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DiPiero MA, Rodrigues PG, Justman M, Roche S, Bond E, Gonzalez JG, Davidson RJ, Planalp EM, Dean DC. Gray matter based spatial statistics framework in the 1-month brain: insights into gray matter microstructure in infancy. Brain Struct Funct 2024:10.1007/s00429-024-02853-w. [PMID: 39313671 DOI: 10.1007/s00429-024-02853-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024]
Abstract
The neurodevelopmental epoch from fetal stages to early life embodies a critical window of peak growth and plasticity in which differences believed to be associated with many neurodevelopmental and psychiatric disorders first emerge. Obtaining a detailed understanding of the developmental trajectories of the cortical gray matter microstructure is necessary to characterize differential patterns of neurodevelopment that may subserve future intellectual, behavioral, and psychiatric challenges. The neurite orientation dispersion density imaging (NODDI) Gray-Matter Based Spatial Statistics (GBSS) framework leverages information from the NODDI model to enable sensitive characterization of the gray matter microstructure while limiting partial volume contamination and misregistration errors between images collected in different spaces. However, limited contrast of the underdeveloped brain poses challenges for implementing this framework with infant diffusion MRI (dMRI) data. In this work, we aim to examine the development of cortical microstructure in infants. We utilize the NODDI GBSS framework and propose refinements to the original framework that aim to improve the delineation and characterization of gray matter in the infant brain. Taking this approach, we cross-sectionally investigate age relationships in the developing gray matter microstructural organization in infants within the first month of life and reveal widespread relationships with the gray matter architecture.
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Affiliation(s)
- Marissa A DiPiero
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | | | - McKaylie Justman
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
| | - Sophia Roche
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
| | - Elizabeth Bond
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
| | - Jose Guerrero Gonzalez
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Richard J Davidson
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Elizabeth M Planalp
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, 53705, WI, USA.
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA.
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA.
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Li Y, Zhuo Z, Liu C, Duan Y, Shi Y, Wang T, Li R, Wang Y, Jiang J, Xu J, Tian D, Zhang X, Shi F, Zhang X, Carass A, Barkhof F, Prince JL, Ye C, Liu Y. Deep learning enables accurate brain tissue microstructure analysis based on clinically feasible diffusion magnetic resonance imaging. Neuroimage 2024:120858. [PMID: 39317273 DOI: 10.1016/j.neuroimage.2024.120858] [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: 08/05/2024] [Revised: 09/14/2024] [Accepted: 09/17/2024] [Indexed: 09/26/2024] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) allows non-invasive assessment of brain tissue microstructure. Current model-based tissue microstructure reconstruction techniques require a large number of diffusion gradients, which is not clinically feasible due to imaging time constraints, and this has limited the use of tissue microstructure information in clinical settings. Recently, approaches based on deep learning (DL) have achieved promising tissue microstructure reconstruction results using clinically feasible dMRI. However, it remains unclear whether the subtle tissue changes associated with disease or age are properly preserved with DL approaches and whether DL reconstruction results can benefit clinical applications. Here, we provide the first evidence that DL approaches to tissue microstructure reconstruction yield reliable brain tissue microstructure analysis based on clinically feasible dMRI scans. Specifically, we reconstructed tissue microstructure from four different brain dMRI datasets with only 12 diffusion gradients, a clinically feasible protocol, and the neurite orientation dispersion and density imaging (NODDI) and spherical mean technique (SMT) models were considered. With these results we show that disease-related and age-dependent alterations of brain tissue were accurately identified. These findings demonstrate that DL tissue microstructure reconstruction can accurately quantify microstructural alterations in the brain based on clinically feasible dMRI.
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Affiliation(s)
- Yuxing Li
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, China
| | - Zhizheng Zhuo
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chenghao Liu
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, China
| | - Yunyun Duan
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yulu Shi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tingting Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Runzhi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing, China
| | - Yanli Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing, China
| | - Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Decai Tian
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xinghu Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Fudong Shi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Beijing, China; Department of Neurology and Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaofeng Zhang
- School of Information and Electronics, Beijing Institute of Technology, Zhuhai, China
| | - Aaron Carass
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, 1081 HV, The Netherlands
| | - Jerry L Prince
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, USA
| | - Chuyang Ye
- School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, China.
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
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Sun P, He Z, Li A, Yang J, Zhu Y, Cai Y, Ma T, Ma S, Guo T. Spatial and temporal patterns of cortical mean diffusivity in Alzheimer's disease and suspected non-Alzheimer's disease pathophysiology. Alzheimers Dement 2024. [PMID: 39132849 DOI: 10.1002/alz.14176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 07/12/2024] [Accepted: 07/16/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION The spatial and temporal patterns of cortical mean diffusivity (cMD), as well as its association with Alzheimer's disease (AD) and suspected non-Alzheimer's pathophysiology (SNAP), are not yet fully understood. METHODS We compared baseline (n = 617) and longitudinal changes (n = 421) of cMD, cortical thickness, and gray matter volume and their relations to vascular risk factors, amyloid beta (Aβ), and tau positron emission tomography (PET), and longitudinal cognitive decline in Aβ PET negative and positive older adults. RESULTS cMD increases were more sensitive to detecting brain structural alterations than cortical thinning and gray matter atrophy. Tau-related cMD increases partially mediated Aβ-related cognitive decline in AD, whereas vascular disease-related increased cMD levels substantially mediated age-related cognitive decline in SNAP. DISCUSSION These findings revealed the dynamic changes of microstructural and macrostructural indicators and their associations with AD and SNAP, providing novel insights into understanding upstream and downstream events of cMD in neurodegenerative disease. HIGHLIGHTS Cortical mean diffusivity (cMD) was more sensitive to detecting structural changes than macrostructural factors. Tau-related cMD increases partially mediated amyloid beta-related cognitive decline in Alzheimer's disease (AD). White matter hyperintensity-related higher cMD mainly explained the age-related cognitive decline in suspected non-Alzheimer's pathophysiology (SNAP). cMD may assist in tracking earlier neurodegenerative signs in AD and SNAP.
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Affiliation(s)
- Pan Sun
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
- Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China
| | - Zhengbo He
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Jie Yang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Yalin Zhu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Yue Cai
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Ting Ma
- School of Electronic and Information Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, China
| | - Shaohua Ma
- Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
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Xiao XY, Zeng JY, Cao YB, Tang Y, Zou ZY, Li JQ, Chen HJ. Cortical microstructural abnormalities in amyotrophic lateral sclerosis: a gray matter-based spatial statistics study. Quant Imaging Med Surg 2024; 14:5774-5788. [PMID: 39144033 PMCID: PMC11320503 DOI: 10.21037/qims-24-236] [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] [Received: 02/05/2024] [Accepted: 06/17/2024] [Indexed: 08/16/2024]
Abstract
Background Amyotrophic lateral sclerosis (ALS)-related white-matter microstructural abnormalities have received considerable attention; however, gray-matter structural abnormalities have not been fully elucidated. This study aimed to evaluate cortical microstructural abnormalities in ALS and determine their association with disease severity. Methods This study included 34 patients with ALS and 30 healthy controls. Diffusion-weighted data were used to estimate neurite orientation dispersion and density imaging (NODDI) parameters, including neurite density index (NDI) and orientation dispersion index (ODI). We performed gray matter-based spatial statistics (GBSS) in a voxel-wise manner to determine the cortical microstructure difference. We used the revised ALS Functional Rating Scale (ALSFRS-R) to assess disease severity and conducted a correlation analysis between NODDI parameters and ALSFRS-R. Results In patients with ALS, the NDI reduction involved several cortical regions [primarily the precentral gyrus, postcentral gyrus, temporal cortex, prefrontal cortex, occipital cortex, and posterior parietal cortex; family-wise error (FWE)-corrected P<0.05]. ODI decreased in relatively few cortical regions (including the precentral gyrus, postcentral gyrus, prefrontal cortex, and inferior parietal lobule; FWE-corrected P<0.05). The NDI value in the left precentral and postcentral gyrus was positively correlated with the ALS disease severity (FWE-corrected P<0.05). Conclusions The decreases in NDI and ODI involved both motor-related and extra-motor regions and indicated the presence of gray-matter microstructural impairment in ALS. NODDI parameters are potential imaging biomarkers for evaluating disease severity in vivo. Our results showed that GBSS is a feasible method for identifying abnormalities in the cortical microstructure of patients with ALS.
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Affiliation(s)
- Xin-Yun Xiao
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jing-Yi Zeng
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Yun-Bin Cao
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Ying Tang
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Zhang-Yu Zou
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jian-Qi Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China
| | - Hua-Jun Chen
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
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Singh K, Barsoum S, Schilling KG, An Y, Ferrucci L, Benjamini D. Neuronal microstructural changes in the human brain are associated with neurocognitive aging. Aging Cell 2024; 23:e14166. [PMID: 38659245 PMCID: PMC11258428 DOI: 10.1111/acel.14166] [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: 12/18/2023] [Revised: 02/22/2024] [Accepted: 03/19/2024] [Indexed: 04/26/2024] Open
Abstract
Gray matter (GM) alterations play a role in aging-related disorders like Alzheimer's disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 participants (394 female; median age = 58, range = 36-90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.
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Affiliation(s)
- Kavita Singh
- Multiscale Imaging and Integrative Biophysics UnitNational Institute on Aging, NIHBaltimoreMarylandUSA
| | - Stephanie Barsoum
- Multiscale Imaging and Integrative Biophysics UnitNational Institute on Aging, NIHBaltimoreMarylandUSA
| | - Kurt G. Schilling
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Yang An
- Brain Aging and Behavior SectionNational Institute on Aging, NIHBaltimoreMarylandUSA
| | - Luigi Ferrucci
- Translational Gerontology BranchNational Institute on Aging, NIHBaltimoreMarylandUSA
| | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics UnitNational Institute on Aging, NIHBaltimoreMarylandUSA
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Billaud CHA, Yu J. The hippocampus as a structural and functional network epicentre for distant cortical thinning in neurocognitive aging. Neurobiol Aging 2024; 139:82-89. [PMID: 38657394 DOI: 10.1016/j.neurobiolaging.2024.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 04/05/2024] [Accepted: 04/09/2024] [Indexed: 04/26/2024]
Abstract
Alterations in grey matter (GM) and white matter (WM) are associated with memory impairment across the neurocognitive aging spectrum and theorised to spread throughout brain networks. Functional and structural connectivity (FC,SC) may explain widespread atrophy. We tested the effect of SC and FC to the hippocampus on cortical thickness (CT) of connected areas. In 419 (223 F) participants (agemean=73 ± 8) from the Alzheimer's Disease Neuroimaging Initiative, cortical regions associated with memory (Rey Auditory Verbal Learning Test) were identified using Lasso regression. Two structural equation models (SEM), for SC and resting-state FC, were fitted including CT areas, and SC and FC to the left and right hippocampus (LHIP,RHIP). LHIP (β=-0.150,p=<.001) and RHIP (β=-0.139,p=<.001) SC predicted left temporopolar/rhinal CT; RHIP SC predicted right temporopolar/rhinal CT (β=-0.191,p=<.001). LHIP SC predicted right fusiform/parahippocampal (β=-0.104,p=.011) and intraparietal sulcus/superior parietal CT (β=0.101,p=.028). Increased RHIP FC predicted higher left inferior parietal CT (β=0.132,p=.042) while increased LHIP FC predicted lower right fusiform/parahippocampal CT (β=-0.97; p=.023). The hippocampi may be epicentres for cortical thinning through disrupted connectivity.
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Affiliation(s)
- Charly Hugo Alexandre Billaud
- Nanyang Technological University, Psychology, School of Social Sciences, 48 Nanyang Avenue, Singapore City 639798, Singapore.
| | - Junhong Yu
- Nanyang Technological University, Psychology, School of Social Sciences, 48 Nanyang Avenue, Singapore City 639798, Singapore
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Yu X, Przybelski SA, Reid RI, Lesnick TG, Raghavan S, Graff‐Radford J, Lowe VJ, Kantarci K, Knopman DS, Petersen RC, Jack CR, Vemuri P. NODDI in gray matter is a sensitive marker of aging and early AD changes. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12627. [PMID: 39077685 PMCID: PMC11284641 DOI: 10.1002/dad2.12627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 06/17/2024] [Accepted: 07/02/2024] [Indexed: 07/31/2024]
Abstract
INTRODUCTION Age-related and Alzheimer's disease (AD) dementia-related neurodegeneration impact brain health. While morphometric measures from T1-weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker. METHODS We contrasted regional gray matter NODDI and morphometric evaluations concerning their correlation with (1) age, (2) clinical diagnosis stage, and (3) tau pathology as assessed by AV1451 positron emission tomography. RESULTS Our study hypothesizes that NODDI measures are more sensitive to aging and early AD changes than morphometric measures. One NODDI output, free water fraction (FWF), showed higher sensitivity to age-related changes, generally better effect sizes in separating mild cognitively impaired from cognitively unimpaired participants, and stronger associations with regional tau deposition than morphometric measures. DISCUSSION These findings underscore NODDI's utility in capturing early neurodegenerative changes and enhancing our understanding of aging and AD. Highlights Neurite orientation dispersion and density imaging can serve as an effective brain health biomarker for aging and early Alzheimer's disease (AD).Free water fraction has higher sensitivity to normal brain aging.Free water fraction has stronger associations with early AD and regional tau deposition.
