Thirty-three participants in the Cleveland Alzheimer's Disease Research Center (CADRC) (19 with normal cognition (NC), 10 with mild cognitive impairment (MCI), 4 with dementia due to AD) were enrolled in this study. Multi-shell dMRI was acquired, and voxelwise fits were performed with two models: 1) diffusion tensor imaging (DTI) that was corrected for PVA and 2) neurite orientation dispersion and density imaging (NODDI). Values of tissue integrity in fornix were correlated with neuropsychological scores taken from the Uniform Data Set (UDS), including the UDS Global Composite 5 score (UDSGC5). RESULTS Statistically significant correlations were found between the UDSGC5 and PVA-corrected measure of mean diffusivity (MDc, r = -0.35, p < 0.05) from DTI and the intracelluar volume fraction (ficvf, r = 0.37, p < 0.04) from NODDI. A sensitivity analysis showed that the relationship to MDc was driven by episodic memory, which is often affected early in AD, and language. CONCLUSION This cross-sectional study suggests that multi-shell dMRI of the fornix that has been corrected for PVA is a potential biomarker for early cognitive domain changes in AD. A longitudinal study will be necessary to determine if the imaging measure can predict cognitive decline.
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Affiliation(s)
- Ken Sakaie
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA.
| | - Katherine Koenig
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
| | - Alan Lerner
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Brian Appleby
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Paula Ogrocki
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Jagan A Pillai
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - Stephen Rao
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - Mark J Lowe
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
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Kozak A, Ninghetto M, Wieteska M, Fiedorowicz M, Wełniak-Kamińska M, Kossowski B, Eysel UT, Arckens L, Burnat K. Visual training after central retinal loss limits structural white matter degradation: an MRI study. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2024; 20:13. [PMID: 38789988 PMCID: PMC11127408 DOI: 10.1186/s12993-024-00239-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 05/13/2024] [Indexed: 05/26/2024]
Abstract
BACKGROUND Macular degeneration of the eye is a common cause of blindness and affects 8% of the worldwide human population. In adult cats with bilateral lesions of the central retina, we explored the possibility that motion perception training can limit the associated degradation of the visual system. We evaluated how visual training affects behavioral performance and white matter structure. Recently, we proposed (Kozak et al. in Transl Vis Sci Technol 10:9, 2021) a new motion-acuity test for low vision patients, enabling full visual field functional assessment through simultaneous perception of shape and motion. Here, we integrated this test as the last step of a 10-week motion-perception training. RESULTS Cats were divided into three groups: retinal-lesioned only and two trained groups, retinal-lesioned trained and control trained. The behavioral data revealed that trained cats with retinal lesions were superior in motion tasks, even when the difficulty relied only on acuity. 7 T-MRI scanning was done before and after lesioning at 5 different timepoints, followed by Fixel-Based and Fractional Anisotropy Analysis. In cats with retinal lesions, training resulted in a more localized and reduced percentage decrease in Fixel-Based Analysis metrics in the dLGN, caudate nucleus and hippocampus compared to untrained cats. In motion-sensitive area V5/PMLS, the significant decreases in fiber density were equally strong in retinal-lesioned untrained and trained cats, up to 40% in both groups. The only cortical area with Fractional Anisotropy values not affected by central retinal loss was area V5/PMLS. In other visual ROIs, the Fractional Anisotropy values increased over time in the untrained retinal lesioned group, whereas they decreased in the retinal lesioned trained group and remained at a similar level as in trained controls. CONCLUSIONS Overall, our MRI results showed a stabilizing effect of motion training applied soon after central retinal loss induction on white matter structure. We propose that introducing early motion-acuity training for low vision patients, aimed at the intact and active retinal peripheries, may facilitate brain plasticity processes toward better vision.
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Affiliation(s)
- Anna Kozak
- Laboratory of Brain Imaging, Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Marco Ninghetto
- Laboratory of Brain Imaging, Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Michał Wieteska
- Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland
- Small Animal Magnetic Resonance Imaging Laboratory, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland
| | - Michał Fiedorowicz
- Small Animal Magnetic Resonance Imaging Laboratory, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland
| | - Marlena Wełniak-Kamińska
- Small Animal Magnetic Resonance Imaging Laboratory, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland
| | - Bartosz Kossowski
- Laboratory of Brain Imaging, Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Ulf T Eysel
- Department of Neurophysiology, Ruhr University, Bochum, Germany
| | - Lutgarde Arckens
- Laboratory of Neuroplasticity and Neuroproteomics, Department of Biology, KU Leuven, Louvain, Belgium
- KU Leuven Brain Institute, KU Leuven, Louvain, Belgium
| | - Kalina Burnat
- Laboratory of Brain Imaging, Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.
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Wei YC, Kung YC, Lin CP, Chen CK, Lin C, Tseng RY, Chen YL, Huang WY, Chen PY, Chong ST, Shyu YC, Chang WC, Yeh CH. White matter alterations and their associations with biomarkers and behavior in subjective cognitive decline individuals: a fixel-based analysis. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2024; 20:12. [PMID: 38778325 PMCID: PMC11110460 DOI: 10.1186/s12993-024-00238-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 05/04/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Subjective cognitive decline (SCD) is an early stage of dementia linked to Alzheimer's disease pathology. White matter changes were found in SCD using diffusion tensor imaging, but there are known limitations in voxel-wise tensor-based methods. Fixel-based analysis (FBA) can help understand changes in white matter fibers and how they relate to neurodegenerative proteins and multidomain behavior data in individuals with SCD. METHODS Healthy adults with normal cognition were recruited in the Northeastern Taiwan Community Medicine Research Cohort in 2018-2022 and divided into SCD and normal control (NC). Participants underwent evaluations to assess cognitive abilities, mental states, physical activity levels, and susceptibility to fatigue. Neurodegenerative proteins were measured using an immunomagnetic reduction technique. Multi-shell diffusion MRI data were collected and analyzed using whole-brain FBA, comparing results between groups and correlating them with multidomain assessments. RESULTS The final enrollment included 33 SCD and 46 NC participants, with no significant differences in age, sex, or education between the groups. SCD had a greater fiber-bundle cross-section than NC (pFWE < 0.05) at bilateral frontal superior longitudinal fasciculus II (SLFII). These white matter changes correlate negatively with plasma Aβ42 level (r = -0.38, p = 0.01) and positively with the AD8 score for subjective cognitive complaints (r = 0.42, p = 0.004) and the Hamilton Anxiety Rating Scale score for the degree of anxiety (Ham-A, r = 0.35, p = 0.019). The dimensional analysis of FBA metrics and blood biomarkers found positive correlations of plasma neurofilament light chain with fiber density at the splenium of corpus callosum (pFWE < 0.05) and with fiber-bundle cross-section at the right thalamus (pFWE < 0.05). Further examination of how SCD grouping interacts between the correlations of FBA metrics and multidomain assessments showed interactions between the fiber density at the corpus callosum with letter-number sequencing cognitive score (pFWE < 0.01) and with fatigue to leisure activities (pFWE < 0.05). CONCLUSION Based on FBA, our investigation suggests white matter structural alterations in SCD. The enlargement of SLFII's fiber cross-section is linked to plasma Aβ42 and neuropsychiatric symptoms, which suggests potential early axonal dystrophy associated with Alzheimer's pathology in SCD. The splenium of the corpus callosum is also a critical region of axonal degeneration and cognitive alteration for SCD.
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Affiliation(s)
- Yi-Chia Wei
- Department of Neurology, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
| | - Yi-Chia Kung
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
- Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
| | - Chih-Ken Chen
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Chemin Lin
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Rung-Yu Tseng
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 333, Taiwan
| | - Yao-Liang Chen
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 333, Taiwan
- Department of Radiology, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Wen-Yi Huang
- Department of Neurology, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
| | - Pin-Yuan Chen
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, 333, Taiwan
- Department of Neurosurgery, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
| | - Shin-Tai Chong
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, 112, Taiwan
| | - Yu-Chiau Shyu
- Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, 204, Taiwan
- Department of Nursing, Chang Gung University of Science and Technology, Taoyuan, 333, Taiwan
| | - Wei-Chou Chang
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114, Taiwan
| | - Chun-Hung Yeh
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 333, Taiwan.
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, 333, Taiwan.
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Jiang M, Zhang H, Liu Y, Song X, Song Y, Sun J, Tang Y, Zhu L, Zhou H, Li Y, Tao X. White Matter Alterations of Visual Pathway in Thyroid Eye Disease: A Fixel-Based Analysis. J Magn Reson Imaging 2024. [PMID: 38682584 DOI: 10.1002/jmri.29387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 03/28/2024] [Accepted: 03/28/2024] [Indexed: 05/01/2024] Open
Abstract
BACKGROUND Thyroid eye disease (TED), particularly its sight-threatening complication, dysthyroid optic neuropathy (DON), profoundly impacts patients' visual health. The pathological changes in the white matter (WM) fibers within the intracranial visual pathway in TED have been infrequently studied. Understanding these changes holds crucial importance for exploring the pathogenesis and prognosis of TED. PURPOSE To utilize fixel-based analysis (FBA) to clarify the type of microstructural damage occurring in the visual pathway in TED. STUDY TYPE Prospective. SUBJECTS 28 TED with DON patients (11 males and 17 females), 28 TED without DON (non-DON) patients (12 males and 16 females), and 28 healthy controls (HCs) (12 males and 16 females). FIELD STRENGTH/SEQUENCE 3 T; multishell diffusion MRI using echo planar imaging. ASSESSMENT Fiber density (FD) and fiber-bundle cross-section (FC) were calculated to characterize WM microstructural alteration in TED visual pathway. The correlations between FBA metrics and visual field index and mean deviation were examined. STATISTICAL TESTS One-way analysis of variance, Kruskal-Wallis, t-tests, Mann-Whitney U, Chi-square, and Pearson correlation, were conducted with false discovery rate and family wise error corrections. Significance was set at P < 0.05. RESULTS Both DON and non-DON groups showed significant FD loss in the right optic tract compared with HCs, with DON patients experiencing more severe FD loss. Only DON patients had FD loss in the right optic radiation (OR) compared with the non-DON patients and HCs, with no FC difference across groups. FD in DON patients' ORs significantly correlated with visual field index (r = 0.857) and mean deviation (r = 0.751). DATA CONCLUSION Both DON and non-DON affect the WM microstructure of the visual pathway to varying extents. Visual field metrics can reflect the severity of FD damage to the OR in the visual pathway of DON patients. EVIDENCE LEVEL 2. TECHNICAL EFFICACY Stage 3.
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Affiliation(s)
- Mengda Jiang
- Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Haiyang Zhang
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Yuting Liu
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Xuefei Song
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Yang Song
- Department of MR Scientific Marketing, Siemens Healthcare, Shanghai, China
| | - Jing Sun
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Yan Tang
- Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ling Zhu
- Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huifang Zhou
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Yinwei Li
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai, China
| | - Xiaofeng Tao
- Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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González Rodríguez LL, Osorio I, Cofre G. A, Hernandez Larzabal H, Román C, Poupon C, Mangin JF, Hernández C, Guevara P. Phybers: a package for brain tractography analysis. Front Neurosci 2024; 18:1333243. [PMID: 38529266 PMCID: PMC10962387 DOI: 10.3389/fnins.2024.1333243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 02/09/2024] [Indexed: 03/27/2024] Open
Abstract
We present a Python library (Phybers) for analyzing brain tractography data. Tractography datasets contain streamlines (also called fibers) composed of 3D points representing the main white matter pathways. Several algorithms have been proposed to analyze this data, including clustering, segmentation, and visualization methods. The manipulation of tractography data is not straightforward due to the geometrical complexity of the streamlines, the file format, and the size of the datasets, which may contain millions of fibers. Hence, we collected and structured state-of-the-art methods for the analysis of tractography and packed them into a Python library, to integrate and share tools for tractography analysis. Due to the high computational requirements, the most demanding modules were implemented in C/C++. Available functions include brain Bundle Segmentation (FiberSeg), Hierarchical Fiber Clustering (HClust), Fast Fiber Clustering (FFClust), normalization to a reference coordinate system, fiber sampling, calculation of intersection between sets of brain fibers, tools for cluster filtering, calculation of measures from clusters, and fiber visualization. The library tools were structured into four principal modules: Segmentation, Clustering, Utils, and Visualization (Fibervis). Phybers is freely available on a GitHub repository under the GNU public license for non-commercial use and open-source development, which provides sample data and extensive documentation. In addition, the library can be easily installed on both Windows and Ubuntu operating systems through the pip library.
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Affiliation(s)
| | - Ignacio Osorio
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
| | - Alejandro Cofre G.
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
| | - Hernan Hernandez Larzabal
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
| | - Claudio Román
- Centro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso, Chile
| | - Cyril Poupon
- CEA, CNRS, Baobab, Neurospin, Université Paris-Saclay, Gif-sur-Yvette, France
| | | | - Cecilia Hernández
- Department of Computer Science, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
- Center for Biotechnology and Bioengineering (CeBiB), Santiago, Chile
| | - Pamela Guevara
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
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Sun Z, Naismith SL, Meikle S, Calamante F. A novel method for PET connectomics guided by fibre-tracking MRI: Application to Alzheimer's disease. Hum Brain Mapp 2024; 45:e26659. [PMID: 38491564 PMCID: PMC10943179 DOI: 10.1002/hbm.26659] [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: 11/14/2023] [Revised: 02/20/2024] [Accepted: 02/29/2024] [Indexed: 03/18/2024] Open
Abstract
This study introduces a novel brain connectome matrix, track-weighted PET connectivity (twPC) matrix, which combines positron emission tomography (PET) and diffusion magnetic resonance imaging data to compute a PET-weighted connectome at the individual subject level. The new method is applied to characterise connectivity changes in the Alzheimer's disease (AD) continuum. The proposed twPC samples PET tracer uptake guided by the underlying white matter fibre-tracking streamline point-to-point connectivity calculated from diffusion MRI (dMRI). Using tau-PET, dMRI and T1-weighted MRI from the Alzheimer's Disease Neuroimaging Initiative database, structural connectivity (SC) and twPC matrices were computed and analysed using the network-based statistic (NBS) technique to examine topological alterations in early mild cognitive impairment (MCI), late MCI and AD participants. Correlation analysis was also performed to explore the coupling between SC and twPC. The NBS analysis revealed progressive topological alterations in both SC and twPC as cognitive decline progressed along the continuum. Compared to healthy controls, networks with decreased SC were identified in late MCI and AD, and networks with increased twPC were identified in early MCI, late MCI and AD. The altered network topologies were mostly different between twPC and SC, although with several common edges largely involving the bilateral hippocampus, fusiform gyrus and entorhinal cortex. Negative correlations were observed between twPC and SC across all subject groups, although displaying an overall reduction in the strength of anti-correlation with disease progression. twPC provides a new means for analysing subject-specific PET and MRI-derived information within a hybrid connectome using established network analysis methods, providing valuable insights into the relationship between structural connections and molecular distributions. PRACTITIONER POINTS: New method is proposed to compute patient-specific PET connectome guided by MRI fibre-tracking. Track-weighted PET connectivity (twPC) matrix allows to leverage PET and structural connectivity information. twPC was applied to dementia, to characterise the PET nework abnormalities in Alzheimer's disease and mild cognitive impairment.