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Affiliation(s)
- Xi Yu
- Department of Physiology and Biomedical EngineeringMayo ClinicRochesterMinnesotaUSA
| | - Scott A. Przybelski
- Department of Health Sciences ResearchDivision of Biomedical Statistics and InformaticsMayo Clinic‐RochesterRochesterMinnesotaUSA
| | - Robert I. Reid
- Department of Health Sciences ResearchDivision of Biomedical Statistics and InformaticsMayo Clinic‐RochesterRochesterMinnesotaUSA
- Department of RadiologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | - Timothy G. Lesnick
- Department of Health Sciences ResearchDivision of Biomedical Statistics and InformaticsMayo Clinic‐RochesterRochesterMinnesotaUSA
| | | | | | - Val J. Lowe
- Department of RadiologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | - Kejal Kantarci
- Department of RadiologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | - David S. Knopman
- Department of NeurologyMayo Clinic‐RochesterRochesterMinnesotaUSA
| | | | - Clifford R. Jack
- Department of RadiologyMayo Clinic‐RochesterRochesterMinnesotaUSA
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Yang G, Xie W, Li B, Zhao G, Li J, Xiao W, Li Y. Casual associations between brain structure and sarcopenia: A large-scale genetic correlation and mendelian randomization study. Aging Cell 2024:e14252. [PMID: 38881464 DOI: 10.1111/acel.14252] [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: 02/29/2024] [Revised: 05/15/2024] [Accepted: 05/20/2024] [Indexed: 06/18/2024] Open
Abstract
Sarcopenia presenting a critical challenge in population-aging healthcare. The elucidation of the interplay between brain structure and sarcopenia necessitates further research. The aim of this study is to explore the casual association between brain structure and sarcopenia. Linkage disequilibrium score regression (LDSC) was conducted to estimate the genetic correlations; MR was then performed to explore the causal relationship between Brain imaging-derived phenotypes (BIDPs) and three sarcopenia-related traits: handgrip strength, walking pace, and appendicular lean mass (ALM). The main analyses were conducted using the inverse-variance weighted method. Moreover, weighted median and MR-Egger were conducted as sensitivity analyses. Genetic association between 6.41% of BIDPs and ALM was observed, and 4.68% of BIDPs exhibited causal MR association with handgrip strength, 2.11% of BIDPs were causally associated with walking pace, and 2.04% of BIDPs showed causal association with ALM. Volume of ventromedial hypothalamus was associated with increased odds of handgrip strength (OR: 1.18, 95% CI: 1.02 to 1.37) and ALM (OR: 1.05, 95% CI: 1.01 to 1.09). Mean thickness of G-pariet-inf-Angular was associated with decreased odds of handgrip strength (OR: 0.83, 95% CI: 0.70 to 0.97) and walking pace (OR: 0.97, 95% CI: 0.93 to 0.99). As part of the brain structure forward causally influences sarcopenia, which may provide new perspectives for the prevention of sarcopenia and offer valuable insights for further research on the brain-muscle axis.
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Affiliation(s)
- Guang Yang
- Department of Orthopedics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Wenqing Xie
- Department of Orthopedics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Bin Li
- Bioinformatics Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Guihu Zhao
- Bioinformatics Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jinchen Li
- Bioinformatics Center, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan, China
| | - Wenfeng Xiao
- Department of Orthopedics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yusheng Li
- Department of Orthopedics, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China
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9
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Tang R, Franz CE, Hauger RL, Dale AM, Dorros SM, Eyler LT, Fennema-Notestine C, Hagler DJ, Lyons MJ, Panizzon MS, Puckett OK, Williams ME, Elman JA, Kremen WS. Early Cortical Microstructural Changes in Aging Are Linked to Vulnerability to Alzheimer's Disease Pathology. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00158-7. [PMID: 38878863 DOI: 10.1016/j.bpsc.2024.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 05/09/2024] [Accepted: 05/29/2024] [Indexed: 08/15/2024]
Abstract
BACKGROUND Early identification of Alzheimer's disease (AD) risk is critical for improving treatment success. Cortical thickness is a macrostructural measure used to assess neurodegeneration in AD. However, cortical microstructural changes appear to precede macrostructural atrophy and may improve early risk identification. Currently, whether cortical microstructural changes in aging are linked to vulnerability to AD pathophysiology remains unclear in nonclinical populations, who are precisely the target for early risk identification. METHODS In 194 adults, we calculated magnetic resonance imaging-derived maps of changes in cortical mean diffusivity (microstructure) and cortical thickness (macrostructure) over 5 to 6 years (mean age: time 1 = 61.82 years; time 2 = 67.48 years). Episodic memory was assessed using 3 well-established tests. We obtained positron emission tomography-derived maps of AD pathology deposition (amyloid-β, tau) and neurotransmitter receptors (cholinergic, glutamatergic) implicated in AD pathophysiology. Spatial correlational analyses were used to compare pattern similarity among maps. RESULTS Spatial patterns of cortical macrostructural changes resembled patterns of cortical organization sensitive to age-related processes (r = -0.31, p < .05), whereas microstructural changes resembled the patterns of tau deposition in AD (r = 0.39, p = .038). Individuals with patterns of microstructural changes that more closely resembled stereotypical tau deposition exhibited greater memory decline (β = 0.22, p = .029). Microstructural changes and AD pathology deposition were enriched in areas with greater densities of cholinergic and glutamatergic receptors (ps < .05). CONCLUSIONS Patterns of cortical microstructural changes were more AD-like than patterns of macrostructural changes, which appeared to reflect more general aging processes. Microstructural changes may better inform early risk prediction efforts as a sensitive measure of vulnerability to pathological processes prior to overt atrophy and cognitive decline.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California.
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California; Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California; Department of Neurosciences, University of California San Diego, La Jolla, California
| | - Stephen M Dorros
- Department of Radiology, University of California San Diego, La Jolla, California
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California; Desert Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, California; Department of Radiology, University of California San Diego, La Jolla, California
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, California
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - McKenna E Williams
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, California
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
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Brown C, Das S, Xie L, Nasrallah I, Detre J, Chen‐Plotkin A, Shaw L, McMillan C, Yushkevich P, Wolk D. Medial temporal lobe gray matter microstructure in preclinical Alzheimer's disease. Alzheimers Dement 2024; 20:4147-4158. [PMID: 38747539 PMCID: PMC11180947 DOI: 10.1002/alz.13832] [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: 11/21/2023] [Revised: 02/21/2024] [Accepted: 03/18/2024] [Indexed: 05/28/2024]
Abstract
INTRODUCTION Typical MRI measures of neurodegeneration have limited sensitivity in early disease stages. Diffusion MRI (dMRI) microstructural measures may allow for detection in preclinical stages. METHODS Participants had dMRI and either beta-amyloid PET or plasma biomarkers of Alzheimer's pathology within 18 months of MRI. Microstructure was measured in portions of the medial temporal lobe (MTL) with high neurofibrillary tangle (NFT) burden based on a previously developed post mortem 3D-map. Regressions examined relationships between microstructure and markers of Alzheimer's pathology in preclinical disease and then across disease stages. RESULTS There was higher isometric volume fraction in amyloid-positive compared to amyloid-negative cognitively unimpaired individuals in high tangle MTL regions. Similarly, plasma biomarkers and 18F-flortaucipir were associated with microstructural changes in preclinical disease. Additional microstructural effects were seen across disease stages. DISCUSSION Combining a post mortem atlas of NFT pathology with microstructural measures allows for detection of neurodegeneration in preclinical Alzheimer's disease. Highlights Typical markers of neurodegeneration are not sensitive in preclinical Alzheimer's. dMRI measured microstructure in regions with high NFT. Microstructural changes occur in medial temporal regions in preclinical disease. Microstructural changes occur in other typical Alzheimer's regions in later stages. Combining post mortem pathology atlases with in vivo MRI is a powerful framework.
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Affiliation(s)
- Christopher Brown
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sandhitsu Das
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Long Xie
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Siemens HealthineersDigital Technology and InnovationPrincetonNew JerseyUSA
| | - Ilya Nasrallah
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - John Detre
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Alice Chen‐Plotkin
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Leslie Shaw
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Corey McMillan
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Paul Yushkevich
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David Wolk
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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11
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Han L, Yang J, Yuan C, Zhang W, Huang Y, Zeng L, Zhong J. Assessing brain microstructural changes in chronic kidney disease: a diffusion imaging study using multiple models. Front Neurol 2024; 15:1387021. [PMID: 38751882 PMCID: PMC11094287 DOI: 10.3389/fneur.2024.1387021] [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: 02/19/2024] [Accepted: 04/22/2024] [Indexed: 05/18/2024] Open
Abstract
Objectives To explore the effectiveness of diffusion quantitative parameters derived from advanced diffusion models in detecting brain microstructural changes in patients with chronic kidney disease (CKD). Methods The study comprised 44 CKD patients (eGFR<59 mL/min/1.73 m2) and 35 age-and sex-matched healthy controls. All patients underwent diffusion spectrum imaging (DSI) and conventional magnetic resonance imaging. Reconstructed to obtain diffusion MRI models, including diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI) and Mean Apparent Propagator (MAP)-MRI, were processed to obtain multi-parameter maps. The Tract-Based Spatial Statistics (TBSS) analysis was utilized for detecting microstructural differences and Pearson correlation analysis assessed the relationship between renal metabolism markers and diffusion parameters in the brain regions of CKD patients. Receiver operating characteristic (ROC) curve analysis assessed the diagnostic performance of diffusion models, with AUC comparisons made using DeLong's method. Results Significant differences were noted in DTI, NODDI, and MAP-MRI parameters between CKD patients and controls (p < 0.05). DTI indicated a decrease in Fractional Anisotropy(FA) and an increase in Mean and Radial Diffusivity (MD and RD) in CKD patients. NODDI indicated decreased Intracellular and increased Extracellular Volume Fractions (ICVF and ECVF). MAP-MRI identified extensive microstructural changes, with elevated Mean Squared Displacement (MSD) and Q-space Inverse Variance (QIV) values, and reduced Non-Gaussianity (NG), Axial Non-Gaussianity (NGAx), Radial Non-Gaussianity (NGRad), Return-to-Origin Probability (RTOP), Return-to-Axis Probability (RTAP), and Return-to-Plane Probability (RTPP). There was a moderate correlation between serum uric acid (SUA) and diffusion parameters in six brain regions (p < 0.05). ROC analysis showed the AUC values of DTI_FA ranged from 0.70 to 0.793. MAP_NGAx in the Retrolenticular part of the internal capsule R reported a high AUC value of 0.843 (p < 0.05), which was not significantly different from other diffusion parameters (p > 0.05). Conclusion The advanced diffusion models (DTI, NODDI, and MAP-MRI) are promising for detecting brain microstructural changes in CKD patients, offering significant insights into CKD-affected brain areas.