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Affiliation(s)
- Zhuopin Sun
- School of Biomedical EngineeringThe University of SydneySydneyNew South WalesAustralia
| | - Sharon L. Naismith
- Brain and Mind CentreThe University of SydneySydneyNew South WalesAustralia
- Faculty of Science, School of PsychologyThe University of SydneySydneyNew South WalesAustralia
- Charles Perkins CenterThe University of SydneySydneyNew South WalesAustralia
| | - Steven Meikle
- Brain and Mind CentreThe University of SydneySydneyNew South WalesAustralia
- Sydney ImagingThe University of SydneySydneyNew South WalesAustralia
- School of Health SciencesThe University of SydneySydneyNew South WalesAustralia
| | - Fernando Calamante
- School of Biomedical EngineeringThe University of SydneySydneyNew South WalesAustralia
- Brain and Mind CentreThe University of SydneySydneyNew South WalesAustralia
- Sydney ImagingThe University of SydneySydneyNew South WalesAustralia
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Meneghetti N, Vannini E, Mazzoni A. Rodents' visual gamma as a biomarker of pathological neural conditions. J Physiol 2024; 602:1017-1048. [PMID: 38372352 DOI: 10.1113/jp283858] [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: 12/13/2022] [Accepted: 01/23/2024] [Indexed: 02/20/2024] Open
Abstract
Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.
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Affiliation(s)
- Nicolò Meneghetti
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Eleonora Vannini
- Neuroscience Institute, National Research Council (CNR), Pisa, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence for Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
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9
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Bonthrone AF, Green D, Morgan AT, Mankad K, Clark CA, Liégeois FJ. Attention and motor profiles in children with developmental coordination disorder: A neuropsychological and neuroimaging investigation. Dev Med Child Neurol 2024; 66:362-378. [PMID: 37667426 PMCID: PMC10952571 DOI: 10.1111/dmcn.15745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 07/28/2023] [Accepted: 08/02/2023] [Indexed: 09/06/2023]
Abstract
AIM This study aimed to (1) quantify attention and executive functioning in children with developmental coordination disorder (DCD), (2) assess whether some children with DCD are more likely to show attention difficulties, and (3) characterize brain correlates of motor and attention deficits. METHOD Fifty-three children (36 with DCD and 17 without) aged 8 to 10 years underwent T1-weighted and diffusion-weighted magnetic resonance imaging, and standardized attention and motor assessments. Parents completed questionnaires of executive functioning and symptoms of inattention and hyperactivity. We assessed regional cortical thickness and surface area, and cerebellar, callosal, and primary motor tract structure. RESULTS Analyses of covariance and one-sample t-tests identified impaired attention, non-motor processing speed, and executive functioning in children with DCD, yet partial Spearman's rank correlation coefficients revealed these were unrelated to one another or the type or severity of the motor deficit. Robust regression analyses revealed that cortical morphology in the posterior cingulate was associated with both gross motor skills and inattentive symptoms in children with DCD, while gross motor skills were also associated with left corticospinal tract (CST) morphology. INTERPRETATION Children with DCD may benefit from routine attention and hyperactivity assessments. Alterations in the posterior cingulate and CST may be linked to impaired forward modelling during movements in children with DCD. Overall, alterations in these regions may explain the high rate of non-motor impairments in children with DCD. WHAT THIS PAPER ADDS Children with developmental coordination disorder have difficulties in attention, processing speed, and executive functioning. Non-motor impairments were not interrelated or correlated with the type or severity of motor deficit. Posterior cingulate morphology was associated with gross motor skills and inattention. Gross motor skills were also associated with left corticospinal tract morphology.
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Affiliation(s)
- Alexandra F. Bonthrone
- Clinical Systems Neuroscience Section, UCL Great Ormond Street Institute of Child HealthUCL Great Ormond Street Institute of Child HealthLondonUK
| | - Dido Green
- Department of RehabilitationJönköping UniversityJönköpingSweden
- Royal Free London NHS Foundation TrustLondonUK
- Department of Health SciencesBrunel University LondonUxbridgeUK
| | - Angela T. Morgan
- Speech and Language GroupMurdoch Children's Research InstituteMelbourneParkville, VICAustralia
- Department of Audiology and Speech PathologyThe University of MelbourneMelbourneParkville, VICAustralia
| | - Kshitij Mankad
- Radiology DepartmentGreat Ormond Street Hospital for Children NHS Foundation TrustLondonUK
| | - Christopher A. Clark
- Clinical Systems Neuroscience Section, UCL Great Ormond Street Institute of Child HealthUCL Great Ormond Street Institute of Child HealthLondonUK
| | - Frédérique J. Liégeois
- Clinical Systems Neuroscience Section, UCL Great Ormond Street Institute of Child HealthUCL Great Ormond Street Institute of Child HealthLondonUK
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10
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Kumar PR, Jha RK, Katti A. Brain tissue segmentation in neurosurgery: a systematic analysis for quantitative tractography approaches. Acta Neurol Belg 2024; 124:1-15. [PMID: 36609837 DOI: 10.1007/s13760-023-02170-9] [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: 07/14/2022] [Accepted: 12/31/2022] [Indexed: 01/09/2023]
Abstract
Diffusion magnetic resonance imaging (dMRI) is a cutting-edge imaging method that provides a macro-scale in vivo map of the white matter pathways in the brain. The measurement of brain microstructure and the enhancement of tractography rely heavily on dMRI tissue segmentation. Anatomical MRI technique (e.g., T1- and T2-weighted imaging) is the most widely used method for segmentation in dMRI. In comparison to anatomical MRI, dMRI suffers from higher image distortions, lower image quality, and making inter-modality registration more difficult. The dMRI tractography study of brain connectivity has become a major part of the neuroimaging landscape in recent years. In this research, we provide a high-level overview of the methods used to segment several brain tissues types, including grey and white matter and cerebrospinal fluid, to enable quantitative studies of structural connectivity in the brain in health and illness. In the first part of our review, we discuss the three main phases in the quantitative analysis of tractography, which are correction, segmentation, and quantification. Methodological possibilities are described for each phase, along with their popularity and potential benefits and drawbacks. After that, we will look at research that used quantitative tractography approaches to examine the white and grey matter of the brain, with an emphasis on neurodevelopment, ageing, neurological illnesses, mental disorders, and neurosurgery as possible applications. Even though there have been substantial advancements in methodological technology and the spectrum of applications, there is still no consensus regarding the "optimal" approach in the quantitative analysis of tractography. As a result, researchers should tread carefully when interpreting the findings of quantitative analysis of tractography.
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Affiliation(s)
- Puranam Revanth Kumar
- Department of Electronics and Communication Engineering, IcfaiTech (Faculty of Science and Technology), IFHE University, Hyderabad, 501203, India.
| | - Rajesh Kumar Jha
- Department of Electronics and Communication Engineering, IcfaiTech (Faculty of Science and Technology), IFHE University, Hyderabad, 501203, India
| | - Amogh Katti
- Department of Computer Science and Engineering, Gitam School of Technology, GITAM University, Hyderabad, 502329, India
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Korbmacher M, van der Meer D, Beck D, de Lange AMG, Eikefjord E, Lundervold A, Andreassen OA, Westlye LT, Maximov II. Brain asymmetries from mid- to late life and hemispheric brain age. Nat Commun 2024; 15:956. [PMID: 38302499 PMCID: PMC10834516 DOI: 10.1038/s41467-024-45282-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/19/2024] [Indexed: 02/03/2024] Open
Abstract
The human brain demonstrates structural and functional asymmetries which have implications for ageing and mental and neurological disease development. We used a set of magnetic resonance imaging (MRI) metrics derived from structural and diffusion MRI data in N=48,040 UK Biobank participants to evaluate age-related differences in brain asymmetry. Most regional grey and white matter metrics presented asymmetry, which were higher later in life. Informed by these results, we conducted hemispheric brain age (HBA) predictions from left/right multimodal MRI metrics. HBA was concordant to conventional brain age predictions, using metrics from both hemispheres, but offers a supplemental general marker of brain asymmetry when setting left/right HBA into relationship with each other. In contrast to WM brain asymmetries, left/right discrepancies in HBA are lower at higher ages. Our findings outline various sex-specific differences, particularly important for brain age estimates, and the value of further investigating the role of brain asymmetries in brain ageing and disease development.
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Affiliation(s)
- Max Korbmacher
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway.
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway.
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway.
| | - Dennis van der Meer
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Dani Beck
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ann-Marie G de Lange
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Eli Eikefjord
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway
| | - Arvid Lundervold
- Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Ole A Andreassen
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ivan I Maximov
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway.
- NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway.
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12
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Yang S, Niou ZX, Enriquez A, LaMar J, Huang JY, Ling K, Jafar-Nejad P, Gilley J, Coleman MP, Tennessen JM, Rangaraju V, Lu HC. NMNAT2 supports vesicular glycolysis via NAD homeostasis to fuel fast axonal transport. Mol Neurodegener 2024; 19:13. [PMID: 38282024 PMCID: PMC10823734 DOI: 10.1186/s13024-023-00690-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 11/28/2023] [Indexed: 01/30/2024] Open
Abstract
BACKGROUND Bioenergetic maladaptations and axonopathy are often found in the early stages of neurodegeneration. Nicotinamide adenine dinucleotide (NAD), an essential cofactor for energy metabolism, is mainly synthesized by Nicotinamide mononucleotide adenylyl transferase 2 (NMNAT2) in CNS neurons. NMNAT2 mRNA levels are reduced in the brains of Alzheimer's, Parkinson's, and Huntington's disease. Here we addressed whether NMNAT2 is required for axonal health of cortical glutamatergic neurons, whose long-projecting axons are often vulnerable in neurodegenerative conditions. We also tested if NMNAT2 maintains axonal health by ensuring axonal ATP levels for axonal transport, critical for axonal function. METHODS We generated mouse and cultured neuron models to determine the impact of NMNAT2 loss from cortical glutamatergic neurons on axonal transport, energetic metabolism, and morphological integrity. In addition, we determined if exogenous NAD supplementation or inhibiting a NAD hydrolase, sterile alpha and TIR motif-containing protein 1 (SARM1), prevented axonal deficits caused by NMNAT2 loss. This study used a combination of techniques, including genetics, molecular biology, immunohistochemistry, biochemistry, fluorescent time-lapse imaging, live imaging with optical sensors, and anti-sense oligos. RESULTS We provide in vivo evidence that NMNAT2 in glutamatergic neurons is required for axonal survival. Using in vivo and in vitro studies, we demonstrate that NMNAT2 maintains the NAD-redox potential to provide "on-board" ATP via glycolysis to vesicular cargos in distal axons. Exogenous NAD+ supplementation to NMNAT2 KO neurons restores glycolysis and resumes fast axonal transport. Finally, we demonstrate both in vitro and in vivo that reducing the activity of SARM1, an NAD degradation enzyme, can reduce axonal transport deficits and suppress axon degeneration in NMNAT2 KO neurons. CONCLUSION NMNAT2 ensures axonal health by maintaining NAD redox potential in distal axons to ensure efficient vesicular glycolysis required for fast axonal transport.
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Affiliation(s)
- Sen Yang
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
- Max Planck Florida Institute for Neuroscience, Jupiter, FL, 33458, USA
| | - Zhen-Xian Niou
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Andrea Enriquez
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA
| | - Jacob LaMar
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
- Max Planck Florida Institute for Neuroscience, Jupiter, FL, 33458, USA
- Present address: Department of Biomedical Science, Florida Atlantic University, Jupiter, FL, 33458, USA
| | - Jui-Yen Huang
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
| | - Karen Ling
- Neuroscience Drug Discovery, Ionis Pharmaceuticals, Inc., 2855, Gazelle Court, Carlsbad, CA, 92010, USA
| | - Paymaan Jafar-Nejad
- Neuroscience Drug Discovery, Ionis Pharmaceuticals, Inc., 2855, Gazelle Court, Carlsbad, CA, 92010, USA
| | - Jonathan Gilley
- Department of Clinical Neuroscience, Cambridge University, Cambridge, UK
| | - Michael P Coleman
- Department of Clinical Neuroscience, Cambridge University, Cambridge, UK
| | - Jason M Tennessen
- Department of Biology, Indiana University, Bloomington, IN, 47405, USA
| | - Vidhya Rangaraju
- Max Planck Florida Institute for Neuroscience, Jupiter, FL, 33458, USA
| | - Hui-Chen Lu
- The Linda and Jack Gill Center for Biomolecular Sciences, Indiana University, Bloomington, IN, 47405, USA.
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA.
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405, USA.
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13
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Liu SW, Ma XT, Yu S, Weng XF, Li M, Zhu J, Liu CF, Hu H. Bridging Reduced Grip Strength and Altered Executive Function: Specific Brain White Matter Structural Changes in Patients with Alzheimer's Disease. Clin Interv Aging 2024; 19:93-107. [PMID: 38250174 PMCID: PMC10799618 DOI: 10.2147/cia.s438782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 01/09/2024] [Indexed: 01/23/2024] Open
Abstract
Objective To investigate the correlation between specific fiber tracts and grip strength and cognitive function in patients with Alzheimer's disease (AD) by fixel-based analysis (FBA). Methods AD patients were divided into AD with low grip strength (AD-LGS, n=29) and AD without low grip strength (AD-nLGS, n=25), along with 31 normal controls (NC). General data, neuropsychological tests, grip strength and cranial magnetic resonance imaging (MRI) scans were collected. FBA evaluated white matter (WM) fiber metrics, including fiber density (FD), fiber cross-sectional (FC), and fiber density and cross-sectional area (FDC). The mean fiber indicators of the fiber tracts of interest (TOI) were extracted in cerebral region of significant statistical differences in FBA to further compare the differences between groups and analyze the correlation between fiber properties and neuropsychological test scores. Results Compared to AD-nLGS group, AD-LGS group showed significant reductions in FDC in several cerebral regions. In AD patients, FDC values of bilateral uncinate fasciculus and left superior longitudinal fasciculus were positively correlated with Clock Drawing Test scores, while FDC of splenium of corpus callosum, bilateral anterior cingulate tracts, forceps major, and bilateral inferior longitudinal fasciculus were positively correlated with the Executive Factor Score of Memory and Executive Screening scale scores. Conclusion Reduced grip strength in AD patients is associated with extensive impairment of WM structural integrity. Changes in FDC of specific WM fiber tracts related to executive function play a significant mediating role in the reduction of grip strength in AD patients.
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Affiliation(s)
- Shan-Wen Liu
- Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Xiao-Ting Ma
- Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Shuai Yu
- Department of Neurology, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, 215000, People’s Republic of China
| | - Xiao-Fen Weng
- Department of Geriatric Medicine, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, 215000, People’s Republic of China
| | - Meng Li
- Department of Imaging, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Jiangtao Zhu
- Department of Imaging, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Chun-Feng Liu
- Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
| | - Hua Hu
- Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
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Jung Y, Damoiseaux JS. The potential of blood neurofilament light as a marker of neurodegeneration for Alzheimer's disease. Brain 2024; 147:12-25. [PMID: 37540027 DOI: 10.1093/brain/awad267] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 07/22/2023] [Accepted: 07/28/2023] [Indexed: 08/05/2023] Open
Abstract
Over the past several years, there has been a surge in blood biomarker studies examining the value of plasma or serum neurofilament light (NfL) as a biomarker of neurodegeneration for Alzheimer's disease. However, there have been limited efforts to combine existing findings to assess the utility of blood NfL as a biomarker of neurodegeneration for Alzheimer's disease. In addition, we still need better insight into the specific aspects of neurodegeneration that are reflected by the elevated plasma or serum concentration of NfL. In this review, we survey the literature on the cross-sectional and longitudinal relationships between blood-based NfL levels and other, neuroimaging-based, indices of neurodegeneration in individuals on the Alzheimer's continuum. Then, based on the biomarker classification established by the FDA-NIH Biomarker Working group, we determine the utility of blood-based NfL as a marker for monitoring the disease status (i.e. monitoring biomarker) and predicting the severity of neurodegeneration in older adults with and without cognitive decline (i.e. a prognostic or a risk/susceptibility biomarker). The current findings suggest that blood NfL exhibits great promise as a monitoring biomarker because an increased NfL level in plasma or serum appears to reflect the current severity of atrophy, hypometabolism and the decline of white matter integrity, particularly in the brain regions typically affected by Alzheimer's disease. Longitudinal evidence indicates that blood NfL can be useful not only as a prognostic biomarker for predicting the progression of neurodegeneration in patients with Alzheimer's disease but also as a susceptibility/risk biomarker predicting the likelihood of abnormal alterations in brain structure and function in cognitively unimpaired individuals with a higher risk of developing Alzheimer's disease (e.g. those with a higher amyloid-β). There are still limitations to current research, as discussed in this review. Nevertheless, the extant literature strongly suggests that blood NfL can serve as a valuable prognostic and susceptibility biomarker for Alzheimer's disease-related neurodegeneration in clinical settings, as well as in research settings.
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Affiliation(s)
- Youjin Jung
- Department of Psychology, Wayne State University, Detroit, MI 48202, USA
- Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
| | - Jessica S Damoiseaux
- Department of Psychology, Wayne State University, Detroit, MI 48202, USA
- Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
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15
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Tu Y, Li Z, Xiong F, Gao F. Progressive white matter degeneration in patients with spinocerebellar ataxia type 2. Neuroradiology 2024; 66:101-108. [PMID: 38040824 DOI: 10.1007/s00234-023-03260-4] [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: 08/07/2023] [Accepted: 11/23/2023] [Indexed: 12/03/2023]
Abstract
PURPOSE Spinocerebellar ataxia type 2 (SCA2) is a progressive neurodegenerative disorder characterized by cerebellar atrophy. However, studies to elucidate the longitudinal progression of the neuropathology are limited. We sought to identify brain macrostructural and microstructural alterations in patients with SCA2 using fixel-based analysis (FBA) to better understand its distribution patterns and progression. METHODS We enrolled 9 patients with SCA2 and 16 age- and gender-matched controls. Longitudinal clinical and imaging data were collected at baseline, and 3.5 years later. Fiber density (FD), fiber-bundle cross-section (FC), and a combination of FD and FC (FDC) were calculated. The paired t-test was used to examine longitudinal differences. The associations between fixel-based metrics and clinical variables were explored in SCA2 patients. RESULTS At baseline, patients with SCA2 displayed multiple white matter tracts with significantly decreased FD, FC, and FDC in the corticospinal tract, cerebellar peduncles, brainstem, corpus callosum, thalamus, striatum, and prefrontal cortex, compared to controls. Over time, many of these macrostructural and microstructural alterations progressed, manifesting lower FD, FC, and FDC in corticospinal tract, middle cerebellar peduncle, brainstem, striatum, fornix, and cingulum. No significant brain white matter alterations were found in the healthy controls over time. There was no association between the FBA-derived metrics and clinical variables in SCA2. CONCLUSION This study provides evidence of brain macrostructural and microstructural alterations and of progression over time in SCA2. The FBA-derived metrics may serve as potential biomarkers of SCA2 progression.
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Affiliation(s)
- Ye Tu
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Clinical Research Center for Geriatric Anesthesia, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zheng Li
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Clinical Research Center for Geriatric Anesthesia, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fei Xiong
- Department of Radiology, General Hospital of Central Theater Command, Wuhan, China.
| | - Feng Gao
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Hubei Key Laboratory of Geriatric Anesthesia and Perioperative Brain Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Wuhan Clinical Research Center for Geriatric Anesthesia, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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16
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Mito R, Pedersen M, Pardoe H, Parker D, Smith RE, Cameron J, Scheffer IE, Berkovic SF, Vaughan DN, Jackson GD. Exploring individual fixel-based white matter abnormalities in epilepsy. Brain Commun 2023; 6:fcad352. [PMID: 38187877 PMCID: PMC10768884 DOI: 10.1093/braincomms/fcad352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 11/02/2023] [Accepted: 12/21/2023] [Indexed: 01/09/2024] Open
Abstract
Diffusion MRI has provided insight into the widespread structural connectivity changes that characterize epilepsies. Although syndrome-specific white matter abnormalities have been demonstrated, studies to date have predominantly relied on statistical comparisons between patient and control groups. For diffusion MRI techniques to be of clinical value, they should be able to detect white matter microstructural changes in individual patients. In this study, we apply an individualized approach to a technique known as fixel-based analysis, to examine fibre-tract-specific abnormalities in individuals with epilepsy. We explore the potential clinical value of this individualized fixel-based approach in epilepsy patients with differing syndromic diagnoses. Diffusion MRI data from 90 neurologically healthy control participants and 10 patients with epilepsy (temporal lobe epilepsy, progressive myoclonus epilepsy, and Dravet Syndrome, malformations of cortical development) were included in this study. Measures of fibre density and cross-section were extracted for all participants across brain white matter fixels, and mean values were computed within select tracts-of-interest. Scanner harmonized and normalized data were then used to compute Z-scores for individual patients with epilepsy. White matter abnormalities were observed in distinct patterns in individual patients with epilepsy, both at the tract and fixel level. For patients with specific epilepsy syndromes, the detected white matter abnormalities were in line with expected syndrome-specific clinical phenotypes. In patients with lesional epilepsies (e.g. hippocampal sclerosis, periventricular nodular heterotopia, and bottom-of-sulcus dysplasia), white matter abnormalities were spatially concordant with lesion location. This proof-of-principle study demonstrates the clinical potential of translating advanced diffusion MRI methodology to individual-patient-level use in epilepsy. This technique could be useful both in aiding diagnosis of specific epilepsy syndromes, and in localizing structural abnormalities, and is readily amenable to other neurological disorders. We have included code and data for this study so that individualized white matter changes can be explored robustly in larger cohorts in future work.
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Affiliation(s)
- Remika Mito
- Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria 3084, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Mangor Pedersen
- Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria 3084, Australia
- Department of Psychology and Neuroscience, Auckland University of Technology (AUT), Auckland 1142, New Zealand
| | - Heath Pardoe
- Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria 3084, Australia
| | - Donna Parker
- Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria 3084, Australia
| | - Robert E Smith
- Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria 3084, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Jillian Cameron
- Epilepsy Research Centre, Department of Medicine, University of Melbourne, Austin Health, Heidelberg, Victoria 3084, Australia
| | - Ingrid E Scheffer
- Epilepsy Research Centre, Department of Medicine, University of Melbourne, Austin Health, Heidelberg, Victoria 3084, Australia
| | - Samuel F Berkovic
- Epilepsy Research Centre, Department of Medicine, University of Melbourne, Austin Health, Heidelberg, Victoria 3084, Australia
| | - David N Vaughan
- Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria 3084, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria 3010, Australia
- Department of Neurology, Austin Health, Heidelberg, Victoria 3084, Australia
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria 3084, Australia
- Florey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria 3010, Australia
- Department of Neurology, Austin Health, Heidelberg, Victoria 3084, Australia
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Ramanan S, Halai AD, Garcia-Penton L, Perry AG, Patel N, Peterson KA, Ingram RU, Storey I, Cappa SF, Catricala E, Patterson K, Rowe JB, Garrard P, Ralph MAL. The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia. Alzheimers Res Ther 2023; 15:219. [PMID: 38102724 PMCID: PMC10724982 DOI: 10.1186/s13195-023-01350-2] [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: 07/18/2023] [Accepted: 11/08/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND Clinical variants of primary progressive aphasia (PPA) are diagnosed based on characteristic patterns of language deficits, supported by corresponding neural changes on brain imaging. However, there is (i) considerable phenotypic variability within and between each diagnostic category with partially overlapping profiles of language performance between variants and (ii) accompanying non-linguistic cognitive impairments that may be independent of aphasia magnitude and disease severity. The neurobiological basis of this cognitive-linguistic heterogeneity remains unclear. Understanding the relationship between these variables would improve PPA clinical/research characterisation and strengthen clinical trial and symptomatic treatment design. We address these knowledge gaps using a data-driven transdiagnostic approach to chart cognitive-linguistic differences and their associations with grey/white matter degeneration across multiple PPA variants. METHODS Forty-seven patients (13 semantic, 15 non-fluent, and 19 logopenic variant PPA) underwent assessment of general cognition, errors on language performance, and structural and diffusion magnetic resonance imaging to index whole-brain grey and white matter changes. Behavioural data were entered into varimax-rotated principal component analyses to derive orthogonal dimensions explaining the majority of cognitive variance. To uncover neural correlates of cognitive heterogeneity, derived components were used as covariates in neuroimaging analyses of grey matter (voxel-based morphometry) and white matter (network-based statistics of structural connectomes). RESULTS Four behavioural components emerged: general cognition, semantic memory, working memory, and motor speech/phonology. Performance patterns on the latter three principal components were in keeping with each variant's characteristic profile, but with a spectrum rather than categorical distribution across the cohort. General cognitive changes were most marked in logopenic variant PPA. Regardless of clinical diagnosis, general cognitive impairment was associated with inferior/posterior parietal grey/white matter involvement, semantic memory deficits with bilateral anterior temporal grey/white matter changes, working memory impairment with temporoparietal and frontostriatal grey/white matter involvement, and motor speech/phonology deficits with inferior/middle frontal grey matter alterations. CONCLUSIONS Cognitive-linguistic heterogeneity in PPA closely relates to individual-level variations on multiple behavioural dimensions and grey/white matter degeneration of regions within and beyond the language network. We further show that employment of transdiagnostic approaches may help to understand clinical symptom boundaries and reveal clinical and neural profiles that are shared across categorically defined variants of PPA.