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Affiliation(s)
- Limei Han
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan Province, China
- Department of Radiology, Zigong First People's Hospital, Zigong, Sichuan Province, China
| | - Jie Yang
- Department of Radiology, Zigong First People's Hospital, Zigong, Sichuan Province, China
| | - Chao Yuan
- Department of Radiology, Zigong First People's Hospital, Zigong, Sichuan Province, China
| | - Wei Zhang
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan Province, China
- Department of Radiology, Zigong First People's Hospital, Zigong, Sichuan Province, China
| | - Yantao Huang
- Department of Radiology, Zigong First People's Hospital, Zigong, Sichuan Province, China
| | - Lingli Zeng
- Department of Radiology, Zigong First People's Hospital, Zigong, Sichuan Province, China
| | - Jianquan Zhong
- Department of Radiology, Zigong First People's Hospital, Zigong, Sichuan Province, China
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12
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Mak E, Dounavi ME, Operto G, Ziukelis ET, Jones PS, Low A, Swann P, Newton C, Muniz Terrera G, Malhotra P, Koychev I, Falcon C, Mackay C, Lawlor B, Naci L, Wells K, Ritchie C, Ritchie K, Su L, Gispert JD, O’Brien JT. APOE ɛ4 exacerbates age-dependent deficits in cortical microstructure. Brain Commun 2024; 6:fcad351. [PMID: 38384997 PMCID: PMC10881196 DOI: 10.1093/braincomms/fcad351] [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: 05/30/2023] [Revised: 10/20/2023] [Accepted: 02/09/2024] [Indexed: 02/23/2024] Open
Abstract
The apolipoprotein E ɛ4 allele is the primary genetic risk factor for the sporadic type of Alzheimer's disease. However, the mechanisms by which apolipoprotein E ɛ4 are associated with neurodegeneration are still poorly understood. We applied the Neurite Orientation Dispersion Model to characterize the effects of apolipoprotein ɛ4 and its interactions with age and education on cortical microstructure in cognitively normal individuals. Data from 1954 participants were included from the PREVENT-Dementia and ALFA (ALzheimer and FAmilies) studies (mean age = 57, 1197 non-carriers and 757 apolipoprotein E ɛ4 carriers). Structural MRI datasets were processed with FreeSurfer v7.2. The Microstructure Diffusion Toolbox was used to derive Orientation Dispersion Index maps from diffusion MRI datasets. Primary analyses were focused on (i) the main effects of apolipoprotein E ɛ4, and (ii) the interactions of apolipoprotein E ɛ4 with age and education on lobar and vertex-wise Orientation Dispersion Index and implemented using Permutation Analysis of Linear Models. There were apolipoprotein E ɛ4 × age interactions in the temporo-parietal and frontal lobes, indicating steeper age-dependent Orientation Dispersion Index changes in apolipoprotein E ɛ4 carriers. Steeper age-related Orientation Dispersion Index declines were observed among apolipoprotein E ɛ4 carriers with lower years of education. We demonstrated that apolipoprotein E ɛ4 worsened age-related Orientation Dispersion Index decreases in brain regions typically associated with atrophy patterns of Alzheimer's disease. This finding also suggests that apolipoprotein E ɛ4 may hasten the onset age of dementia by accelerating age-dependent reductions in cortical Orientation Dispersion Index.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Grégory Operto
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
| | - Elina T Ziukelis
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Simon Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Swann
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Coco Newton
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Paresh Malhotra
- Department of Brain Sciences, Imperial College, London W12 0NN, UK
| | - Ivan Koychev
- Department of Psychiatry, Oxford University, Oxford OX3 7JX, UK
| | - Carles Falcon
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid 28029, Spain
| | - Clare Mackay
- Department of Psychiatry, Oxford University, Oxford OX3 7JX, UK
| | - Brian Lawlor
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin D02 PX31, Ireland
| | - Lorina Naci
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin D02 PX31, Ireland
| | - Katie Wells
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Craig Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Karen Ritchie
- Institut National de la Santé et de la Recherche Médicale, U1061 Neuropsychiatrie, Montpellier 34093, France
- Faculty of Medicine, University of Montpellier, Montpellier 34093, France
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid 28029, Spain
| | - John T O’Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
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13
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Spotorno N, Najac C, Strandberg O, Stomrud E, van Westen D, Nilsson M, Ronen I, Hansson O. Diffusion weighted magnetic resonance spectroscopy revealed neuronal specific microstructural alterations in Alzheimer's disease. Brain Commun 2024; 6:fcae026. [PMID: 38370447 PMCID: PMC10873577 DOI: 10.1093/braincomms/fcae026] [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: 05/31/2023] [Revised: 12/19/2023] [Accepted: 01/31/2024] [Indexed: 02/20/2024] Open
Abstract
In Alzheimer's disease, reconfiguration and deterioration of tissue microstructure occur before substantial degeneration become evident. We explored the diffusion properties of both water, a ubiquitous marker measured by diffusion MRI, and N-acetyl-aspartate, a neuronal metabolite probed by diffusion-weighted magnetic resonance spectroscopy, for investigating cortical microstructural changes downstream of Alzheimer's disease pathology. To this aim, 50 participants from the Swedish BioFINDER-2 study were scanned on both 7 and 3 T MRI systems. We found that in cognitively impaired participants with evidence of both abnormal amyloid-beta (CSF amyloid-beta42/40) and tau accumulation (tau-PET), the N-acetyl-aspartate diffusion rate was significantly lower than in cognitively unimpaired participants (P < 0.05). This supports the hypothesis that intraneuronal tau accumulation hinders diffusion in the neuronal cytosol. Conversely, water diffusivity was higher in cognitively impaired participants (P < 0.001) and was positively associated with the concentration of myo-inositol, a preferentially astrocytic metabolite (P < 0.001), suggesting that water diffusion is sensitive to alterations in the extracellular space and in glia. In conclusion, measuring the diffusion properties of both water and N-acetyl-aspartate provides rich information on the cortical microstructure in Alzheimer's disease, and can be used to develop new sensitive and specific markers to microstructural changes occurring during the disease course.
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Affiliation(s)
- Nicola Spotorno
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Lund 22184, Sweden
| | - Chloé Najac
- Department of Radiology, C.J. Gorter MRI Center, Leiden University Medical Center, Leiden 2333, The Netherlands
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Lund 22184, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Lund 22184, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 20502, Sweden
| | - Danielle van Westen
- Image and Function, Skane University Hospital, Lund 22185, Sweden
- Diagnostic Radiology, Institution for Clinical Sciences, Lund University, Lund 22185, Sweden
| | - Markus Nilsson
- Diagnostic Radiology, Institution for Clinical Sciences, Lund University, Lund 22185, Sweden
| | - Itamar Ronen
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Falmer BN1 9RR, UK
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Lund 22184, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 20502, Sweden
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Nir TM, Villalón-Reina JE, Salminen LE, Haddad E, Zheng H, Thomopoulos SI, Jack CR, Weiner MW, Thompson PM, Jahanshad N. Cortical microstructural associations with CSF amyloid and pTau. Mol Psychiatry 2024; 29:257-268. [PMID: 38092890 PMCID: PMC11116103 DOI: 10.1038/s41380-023-02321-7] [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: 02/13/2023] [Revised: 10/25/2023] [Accepted: 11/07/2023] [Indexed: 12/26/2023]
Abstract
Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8 ± 6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures, but not cortical thickness measures, were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+ from pTau- participants. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI metrics sensitive to early AD pathogenesis and microstructural damage may be better measures of subtle neurodegeneration in comparison to standard cortical thickness and help to elucidate mechanisms underlying cognitive decline.
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Affiliation(s)
- Talia M Nir
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
| | - Julio E Villalón-Reina
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Elizabeth Haddad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Hong Zheng
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Michael W Weiner
- Department of Radiology, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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15
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Singh K, Barsoum S, Schilling KG, An Y, Ferrucci L, Benjamini D. Neuronal microstructural changes in the human brain are associated with neurocognitive aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575206. [PMID: 38260525 PMCID: PMC10802615 DOI: 10.1101/2024.01.11.575206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Gray matter (GM) alterations play a role in aging-related disorders like Alzheimer's disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 unimpaired participants (394 female; median age = 58, range = 36-90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.
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Affiliation(s)
- Kavita Singh
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Stephanie Barsoum
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yang An
- Brain Aging and Behavior Section, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, USA
| | - Dan Benjamini
- Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, USA
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16
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Anderson JA, Rashidi-Ranjbar N, Nazeri A, Chad JA, Zhukovsky P, Mulsant BH, Herrmann N, Mah L, Flint AJ, Fischer CE, Pollock BG, Rajji TK, Voineskos AN. Age-Related Alterations in Gray Matter Microstructure in Older People With Remitted Major Depression at Risk for Dementia. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:374-384. [PMID: 38298786 PMCID: PMC10829634 DOI: 10.1016/j.bpsgos.2023.08.018] [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] [Received: 04/28/2023] [Revised: 08/15/2023] [Accepted: 08/27/2023] [Indexed: 02/02/2024] Open
Abstract
Background Major depressive disorder (MDD) in late life is a risk factor for mild cognitive impairment (MCI) and Alzheimer's disease. However, studies of gray matter changes have produced varied estimates of which structures are implicated in MDD and dementia. Changes in gray matter volume and cortical thickness are macrostructural measures for the microstructural processes of free water accumulation and dendritic spine loss. Methods We conducted multishell diffusion imaging to assess gray matter microstructure in 244 older adults with remitted MDD (n = 44), MCI (n = 115), remitted MDD+MCI (n = 61), or without psychiatric disorders or cognitive impairment (healthy control participants; n = 24). We estimated measures related to neurite density, orientation dispersion, and free water (isotropic volume fraction) using a biophysically plausible model (neurite orientation dispersion and density imaging). Results Results showed that increasing age was correlated with an increase in isotropic volume fraction and a decrease in orientation dispersion index, which is consistent with neuropathology dendritic loss. In addition, this relationship between age and increased isotropic volume fraction was more disrupted in the MCI group than in the remitted MDD or healthy control groups. However, the association between age and orientation dispersion index was similar for all 3 groups. Conclusions The findings suggest that the neurite orientation dispersion and density imaging measures could be used to identify biological risk factors for Alzheimer's disease, signifying both conventional neurodegeneration observed with MCI and dendritic loss seen in MDD.
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Affiliation(s)
- John A.E. Anderson
- Department of Cognitive Science, Carleton University, Ottawa, Ontario, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Neda Rashidi-Ranjbar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
| | - Arash Nazeri
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri (AN)
| | - Jordan A. Chad
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Peter Zhukovsky
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Benoit H. Mulsant
- 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
| | - Nathan Herrmann
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Linda Mah
- Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Alastair J. Flint
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Centre for Mental Health, University Health Network, Toronto, Ontario, Canada
| | - Corinne E. Fischer
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Bruce G. Pollock
- 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
| | - Tarek K. Rajji
- 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
- Toronto Dementia Research Alliance, University of Toronto, Toronto, Ontario, Canada
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - PACt-MD Study Group
- Department of Cognitive Science, Carleton University, Ottawa, Ontario, Canada
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri (AN)
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Centre for Mental Health, University Health Network, Toronto, Ontario, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, Ontario, Canada
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Mirmosayyeb O, Ghaffary EM, Dehghan MS, Ghoshouni H, Bagherieh S, Barzegar M, Shaygannejad V. Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease and COVID-19: A Systematic Review. J Cent Nerv Syst Dis 2023; 15:11795735231167869. [PMID: 37008248 PMCID: PMC10063869 DOI: 10.1177/11795735231167869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 03/15/2023] [Indexed: 03/30/2023] Open
Abstract
Background Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is an uncommon neurological disease affecting the central nervous system (CNS). Numerous neurological disorders, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), acute transverse myelitis (ATM), and MOGAD, have been reported following the COVID-19 infection during the current COVID-19 pandemic. On the other hand, it has been suggested that patients with MOGAD may be at greater risk for infection (particularly in the current pandemic). Objective In this systematic review, we gathered separately 1) MOGAD cases following COVID-19 infection as well as 2) clinical course of patients with MOGAD infected with COVID-19 based on case reports/series. Methods 329 articles were collected from 4 databases. These articles were conducted from inception to March 1st, 2022. Results Following the screening, exclusion criteria were followed and eventually, 22 studies were included. In 18 studies, a mean ± SD time interval of 18.6 ± 14.9 days was observed between infection with COVID-19 and the onset of MOGAD symptoms. Symptoms were partially or completely recovered in a mean of 67 days of follow-up. Among 4 studies on MOGAD patients, the hospitalization rate was 25%, and 15% of patients were hospitalized in the intensive care unit (ICU). Conclusion Our systematic review demonstrated that following COVID-19 infection, there is a rare possibility of contracting MOGAD. Moreover, there is no clear consensus on the susceptibility of MOGAD patients to severe COVID-19. However, obtaining deterministic results requires studies with a larger sample size.
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Affiliation(s)
- Omid Mirmosayyeb
- Department of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Elham Moases Ghaffary
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammad S. Dehghan
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Hamed Ghoshouni
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Sara Bagherieh
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mahdi Barzegar
- Department of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Vahid Shaygannejad
- Department of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
- Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
- Vahid Shaygannejad, Isfahan Neurosciences Research Center, Isfahan University of Medical Sciences, Kashani Street, Kashani Hospital, Isfahan 81746 73461, Iran.
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18
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Zhong S, Lou J, Ma K, Shu Z, Chen L, Li C, Ye Q, Zhou L, Shen Y, Ye X, Zhang J. Disentangling in-vivo microstructural changes of white and gray matter in mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis. Brain Imaging Behav 2023; 17:764-777. [PMID: 37752311 DOI: 10.1007/s11682-023-00805-2] [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] [Accepted: 09/14/2023] [Indexed: 09/28/2023]
Abstract
The microstructural characteristics of white and gray matter in mild cognitive impairment (MCI) and the early-stage of Alzheimer's disease (AD) remain unclear. This study aimed to systematically identify the microstructural damages of MCI/AD in studies using neurite orientation dispersion and density imaging (NODDI), and explore their correlations with cognitive performance. Multiple databases were searched for eligible studies. The 10 eligible NODDI studies were finally included. Patients with MCI/AD showed overall significant reductions in neurite density index (NDI) of specific white matter structures in bilateral hemispheres (left hemisphere: -0.40 [-0.53, -0.27], P < 0.001; right: -0.33 [-0.47, -0.19], P < 0.001), involving the bilateral superior longitudinal fasciculus (SLF), uncinate fasciculus (UF), the left posterior thalamic radiation (PTR), and the left cingulum. White matter regions exhibited significant increased orientation dispersion index (ODI) (left: 0.25 [0.02, 0.48], P < 0.05; right: 0.27 [0.07, 0.46], P < 0.05), including the left cingulum, the right UF, and the bilateral parahippocampal cingulum (PHC), and PTR. Additionally, the ODI of gray matter showed significant reduction in bilateral hippocampi (left: -0.97 [-1.42, -0.51], P < 0.001; right: -0.90 [-1.35, -0.45], P < 0.001). The cognitive performance in MCI/AD was significantly associated with NDI (r = 0.50, P < 0.001). Our findings highlight the microstructural changes in MCI/AD were characterized by decreased fiber orientation dispersion in the hippocampus, and decreased neurite density and increased fiber orientation dispersion in specific white matter tracts, including the cingulum, UF, and PTR. Moreover, the decreased NDI may indicate the declined cognitive level of MCI/AD patients.