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Affiliation(s)
- Siddharth Ramanan
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, UK.
| | - Ajay D Halai
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, UK
| | - Lorna Garcia-Penton
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, UK
| | - Alistair G Perry
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Nikil Patel
- Molecular and Clinical Sciences Research Institute, St. George's, University of London, London, UK
| | - Katie A Peterson
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Ruth U Ingram
- Division of Psychology and Mental Health, University of Manchester, Manchester, UK
| | - Ian Storey
- Molecular and Clinical Sciences Research Institute, St. George's, University of London, London, UK
| | - Stefano F Cappa
- IUSS Cognitive Neuroscience Center (ICoN), University Institute of Advanced Studies IUSS, Pavia, Italy
- Dementia Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Eleonora Catricala
- IUSS Cognitive Neuroscience Center (ICoN), University Institute of Advanced Studies IUSS, Pavia, Italy
- Dementia Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Karalyn Patterson
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, UK
| | - James B Rowe
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Peter Garrard
- Molecular and Clinical Sciences Research Institute, St. George's, University of London, London, UK
| | - Matthew A Lambon Ralph
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge, CB2 7EF, UK
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Groechel RC, Alosco ML, Dixon D, Tripodis Y, Mez J, Goldstein L, Budson AE, Qiu WQ, Killiany RJ. Associations between white matter integrity of the cingulum bundle, surrounding gray matter regions, and cognition across the dementia continuum. J Comp Neurol 2023; 531:2162-2171. [PMID: 38010204 PMCID: PMC10841586 DOI: 10.1002/cne.25564] [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: 10/26/2022] [Revised: 10/19/2023] [Accepted: 10/21/2023] [Indexed: 11/29/2023]
Abstract
INTRODUCTION Previous Alzheimer's disease and related dementias (AD/ADRD) research studies have illustrated the significance of studying alterations in white matter (WM). Fewer studies have examined how WM integrity, measured with diffusion tensor imaging (DTI), is associated with volume of gray matter (GM) regions and measures of cognitive function in aged participants spanning the dementia continuum. METHODS Magnetic resonance imaging and cognitive data were collected from 241 Boston University Alzheimer's Disease Research Center participants who spanned from cognitively normal controls to amnestic mild cognitive impairment to having dementia. Primary DTI tracts of interest were the cingulum ventral (CV) and cingulum dorsal (CD) pathways. GM regions of interest (ROIs) were in the medial temporal lobe (MTL), prefrontal cortex, and retrosplenial cortex. Analyses of covariance models were used to assess differences in WM integrity across groups (control, amnestic mild cognitive impairment, and dementia). Multiple linear regression models were used to assess associations between WM integrity and GM volume, and with measures of memory and executive function. RESULTS Differences in WM integrity were shown in both cingulum pathways in participants across the dementia continuum. Associations between WM integrity of both cingulum pathways and volume of selected GM ROIs were widespread. Functionally significant associations were found between WM of the CV pathway and memory, independent of MTL GM volume. DISCUSSION Differences in WM integrity of the cingulum bundle and surrounding GM ROI are likely related to the progression of AD/ADRD. Such differences should continue to be studied, particularly in association with memory performance.
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Affiliation(s)
- Renée C. Groechel
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine
- National Institute of Neurological Disorders & Stroke Intramural Research Program
| | - Michael L. Alosco
- Boston University Alzheimer’s Disease Research Center
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine
- Boston University Chronic Traumatic Encephalopathy Center
| | - Diane Dixon
- Boston University Alzheimer’s Disease Research Center
- Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health
| | - Yorghos Tripodis
- Boston University Alzheimer’s Disease Research Center
- Department of Biostatistics, Boston University School of Public Health
| | - Jesse Mez
- Boston University Alzheimer’s Disease Research Center
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine
- Boston University Chronic Traumatic Encephalopathy Center
| | - Lee Goldstein
- Boston University Alzheimer’s Disease Research Center
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine
| | - Andrew E. Budson
- Boston University Alzheimer’s Disease Research Center
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine
- Neurology Service, VA Boston Healthcare System
| | - Wei Qiao Qiu
- Boston University Alzheimer’s Disease Research Center
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine
| | - Ronald J. Killiany
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine
- Boston University Alzheimer’s Disease Research Center
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine
- Department of Radiology, Boston University Chobanian & Avedisian School of Medicine
- Department of Environmental Health, Boston University School of Public Health
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Khan T, Waseem R, Shahid M, Ansari J, Ahanger IA, Hassan I, Islam A. Recent advancement in therapeutic strategies for Alzheimer's disease: Insights from clinical trials. Ageing Res Rev 2023; 92:102113. [PMID: 37918760 DOI: 10.1016/j.arr.2023.102113] [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: 09/11/2023] [Revised: 10/16/2023] [Accepted: 10/27/2023] [Indexed: 11/04/2023]
Abstract
Alzheimer's disease (AD) is the most prevalent form of dementia, characterized by the presence of plaques of amyloid beta and Tau proteins. There is currently no permanent cure for AD; the only medications approved by the FDA for mild to moderate AD are cholinesterase inhibitors, NMDA receptor antagonists, and immunotherapies against core pathophysiology, that provide temporary relief only. Researchers worldwide have made significant attempts to find new targets and develop innovative therapeutic molecules to treat AD. The FDA-approved drugs are palliative and couldn't restore the damaged neuron cells of AD. Stem cells have self-differentiation properties, making them prospective therapeutics to treat AD. The promising results in pre-clinical studies of stem cell therapy for AD seek attention worldwide. Various stem cells, mainly mesenchymal stem cells, are currently in different phases of clinical trials and need more advancements to take this therapy to the translational level. Here, we review research from the past decade that has identified several hypotheses related to AD pathology. Moreover, this article also focuses on the recent advancement in therapeutic strategies for AD treatment including immunotherapy and stem cell therapy detailing the clinical trials that are currently undergoing development.
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Affiliation(s)
- Tanzeel Khan
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Rashid Waseem
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Mohammad Shahid
- Department of Basic Medical Sciences, College of Medicine, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia
| | - Jaoud Ansari
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Ishfaq Ahmad Ahanger
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India; Department of Clinical Biochemistry, University of Kashmir,190006, India
| | - Imtaiyaz Hassan
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India
| | - Asimul Islam
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, Jamia Nagar, New Delhi 110025, India.
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20
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Shao Y, Li L, Peng W, Lu W, Wang Y. Age-related changes in the healthy adult visual pathway: evidence from diffusion tensor imaging with fixel-based analysis. RADIOLOGIE (HEIDELBERG, GERMANY) 2023; 63:73-81. [PMID: 37603069 DOI: 10.1007/s00117-023-01192-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 06/06/2023] [Indexed: 08/22/2023]
Abstract
BACKGROUND AND PURPOSE Fixel-based analysis (FBA) is a new method that overcomes the technical limitations of diffusion tensor imaging (DTI) by enabling the characterization of multiple fiber populations within a voxel, and provides biologically meaningful indicators. This study aimed to explore age-related changes in the visual pathway in healthy adults and to observe differences in imaging quality between data collected using different b‑values. METHODS In this prospective cross-sectional study, brain DTI scans which were collected with more than six uniformly distributed gradient directions and higher b‑values (up to 2000 s/mm2) than traditional DTI were performed in 72 healthy adults across the adult lifespan (20-79 years). After image preprocessing, FBA was used to process the dataset. At the same time, conventional DTI metrics were also calculated. RESULTS Pearson's correlation analysis showed that DTI parameters of white matter (optic nerve, optic chiasma, optic tract, and optic radiation) in the optic pathway were correlated with age. FA values were negatively correlated with age, while MD/AD/RD showed a positive correlation (P < 0.05). FBA showed that the index including FD/FC/FDC tended to decline with age (P < 0.05). Linear regression analysis showed a linear relationship between DTI metrics of the dataset collected by b‑values of 1000 and 2000 s/mm2 (P < 0.05). CONCLUSION FBA provides a useful method to assess age-related changes in the visual pathway, which is sensitive to diffusion. In addition, the b‑value influences DTI parameters and signal-to-noise ratio of the image.
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Affiliation(s)
- Yan Shao
- The Second Affiliated Hospital of Shandong First Medical University, 271000, Taian, Shandong, China
| | - Li Li
- The Second Affiliated Hospital of Shandong First Medical University, 271000, Taian, Shandong, China
| | - Wei Peng
- Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430000, Wuhan, Hubei, China
| | - Weizhao Lu
- The Second Affiliated Hospital of Shandong First Medical University, 271000, Taian, Shandong, China
| | - Yi Wang
- Department of Ophthalmology, The Second Affiliated Hospital of Shandong First Medical University & Shandong Academy of Medical Sciences, 271000, Taian, Shandong, China.
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21
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Dan L, Zhang Z. Alzheimer's disease: an axonal injury disease? Front Aging Neurosci 2023; 15:1264448. [PMID: 37927337 PMCID: PMC10620718 DOI: 10.3389/fnagi.2023.1264448] [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: 07/20/2023] [Accepted: 09/14/2023] [Indexed: 11/07/2023] Open
Abstract
Alzheimer's disease (AD) is the primary cause of dementia and is anticipated to impose a substantial economic burden in the future. Over a significant period, the widely accepted amyloid cascade hypothesis has guided research efforts, and the recent FDA approval of an anti- amyloid-beta (Aβ) protofibrils antibody, believed to decelerate AD progression, has further solidified its significance. However, the excessive emphasis placed on the amyloid cascade hypothesis has overshadowed the physiological nature of Aβ and tau proteins within axons. Axons, specialized neuronal structures, sustain damage during the early stages of AD, exerting a pivotal influence on disease progression. In this review, we present a comprehensive summary of the relationship between axonal damage and AD pathology, amalgamating the physiological roles of Aβ and tau proteins, along with the impact of AD risk genes such as APOE and TREM2. Furthermore, we underscore the exceptional significance of axonal damage in the context of AD.
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Affiliation(s)
| | - Zhaohui Zhang
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
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22
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Gallagher RL, Koscik RL, Moody JF, Vogt NM, Adluru N, Kecskemeti SR, Van Hulle CA, Chin NA, Asthana S, Kollmorgen G, Suridjan I, Carlsson CM, Johnson SC, Dean DC, Zetterberg H, Blennow K, Alexander AL, Bendlin BB. Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status. Alzheimers Res Ther 2023; 15:180. [PMID: 37848950 PMCID: PMC10583332 DOI: 10.1186/s13195-023-01281-y] [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: 12/03/2021] [Accepted: 07/27/2023] [Indexed: 10/19/2023]
Abstract
BACKGROUND Alzheimer's disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical. METHODS Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination). RESULTS Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone. CONCLUSION Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged.
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Affiliation(s)
- Rigina L Gallagher
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Rebecca Langhough Koscik
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Jason F Moody
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Nicholas M Vogt
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Medical Scientist Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Nagesh Adluru
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | | | - Carol A Van Hulle
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Nathaniel A Chin
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
| | - Sanjay Asthana
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | | | | | - Cynthia M Carlsson
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | - Sterling C Johnson
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Wisconsin Alzheimer's Institute, Madison, WI, USA
- Veterans Administration, Madison, WI, USA
| | - Douglas C Dean
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | - Henrik Zetterberg
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Andrew L Alexander
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Waisman Research Center, Madison, WI, USA
| | - Barbara B Bendlin
- School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
- Wisconsin Alzheimer's Disease Research Center, Madison, WI, USA.
- Wisconsin Alzheimer's Institute, Madison, WI, USA.
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Matorina N, Tseng J, Ladyka-Wojcik N, Olsen R, Mabbott DJ, Barense MD. Sleep Differentially and Profoundly Impairs Recall Memory in a Patient with Fornix Damage. J Cogn Neurosci 2023; 35:1635-1655. [PMID: 37584584 DOI: 10.1162/jocn_a_02038] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
In March 2020, C.T., a kind, bright, and friendly young woman underwent surgery for a midline tumor involving her septum pellucidum and extending down into her fornices bilaterally. Following tumor diagnosis and surgery, C.T. experienced significant memory deficits: C.T.'s family reported that she could remember things throughout the day, but when she woke up in the morning or following a nap, she would expect to be in the hospital, forgetting all the information that she had learned before sleep. The current study aimed to empirically validate C.T.'s pattern of memory loss and explore its neurological underpinnings. On two successive days, C.T. and age-matched controls watched an episode of a TV show and took a nap or stayed awake before completing a memory test. Although C.T. performed numerically worse than controls in both conditions, sleep profoundly exacerbated her memory impairment, such that she could not recall any details following a nap. This effect was replicated in a second testing session. High-resolution MRI scans showed evidence of the trans-callosal surgical approach's impact on the mid-anterior corpus callosum, indicated that C.T. had perturbed white matter particularly in the right fornix column, and demonstrated that C.T.'s hippocampal volumes did not differ from controls. These findings suggest that the fornix is important for processing episodic memories during sleep. As a key output pathway of the hippocampus, the fornix may ensure that specific memories are replayed during sleep, maintain the balance of sleep stages, or allow for the retrieval of memories following sleep.
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Affiliation(s)
| | - Julie Tseng
- Neurosciences and Mental Health Program, Hospital for Sick Children, Toronto, Ontario, Canada
| | | | | | - Donald J Mabbott
- University of Toronto, Ontario, Canada
- Neurosciences and Mental Health Program, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Morgan D Barense
- University of Toronto, Ontario, Canada
- Rotman Research Institute, Toronto, Ontario, Canada
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Han A, Dhollander T, Sun YL, Chad JA, Chen JJ. Fiber-specific age-related differences in the white matter of healthy adults uncovered by fixel-based analysis. Neurobiol Aging 2023; 130:22-29. [PMID: 37423114 DOI: 10.1016/j.neurobiolaging.2023.06.007] [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: 11/28/2022] [Revised: 05/31/2023] [Accepted: 06/08/2023] [Indexed: 07/11/2023]
Abstract
Diffusion magnetic resonance imaging studies often investigate white matter (WM) microstructural degeneration in aging by probing WM regions that exhibit negative age associations of fractional anisotropy (FA). However, WM regions in which FA is unassociated with age are not necessarily "spared" in aging. Besides the confound of inter-participant heterogeneity, FA conflates all intravoxel fiber populations and does not allow the detection of individual fiber-specific age associations. In this study of 541 healthy adults aged 36-100 years, we use fixel-based analysis to investigate age associations among each "fixel" within a voxel, representing individual fiber populations. We find age associations of fixel-based measures that indicate age-related differences in individual fiber populations amid complex fiber architectures. Different crossing fiber populations exhibit different slopes of age associations. Our findings may provide evidence of selective degeneration of intravoxel WM fibers in aging, which does not necessarily manifest as a change in FA and therefore escapes notice if conventional voxel-based analyses are relied upon alone.