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Affiliation(s)
- Shuchang Zhong
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jingjing Lou
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Ke Ma
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Zhenyu Shu
- Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Lin Chen
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Chao Li
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Qing Ye
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Liang Zhou
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Ye Shen
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xiangming Ye
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jie Zhang
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
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19
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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: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 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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20
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Lin S, Zhang H, Qi M, Cooper DN, Yang Y, Yang Y, Zhao H. Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization. Neuroimage 2023; 279:120325. [PMID: 37579999 DOI: 10.1016/j.neuroimage.2023.120325] [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: 04/13/2023] [Revised: 07/09/2023] [Accepted: 08/11/2023] [Indexed: 08/16/2023] Open
Abstract
Observational studies consistently disclose brain imaging-derived phenotypes (IDPs) as critical markers for early diagnosis of both brain disorders and cardiovascular diseases. However, it remains unclear about the shared genetic landscape between brain IDPs and the risk of brain disorders and cardiovascular diseases, restricting the applications of potential diagnostic techniques through brain IDPs. Here, we reported genetic correlations and putative causal relationships between 921 brain IDPs, 20 brain disorders and six cardiovascular diseases by leveraging their large-scale genome-wide association study (GWAS) summary statistics. Applications of Mendelian randomization (MR) identified significant putative causal effects of multiple region-specific brain IDPs in relation to the increased risks for amyotrophic lateral sclerosis (ALS), major depressive disorder (MDD), autism spectrum disorder (ASD) and schizophrenia (SCZ). We also found brain IDPs specifically from temporal lobe as a putatively causal consequence of hypertension. The genome-wide colocalization analysis identified three genomic regions in which MDD, ASD and SCZ colocalized with the brain IDPs, and two novel SNPs to be associated with ASD, SCZ, and multiple brain IDPs. Furthermore, we identified a list of candidate genes involved in the shared genetics underlying pairs of brain IDPs and MDD, ASD, SCZ, ALS and hypertension. Our results provide novel insights into the genetic relationships between brain disorders and cardiovascular diseases and brain IDP, which may server as clues for using brain IDPs to predict risks of diseases.
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Affiliation(s)
- Siying Lin
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China; School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China
| | - Haoyang Zhang
- School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China
| | - Mengling Qi
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, United Kingdom
| | - Yuedong Yang
- School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China.
| | - Yuanhao Yang
- Mater Research Institute, The University of Queensland, Brisbane, QLD, Australia.
| | - Huiying Zhao
- Department of Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, China.
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21
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Chouliaras L, O'Brien JT. The use of neuroimaging techniques in the early and differential diagnosis of dementia. Mol Psychiatry 2023; 28:4084-4097. [PMID: 37608222 PMCID: PMC10827668 DOI: 10.1038/s41380-023-02215-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 07/27/2023] [Accepted: 08/03/2023] [Indexed: 08/24/2023]
Abstract
Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.
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Affiliation(s)
- Leonidas Chouliaras
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Specialist Dementia and Frailty Service, Essex Partnership University NHS Foundation Trust, St Margaret's Hospital, Epping, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK.
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
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22
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Thaker AA, McConnell BV, Rogers DM, Carlson NE, Coughlan C, Jensen AM, Lopez-Paniagua D, Holden SK, Pressman PS, Pelak VS, Filley CM, Potter H, Solano DA, Heffernan KS, Bettcher BM. Astrogliosis, neuritic microstructure, and sex effects: GFAP is an indicator of neuritic orientation in women. Brain Behav Immun 2023; 113:124-135. [PMID: 37394144 PMCID: PMC10584366 DOI: 10.1016/j.bbi.2023.06.026] [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: 12/08/2022] [Revised: 06/14/2023] [Accepted: 06/27/2023] [Indexed: 07/04/2023] Open
Abstract
BACKGROUND Data from human studies suggest that immune dysregulation is associated with Alzheimer's disease (AD) pathology and cognitive decline and that neurites may be affected early in the disease trajectory. Data from animal studies further indicate that dysfunction in astrocytes and inflammation may have a pivotal role in facilitating dendritic damage, which has been linked with negative cognitive outcomes. To elucidate these relationships further, we have examined the relationship between astrocyte and immune dysregulation, AD-related pathology, and neuritic microstructure in AD-vulnerable regions in late life. METHODS We evaluated panels of immune, vascular, and AD-related protein markers in blood and conducted in vivo multi-shell neuroimaging using Neurite Orientation Dispersion and Density Imaging (NODDI) to assess indices of neuritic density (NDI) and dispersion (ODI) in brain regions vulnerable to AD in a cohort of older adults (n = 109). RESULTS When examining all markers in tandem, higher plasma GFAP levels were strongly related to lower neurite dispersion (ODI) in grey matter. No biomarker associations were found with higher neuritic density. Associations between GFAP and neuritic microstructure were not significantly impacted by symptom status, APOE status, or plasma Aβ42/40 ratio; however, there was a large sex effect observed for neurite dispersion, wherein negative associations between GFAP and ODI were only observed in females. DISCUSSION This study provides a comprehensive, concurrent appraisal of immune, vascular, and AD-related biomarkers in the context of advanced grey matter neurite orientation and dispersion methodology. Sex may be an important modifier of the complex associations between astrogliosis, immune dysregulation, and brain microstructure in older adults.
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Affiliation(s)
- Ashesh A Thaker
- Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Brice V McConnell
- Department of Neurology, Behavioral Neurology Section, University of Colorado Alzheimer's & Cognition Center, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Dustin M Rogers
- Department of Biostatistics and Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Nichole E Carlson
- Department of Biostatistics and Informatics, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Christina Coughlan
- Department of Neurology, University of Colorado Alzheimer's & Cognition Center, Linda Crnic Institute for Down Syndrome, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Alexandria M Jensen
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Dan Lopez-Paniagua
- Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Samantha K Holden
- Department of Neurology, Behavioral Neurology Section, University of Colorado Alzheimer's & Cognition Center, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Peter S Pressman
- Department of Neurology, Behavioral Neurology Section, University of Colorado Alzheimer's & Cognition Center, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | - Victoria S Pelak
- Department of Neurology, Behavioral Neurology Section, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA; Department of Ophthalmology, Sue Anschutz-Rodgers University of Colorado Eye Center, University of Colorado School of Medicine, Aurora, CO, USA
| | - Christopher M Filley
- Behavioral Neurology Section, Departments of Neurology and Psychiatry, University of Colorado Alzheimer's & Cognition Center, Marcus Institute for Brain Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Huntington Potter
- Department of Neurology, University of Colorado Alzheimer's & Cognition Center, Linda Crnic Institute for Down Syndrome, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - D Adriana Solano
- Department of Neurology, University of Colorado Alzheimer's & Cognition Center, Linda Crnic Institute for Down Syndrome, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kate S Heffernan
- Division of Neuropharmacology and Neurological Disorders, Emory National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Brianne M Bettcher
- Department of Neurology, Behavioral Neurology Section, University of Colorado Alzheimer's & Cognition Center, University of Colorado, Anschutz Medical Campus, Aurora, CO, USA.
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23
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Williams ME, Gillespie NA, Bell TR, Dale AM, Elman JA, Eyler LT, Fennema-Notestine C, Franz CE, Hagler DJ, Lyons MJ, McEvoy LK, Neale MC, Panizzon MS, Reynolds CA, Sanderson-Cimino M, Kremen WS. Genetic and Environmental Influences on Structural and Diffusion-Based Alzheimer's Disease Neuroimaging Signatures Across Midlife and Early Old Age. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:918-927. [PMID: 35738479 PMCID: PMC9827615 DOI: 10.1016/j.bpsc.2022.06.007] [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: 03/28/2022] [Revised: 05/04/2022] [Accepted: 06/07/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Composite scores of magnetic resonance imaging-derived metrics in brain regions associated with Alzheimer's disease (AD), commonly termed AD signatures, have been developed to distinguish early AD-related atrophy from normal age-associated changes. Diffusion-based gray matter signatures may be more sensitive to early AD-related changes compared with thickness/volume-based signatures, demonstrating their potential clinical utility. The timing of early (i.e., midlife) changes in AD signatures from different modalities and whether diffusion- and thickness/volume-based signatures each capture unique AD-related phenotypic or genetic information remains unknown. METHODS Our validated thickness/volume signature, our novel mean diffusivity (MD) signature, and a magnetic resonance imaging-derived measure of brain age were used in biometrical analyses to examine genetic and environmental influences on the measures as well as phenotypic and genetic relationships between measures over 12 years. Participants were 736 men from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) (baseline/wave 1: mean age [years] = 56.1, SD = 2.6, range = 51.1-60.2). Subsequent waves occurred at approximately 5.7-year intervals. RESULTS MD and thickness/volume signatures were highly heritable (56%-72%). Baseline MD signatures predicted thickness/volume signatures over a decade later, but baseline thickness/volume signatures showed a significantly weaker relationship with future MD signatures. AD signatures and brain age were correlated, but each measure captured unique phenotypic and genetic variance. CONCLUSIONS Cortical MD and thickness/volume AD signatures are heritable, and each signature captures unique variance that is also not explained by brain age. Moreover, results are in line with changes in MD emerging before changes in cortical thickness, underscoring the utility of MD as a very early predictor of AD risk.
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Affiliation(s)
- McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, California.
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Tyler R Bell
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
| | - Anders M Dale
- Department of Radiology, University of California San Diego, San Diego, California; Department of Neuroscience, University of California San Diego, San Diego, California
| | - Jeremy A Elman
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
| | - Lisa T Eyler
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, California; Department of Radiology, University of California San Diego, San Diego, California
| | - Carol E Franz
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, California
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, San Diego, California
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Matthew S Panizzon
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, California
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, California
| | - William S Kremen
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
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24
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Tatsuo S, Watanabe K, Ide S, Tsushima F, Tatsuo S, Matsuzaka M, Murakami H, Ishida M, Iwane T, Daimon M, Yodono H, Nakaji S, Kakeda S. Association of prediabetes with reduced brain volume in a general elderly Japanese population. Eur Radiol 2023; 33:5378-5384. [PMID: 36892647 DOI: 10.1007/s00330-023-09509-z] [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: 06/14/2022] [Revised: 12/30/2022] [Accepted: 02/05/2023] [Indexed: 03/10/2023]
Abstract
OBJECTIVES Diabetes frequently results in cognitive impairment, but it is less clear if brain health is adversely affected during the prediabetic stage. Our aim is to identify possible changes in brain volume as measured by magnetic resonance imaging (MRI) in a large elderly population stratified according to level of "dysglycemia." METHODS This is a cross-sectional study of 2144 participants (median age 69 years, 60.9% female) who underwent 3-T brain MRI. Participants were divided into 4 dysglycemia groups based on HbA1c levels (%): normal glucose metabolism (NGM) (< 5.7%), prediabetes (5.7 to < 6.5%), undiagnosed diabetes (6.5% or higher), and known diabetes (defined by self-report). RESULTS Of the 2144 participants, 982 had NGM, 845 prediabetes, 61 undiagnosed diabetes, and 256 known diabetes. After adjustment for age, sex, education, body weight, cognitive status, smoking, drinking, and disease history, total gray matter volume was significantly lower among participants with prediabetes (0.41% lower, standardized β = - 0.0021 [95% CI - 0.0039, - 0.00039], p = 0.016), undiagnosed diabetes (1.4% lower, standardized β = - 0.0069 [95% CI - 0.012, - 0.002], p = 0.005), and known diabetes (1.1% lower, standardized β = - 0.0055 [95% CI - 0.0081, - 0.0029], p < 0.001) compared to the NGM group. After adjustment, total white matter volume and hippocampal volume did not differ significantly between the NGM group and either the prediabetes group or the diabetes group. CONCLUSION Sustained hyperglycemia may have deleterious effects on gray matter integrity even prior to the onset of clinical diabetes. KEY POINTS • Sustained hyperglycemia has deleterious effects on gray matter integrity even prior to the onset of clinical diabetes.
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Affiliation(s)
- Soichiro Tatsuo
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Keita Watanabe
- Open Innovation Institute, Kyoto University, Kyoto, Japan
| | - Satoru Ide
- Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Japan.
| | - Fumiyasu Tsushima
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Sayuri Tatsuo
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Masashi Matsuzaka
- Department of Medical Informatics and Clinical Research Support Center, Hirosaki University Hospital, Hirosaki, Japan
| | - Hiroshi Murakami
- Department of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Mizuri Ishida
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Takuro Iwane
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Makoto Daimon
- Department of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Hiraku Yodono
- Department of Radiology, Narumi Hospital, Hirosaki, Japan
| | - Shigeyuki Nakaji
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Shingo Kakeda
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
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Lee EY. Memory Deficits in Parkinson's Disease Are Associated with Impaired Attentional Filtering and Memory Consolidation Processes. J Clin Med 2023; 12:4594. [PMID: 37510708 PMCID: PMC10380592 DOI: 10.3390/jcm12144594] [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: 04/17/2023] [Revised: 07/07/2023] [Accepted: 07/08/2023] [Indexed: 07/30/2023] Open
Abstract
The present study examined mechanisms underlying memory deficits in Parkinson's disease (PD) and their associations with brain structural metrics. Nineteen PD patients and twenty-two matched controls underwent two memory experiments. In Experiment 1 (delayed memory task), subjects were asked to remember an array of colored rectangles with varying memory set sizes (Low-Load (2 items), Low-Load (relevant 2 items) with Distractor (irrelevant 3 items), and High-Load (5 items)). After a 7 s delay period, they reported whether the orientation of any relevant figures had changed (test period). In Experiment 2 (working memory task), memory arrays were presented in varying set sizes (2 to 6 items) without distractors, followed by a 2 s delay period and a subsequent test period. Brain MRI data were acquired to assess structural differences (volumes and cortical thickness) in areas related to attention, working memory storage capacity, and episodic memory. Multivariate analyses of covariance revealed that, compared with controls, PD patients had lower memory capacity scores in all memory load conditions for Experiment 1 (p < 0.021), whereas there were no group differences in any memory load conditions for Experiment 2 (p > 0.06). In addition, PD patients had lower cortical thickness in the left superior temporal gyrus (p = 0.02), a region related to the ventral attentional system. Moreover, regression analyses revealed that lower cortical thickness values in the left superior temporal gyrus significantly predicted lower memory scores of Low-Load and Low-Load with Distractor conditions in Experiment 1 (p < 0.044) and lower scores of memory load conditions of 4 and 5 items in Experiment 2 (p < 0.012). These findings suggest that memory deficits in PD may partly be due to impaired attentional filtering and memory consolidation processes that may be related to superior temporal neurodegeneration. Future studies are warranted to confirm the current findings to guide the development of effective treatments for memory deficits in PD.
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Affiliation(s)
- Eun-Young Lee
- Department of Health Care and Science, Dong-A University, Busan 49315, Republic of Korea
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26
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Schilling KG, Archer D, Rheault F, Lyu I, Huo Y, Cai LY, Bunge SA, Weiner KS, Gore JC, Anderson AW, Landman BA. Superficial white matter across development, young adulthood, and aging: volume, thickness, and relationship with cortical features. Brain Struct Funct 2023; 228:1019-1031. [PMID: 37074446 PMCID: PMC10320929 DOI: 10.1007/s00429-023-02642-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 04/08/2023] [Indexed: 04/20/2023]
Abstract
Superficial white matter (SWM) represents a significantly understudied part of the human brain, despite comprising a large portion of brain volume and making up a majority of cortico-cortical white matter connections. Using multiple, high-quality datasets with large sample sizes (N = 2421, age range 5-100) in combination with methodological advances in tractography, we quantified features of SWM volume and thickness across the brain and across development, young adulthood, and aging. We had four primary aims: (1) characterize SWM thickness across brain regions (2) describe associations between SWM volume and age (3) describe associations between SWM thickness and age, and (4) quantify relationships between SWM thickness and cortical features. Our main findings are that (1) SWM thickness varies across the brain, with patterns robust across individuals and across the population at the region-level and vertex-level; (2) SWM volume shows unique volumetric trajectories with age that are distinct from gray matter and other white matter trajectories; (3) SWM thickness shows nonlinear cross-sectional changes across the lifespan that vary across regions; and (4) SWM thickness is associated with features of cortical thickness and curvature. For the first time, we show that SWM volume follows a similar trend as overall white matter volume, peaking at a similar time in adolescence, leveling off throughout adulthood, and decreasing with age thereafter. Notably, the relative fraction of total brain volume of SWM continuously increases with age, and consequently takes up a larger proportion of total white matter volume, unlike the other tissue types that decrease with respect to total brain volume. This study represents the first characterization of SWM features across the large portion of the lifespan and provides the background for characterizing normal aging and insight into the mechanisms associated with SWM development and decline.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA.
| | - Derek Archer
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Francois Rheault
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Ilwoo Lyu
- Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Yuankai Huo
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Silvia A Bunge
- Department of Psychology, University of California at Berkeley, Berkeley, USA
| | - Kevin S Weiner
- Department of Psychology, University of California at Berkeley, Berkeley, USA
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, USA
| | - John C Gore
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
- Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
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Nir TM, Villalón-Reina JE, Salminen L, Haddad E, Zheng H, Thomopoulos SI, Jack CR, Weiner MW, Thompson PM, Jahanshad N. Cortical microstructural associations with CSF amyloid and pTau. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.10.23288366. [PMID: 37090601 PMCID: PMC10120803 DOI: 10.1101/2023.04.10.23288366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI, in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8±6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+/- participants. Conversely, cortical thickness was more tightly linked with pTau181. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI measures sensitive to early AD pathogenesis and microstructural damage may elucidate mechanisms underlying cognitive decline.
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Affiliation(s)
- Talia M. Nir
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Julio E. Villalón-Reina
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Lauren Salminen
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Elizabeth Haddad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Hong Zheng
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Clifford R. Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Michael W. Weiner
- Department of Radiology, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
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Ding W, Ren P, Yi L, Si Y, Yang F, Li Z, Bao H, Yan S, Zhang X, Li S, Liang X, Yao L. Association of cortical and subcortical microstructure with disease severity: impact on cognitive decline and language impairments in frontotemporal lobar degeneration. Alzheimers Res Ther 2023; 15:58. [PMID: 36941645 PMCID: PMC10029187 DOI: 10.1186/s13195-023-01208-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 03/13/2023] [Indexed: 03/23/2023]
Abstract
BACKGROUND Cortical and subcortical microstructural modifications are critical to understanding the pathogenic changes in frontotemporal lobar degeneration (FTLD) subtypes. In this study, we investigated cortical and subcortical microstructure underlying cognitive and language impairments across behavioral variant of frontotemporal dementia (bvFTD), semantic variant of primary progressive aphasia (svPPA), and nonfluent variant of primary progressive aphasia (nfvPPA) subtypes. METHODS The current study characterized 170 individuals with 3 T MRI structural and diffusion-weighted imaging sequences as portion of the Frontotemporal Lobar Degeneration Neuroimaging Initiative study: 41 bvFTD, 35 nfvPPA, 34 svPPA, and 60 age-matched cognitively unimpaired controls. To determine the severity of the disease, clinical dementia rating plus national Alzheimer's coordinating center behavior and language domains sum of boxes scores were used; other clinical measures, including the Boston naming test and verbal fluency test, were also evaluated. We computed surface-based cortical thickness and cortical and subcortical microstructural metrics using tract-based spatial statistics and explored their relationships with clinical and cognitive assessments. RESULTS Compared with controls, those with FTLD showed substantial cortical mean diffusivity alterations extending outside the regions with cortical thinning. Tract-based spatial statistics revealed that anomalies in subcortical white matter diffusion were widely distributed across the frontotemporal and parietal areas. Patients with bvFTD, nfvPPA, and svPPA exhibited distinct patterns of cortical and subcortical microstructural abnormalities, which appeared to correlate with disease severity, and separate dimensions of language functions. CONCLUSIONS Our findings imply that cortical and subcortical microstructures may serve as sensitive biomarkers for the investigation of neurodegeneration-associated microstructural alterations in FTLD subtypes. Flowchart of the study design (see materials and methods for detailed description).
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Affiliation(s)
- Wencai Ding
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Peng Ren
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, 150001, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China
| | - Liye Yi
- Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Yao Si
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Fan Yang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Zhipeng Li
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, 150001, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China
| | - Hongbo Bao
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, 150001, China
| | - Shi Yan
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Xinyu Zhang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Siyang Li
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, 150001, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China
| | - Xia Liang
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, 150001, China.
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China.
| | - Lifen Yao
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
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Cabeen RP, Toga AW, Allman JM. Mapping frontoinsular cortex from diffusion microstructure. Cereb Cortex 2023; 33:2715-2733. [PMID: 35753692 PMCID: PMC10016069 DOI: 10.1093/cercor/bhac237] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/20/2022] [Accepted: 05/21/2022] [Indexed: 11/13/2022] Open
Abstract
We developed a novel method for mapping the location, surface area, thickness, and volume of frontoinsular cortex (FI) using structural and diffusion magnetic resonance imaging. FI lies in the ventral part of anterior insular cortex and is characterized by its distinctive population von Economo neurons (VENs). Functional neuroimaging studies have revealed its involvement in affective processing, and histopathology has implicated VEN loss in behavioral-variant frontotemporal dementia and chronic alcoholism; however, structural neuroimaging of FI has been relatively limited. We delineated FI by jointly modeling cortical surface geometry and its coincident diffusion microstructure parameters. We found that neurite orientation dispersion in cortical gray matter can be used to map FI in specific individuals, and the derived measures reflect a range of behavioral factors in young adults from the Human Connectome Project (N=1052). FI volume was larger in the left hemisphere than the right (31%), and the percentage volume of FI was larger in women than men (15.3%). FI volume was associated with measures of decision-making (delay discounting, substance abuse), emotion (negative intrusive thinking and perception of hostility), and social behavior (theory of mind and working memory for faces). The common denominator is that larger FI size is related to greater self-control and social awareness.
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Affiliation(s)
- Ryan P Cabeen
- Laboratory of Neuro Imaging, USC Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, United States
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, United States
| | - John M Allman
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States
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30
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Du Y, Wang G, Wang C, Zhang Y, Xi X, Zhang L, Liu M. Accurate module induced brain network construction for mild cognitive impairment identification with functional MRI. Front Aging Neurosci 2023; 15:1101879. [PMID: 36875703 PMCID: PMC9978189 DOI: 10.3389/fnagi.2023.1101879] [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: 11/18/2022] [Accepted: 01/30/2023] [Indexed: 02/18/2023] Open
Abstract
Introduction Functional brain networks (FBNs) estimated from functional magnetic resonance imaging (fMRI) data has become a potentially useful way for computer-aided diagnosis of neurological disorders, such as mild cognitive impairment (MCI), a prodromal stage of Alzheimer's Disease (AD). Currently, Pearson's correlation (PC) is the most widely-used method for constructing FBNs. Despite its popularity and simplicity, the conventional PC-based method usually results in dense networks where regions-of-interest (ROIs) are densely connected. This is not accordance with the biological prior that ROIs may be sparsely connected in the brain. To address this issue, previous studies proposed to employ a threshold or l_1-regularizer to construct sparse FBNs. However, these methods usually ignore rich topology structures, such as modularity that has been proven to be an important property for improving the information processing ability of the brain. Methods To this end, in this paper, we propose an accurate module induced PC (AM-PC) model to estimate FBNs with a clear modular structure, by including sparse and low-rank constraints on the Laplacian matrix of the network. Based on the property that zero eigenvalues of graph Laplacian matrix indicate the connected components, the proposed method can reduce the rank of the Laplacian matrix to a pre-defined number and obtain FBNs with an accurate number of modules. Results To validate the effectiveness of the proposed method, we use the estimated FBNs to classify subjects with MCI from healthy controls. Experimental results on 143 subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) with resting-state functional MRIs show that the proposed method achieves better classification performance than previous methods.
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Affiliation(s)
- Yue Du
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong, China
- School of Mathematics Science, Liaocheng University, Liaocheng, Shandong, China
| | - Guangyu Wang
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong, China
- School of Mathematics Science, Liaocheng University, Liaocheng, Shandong, China
| | - Chengcheng Wang
- School of Mathematics Science, Liaocheng University, Liaocheng, Shandong, China
| | - Yangyang Zhang
- School of Mathematics Science, Liaocheng University, Liaocheng, Shandong, China
- School of Computer Science and Cyberspace Security, Hainan University, Haikou, Hainan, China
| | - Xiaoming Xi
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong, China
| | - Limei Zhang
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong, China
| | - Mingxia Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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31
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Murdy TJ, Dunn AR, Singh S, Telpoukhovskaia MA, Zhang S, White JK, Kahn I, Febo M, Kaczorowski CC. Leveraging genetic diversity in mice to inform individual differences in brain microstructure and memory. Front Behav Neurosci 2023; 16:1033975. [PMID: 36703722 PMCID: PMC9871587 DOI: 10.3389/fnbeh.2022.1033975] [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: 09/01/2022] [Accepted: 12/08/2022] [Indexed: 01/11/2023] Open
Abstract
In human Alzheimer's disease (AD) patients and AD mouse models, both differential pre-disease brain features and differential disease-associated memory decline are observed, suggesting that certain neurological features may protect against AD-related cognitive decline. The combination of these features is known as brain reserve, and understanding the genetic underpinnings of brain reserve may advance AD treatment in genetically diverse human populations. One potential source of brain reserve is brain microstructure, which is genetically influenced and can be measured with diffusion MRI (dMRI). To investigate variation of dMRI metrics in pre-disease-onset, genetically diverse AD mouse models, we utilized a population of genetically distinct AD mice produced by crossing the 5XFAD transgenic mouse model of AD to 3 inbred strains (C57BL/6J, DBA/2J, FVB/NJ) and two wild-derived strains (CAST/EiJ, WSB/EiJ). At 3 months of age, these mice underwent diffusion magnetic resonance imaging (dMRI) to probe neural microanatomy in 83 regions of interest (ROIs). At 5 months of age, these mice underwent contextual fear conditioning (CFC). Strain had a significant effect on dMRI measures in most ROIs tested, while far fewer effects of sex, sex*strain interactions, or strain*sex*5XFAD genotype interactions were observed. A main effect of 5XFAD genotype was observed in only 1 ROI, suggesting that the 5XFAD transgene does not strongly disrupt neural development or microstructure of mice in early adulthood. Strain also explained the most variance in mouse baseline motor activity and long-term fear memory. Additionally, significant effects of sex and strain*sex interaction were observed on baseline motor activity, and significant strain*sex and sex*5XFAD genotype interactions were observed on long-term memory. We are the first to study the genetic influences of brain microanatomy in genetically diverse AD mice. Thus, we demonstrated that strain is the primary factor influencing brain microstructure in young adult AD mice and that neural development and early adult microstructure are not strongly altered by the 5XFAD transgene. We also demonstrated that strain, sex, and 5XFAD genotype interact to influence memory in genetically diverse adult mice. Our results support the usefulness of the 5XFAD mouse model and convey strong relationships between natural genetic variation, brain microstructure, and memory.