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Affiliation(s)
- Ana Han
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Yutong L Sun
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Department of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
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25
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Ali DG, Bahrani AA, El Khouli RH, Gold BT, Jiang Y, Zachariou V, Wilcock DM, Jicha GA. White matter hyperintensities influence distal cortical β-amyloid accumulation in default mode network pathways. Brain Behav 2023; 13:e3209. [PMID: 37534614 PMCID: PMC10570488 DOI: 10.1002/brb3.3209] [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: 02/16/2023] [Revised: 07/19/2023] [Accepted: 07/22/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND AND PURPOSE Cerebral small vessel disease (SVD) has been suggested to contribute to the pathogenesis of Alzheimer's disease (AD). Yet, the role of SVD in potentially contributing to AD pathology is unclear. The main objective of this study was to test the hypothesis that WMHs influence amyloid β (Aβ) levels within connected default mode network (DMN) tracts and cortical regions in cognitively unimpaired older adults. METHODS Regional standard uptake value ratios (SUVr) from Aβ-PET and white matter hyperintensity (WMH) volumes from three-dimensional magnetic resonance imaging FLAIR images were analyzed across a sample of 72 clinically unimpaired (mini-mental state examination ≥26), older adults (mean age 74.96 and standard deviation 8.13) from the Alzheimer's Disease Neuroimaging Initiative (ADNI3). The association of WMH volumes in major fiber tracts projecting from cortical DMN regions and Aβ-PET SUVr in the connected cortical DMN regions was analyzed using linear regression models adjusted for age, sex, ApoE, and total brain volumes. RESULTS The regression analyses demonstrate that increased WMH volumes in the superior longitudinal fasciculus were associated with increased regional SUVr in the inferior parietal lobule (p = .011). CONCLUSION The findings suggest that the relation between Aβ in parietal cortex is associated with SVD in downstream white matter (WM) pathways in preclinical AD. The biological relationships and interplay between Aβ and WM microstructure alterations that precede overt WMH development across the continuum of AD progression warrant further study.
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Affiliation(s)
- Doaa G. Ali
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Ahmed A. Bahrani
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Riham H. El Khouli
- Department of Radiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Brian T. Gold
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Yang Jiang
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Valentinos Zachariou
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Donna M. Wilcock
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Physiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Gregory A. Jicha
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
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Qu Y, Wang P, Yao H, Wang D, Song C, Yang H, Zhang Z, Chen P, Kang X, Du K, Fan L, Zhou B, Han T, Yu C, Zhang X, Zuo N, Jiang T, Zhou Y, Liu B, Han Y, Lu J, Liu Y. Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer's Disease. Neurosci Bull 2023; 39:1533-1543. [PMID: 37014553 PMCID: PMC10533766 DOI: 10.1007/s12264-023-01041-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 11/29/2022] [Indexed: 04/05/2023] Open
Abstract
Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.
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Affiliation(s)
- Yida Qu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Hongxiang Yao
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Dawei Wang
- Department of Radiology, Department of Epidemiology and Health Statistics, School of Public Health, Qilu Hospital of Shandong University, Ji'nan, 250063, China
| | - Chengyuan Song
- Department of Neurology, Qilu Hospital of Shandong University, Ji'nan, 250063, China
| | - Hongwei Yang
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Zengqiang Zhang
- Branch of Chinese, PLA General Hospital, Sanya, 572022, China
| | - Pindong Chen
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiaopeng Kang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kai Du
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Bo Zhou
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100089, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, 300222, China
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xi Zhang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100089, China
| | - Nianming Zuo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yuying Zhou
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, 300222, China
| | - Bing Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Lab of Cognition Neuroscience & Learning, Beijing Normal University, Beijing, 100091, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
- Beijing Institute of Geriatrics, Beijing, 100053, China
- National Clinical Research Center for Geriatric Disorders, Beijing, 100053, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China.
| | - Yong Liu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
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Badji A, Youwakim J, Cooper A, Westman E, Marseglia A. Vascular cognitive impairment - Past, present, and future challenges. Ageing Res Rev 2023; 90:102042. [PMID: 37634888 DOI: 10.1016/j.arr.2023.102042] [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: 01/26/2023] [Revised: 08/22/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
Vascular cognitive impairment (VCI) is a lifelong process encompassing a broad spectrum of cognitive disorders, ranging from subtle or mild deficits to prodromal and fully developed dementia, originating from cerebrovascular lesions such as large and small vessel disease. Genetic predisposition and environmental exposure to risk factors such as unhealthy lifestyles, hypertension, cardiovascular disease, and metabolic disorders will synergistically interact, yielding biochemical and structural brain changes, ultimately culminating in VCI. However, little is known about the pathological processes underlying VCI and the temporal dynamics between risk factors and disease mechanisms (biochemical and structural brain changes). This narrative review aims to provide an evidence-based summary of the link between individual vascular risk/disorders and cognitive dysfunction and the potential structural and biochemical pathophysiological processes. We also discuss some key challenges for future research on VCI. There is a need to shift from individual risk factors/disorders to comorbid vascular burden, identifying and integrating imaging and fluid biomarkers, implementing a life-course approach, considering possible neuroprotective influences of positive life exposures, and addressing biological sex at birth and gender differences. Finally, this review highlights the need for future researchers to leverage and integrate multidimensional data to advance our understanding of the mechanisms and pathophysiology of VCI.
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Affiliation(s)
- Atef Badji
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Jessica Youwakim
- Department of Pharmacology and Physiology, Université de Montréal, Montreal, QC, Canada; Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Montreal, QC, Canada; Groupe de Recherche sur la Signalisation Neuronal et la Circuiterie (SNC), Montreal, QC, Canada
| | - Alexandra Cooper
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Anna Marseglia
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
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Zhou Y, Wei L, Gao S, Wang J, Hu Z. Characterization of diffusion magnetic resonance imaging revealing relationships between white matter disconnection and behavioral disturbances in mild cognitive impairment: a systematic review. Front Neurosci 2023; 17:1209378. [PMID: 37360170 PMCID: PMC10285107 DOI: 10.3389/fnins.2023.1209378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 05/23/2023] [Indexed: 06/28/2023] Open
Abstract
White matter disconnection is the primary cause of cognition and affection abnormality in mild cognitive impairment (MCI). Adequate understanding of behavioral disturbances, such as cognition and affection abnormality in MCI, can help to intervene and slow down the progression of Alzheimer's disease (AD) promptly. Diffusion MRI is a non-invasive and effective technique for studying white matter microstructure. This review searched the relevant papers published from 2010 to 2022. Sixty-nine studies using diffusion MRI for white matter disconnections associated with behavioral disturbances in MCI were screened. Fibers connected to the hippocampus and temporal lobe were associated with cognition decline in MCI. Fibers connected to the thalamus were associated with both cognition and affection abnormality. This review summarized the correspondence between white matter disconnections and behavioral disturbances such as cognition and affection, which provides a theoretical basis for the future diagnosis and treatment of AD.
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Affiliation(s)
- Yu Zhou
- College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
| | - Lan Wei
- Business School, The University of Sydney, Sydney, NSW, Australia
| | - Song Gao
- College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, China
| | - Jun Wang
- School of Information Engineering, Henan University of Science and Technology, Luoyang, China
| | - Zhigang Hu
- College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
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Tian J, Raghavan S, Reid RI, Przybelski SA, Lesnick TG, Gebre RK, Graff-Radford J, Schwarz CG, Lowe VJ, Kantarci K, Knopman DS, Petersen RC, Jack CR, Vemuri P. White Matter Degeneration Pathways Associated With Tau Deposition in Alzheimer Disease. Neurology 2023; 100:e2269-e2278. [PMID: 37068958 PMCID: PMC10259272 DOI: 10.1212/wnl.0000000000207250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 02/16/2023] [Indexed: 04/19/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The dynamics of white matter (WM) changes are understudied in Alzheimer disease (AD). Our goal was to study the association between flortaucipir PET and WM health using neurite orientation dispersion and density imaging (NODDI) and evaluate its association with cognitive performance. Specifically, we focused on NODDI's Neurite Density Index (NDI), which aids in capturing axonal degeneration in WM and has greater specificity than single-shell diffusion MRI methods. METHOD We estimated regional flortaucipir PET standard uptake value ratios (SUVRs) from 3 regions corresponding to Braak stage I, III/IV, and V/VI to capture the spatial distribution pattern of the 3R/4R tau in AD. Then, we evaluated the associations between these measurements and NDIs in 29 candidate WM tracts using Pearson correlation and multiple regression models. RESULTS Based on 223 participants who were amyloid positive (mean age of 78 years and 57.0% male, 119 cognitively unimpaired, 56 mild cognitive impairment, and 48 dementia), the results showed that WM tracts NDI decreased with increasing regional Braak tau SUVRs. Of all the significant WM tracts, the uncinate fasciculus (r = -0.274 for Braak I, -0.311 for Braak III/IV, and -0.292 for Braak V/VI, p < 0.05) and cingulum adjoining hippocampus (r = -0.274, -0.288, -0.233, p < 0.05), both tracts anatomically connected to areas of early tau deposition, were consistently found to be within the top 5 distinguishing WM tracts associated with flortaucipir SUVRs. The increase in tau deposition measurable outside the medial temporal lobes in Braak III-VI was associated with a decrease in NDI in the middle and inferior temporal WM tracts. For cognitive performance, WM NDI had similar coefficients of determination (r 2 = 31%) as regional Braak flortaucipir SUVRs (29%), and together WM NDI and regional Braak flortaucipir SUVRs explained 46% of the variance in cognitive performance. DISCUSSION We found spatially dependent WM degeneration associated with regional flortaucipir SUVRs in Braak stages, suggesting a spatial pattern in WM damage. NDI, a specific marker of axonal density, provides complementary information about disease staging and progression in addition to tau deposition. Measurements of WM changes are important for the mechanistic understanding of multifactorial pathways through which AD causes cognitive dysfunction.
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Affiliation(s)
- Jianqiao Tian
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Sheelakumari Raghavan
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Robert I Reid
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Scott A Przybelski
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Timothy G Lesnick
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Robel K Gebre
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Jonathan Graff-Radford
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Christopher G Schwarz
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Val J Lowe
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Kejal Kantarci
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - David S Knopman
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Ronald C Petersen
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Prashanthi Vemuri
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN.
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Yang S, Niou ZX, Enriquez A, LaMar J, Huang JY, Ling K, Jafar-Nejad P, Gilley J, Coleman MP, Tennessen JM, Rangaraju V, Lu HC. NMNAT2 supports vesicular glycolysis via NAD homeostasis to fuel fast axonal transport. RESEARCH SQUARE 2023:rs.3.rs-2859584. [PMID: 37292715 PMCID: PMC10246254 DOI: 10.21203/rs.3.rs-2859584/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Background Bioenergetic maladaptations and axonopathy are often found in the early stages of neurodegeneration. Nicotinamide adenine dinucleotide (NAD), an essential cofactor for energy metabolism, is mainly synthesized by Nicotinamide mononucleotide adenylyl transferase 2 (NMNAT2) in CNS neurons. NMNAT2 mRNA levels are reduced in the brains of Alzheimer's, Parkinson's, and Huntington's disease. Here we addressed whether NMNAT2 is required for axonal health of cortical glutamatergic neurons, whose long-projecting axons are often vulnerable in neurodegenerative conditions. We also tested if NMNAT2 maintains axonal health by ensuring axonal ATP levels for axonal transport, critical for axonal function. Methods We generated mouse and cultured neuron models to determine the impact of NMNAT2 loss from cortical glutamatergic neurons on axonal transport, energetic metabolism, and morphological integrity. In addition, we determined if exogenous NAD supplementation or inhibiting a NAD hydrolase, sterile alpha and TIR motif-containing protein 1 (SARM1), prevented axonal deficits caused by NMNAT2 loss. This study used a combination of genetics, molecular biology, immunohistochemistry, biochemistry, fluorescent time-lapse imaging, live imaging with optical sensors, and anti-sense oligos. Results We provide in vivo evidence that NMNAT2 in glutamatergic neurons is required for axonal survival. Using in vivo and in vitro studies, we demonstrate that NMNAT2 maintains the NAD-redox potential to provide "on-board" ATP via glycolysis to vesicular cargos in distal axons. Exogenous NAD+ supplementation to NMNAT2 KO neurons restores glycolysis and resumes fast axonal transport. Finally, we demonstrate both in vitro and in vivo that reducing the activity of SARM1, an NAD degradation enzyme, can reduce axonal transport deficits and suppress axon degeneration in NMNAT2 KO neurons. Conclusion NMNAT2 ensures axonal health by maintaining NAD redox potential in distal axons to ensure efficient vesicular glycolysis required for fast axonal transport.
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Zito GA, Tarrano C, Ouarab S, Jegatheesan P, Ekmen A, Béranger B, Valabregue R, Hubsch C, Sangla S, Bonnet C, Delorme C, Méneret A, Degos B, Bouquet F, Apoil Brissard M, Vidailhet M, Hasboun D, Worbe Y, Roze E, Gallea C. Fixel-Based Analysis Reveals Whole-Brain White Matter Abnormalities in Cervical Dystonia. Mov Disord 2023. [PMID: 37148555 DOI: 10.1002/mds.29425] [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: 02/06/2023] [Revised: 04/04/2023] [Accepted: 04/12/2023] [Indexed: 05/08/2023] Open
Abstract
BACKGROUND Cervical dystonia (CD) is a form of isolated focal dystonia typically associated to abnormal head, neck, and shoulder movements and postures. The complexity of the clinical presentation limits the investigation of its pathophysiological mechanisms, and the neural networks associated to specific motor manifestations are still the object of debate. OBJECTIVES We investigated the morphometric properties of white matter fibers in CD and explored the networks associated with motor symptoms, while regressing out nonmotor scores. METHODS Nineteen patients affected by CD and 21 healthy controls underwent diffusion-weighted magnetic resonance imaging. We performed fixel-based analysis, a novel method evaluating fiber orientation within specific fiber bundles, and compared fiber morphometric properties between groups. Moreover, we correlated fiber morphometry with the severity of motor symptoms in patients. RESULTS Compared to controls, patients exhibited decreased white matter fibers in the right striatum. Motor symptom severity negatively correlated with white matter fibers passing through inferior parietal areas and the head representation area of the motor cortex. CONCLUSIONS Abnormal white matter integrity at the basal ganglia level may affect several functional networks involved, for instance, in motor preparation and execution, visuomotor coordination, and multimodal integration. This may result in progressive maladaptive plasticity, culminating in overt symptoms of dystonia. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
| | - Clément Tarrano
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- Department of Neurology, Assistance Publique-Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France
| | - Salim Ouarab
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Prasanthi Jegatheesan
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Asya Ekmen
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Benoît Béranger
- Center for NeuroImaging Research (CENIR), Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR 7225, Paris, France
| | - Romain Valabregue
- Center for NeuroImaging Research (CENIR), Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR 7225, Paris, France
| | - Cécile Hubsch
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Sophie Sangla
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Cécilia Bonnet
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Cécile Delorme
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | - Aurélie Méneret
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- DMU Neurosciences, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Bertrand Degos
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- Neurology Unit, AP-HP, Avicenne University Hospital, Sorbonne Paris Nord, Bobigny, France
- Center for Interdisciplinary Research in Biology, Collège de France, CNRS UMR7241/INSERM U1050, Université PSL, Paris, France
| | - Floriane Bouquet
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
| | | | - Marie Vidailhet
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- DMU Neurosciences, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Dominique Hasboun
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- Department of Neurology, Assistance Publique-Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Paris, France
| | - Yulia Worbe
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- Department of Neurophysiology, Saint-Antoine Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Emmanuel Roze
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
- DMU Neurosciences, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Cécile Gallea
- Movement Investigation and Therapeutics Team, Paris Brain Institute, Sorbonne University, Inserm U1127, CNRS UMR7225, Paris, France
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Clemente A, Attyé A, Renard F, Calamante F, Burmester A, Imms P, Deutscher E, Akhlaghi H, Beech P, Wilson PH, Poudel G, Domínguez D JF, Caeyenberghs K. Individualised profiling of white matter organisation in moderate-to-severe traumatic brain injury patients. Brain Res 2023; 1806:148289. [PMID: 36813064 DOI: 10.1016/j.brainres.2023.148289] [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: 11/03/2022] [Revised: 12/22/2022] [Accepted: 02/15/2023] [Indexed: 02/22/2023]
Abstract
BACKGROUND AND PURPOSE Approximately 65% of moderate-to-severe traumatic brain injury (m-sTBI) patients present with poor long-term behavioural outcomes, which can significantly impair activities of daily living. Numerous diffusion-weighted MRI studies have linked these poor outcomes to decreased white matter integrity of several commissural tracts, association fibres and projection fibres in the brain. However, most studies have focused on group-based analyses, which are unable to deal with the substantial between-patient heterogeneity in m-sTBI. As a result, there is increasing interest and need in conducting individualised neuroimaging analyses. MATERIALS AND METHODS Here, we generated a detailed subject-specific characterisation of microstructural organisation of white matter tracts in 5 chronic patients with m-sTBI (29 - 49y, 2 females), presented as a proof-of-concept. We developed an imaging analysis framework using fixel-based analysis and TractLearn to determine whether the values of fibre density of white matter tracts at the individual patient level deviate from the healthy control group (n = 12, 8F, Mage = 35.7y, age range 25 - 64y). RESULTS Our individualised analysis revealed unique white matter profiles, confirming the heterogenous nature of m-sTBI and the need of individualised profiles to properly characterise the extent of injury. Future studies incorporating clinical data, as well as utilising larger reference samples and examining the test-retest reliability of the fixel-wise metrics are warranted. CONCLUSIONS Individualised profiles may assist clinicians in tracking recovery and planning personalised training programs for chronic m-sTBI patients, which is necessary to achieve optimal behavioural outcomes and improved quality of life.
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Affiliation(s)
- Adam Clemente
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural, Health and Human Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia.
| | - Arnaud Attyé
- CNRS LPNC UMR 5105, University of Grenoble Alpes, Grenoble, France; School of Biomedical Engineering, The University of Sydney, Sydney, New South Wales 2006, Australia
| | - Félix Renard
- CNRS LPNC UMR 5105, University of Grenoble Alpes, Grenoble, France
| | - Fernando Calamante
- School of Biomedical Engineering, The University of Sydney, Sydney, New South Wales 2006, Australia; Sydney Imaging - The University of Sydney, Sydney, Australia
| | - Alex Burmester
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Phoebe Imms
- Leonard Davis School of Gerontology, University of Southern California, Australia
| | - Evelyn Deutscher
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Hamed Akhlaghi
- Emergency Department, St. Vincent's Hospital, University of Melbourne, Melbourne, Victoria, Australia; Department of Psychology, Faculty of Health, Deakin University, Australia
| | - Paul Beech
- Department of Radiology and Nuclear Medicine, The Alfred Hospital, Melbourne, Victoria, Australia
| | - Peter H Wilson
- Development and Disability over the Lifespan Program, Healthy Brain and Mind Research Centre, School of Behavioural, Health and Human Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia
| | - Govinda Poudel
- Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, Australia
| | - Juan F Domínguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Victoria, Australia
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Egorova-Brumley N, Dhollander T, Khan W, Khlif MS, Ebaid D, Brodtmann A. Changes in White Matter Microstructure Over 3 Years in People With and Without Stroke. Neurology 2023; 100:e1664-e1672. [PMID: 36792378 PMCID: PMC10115498 DOI: 10.1212/wnl.0000000000207065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 01/03/2023] [Indexed: 02/17/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Cerebral white matter health can be estimated by MRI-derived indices of microstructure. White matter dysfunction is increasingly recognized as a contributor to neurodegenerative disorders affecting cognition and to functional outcomes after stroke. Reduced indices of white matter microstructure have been demonstrated cross-sectionally in stroke survivors compared with stroke-free participants, but longitudinal changes in the structure of white matter after stroke remain largely unexplored. We aimed to characterize white matter micro- and macrostructure over 3 years after stroke and study associations with white matter metrics and cognitive functions. METHODS Patients with first-ever or recurrent ischemic stroke of any etiology in any vascular territory were compared with stroke-free age- and sex-matched controls. Those diagnosed with hemorrhagic stroke, TIA, venous infarction, or significant medical comorbidities, psychiatric and neurodegenerative disorders, substance abuse, or history of dementia were excluded. Diffusion-weighted MRI data at 3, 12, and 36 months were analyzed using a longitudinal fixel-based analysis, sensitive to fiber tract-specific differences within a voxel. It was used to examine whole-brain white matter degeneration in stroke compared with control participants. We studied microstructural differences in fiber density and macrostructural changes in fiber-bundle cross-section, in relation to cognitive performance. Analyses were performed controlling for age, intracranial volume, and education (family-wise error-corrected p < 0.05, nonparametric testing over 5,000 permutations). RESULTS We included 71 participants with stroke (age 66 ± 12 years, 22 women) and 36 controls (age 69 ± 5 years, 13 women). We observed extensive white matter structural degeneration across the whole brain, particularly affecting the thalamic, cerebellar, striatal, and superior longitudinal tracts and corpus callosum. Importantly, follow-up regression analyses in 72 predefined tracts showed that the decline in fiber density and cross-section from 3 months to 3 years was associated with worse cognitive performance at 3 years after stroke, especially affecting visuospatial processing, processing speed, language, and recognition memory. DISCUSSION We conclude that white matter neurodegeneration in ipsi- and contralesional thalamic, striatal, and cerebellar tracts continues to be greater in stroke survivors compared with stroke-free controls. White matter degeneration persists even years after stroke and is associated with poststroke cognitive impairment. TRIAL REGISTRATION INFORMATION ClinicalTrails.gov NCT02205424.
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Affiliation(s)
- Natalia Egorova-Brumley
- From the Melbourne School of Psychological Sciences (N.E.-B.), University of Melbourne; Dementia Theme (N.E.-B., W.K., M.S.K., D.E., A.B.), The Florey Institute of Neuroscience and Mental Health; Developmental Imaging (T.D.), Murdoch Children's Research Institute; and Cognitive Health Initiative (M.S.K., A.B.), Central Clinical School (CCS), Monash University, Melbourne, Australia.
| | - Thijs Dhollander
- From the Melbourne School of Psychological Sciences (N.E.-B.), University of Melbourne; Dementia Theme (N.E.-B., W.K., M.S.K., D.E., A.B.), The Florey Institute of Neuroscience and Mental Health; Developmental Imaging (T.D.), Murdoch Children's Research Institute; and Cognitive Health Initiative (M.S.K., A.B.), Central Clinical School (CCS), Monash University, Melbourne, Australia
| | - Wasim Khan
- From the Melbourne School of Psychological Sciences (N.E.-B.), University of Melbourne; Dementia Theme (N.E.-B., W.K., M.S.K., D.E., A.B.), The Florey Institute of Neuroscience and Mental Health; Developmental Imaging (T.D.), Murdoch Children's Research Institute; and Cognitive Health Initiative (M.S.K., A.B.), Central Clinical School (CCS), Monash University, Melbourne, Australia
| | - Mohamed Salah Khlif
- From the Melbourne School of Psychological Sciences (N.E.-B.), University of Melbourne; Dementia Theme (N.E.-B., W.K., M.S.K., D.E., A.B.), The Florey Institute of Neuroscience and Mental Health; Developmental Imaging (T.D.), Murdoch Children's Research Institute; and Cognitive Health Initiative (M.S.K., A.B.), Central Clinical School (CCS), Monash University, Melbourne, Australia
| | - Deena Ebaid
- From the Melbourne School of Psychological Sciences (N.E.-B.), University of Melbourne; Dementia Theme (N.E.-B., W.K., M.S.K., D.E., A.B.), The Florey Institute of Neuroscience and Mental Health; Developmental Imaging (T.D.), Murdoch Children's Research Institute; and Cognitive Health Initiative (M.S.K., A.B.), Central Clinical School (CCS), Monash University, Melbourne, Australia
| | - Amy Brodtmann
- From the Melbourne School of Psychological Sciences (N.E.-B.), University of Melbourne; Dementia Theme (N.E.-B., W.K., M.S.K., D.E., A.B.), The Florey Institute of Neuroscience and Mental Health; Developmental Imaging (T.D.), Murdoch Children's Research Institute; and Cognitive Health Initiative (M.S.K., A.B.), Central Clinical School (CCS), Monash University, Melbourne, Australia
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Wu BS, Ge YJ, Zhang W, Chen SD, Xiang ST, Zhang YR, Ou YN, Jiang YC, Tan L, Cheng W, Suckling J, Feng JF, Yu JT, Mao Y. Genome-wide association study of cerebellar white matter microstructure and genetic overlap with common brain disorders. Neuroimage 2023; 269:119928. [PMID: 36740028 DOI: 10.1016/j.neuroimage.2023.119928] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 01/12/2023] [Accepted: 02/02/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND The cerebellum is recognized as being involved in neurocognitive and motor functions with communication with extra-cerebellar regions relying on the white matter integrity of the cerebellar peduncles. However, the genetic determinants of cerebellar white matter integrity remain largely unknown. METHODS We conducted a genome-wide association analysis of cerebellar white matter microstructure using diffusion tensor imaging data from 25,415 individuals from UK Biobank. The integrity of cerebellar white matter microstructure was measured as fractional anisotropy (FA) and mean diffusivity (MD). Identification of independent genomic loci, functional annotation, and tissue and cell-type analysis were conducted with FUMA. The linkage disequilibrium score regression (LDSC) was used to calculate genetic correlations between cerebellar white matter microstructure and regional brain volumes and brain-related traits. Furthermore, the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework was employed to identify the shared genetic basis between cerebellar white matter microstructure and common brain disorders. RESULTS We identified 11 genetic loci (P < 8.3 × 10-9) and 86 genes associated with cerebellar white matter microstructure. Further functional enrichment analysis implicated the involvement of GABAergic neurons and cholinergic pathways. Significant polygenetic overlap between cerebellar white matter tracts and their anatomically connected or adjacent brain regions was detected. In addition, we report the overall genetic correlation and specific loci shared between cerebellar white matter microstructural integrity and brain-related traits, including movement, cognitive, psychiatric, and cerebrovascular categories. CONCLUSIONS Collectively, this study represents a step forward in understanding the genetics of cerebellar white matter microstructure and its shared genetic etiology with common brain disorders.