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Affiliation(s)
| | - Amy R. Dunn
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - Surjeet Singh
- The Jackson Laboratory, Bar Harbor, ME, United States
| | | | | | | | - Itamar Kahn
- Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, United States
| | - Marcelo Febo
- Department of Neuroscience, University of Florida College of Medicine, Gainesville, FL, United States
| | - Catherine C. Kaczorowski
- The Jackson Laboratory, Bar Harbor, ME, United States,*Correspondence: Catherine C. Kaczorowski,
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Moody JF, Dean DC, Kecskemeti SR, Blennow K, Zetterberg H, Kollmorgen G, Suridjan I, Wild N, Carlsson CM, Johnson SC, Alexander AL, Bendlin BB. Associations between diffusion MRI microstructure and cerebrospinal fluid markers of Alzheimer's disease pathology and neurodegeneration along the Alzheimer's disease continuum. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12381. [PMID: 36479018 PMCID: PMC9720004 DOI: 10.1002/dad2.12381] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 09/14/2022] [Accepted: 10/29/2022] [Indexed: 12/07/2022]
Abstract
Introduction White matter (WM) degeneration is a critical component of early Alzheimer's disease (AD) pathophysiology. Diffusion-weighted imaging (DWI) models, including diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and mean apparent propagator MRI (MAP-MRI), have the potential to identify early neurodegenerative WM changes associated with AD. Methods We imaged 213 (198 cognitively unimpaired) aging adults with DWI and used tract-based spatial statistics to compare 15 DWI metrics of WM microstructure to 9 cerebrospinal fluid (CSF) markers of AD pathology and neurodegeneration treated as continuous variables. Results We found widespread WM injury in AD, as indexed by robust associations between DWI metrics and CSF biomarkers. MAP-MRI had more spatially diffuse relationships with Aβ42/40 and pTau, compared with NODDI and DTI. Discussion Our results suggest that WM degeneration may be more pervasive in AD than is commonly appreciated and that innovative DWI models such as MAP-MRI may provide clinically viable biomarkers of AD-related neurodegeneration in the earliest stages of AD progression.
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Affiliation(s)
- Jason F. Moody
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Douglas C. Dean
- Waisman CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of PediatricsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | | | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- UK Dementia Research InstituteUCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | | | | | | | - Cynthia M. Carlsson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Sterling C. Johnson
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Geriatric Research Education and Clinical CenterMiddleton Memorial VA HospitalMadisonWisconsinUSA
| | - Andrew L. Alexander
- Waisman CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of PsychiatryUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Barbara B. Bendlin
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
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Bai X, Guo T, Chen J, Guan X, Zhou C, Wu J, Liu X, Wu H, Wen J, Gu L, Gao T, Xuan M, Huang P, Zhang B, Xu X, Zhang M. Microstructural but not macrostructural cortical degeneration occurs in Parkinson’s disease with mild cognitive impairment. NPJ Parkinsons Dis 2022; 8:151. [DOI: 10.1038/s41531-022-00416-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 10/14/2022] [Indexed: 11/11/2022] Open
Abstract
AbstractThis study aimed to investigate the cortical microstructural/macrostructural degenerative patterns in Parkinson’s disease (PD) patients with mild cognitive impairment (MCI). Overall, 38 PD patients with normal cognition (PD-NC), 38 PD-MCI, and 32 healthy controls (HC) were included. PD-MCI was diagnosed according to the MDS Task Force level II criteria. Cortical microstructural alterations were evaluated with Neurite Orientation Dispersion and Density Imaging. Cortical thickness analyses were derived from T1-weighted imaging using the FreeSurfer software. For cortical microstructural analyses, compared with HC, PD-NC showed lower orientation dispersion index (ODI) in bilateral cingulate and paracingulate gyri, supplementary motor area, right paracentral lobule, and precuneus (PFWE < 0.05); while PD-MCI showed lower ODI in widespread regions covering bilateral frontal, parietal, occipital, and right temporal areas and lower neurite density index in left frontal area, left cingulate, and paracingulate gyri (PFWE < 0.05). Furthermore, compared with PD-NC, PD-MCI showed reduced ODI in right frontal area and bilateral caudate nuclei (voxel P < 0.01 and cluster >100 voxels) and the ODI values were associated with the Montreal Cognitive Assessment scores (r = 0.440, P < 0.001) and the memory performance (r = 0.333, P = 0.004) in the PD patients. However, for cortical thickness analyses, there was no difference in the between-group comparisons. In conclusion, cortical microstructural alterations may precede macrostructural changes in PD-MCI. This study provides insightful evidence for the degenerative patterns in PD-MCI and contributes to our understanding of the latent biological basis of cortical neurite changes for early cognitive impairment in PD.
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Huang H, Ma X, Yue X, Kang S, Rao Y, Long W, Liang Y, Li Y, Chen Y, Lyu W, Wu J, Tan X, Qiu S. Cortical gray matter microstructural alterations in patients with type 2 diabetes mellitus. Brain Behav 2022; 12:e2746. [PMID: 36059152 PMCID: PMC9575596 DOI: 10.1002/brb3.2746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/02/2022] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND AND PURPOSE Neurodegenerative processes are widespread in the brains of type 2 diabetes mellitus (T2DM) patients; gaps remain to exist in the current knowledge of the associated gray matter (GM) microstructural alterations. METHODS A cross-sectional study was conducted to investigate alterations in GM microarchitecture in T2DM patients by diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI). Seventy-eight T2DM patients and seventy-four age-, sex-, and education level-matched healthy controls (HCs) without cognitive impairment were recruited. Cortical macrostructure and GM microstructure were assessed by surface-based analysis and GM-based spatial statistics (GBSS), respectively. Machine learning models were trained to evaluate the diagnostic values of cortical intracellular volume fraction (ICVF) for the classification of T2DM versus HCs. RESULTS There were no differences in cortical thickness or area between the groups. GBSS analysis revealed similar GM microstructural patterns of significantly decreased fractional anisotropy, increased mean diffusivity and radial diffusivity in T2DM patients involving the frontal and parietal lobes, and significantly lower ICVF values were observed in nearly all brain regions of T2DM patients. A support vector machine model with a linear kernel was trained to realize the T2DM versus HC classification and exhibited the highest performance among the trained models, achieving an accuracy of 74% and an area under the curve of 83%. CONCLUSIONS NODDI may help to probe the widespread GM neuritic density loss in T2DM patients occurs before measurable macrostructural alterations. The cortical ICVF values may provide valuable diagnostic information regarding the early GM microstructural alterations in T2DM.
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Affiliation(s)
- Haoming Huang
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Xiaomeng Ma
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Xiaomei Yue
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Shangyu Kang
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Yawen Rao
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Wenjie Long
- Department of Geriatrics, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Yi Liang
- Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Yifan Li
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Yuna Chen
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Wenjiao Lyu
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Jinjian Wu
- The First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China.,Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Xin Tan
- Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, P.R. China
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Elman JA, Puckett OK, Hagler DJ, Pearce RC, Fennema-Notestine C, Hatton SN, Lyons MJ, McEvoy LK, Panizzon MS, Reas ET, Dale AM, Franz CE, Kremen WS. Associations between MRI-assessed locus coeruleus integrity and cortical gray matter microstructure. Cereb Cortex 2022; 32:4191-4203. [PMID: 34969072 PMCID: PMC9528780 DOI: 10.1093/cercor/bhab475] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 11/17/2021] [Accepted: 11/22/2021] [Indexed: 01/27/2023] Open
Abstract
The locus coeruleus (LC) is one of the earliest sites of tau pathology, making it a key structure in early Alzheimer's disease (AD) progression. As the primary source of norepinephrine for the brain, reduced LC integrity may have negative consequences for brain health, yet macrostructural brain measures (e.g. cortical thickness) may not be sensitive to early stages of neurodegeneration. We therefore examined whether LC integrity was associated with differences in cortical gray matter microstructure among 435 men (mean age = 67.5; range = 62-71.7). LC structural integrity was indexed by contrast-to-noise ratio (LCCNR) from a neuromelanin-sensitive MRI scan. Restriction spectrum imaging (RSI), an advanced multi-shell diffusion technique, was used to characterize cortical microstructure, modeling total diffusion in restricted, hindered, and free water compartments. Higher LCCNR (greater integrity) was associated with higher hindered and lower free water diffusion in multiple cortical regions. In contrast, no associations between LCCNR and cortical thickness survived correction. Results suggest lower LC integrity is associated with patterns of cortical microstructure that may reflect a reduction in cytoarchitectural barriers due to broader neurodegenerative processes. These findings highlight the potential utility for LC imaging and advanced diffusion measures of cortical microstructure in assessing brain health and early identification of neurodegenerative processes.
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Affiliation(s)
- Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Emilie T Reas
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Health Care System, La Jolla, CA 92161, USA
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36
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Hakvoort L, Tönjes D. Music-mechanisms at the core of music therapy: Towards a format for a description of music therapy micro-interventions. NORDIC JOURNAL OF MUSIC THERAPY 2022. [DOI: 10.1080/08098131.2022.2070925] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Laurien Hakvoort
- Department of Music therapy, ArtEZ University of the Arts, Enschede, The Netherlands
- Muzis, Private Practice for Music Therapy, Netherlands
| | - Djemida Tönjes
- Department of Music therapy, ArtEZ University of the Arts, Enschede, The Netherlands
- Zorggroep Noorderboog, Meppel, Netherlands
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37
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Qiao H, Zhao W, Guo M, Zhu L, Chen T, Wang J, Xu X, Zhang Z, Wu Y, Chen P. Cerebral Organoids for Modeling of HSV-1-Induced-Amyloid β Associated Neuropathology and Phenotypic Rescue. Int J Mol Sci 2022; 23:ijms23115981. [PMID: 35682661 PMCID: PMC9181143 DOI: 10.3390/ijms23115981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 05/20/2022] [Accepted: 05/23/2022] [Indexed: 11/16/2022] Open
Abstract
Herpes simplex virus type I (HSV-1) infection is a potential risk factor involved in the Amyloid β (Aβ) associated neuropathology. However, further understanding of the neuropathological effects of the HSV-1 infection is hampered by the limitations of existing infection models due to the distinct differences between human brains and other mammalians’ brains. Here we generated cerebral organoid models derived from pluripotent stem cells to investigate the HSV-induced Aβ associated neuropathology and the role of antiviral drugs in the phenotypic rescue. Our results identified that the HSV-1-infected cerebral organoids recapitulated Aβ associated neuropathology including the multicellular Aβ deposition, dysregulated endogenous AD mediators, reactive gliosis, neuroinflammation, and neural loss, indicating that cerebral organoids offer an opportunity for modeling the interaction of HSV-1 with the complex phenotypes across the genetic, cellular, and tissue levels of the human Alzheimer’s disease (AD). Furthermore, we identified that two antiviral drugs, namely Ribavirin (RBV) and Valacyclovir (VCV), inhibited HSV-1 replication and rescued the neuropathological phenotypes associated with AD in the HSV-1-infected cerebral organoids, implying their therapeutic potential to slow down the progression of AD. Our study provides a high-fidelity human-relevant in-vitro HSV-1 infection model to reconstitute the multiscale neuropathological features associated with AD and discover therapeutic drug candidates relevant to the AD viral hypothesis.
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Affiliation(s)
- Haowen Qiao
- Tissue Engineering and Organ Manufacturing (TEOM) Lab, Department of Biomedical Engineering, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China; (H.Q.); (W.Z.); (L.Z.); (T.C.); (J.W.); (X.X.)
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
- State Key Laboratory of Virology, Wuhan University, Wuhan 430071, China
| | - Wen Zhao
- Tissue Engineering and Organ Manufacturing (TEOM) Lab, Department of Biomedical Engineering, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China; (H.Q.); (W.Z.); (L.Z.); (T.C.); (J.W.); (X.X.)
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
| | - Moujian Guo
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
- State Key Laboratory of Virology, Wuhan University, Wuhan 430071, China
- Institute of Medical Virology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China
| | - Lili Zhu
- Tissue Engineering and Organ Manufacturing (TEOM) Lab, Department of Biomedical Engineering, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China; (H.Q.); (W.Z.); (L.Z.); (T.C.); (J.W.); (X.X.)
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
| | - Tao Chen
- Tissue Engineering and Organ Manufacturing (TEOM) Lab, Department of Biomedical Engineering, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China; (H.Q.); (W.Z.); (L.Z.); (T.C.); (J.W.); (X.X.)