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Affiliation(s)
- 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
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 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
| | - Shi-Tong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- 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
| | - Yu-Chao Jiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China; Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - John Suckling
- Department of Psychiatry, Brain Mapping Unit, University of Cambridge, Cambridge, CB2 0SZ, UK
| | - Jian-Feng 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
| | - 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.
| | - Ying Mao
- Department of Neurosurgery 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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Cao Z, Lin H, Gao F, Shen X, Zhang H, Zhang J, Du L, Lai C, Ma X, Wu D. Microstructural Alterations in Projection and Association Fibers in Neonatal Hypoxia-Ischemia. J Magn Reson Imaging 2023; 57:1131-1142. [PMID: 35861468 DOI: 10.1002/jmri.28366] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/29/2022] [Accepted: 07/01/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND Diffusion MRI (dMRI) is known to be sensitive to hypoxic-ischemic encephalopathy (HIE). However, existing dMRI studies used simple diffusion tensor metrics and focused only on a few selected cerebral regions, which cannot provide a comprehensive picture of microstructural injury. PURPOSE To systematically characterize the microstructural alterations in mild, moderate, and severe HIE neonates compared to healthy neonates with advanced dMRI using region of interest (ROI), tract, and fixel-based analyses. STUDY TYPE Prospective. POPULATION A total of 42 neonates (24 males and 18 females). FIELD STRENGTH/SEQUENCE 3-T, diffusion-weighted echo-planar imaging. ASSESSMENT Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), fiber density (FD), fiber cross-section (FC), and fiber density and cross-section (FDC) were calculated in 40 ROIs and 6 tracts. Fixel-based analysis was performed to assess group differences in individual fiber components within a voxel (fixel). STATISTICAL TESTS One-way analysis of covariance (ANCOVA) to compare dMRI metrics among severe/moderate/mild HIE and control groups and general linear model for fixel-wise group differences (age, sex, and body weight as covariates). Adjusted P value < 0.05 was considered statistically significant. RESULTS For severe HIE, ROI-based analysis revealed widespread regions, including the deep nuclei and white matter with reduced FA, while in moderate injury, only FC was decreased around the posterior watershed zones. Tract-based analysis demonstrated significantly reduced FA, FD, and FC in the right inferior fronto-occipital fasciculus (IFOF), right inferior longitudinal fasciculus (ILF), and splenium of corpus callosum (SCC) in moderate HIE, and in right IFOF and left anterior thalamic radiation (ATR) in mild HIE. Correspondingly, we found altered fixels in the right middle-posterior IFOF and ILF, and in the central-to-right part of SCC in moderate HIE. DATA CONCLUSION For severe HIE, extensive microstructural injury was identified. For moderate-mild HIE, association fiber injury in posterior watershed area with a rightward lateralization was found. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Zuozhen Cao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Huijia Lin
- Department of Neonatal Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Fusheng Gao
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, National Clinical Research Center for Child Health, Hangzhou, China
| | - Xiaoxia Shen
- Department of Neonatal Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Hongxi Zhang
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, National Clinical Research Center for Child Health, Hangzhou, China
| | - Jiangyang Zhang
- Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Lizhong Du
- Department of Neonatal Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Can Lai
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, National Clinical Research Center for Child Health, Hangzhou, China
| | - Xiaolu Ma
- Department of Neonatal Intensive Care Unit, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
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Chen Y, Wang Y, Song Z, Fan Y, Gao T, Tang X. Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review. Ageing Res Rev 2023; 87:101911. [PMID: 36931328 DOI: 10.1016/j.arr.2023.101911] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 03/01/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023]
Abstract
Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.
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Affiliation(s)
- Yu Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yifei Wang
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Zeyu Song
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Yingwei Fan
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Tianxin Gao
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
| | - Xiaoying Tang
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China; School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
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Haddad SMH, Pieruccini-Faria F, Montero-Odasso M, Bartha R. Localized White Matter Tract Integrity Measured by Diffusion Tensor Imaging Is Altered in People with Mild Cognitive Impairment and Associated with Dual-Task and Single-Task Gait Speed. J Alzheimers Dis 2023; 92:1367-1384. [PMID: 36911933 DOI: 10.3233/jad-220476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
BACKGROUND Altered white matter (WM) tract integrity may contribute to mild cognitive impairment (MCI) and gait abnormalities. OBJECTIVE The purpose of this study was to determine whether diffusion tensor imaging (DTI) metrics were altered in specific portions of WM tracts in people with MCI and to determine whether gait speed variations were associated with the specific DTI metric changes. METHODS DTI was acquired in 44 people with MCI and 40 cognitively normal elderly controls (CNCs). Fractional anisotropy (FA) and radial diffusivity (RD) were measured along 18 major brain WM tracts using probabilistic tractography. The average FA and RD along the tracts were compared between the groups using MANCOVA and post-hoc tests. The tracts with FA or RD differences between the groups were examined using an along-tract exploratory analysis to identify locations that differed between the groups. Associations between FA and RD in whole tracts and in the segments of the tracts that differed between the groups and usual/dual-task gait velocities and gross cognition were examined. RESULTS Lower FA and higher RD was observed in right cingulum-cingulate gyrus endings (rh.ccg) of the MCI group compared to the CNC group. These changes were localized to the posterior portions of the rh.ccg and correlated with gait velocities. CONCLUSION Lower FA and higher RD in the posterior portion of the rh.ccg adjacent to the posterior cingulate suggests decreased microstructural integrity in the MCI group. The correlation of these metrics with gait velocities suggests an important role for this tract in maintaining normal cognitive-motor function.
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Affiliation(s)
- Seyyed M H Haddad
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Canada
| | - Frederico Pieruccini-Faria
- Department of Medicine, Division of Geriatric Medicine, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada.,Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, Canada
| | - Manuel Montero-Odasso
- Department of Medicine, Division of Geriatric Medicine, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada.,Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, Canada.,Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Canada
| | - Robert Bartha
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Canada
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Graciani AL, Gutierre MU, Coppi AA, Arida RM, Gutierre RC. MYELIN, AGING, AND PHYSICAL EXERCISE. Neurobiol Aging 2023; 127:70-81. [PMID: 37116408 DOI: 10.1016/j.neurobiolaging.2023.03.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/22/2023] [Accepted: 03/24/2023] [Indexed: 04/03/2023]
Abstract
Myelin sheath is a structure in neurons fabricated by oligodendrocytes and Schwann cells responsible for increasing the efficiency of neural synapsis, impulse transmission, and providing metabolic support to the axon. They present morpho-functional changes during health aging as deformities of the sheath and its fragmentation, causing an increased load on microglial phagocytosis, with Alzheimer's disease aggravating. Physical exercise has been studied as a possible protective agent for the nervous system, offering benefits to neuroplasticity. In this regard, studies in animal models for Alzheimer's and depression reported the efficiency of physical exercise in protecting against myelin degeneration. A reduction of myelin damage during aging has also been observed in healthy humans. Physical activity promotes oligodendrocyte proliferation and myelin preservation during old age, although some controversies remain. In this review, we will address how effective physical exercise can be as a protective agent of the myelin sheath against the effects of aging in physiological and pathological conditions.
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Polk SE, Kleemeyer MM, Bodammer NC, Misgeld C, Porst J, Wolfarth B, Kühn S, Lindenberger U, Düzel S, Wenger E. Aerobic exercise is associated with region-specific changes in volumetric, tensor-based, and fixel-based measures of white matter integrity in healthy older adults. NEUROIMAGE: REPORTS 2023. [DOI: 10.1016/j.ynirp.2022.100155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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40
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Marin-Marin L, Miró-Padilla A, Costumero V. Structural But Not Functional Connectivity Differences within Default Mode Network Indicate Conversion to Dementia. J Alzheimers Dis 2023; 91:1483-1494. [PMID: 36641666 DOI: 10.3233/jad-220603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
BACKGROUND Malfunctioning of the default mode network (DMN) has been consistently related to mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, evidence on differences in this network between MCI converters (MCI-c) and non-converters (MCI-nc), which could mark progression to AD, is still inconsistent. OBJECTIVE To multimodally investigate the DMN in the AD continuum. METHODS We measured gray matter (GM) volume, white matter (WM) integrity, and functional connectivity (FC) at rest in healthy elderly controls, MCI-c, MCI-nc, and AD patients, matched on sociodemographic variables. RESULTS Significant differences between AD patients and controls were found in the structure of most of the regions of the DMN. MCI-c only differed from MCI-nc in GM volume of the left parahippocampus and bilateral hippocampi and middle frontal gyri, as well as in WM integrity of the parahippocampal cingulum connecting the left hippocampus and precuneus. We found significant correlations between integrity in some of those regions and global neuropsychological status, as well as an excellent discrimination ability between converters and non-converters for the sum of GM volume of left parahippocampus, bilateral hippocampi, and middle frontal gyri, and WM integrity of left parahippocampal cingulum. However, we found no significant differences in FC. CONCLUSION These results further support the relationship between abnormalities in the DMN and AD, and suggest that structural measures could be more accurate than resting-state estimates as markers of conversion from MCI to AD.
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Affiliation(s)
- Lidón Marin-Marin
- Neuropsychology and Functional Neuroimaging Group, Department of Basic and Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
| | - Anna Miró-Padilla
- Neuropsychology and Functional Neuroimaging Group, Department of Basic and Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
| | - Víctor Costumero
- Neuropsychology and Functional Neuroimaging Group, Department of Basic and Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
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Murthy M, Shireby G, Miki Y, Viré E, Lashley T, Warner TT, Mill J, Bettencourt C. Epigenetic age acceleration is associated with oligodendrocyte proportions in MSA and control brain tissue. Neuropathol Appl Neurobiol 2023; 49:e12872. [PMID: 36542090 PMCID: PMC10107510 DOI: 10.1111/nan.12872] [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: 07/20/2022] [Revised: 11/15/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022]
Abstract
AIMS Epigenetic clocks are widely applied as surrogates for biological age in different tissues and/or diseases, including several neurodegenerative diseases. Despite white matter (WM) changes often being observed in neurodegenerative diseases, no study has investigated epigenetic ageing in white matter. METHODS We analysed the performances of two DNA methylation-based clocks, DNAmClockMulti and DNAmClockCortical , in post-mortem WM tissue from multiple subcortical regions and the cerebellum, and in oligodendrocyte-enriched nuclei. We also examined epigenetic ageing in control and multiple system atrophy (MSA) (WM and mixed WM and grey matter), as MSA is a neurodegenerative disease comprising pronounced WM changes and α-synuclein aggregates in oligodendrocytes. RESULTS Estimated DNA methylation (DNAm) ages showed strong correlations with chronological ages, even in WM (e.g., DNAmClockCortical , r = [0.80-0.97], p < 0.05). However, performances and DNAm age estimates differed between clocks and brain regions. DNAmClockMulti significantly underestimated ages in all cohorts except in the MSA prefrontal cortex mixed tissue, whereas DNAmClockCortical tended towards age overestimations. Pronounced age overestimations in the oligodendrocyte-enriched cohorts (e.g., oligodendrocyte-enriched nuclei, p = 6.1 × 10-5 ) suggested that this cell type ages faster. Indeed, significant positive correlations were observed between estimated oligodendrocyte proportions and DNAm age acceleration estimated by DNAmClockCortical (r > 0.31, p < 0.05), and similar trends were obtained with DNAmClockMulti . Although increased age acceleration was observed in MSA compared with controls, no significant differences were detected upon adjustment for possible confounders (e.g., cell-type proportions). CONCLUSIONS Our findings show that oligodendrocyte proportions positively influence epigenetic age acceleration across brain regions and highlight the need to further investigate this in ageing and neurodegeneration.
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Affiliation(s)
- Megha Murthy
- Queen Square Brain Bank, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
- Department of Clinical and Movement NeurosciencesUCL Queen Square Institute of NeurologyLondonUK
| | - Gemma Shireby
- University of Exeter Medical SchoolUniversity of ExeterExeterUK
| | - Yasuo Miki
- Queen Square Brain Bank, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
- Department of Neuropathology, Institute of Brain ScienceHirosaki University Graduate School of MedicineHirosakiJapan
| | - Emmanuelle Viré
- UCL Institute of Prion Diseases, MRC Prion Unit at UCLUniversity College LondonLondonUK
| | - Tammaryn Lashley
- Queen Square Brain Bank, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
- Department of Neurodegenerative Disease, Queen Square Brain Bank for Neurological DisordersUCL Queen Square Institute of Neurology1 Wakefield StreetLondonWC1N 1PJUK
| | - Thomas T. Warner
- Queen Square Brain Bank, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
- Department of Clinical and Movement NeurosciencesUCL Queen Square Institute of NeurologyLondonUK
- Reta Lila Weston InstituteUCL Queen Square Institute of NeurologyLondonUK
| | - Jonathan Mill
- University of Exeter Medical SchoolUniversity of ExeterExeterUK
| | - Conceição Bettencourt
- Queen Square Brain Bank, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
- Department of Neurodegenerative Disease, Queen Square Brain Bank for Neurological DisordersUCL Queen Square Institute of Neurology1 Wakefield StreetLondonWC1N 1PJUK
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Srivishagan S, Kumaralingam L, Thanikasalam K, Pinidiyaarachchi UAJ, Ratnarajah N. Discriminative patterns of white matter changes in Alzheimer's. Psychiatry Res Neuroimaging 2023; 328:111576. [PMID: 36495726 DOI: 10.1016/j.pscychresns.2022.111576] [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: 09/08/2022] [Revised: 11/12/2022] [Accepted: 11/22/2022] [Indexed: 12/02/2022]
Abstract
Changes in structural connectivity of the Alzheimer's brain have not been widely studied utilizing cutting-edge methodologies. This study develops an efficient structural connectome-based convolutional neural network (CNN) to classify the AD and uses explanations of CNNs' choices in classification to pinpoint the discriminative changes in white matter connectivity in AD. A CNN architecture has been developed to classify normal control (NC) and AD subjects from the weighted structural connectome. Then, the CNN classification decision is visually analyzed using gradient-based localization techniques to identify the discriminative changes in white matter connectivity in Alzheimer's. The cortical regions involved in the identified discriminative structural connectivity changes in AD are highly covered in the temporal/subcortical regions. A specific pattern is identified in the discriminative changes in structural connectivity of AD, where the white matter changes are revealed within the temporal/subcortical regions and from the temporal/subcortical regions to the frontal and parietal regions in both left and right hemispheres. The proposed approach has the potential to comprehensively analyze the discriminative structural connectivity differences in AD, change the way of detecting biomarkers, and help clinicians better understand the structural changes in AD and provide them with more confidence in automated diagnostic systems.
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Affiliation(s)
- Subaramya Srivishagan
- Department of Physical Science, Faculty of Applied Science, University of Vavuniya, Vavuniya, Sri Lanka; PGIS, University of Peradeniya, Peradeniya, Sri Lanka
| | - Logiraj Kumaralingam
- Department of Computer Science, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - Kokul Thanikasalam
- Department of Computer Science, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - U A J Pinidiyaarachchi
- Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka
| | - Nagulan Ratnarajah
- Department of Physical Science, Faculty of Applied Science, University of Vavuniya, Vavuniya, Sri Lanka.