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
| | - Jibo Wang
- Tissue Engineering and Organ Manufacturing (TEOM) Lab, Department of Biomedical Engineering, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China; (H.Q.); (W.Z.); (L.Z.); (T.C.); (J.W.); (X.X.)
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
| | - Xiaodong Xu
- Tissue Engineering and Organ Manufacturing (TEOM) Lab, Department of Biomedical Engineering, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China; (H.Q.); (W.Z.); (L.Z.); (T.C.); (J.W.); (X.X.)
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
| | - Zhentao Zhang
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan 430050, China;
| | - Ying Wu
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
- State Key Laboratory of Virology, Wuhan University, Wuhan 430071, China
- Institute of Medical Virology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China
- Correspondence: (Y.W.); (P.C.)
| | - Pu Chen
- Tissue Engineering and Organ Manufacturing (TEOM) Lab, Department of Biomedical Engineering, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China; (H.Q.); (W.Z.); (L.Z.); (T.C.); (J.W.); (X.X.)
- Hubei Province Key Laboratory of Allergy and Immunology, Wuhan University TaiKang Medical School (School of Basic Medical Sciences), Wuhan 430071, China;
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan 430050, China;
- Correspondence: (Y.W.); (P.C.)
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38
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Toniolo S. What plasma biomarkers tell us about hippocampal microstructural changes in Alzheimer's disease. Brain 2022; 145:1880-1882. [PMID: 35616111 DOI: 10.1093/brain/awac190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 05/18/2022] [Indexed: 11/12/2022] Open
Affiliation(s)
- Sofia Toniolo
- Nuffield Department of Clinical Neurosciences, University of Oxford, UK.,Cognitive Disorder Clinic, John Radcliffe Hospital, Oxford, UK
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39
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Zhang L, Du Y. Lip movements enhance speech representations and effective connectivity in auditory dorsal stream. Neuroimage 2022; 257:119311. [PMID: 35589000 DOI: 10.1016/j.neuroimage.2022.119311] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/09/2022] [Accepted: 05/11/2022] [Indexed: 11/25/2022] Open
Abstract
Viewing speaker's lip movements facilitates speech perception, especially under adverse listening conditions, but the neural mechanisms of this perceptual benefit at the phonemic and feature levels remain unclear. This fMRI study addressed this question by quantifying regional multivariate representation and network organization underlying audiovisual speech-in-noise perception. Behaviorally, valid lip movements improved recognition of place of articulation to aid phoneme identification. Meanwhile, lip movements enhanced neural representations of phonemes in left auditory dorsal stream regions, including frontal speech motor areas and supramarginal gyrus (SMG). Moreover, neural representations of place of articulation and voicing features were promoted differentially by lip movements in these regions, with voicing enhanced in Broca's area while place of articulation better encoded in left ventral premotor cortex and SMG. Next, dynamic causal modeling (DCM) analysis showed that such local changes were accompanied by strengthened effective connectivity along the dorsal stream. Moreover, the neurite orientation dispersion of the left arcuate fasciculus, the bearing skeleton of auditory dorsal stream, predicted the visual enhancements of neural representations and effective connectivity. Our findings provide novel insight to speech science that lip movements promote both local phonemic and feature encoding and network connectivity in the dorsal pathway and the functional enhancement is mediated by the microstructural architecture of the circuit.
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Affiliation(s)
- Lei Zhang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China 100101; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China 100049
| | - Yi Du
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China 100101; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China 100049; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China 200031; Chinese Institute for Brain Research, Beijing, China 102206.
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40
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Callow DD, Purcell JJ, Won J, Smith JC. Neurite dispersion and density mediates the relationship between cardiorespiratory fitness and cognition in healthy younger adults. Neuropsychologia 2022; 169:108207. [PMID: 35259402 PMCID: PMC8985444 DOI: 10.1016/j.neuropsychologia.2022.108207] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 02/28/2022] [Accepted: 03/03/2022] [Indexed: 11/23/2022]
Abstract
Growing evidence suggests physical activity and cardiorespiratory fitness are associated with better cognition across the lifespan. However, the neurobiological underpinnings relating fitness and cognition remain unclear, particularly in healthy younger adults. Using a well-established and popular multi-compartment diffusion modeling approach, called Neurite Orientation and Dispersion and Density Imaging (NODDI), we investigated the relationship between physical fitness (measured via a 2-min walk test), cognition (fluid and crystallized), and gray and white matter microstructure, in a large sample (n = 816) of healthy younger adults (ages 22-35 years) from the human connectome project (HCP). Concurrent with previous literature, we found that fitness was positively associated with both fluid and crystallized cognition. Furthermore, we found that physical fitness was negatively associated with white matter orientation dispersion index (ODIWM) around the cerebellar peduncle and was negatively associated with widespread cortical and subcortical gray matter neurite density index (NDIGM). Lower ODIWM of the cerebral peduncle was associated with better fluid cognitive performance, while lower NDIGM was associated with better crystallized cognition. Finally, we found that while ODIWM partially mediated the relationship between fitness and fluid cognition, NDIGM partially mediated the relationship between fitness and crystallized cognition. This study is the first to explore the relationship between physical fitness and white and gray matter microstructure measures using NODDI. Our findings suggest that in addition to improved cognitive performance, higher physical fitness may be associated with lower white matter tract dispersion and lower neurite density in the cortical and subcortical gray matter of healthy younger adults.
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Affiliation(s)
- Daniel D. Callow
- Department of Kinesiology, University of Maryland, College Park, MD, USA
- Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA
| | | | - Junyeon Won
- Department of Kinesiology, University of Maryland, College Park, MD, USA
| | - J. Carson Smith
- Department of Kinesiology, University of Maryland, College Park, MD, USA
- Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA
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41
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Benitez A, Jensen JH, Thorn K, Dhiman S, Fountain-Zaragoza S, Rieter WJ, Spampinato MV, Hamlett ED, Nietert PJ, Falangola MDF, Helpern JA. Greater diffusion restriction in white matter in Preclinical Alzheimer's disease. Ann Neurol 2022; 91:864-877. [PMID: 35285067 DOI: 10.1002/ana.26353] [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: 11/16/2021] [Revised: 02/14/2022] [Accepted: 03/07/2022] [Indexed: 11/07/2022]
Abstract
OBJECTIVE The Alzheimer's Continuum is biologically defined by beta-amyloid deposition which, at the earliest stages, is superimposed upon white matter degeneration in aging. However, the extent to which these co-occurring changes are characterized is relatively under-explored. The goal of this study was to use Diffusional Kurtosis Imaging (DKI) and biophysical modeling to detect and describe amyloid-related white matter changes in preclinical Alzheimer's disease (AD). METHODS Cognitively unimpaired participants ages 45-85 completed brain MRI, amyloid PET (florbetapir), neuropsychological testing, and other clinical measures at baseline in a cohort study. We tested whether beta amyloid-negative (AB-) and -positive (AB+) participants differed on DKI-based conventional (i.e. Fractional Anisotropy [FA], Mean Diffusivity [MD], Mean Kurtosis [MK]) and modeling (i.e. Axonal Water Fraction [AWF], extra-axonal radial diffusivity [De,⊥ ]) metrics, and whether these metrics were associated with other biomarkers. RESULTS We found significantly greater diffusion restriction (higher FA/AWF, lower MD/ De,⊥ ) in white matter in AB+ than AB- (partial η2 = 0.08-0.19), more notably in the extra-axonal space within primarily late-myelinating tracts. Diffusion metrics predicted amyloid status incrementally over age (AUC=0.84) with modest yet selective associations, where AWF (a marker of axonal density) correlated with speed/executive functions and neurodegeneration, whereas De,⊥ (a marker of gliosis/myelin repair) correlated with amyloid deposition and white matter hyperintensity volume. INTERPRETATION These results support prior evidence of a non-monotonic change in diffusion behavior, where an early increase in diffusion restriction is hypothesized to reflect inflammation and myelin repair prior to an ensuing decrease in diffusion restriction, indicating glial and neuronal degeneration. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Andreana Benitez
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
- Department of Radiology and Radiological Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Kathryn Thorn
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Siddhartha Dhiman
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Stephanie Fountain-Zaragoza
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - William J Rieter
- Department of Radiology and Radiological Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Maria Vittoria Spampinato
- Department of Radiology and Radiological Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Eric D Hamlett
- Department of Pathology and Laboratory Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Paul J Nietert
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Maria de Fatima Falangola
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Joseph A Helpern
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
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42
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Raghavan S, Przybelski SA, Reid RI, Lesnick TG, Ramanan VK, Botha H, Matchett BJ, Murray ME, Reichard RR, Knopman DS, Graff-Radford J, Jones DT, Lowe VJ, Mielke MM, Machulda MM, Petersen RC, Kantarci K, Whitwell JL, Josephs KA, Jack CR, Vemuri P. White matter damage due to vascular, tau, and TDP-43 pathologies and its relevance to cognition. Acta Neuropathol Commun 2022; 10:16. [PMID: 35123591 PMCID: PMC8817561 DOI: 10.1186/s40478-022-01319-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 01/19/2022] [Indexed: 12/27/2022] Open
Abstract
Multi-compartment modelling of white matter microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) can provide information on white matter health through neurite density index and free water measures. We hypothesized that cerebrovascular disease, Alzheimer's disease, and TDP-43 proteinopathy would be associated with distinct NODDI readouts of white matter damage which would be informative for identifying the substrate for cognitive impairment. We identified two independent cohorts with multi-shell diffusion MRI, amyloid and tau PET, and cognitive assessments: specifically, a population-based cohort of 347 elderly randomly sampled from the Olmsted county, Minnesota, population and a clinical research-based cohort of 61 amyloid positive Alzheimer's dementia participants. We observed an increase in free water and decrease in neurite density using NODDI measures in the genu of the corpus callosum associated with vascular risk factors, which we refer to as the vascular white matter component. Tau PET signal reflective of 3R/4R tau deposition was associated with worsening neurite density index in the temporal white matter where we measured parahippocampal cingulum and inferior temporal white matter bundles. Worsening temporal white matter neurite density was associated with (antemortem confirmed) FDG TDP-43 signature. Post-mortem neuropathologic data on a small subset of this sample lend support to our findings. In the community-dwelling cohort where vascular disease was more prevalent, the NODDI vascular white matter component explained variability in global cognition (partial R2 of free water and neurite density = 8.3%) and MMSE performance (8.2%) which was comparable to amyloid PET (7.4% for global cognition and 6.6% for memory). In the AD dementia cohort, tau deposition was the greatest contributor to cognitive performance (9.6%), but there was also a non-trivial contribution of the temporal white matter component (8.5%) to cognitive performance. The differences observed between the two cohorts were reflective of their distinct clinical composition. White matter microstructural damage assessed using advanced diffusion models may add significant value for distinguishing the underlying substrate (whether cerebrovascular disease versus neurodegenerative disease caused by tau deposition or TDP-43 pathology) for cognitive impairment in older adults.
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Affiliation(s)
| | - Scott A. Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905 USA
| | - Robert I. Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905 USA
| | - Timothy G. Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905 USA
| | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905 USA
| | | | | | - R. Ross Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905 USA
| | | | | | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN 55905 USA
| | - Val J. Lowe
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | - Michelle M. Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905 USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905 USA
| | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905 USA
| | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | - Jennifer L. Whitwell
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | | | - Clifford R. Jack
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
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Neuroimaging of Mouse Models of Alzheimer’s Disease. Biomedicines 2022; 10:biomedicines10020305. [PMID: 35203515 PMCID: PMC8869427 DOI: 10.3390/biomedicines10020305] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/25/2022] [Accepted: 01/25/2022] [Indexed: 12/23/2022] Open
Abstract
Magnetic resonance imaging (MRI) and positron emission tomography (PET) have made great strides in the diagnosis and our understanding of Alzheimer’s Disease (AD). Despite the knowledge gained from human studies, mouse models have and continue to play an important role in deciphering the cellular and molecular evolution of AD. MRI and PET are now being increasingly used to investigate neuroimaging features in mouse models and provide the basis for rapid translation to the clinical setting. Here, we provide an overview of the human MRI and PET imaging landscape as a prelude to an in-depth review of preclinical imaging in mice. A broad range of mouse models recapitulate certain aspects of the human AD, but no single model simulates the human disease spectrum. We focused on the two of the most popular mouse models, the 3xTg-AD and the 5xFAD models, and we summarized all known published MRI and PET imaging data, including contrasting findings. The goal of this review is to provide the reader with broad framework to guide future studies in existing and future mouse models of AD. We also highlight aspects of MRI and PET imaging that could be improved to increase rigor and reproducibility in future imaging studies.
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Vogt NM, Hunt JFV, Adluru N, Ma Y, Van Hulle CA, Dean DC, Kecskemeti SR, Chin NA, Carlsson CM, Asthana S, Johnson SC, Kollmorgen G, Batrla R, Wild N, Buck K, Zetterberg H, Alexander AL, Blennow K, Bendlin BB. Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults. Alzheimers Dement 2022; 18:65-76. [PMID: 33984184 PMCID: PMC8589921 DOI: 10.1002/alz.12364] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 03/31/2021] [Accepted: 04/12/2021] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aβ)42 /Aβ40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS We observed a significant CSF Aβ42 /Aβ40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.