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Uchida Y, Onda K, Hou Z, Troncoso JC, Mori S, Oishi K. Microstructural Neurodegeneration of the Entorhinal-Hippocampus Pathway along the Alzheimer's Disease Continuum. J Alzheimers Dis 2023; 95:1107-1117. [PMID: 37638442 PMCID: PMC10578220 DOI: 10.3233/jad-230452] [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] [Accepted: 07/15/2023] [Indexed: 08/29/2023]
Abstract
BACKGROUND Conventional neuroimaging biomarkers for the neurodegeneration of Alzheimer's disease (AD) are not sensitive enough to detect neurodegenerative alterations during the preclinical stage of AD individuals. OBJECTIVE We examined whether neurodegeneration of the entorhinal-hippocampal pathway could be detected along the AD continuum using ultra-high-field diffusion tensor imaging and tractography for ex vivo brain tissues. METHODS Postmortem brain specimens from a cognitively unimpaired individual without AD pathological changes (non-AD), a cognitively unimpaired individual with AD pathological changes (preclinical AD), and a demented individual with AD pathological changes (AD dementia) were scanned with an 11.7T diffusion magnetic resonance imaging. Fractional anisotropy (FA) values of the entorhinal layer II and number of perforant path fibers counted by tractography were compared among the AD continuum. Following the imaging analyses, the status of myelinated fibers and neuronal cells were verified by subsequent serial histological examinations. RESULTS At 250μm (zipped to 125μm) isotropic resolution, the entorhinal layer II islands and the perforant path fibers could be identified in non-AD and preclinical AD, but not in AD dementia, followed by histological verification. The FA value of the entorhinal layer II was the highest among the entorhinal laminae in non-AD and preclinical AD, whereas the FA values in the entorhinal laminae were homogeneously low in AD dementia. The FA values and number of perforant path fibers decreased along the AD continuum (non-AD>preclinical AD > AD dementia). CONCLUSION We successfully detected neurodegenerative alterations of the entorhinal-hippocampal pathway at the preclinical stage of the AD continuum.
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Affiliation(s)
- Yuto Uchida
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kengo Onda
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zhipeng Hou
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Juan C. Troncoso
- Department of Pathology, Division of Neuropathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susumu Mori
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kenichi Oishi
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Richman Family Precision Medicine Center of Excellence in Alzheimer’s Disease, Baltimore, MD, USA
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Li Y, Wang M, Cong L, Hou T, Song L, Wang X, Shi L, Dekhtyar S, Wang Y, Du Y, Qiu C. Lifelong Cognitive Reserve, Imaging Markers of Brain Aging, and Cognitive Function in Dementia-Free Rural Older Adults: A Population-Based Study. J Alzheimers Dis 2023; 92:261-272. [PMID: 36710675 PMCID: PMC10041437 DOI: 10.3233/jad-220864] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/28/2022] [Indexed: 01/28/2023]
Abstract
BACKGROUND Cognitive reserve (CR) partly explains cognitive variability in the presence of pathological brain aging. OBJECTIVE We investigated the interplay of lifelong CR with age, sex, and brain aging markers in cognitive phenotypes among older adults with very limited education. METHODS This population-based cross-sectional study included 179 dementia-free participants (age ≥65 years; 39.7% women; 67.0% had no or elementary education) examined in 2014-2016. We assessed lacunes and volumes of hippocampus, ventricles, grey matter, white matter (WM), and white matter hyperintensities. Lifelong CR score was generated from six lifespan intellectual factors (e.g., education and social support). We used Mini-Mental State Examination (MMSE) score to assess cognition and Petersen's criteria to define mild cognitive impairment (MCI). Data were analyzed using general linear and logistic models. RESULTS The association of higher lifelong CR score (range: -4.0-5.0) with higher MMSE score was stronger in women (multivariable-adjusted β-coefficient and 95% CI: 1.75;0.99-2.51) than in men (0.68;0.33-1.03) (pinteraction = 0.006). The association of higher CR with MCI (multivariable-adjusted odds ratio and 95% CI: 0.77;0.60-0.99) did not vary by age or sex. Among participants with low CR (<1.4[median]), greater hippocampal and WM volumes were related to higher MMSE scores with multivariable-adjusted β-coefficients being 1.77(0.41-3.13) and 0.44(0.15-0.74); the corresponding figures in those with high CR were 0.15(-0.76-1.07) and -0.17(-0.41-0.07) (pinteraction <0.01). There was no statistical interaction of CR with MRI markers on MCI. CONCLUSION Greater lifelong CR capacity is associated with better late-life cognition among people with limited education, possibly by compensating for impact of neurodegeneration.
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Affiliation(s)
- Yuanjing Li
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Mingqi Wang
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Lin Cong
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Tingting Hou
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Lin Song
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Xiang Wang
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, P.R. China
| | - Serhiy Dekhtyar
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
- Cheeloo College of Medicine, Shandong University, Jinan, Shandong, P.R. China
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital, Jinan, Shandong, P.R. China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
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Ni HC, Chao YP, Tseng RY, Wu CT, Cocchi L, Chou TL, Chen RS, Gau SSF, Yeh CH, Lin HY. Lack of effects of four-week theta burst stimulation on white matter macro/microstructure in children and adolescents with autism. Neuroimage Clin 2023; 37:103324. [PMID: 36638598 PMCID: PMC9852693 DOI: 10.1016/j.nicl.2023.103324] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 12/18/2022] [Accepted: 01/05/2023] [Indexed: 01/09/2023]
Abstract
Following the published behavioral and cognitive results of this single-blind parallel sham-controlled randomized clinical trial, the current study aimed to explore the impact of intermittent theta burst stimulation (iTBS), a variant of excitatory transcranial magnetic stimulation, over the bilateral posterior superior temporal sulci (pSTS) on white matter macro/microstructure in intellectually able children and adolescents with autism. Participants were randomized and blindly received active or sham iTBS for 4 weeks (the single-blind sham-controlled phase). Then, all participants continued to receive active iTBS for another 4 weeks (the open-label phase). The clinical results were published elsewhere. Here, we present diffusion magnetic resonance imaging data on potential changes in white matter measures after iTBS. Twenty-two participants in Active-Active group and 27 participants in Sham-Active group underwent multi-shell high angular resolution diffusion imaging (64-direction for b = 2000 & 1000 s/mm2, respectively) at baseline, week 4, and week 8. With longitudinal fixel-based analysis, we found no white matter changes following iTBS from baseline to week 4 (a null treatment by time interaction and a null within-group paired comparison in the Active-Active group), nor from baseline to week 8 (null within-group paired comparisons in both Active-Active and Sham-Active groups). As for the brain-symptoms relationship, we did not find baseline white matter metrics associated with symptom changes at week 4 in either group. Our results raise the question of what the minimal cumulative stimulation dose required to induce the white matter plasticity is.
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Affiliation(s)
- Hsing-Chang Ni
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Yi-Ping Chao
- Deparment of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan; Department of Otorhinolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Rung-Yu Tseng
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan
| | - Chen-Te Wu
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Luca Cocchi
- Clinical Brain Networks Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tai-Li Chou
- Department of Psychology, National Taiwan University, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan
| | - Rou-Shayn Chen
- Department of Neurology, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Susan Shur-Fen Gau
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Chun-Hung Yeh
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan.
| | - Hsiang-Yuan Lin
- Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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Giraldo DL, Smith RE, Struyfs H, Niemantsverdriet E, De Roeck E, Bjerke M, Engelborghs S, Romero E, Sijbers J, Jeurissen B. Investigating Tissue-Specific Abnormalities in Alzheimer's Disease with Multi-Shell Diffusion MRI. J Alzheimers Dis 2022; 90:1771-1791. [PMID: 36336929 PMCID: PMC9789487 DOI: 10.3233/jad-220551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM. OBJECTIVE In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls. METHODS By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons. RESULTS Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus. CONCLUSION This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.
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Affiliation(s)
- Diana L. Giraldo
- Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia,imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Robert E. Smith
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Laboratory of Neurochemistry, Department of Clinical Chemistry, and Center for Neurosciences (C4N), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Department of Neurology, and Center for Neurosciences (C4N), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Eduardo Romero
- Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Jan Sijbers
- imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Ben Jeurissen
- imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium,Lab for Equilibrium Investigations and Aerospace, Department of Physics, University of Antwerp, Antwerp, Belgium,Correspondence to: Ben Jeurissen, PhD, imec - Vision Lab, Department of Physics, University of Antwerp (CDE), Universiteitsplein 1, Building N, 2610 Antwerp, Belgium. Tel.: +32 3 265 24 77; E-mail:
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Mirza-Davies A, Foley S, Caseras X, Baker E, Holmans P, Escott-Price V, Jones DK, Harrison JR, Messaritaki E. The impact of genetic risk for Alzheimer's disease on the structural brain networks of young adults. Front Neurosci 2022; 16:987677. [PMID: 36532292 PMCID: PMC9748570 DOI: 10.3389/fnins.2022.987677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 11/09/2022] [Indexed: 12/02/2022] Open
Abstract
Introduction We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer's disease, using magnetic resonance imaging (MRI) and genotype data from the Avon Longitudinal Study of Parents and Children. Methods Diffusion MRI data were used to perform whole-brain tractography and generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participant's genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and (a) the graph theoretical metrics of the structural networks and (b) the rich-club, feeder and local connectivity of the whole-brain networks. Results In the visual subnetwork, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.19, p = 1.4 × 10-3), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r = 0.16, p = 5.5 × 10-3), and the mean clustering coefficient was negatively correlated with the tau-protein binding PRS (r = -0.16, p = 0.016). In the default mode network, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.14, p = 0.044). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r = -0.16, p = 0.035; r = -0.15, p = 0.036). Discussion We identified small reductions in brain connectivity in young adults at risk of developing Alzheimer's disease in later life.
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Affiliation(s)
- Anastasia Mirza-Davies
- School of Medicine, University Hospital Wales, Cardiff University, Cardiff, United Kingdom
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Xavier Caseras
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Emily Baker
- UK Dementia Research Institute, Cardiff University, Cardiff, United Kingdom
| | - Peter Holmans
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Valentina Escott-Price
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- UK Dementia Research Institute, Cardiff University, Cardiff, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Judith R. Harrison
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Institute for Translational and Clinical Research, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Eirini Messaritaki
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- BRAIN Biomedical Research Unit, School of Medicine, Cardiff University, Cardiff, United Kingdom
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TractoInferno - A large-scale, open-source, multi-site database for machine learning dMRI tractography. Sci Data 2022; 9:725. [PMID: 36433966 PMCID: PMC9700736 DOI: 10.1038/s41597-022-01833-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 11/09/2022] [Indexed: 11/26/2022] Open
Abstract
TractoInferno is the world's largest open-source multi-site tractography database, including both research- and clinical-like human acquisitions, aimed specifically at machine learning tractography approaches and related ML algorithms. It provides 284 samples acquired from 3 T scanners across 6 different sites. Available data includes T1-weighted images, single-shell diffusion MRI (dMRI) acquisitions, spherical harmonics fitted to the dMRI signal, fiber ODFs, and reference streamlines for 30 delineated bundles generated using 4 tractography algorithms, as well as masks needed to run tractography algorithms. Manual quality control was additionally performed at multiple steps of the pipeline. We showcase TractoInferno by benchmarking the learn2track algorithm and 5 variations of the same recurrent neural network architecture. Creating the TractoInferno database required approximately 20,000 CPU-hours of processing power, 200 man-hours of manual QC, 3,000 GPU-hours of training baseline models, and 4 Tb of storage, to produce a final database of 350 Gb. By providing a standardized training dataset and evaluation protocol, TractoInferno is an excellent tool to address common issues in machine learning tractography.
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Zhou J, Zhang P, Zhang B, Kong Y. White Matter Damage in Alzheimer's Disease: Contribution of Oligodendrocytes. Curr Alzheimer Res 2022; 19:CAR-EPUB-127137. [PMID: 36281858 PMCID: PMC9982194 DOI: 10.2174/1567205020666221021115321] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/15/2022] [Accepted: 09/23/2022] [Indexed: 11/22/2022]
Abstract
Alzheimer's disease (AD) is an age-related neurodegenerative disease, seriously influencing the quality of life and is a global health problem. Many factors affect the onset and development of AD, but specific mechanisms underlying the disease are unclear. Most studies investigating AD have focused on neurons and the gray matter in the central nervous system (CNS) but have not led to effective treatments. Recently, an increasing number of studies have focused on the white matter (WM). Magnetic resonance imaging and pathology studies have shown different degrees of WM abnormality during the progression of AD. Myelin sheaths, the main component of WM in the CNS, wrap and insulate axons to ensure conduction of the rapid action potential and axonal integrity. WM damage is characterized by progressive degeneration of axons, oligodendrocytes (OLs), and myelin in one or more areas of the CNS. The contributions of OLs to AD progression have, until recently, been largely overlooked. OLs are integral to myelin production, and the proliferation and differentiation of OLs, an early characteristic of AD, provide a promising target for preclinical diagnosis and treatment. However, despite some progress, the key mechanisms underlying the contributions of OLs to AD remain unclear. Given the heavy burden of medical treatment, a better understanding of the pathophysiological mechanisms underlying AD is vital. This review comprehensively summarize the results on WM abnormalities in AD and explores the relationship between OL progenitor cells and the pathogenesis of AD. Finally, the underlying molecular mechanisms and potential future research directions are discussed.
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Affiliation(s)
- Jinyu Zhou
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing-400042, China
| | - Peng Zhang
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing-400010, China
| | - Bo Zhang
- Department of Basic Medicine, Chongqing Medical and Pharmaceutical College, Chongqing-401331, China
| | - Yuhan Kong
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing-400042, China
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Shastin D, Genc S, Parker GD, Koller K, Tax CMW, Evans J, Hamandi K, Gray WP, Jones DK, Chamberland M. Surface-based tracking for short association fibre tractography. Neuroimage 2022; 260:119423. [PMID: 35809886 PMCID: PMC10009610 DOI: 10.1016/j.neuroimage.2022.119423] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/30/2022] [Accepted: 06/29/2022] [Indexed: 11/16/2022] Open
Abstract
It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.
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Affiliation(s)
- Dmitri Shastin
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom.
| | - Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Greg D Parker
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Kristin Koller
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
| | - John Evans
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom; Department of Neurology, University Hospital of Wales, Cardiff, United Kingdom
| | - William P Gray
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
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