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Affiliation(s)
- Nicholas M. Vogt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Jack F. V. Hunt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Yue Ma
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Carol A. Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C. Dean
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Steven R. Kecskemeti
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | | | - Richard Batrla
- Roche Diagnostics International AG, Rotkreuz, Switzerland
| | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | - Andrew L. Alexander
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Barbara B. Bendlin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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Kothapalli SV, Benzinger TL, Aschenbrenner AJ, Perrin RJ, Hildebolt CF, Goyal MS, Fagan AM, Raichle ME, Morris JC, Yablonskiy DA. Quantitative Gradient Echo MRI Identifies Dark Matter as a New Imaging Biomarker of Neurodegeneration that Precedes Tisssue Atrophy in Early Alzheimer's Disease. J Alzheimers Dis 2022; 85:905-924. [PMID: 34897083 PMCID: PMC8842777 DOI: 10.3233/jad-210503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/27/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Currently, brain tissue atrophy serves as an in vivo MRI biomarker of neurodegeneration in Alzheimer's disease (AD). However, postmortem histopathological studies show that neuronal loss in AD exceeds volumetric loss of tissue and that loss of memory in AD begins when neurons and synapses are lost. Therefore, in vivo detection of neuronal loss prior to detectable atrophy in MRI is essential for early AD diagnosis. OBJECTIVE To apply a recently developed quantitative Gradient Recalled Echo (qGRE) MRI technique for in vivo evaluation of neuronal loss in human hippocampus. METHODS Seventy participants were recruited from the Knight Alzheimer Disease Research Center, representing three groups: Healthy controls [Clinical Dementia Rating® (CDR®) = 0, amyloid β (Aβ)-negative, n = 34]; Preclinical AD (CDR = 0, Aβ-positive, n = 19); and mild AD (CDR = 0.5 or 1, Aβ-positive, n = 17). RESULTS In hippocampal tissue, qGRE identified two types of regions: one, practically devoid of neurons, we designate as "Dark Matter", and the other, with relatively preserved neurons, "Viable Tissue". Data showed a greater loss of neurons than defined by atrophy in the mild AD group compared with the healthy control group; neuronal loss ranged between 31% and 43%, while volume loss ranged only between 10% and 19%. The concept of Dark Matter was confirmed with histopathological study of one participant who underwent in vivo qGRE 14 months prior to expiration. CONCLUSION In vivo qGRE method identifies neuronal loss that is associated with impaired AD-related cognition but is not recognized by MRI measurements of tissue atrophy, therefore providing new biomarkers for early AD detection.
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Affiliation(s)
| | - Tammie L. Benzinger
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Andrew J. Aschenbrenner
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Richard J. Perrin
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Manu S. Goyal
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Anne M. Fagan
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Marcus E. Raichle
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - John C. Morris
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Dmitriy A. Yablonskiy
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
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Takeuchi H, Kawashima R. Effects of Body Mass Index on Brain Structures in the Elderly: Longitudinal Analyses. Front Endocrinol (Lausanne) 2022; 13:824661. [PMID: 35721742 PMCID: PMC9204255 DOI: 10.3389/fendo.2022.824661] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
The relationship between obesity and neurocognitive consequences is complex. Here we investigated associations between body mass index (BMI) and subsequent changes in brain structures, cognitive changes, and the onset of dementia after adjustment of a wide range of potential confounding variables using a large prospective cohort data of UK Biobank. After correcting for confounding factors, higher BMI was associated with greater retention in visuospatial memory performance (decline in error numbers) [beta = -0.019 (CI:-0.027~-0.016), N = 39191], increase in depression tendency scores [beta = 0.036(0.027~0.045)] as well as decreased risk of incident dementia [increasing BMI by 1 is associated with HR of 0.981 (CI:0.969~0.992), N = 398782], but not changes in fluid intelligence or reaction time. Whole brain multiple regression analyses (volumetric analyses: N = 1253, other analyses: N = 1241) revealed positive associations between BMI and subsequent changes in regional gray matter volume (rGMV) in multiple areas, regional white matter volume changes in widespread white matter (WM) tracts, fractional anisotropy changes in several tracts, and intracellular volume fraction (ICVF) and orientation dispersion (OD) in widespread areas, and isotropic volume fraction (ISOVF) in a few areas, and negative associations between BMI and subsequent changes in rGMV in the bilateral medial temporal lobe areas, mean, axial and radial diffusivity, and ISOVF in widespread areas. These results are mostly consistent with the view that less BMI precedes greater neurocognitive aging or atrophy, with a few exceptions including OD findings and the rGMV finding of the medial temporal lobes as most of significant longitudinal associations of higher BMI were opposite to those seen in higher age and dementia. Future epidemiological studies should consider separating effects of higher BMI itself from potential confounders.
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Affiliation(s)
- Hikaru Takeuchi
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- *Correspondence: Hikaru Takeuchi,
| | - Ryuta Kawashima
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Smart Aging Research Center, Tohoku University, Sendai, Japan
- Department of Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
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Li M, Chen X, Xu HL, Huang Z, Chen N, Tu Y, Gan S, Hu J. Brain structural abnormalities in the preclinical stage of Machado-Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3): evaluation by MRI morphometry, diffusion tensor imaging and neurite orientation dispersion and density imaging. J Neurol 2021; 269:2989-2998. [PMID: 34783886 DOI: 10.1007/s00415-021-10890-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 11/02/2021] [Accepted: 11/03/2021] [Indexed: 01/12/2023]
Abstract
OBJECTIVE To investigate whether neurite orientation dispersion and density imaging (NODDI) could provide the added value for detecting brain microstructural alterations in the preclinical stage of Machado-Joseph disease/spinocerebellar ataxia type 3 (MJD/SCA3) compared with MRI morphometry and diffusion tensor imaging (DTI). METHODS Twenty preclinical MJD/SCA3 patients and 21 healthy controls were enrolled. Three b values DWI and 3D T1-weighted images were acquired at 3.0 T. Tract-based spatial statistics (TBSS) approach was used to investigate the white matter (WM) alterations in the DTI metrics and NODDI metrics. Gray matter-based spatial statistics (GBSS) approach was used to investigate the grey matter (GM) alterations in the NODDI metrics. Voxel-based morphometry (VBM) approach was performed on the 3D T1-weighted images. The relationship between the cytosine-adenine-guanine (CAG) repeat length and brain microstructural alterations of preclinical MJD/SCA3 was identified. RESULTS Compared with healthy controls, the preclinical MJD/SCA3 patients showed decreased FA and NDI as well as increased MD, AD, and RD in the WM of cerebellum and brainstem (corrected P < 0.05), and decreased NDI in the GM of cerebellar vermis (corrected P < 0.05). The CAG repeat length in preclinical MJD/SCA3 patients was negatively correlated with the reduced FA and NDI of the infratentorial WM and the reduced NDI of the cerebellum, and positively with the increased MD and RD of the infratentorial WM. CONCLUSIONS NOODI can provide novel quantitative microstructural changes in MJD/SCA3 carriers, expanding our understanding of the gray and white matter (axons and dendrites) degeneration in this frequent ataxia syndrome.
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Affiliation(s)
- Mengcheng Li
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, 350005, Fujian, People's Republic of China
| | - Xinyuan Chen
- Department of Rehabilitation, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, Fujian, People's Republic of China
| | - Hao-Ling Xu
- Department of Neurology, 900th Hospital of Joint Logistics Support Force, Fuzhou, China
| | - Ziqiang Huang
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, 350005, Fujian, People's Republic of China
| | - Naping Chen
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, 350005, Fujian, People's Republic of China
| | - Yuqing Tu
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, 350005, Fujian, People's Republic of China
| | - Shirui Gan
- Department of Neurology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, 350005, Fujian, People's Republic of China. .,Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, 20 ChaZhong Rd, Fuzhou, 350005, Fujian, People's Republic of China.
| | - Jianping Hu
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, 20 ChaZhong Rd, Fuzhou, 350005, Fujian, People's Republic of China.
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Veale T, Malone IB, Poole T, Parker TD, Slattery CF, Paterson RW, Foulkes AJM, Thomas DL, Schott JM, Zhang H, Fox NC, Cash DM. Loss and dispersion of superficial white matter in Alzheimer's disease: a diffusion MRI study. Brain Commun 2021; 3:fcab272. [PMID: 34859218 PMCID: PMC8633427 DOI: 10.1093/braincomms/fcab272] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 09/24/2021] [Accepted: 10/18/2021] [Indexed: 11/22/2022] Open
Abstract
Pathological cerebral white matter changes in Alzheimer's disease have been shown using diffusion tensor imaging. Superficial white matter changes are relatively understudied despite their importance in cortico-cortical connections. Measuring superficial white matter degeneration using diffusion tensor imaging is challenging due to its complex organizational structure and proximity to the cortex. To overcome this, we investigated diffusion MRI changes in young-onset Alzheimer's disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are degenerative (e.g. loss of myelinated fibres) and organizational (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer's disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, grey/white boundary, superficial white matter (1 mm below grey/white boundary) and superficial/deeper white matter (2 mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants' diffusion metrics along the cortical profile. The superficial white matter of young-onset Alzheimer's disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P < 0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P < 0.05). Young-onset Alzheimer's disease individuals had lower fractional anisotropy in the entorhinal and parahippocampus regions (both P < 0.05) and higher fractional anisotropy within the postcentral region (P < 0.05). Mean diffusivity was higher in the young-onset Alzheimer's disease group in the parahippocampal region (P < 0.05) and lower in the postcentral, precentral and superior temporal regions (all P < 0.05). In the overlying grey matter, disease-related changes were largely consistent with superficial white matter findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer's disease individuals (all P < 0.001) but group differences reduced in magnitude and coverage when moving towards the superficial white matter. These results show that microstructural changes occur within superficial white matter and along the cortical profile in individuals with young-onset Alzheimer's disease. Lower neurite density and higher orientation dispersion suggests underlying fibres undergo neurodegeneration and organizational changes, two effects previously indiscernible using standard diffusion tensor metrics in superficial white matter.
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Affiliation(s)
- Thomas Veale
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Ian B Malone
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Teresa Poole
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - Thomas D Parker
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Catherine F Slattery
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Ross W Paterson
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Alexander J M Foulkes
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - David L Thomas
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Jonathan M Schott
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Nick C Fox
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - David M Cash
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
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A pilot [ 11C]PBR28 PET/MRI study of neuroinflammation and neurodegeneration in chronic stroke patients. Brain Behav Immun Health 2021; 17:100336. [PMID: 34589819 PMCID: PMC8474408 DOI: 10.1016/j.bbih.2021.100336] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 08/18/2021] [Accepted: 08/21/2021] [Indexed: 11/24/2022] Open
Abstract
Neuroinflammation occurs in response to acute ischemic stroke, and has been speculated to underlie secondary poststroke pathologies, such as depression, that often develop over time poststroke. However, no study has examined whether neuroinflammation is present in chronic stroke patients (e.g., ≥ 1 year poststroke). This study tested whether neuroinflammation is present in chronic stroke patients, and is associated with neurodegeneration, using [11C]PBR28 PET and diffusion MRI. Eight patients with middle cerebral artery (MCA) ischemic stroke incurred 1–3 years prior and 16 healthy controls underwent [11C]PBR28 PET to measure glial activation and diffusion MRI to measure microstructural integrity by mean diffusivity (MD) and fractional anisotropy (FA) using an integrated PET/MRI scanner. Group differences in [11C]PBR28 binding, MD and FA were analyzed voxelwise across the whole brain excluding the infarct zone defined as voxels containing the infarct in any patient. Compared to controls, patients showed elevations in [11C]PBR28 binding in several brain regions outside the infarct zone, including regions with presumed direct neuroanatomical connections to the infarct (e.g., ipsilesional internal capsule and thalamus) and those without known direct connections (e.g., contralesional thalamus and cingulate gyrus). Patients also showed widespread elevations in MD, with a subset of these regions having reduced FA. In patients, MD was more elevated in regions with co-localized elevations in [11C]PBR28 binding than in contralateral regions without elevations in [11C]PBR28 binding. This pilot study supports the presence of extensive glial activation along with widespread loss in microstructural integrity in non-infarcted tissue in a cohort of patients with chronic MCA stroke. The loss in microstructural integrity was greater in regions with co-localized glial activation. It is possible that stroke risk factors (e.g., hypertension) contributed to these tissue changes in patients. Chronic neuroinflammation speculated to underlie secondary poststroke pathologies such as depression. Measured neuroinflammation in chronic stroke patients using [11C]PBR28 PET. First study showing extensive neuroinflammation in non-infarcted tissue in chronic stroke patients.
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Gozdas E, Fingerhut H, Dacorro L, Bruno JL, Hosseini SMH. Neurite Imaging Reveals Widespread Alterations in Gray and White Matter Neurite Morphology in Healthy Aging and Amnestic Mild Cognitive Impairment. Cereb Cortex 2021; 31:5570-5578. [PMID: 34313731 DOI: 10.1093/cercor/bhab180] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 04/09/2021] [Accepted: 05/19/2021] [Indexed: 12/26/2022] Open
Abstract
Aging is the major risk factor for neurodegenerative diseases and affects neurite distributions throughout the brain, yet underlying neurobiological mechanisms remain unclear. Multi-shell diffusion-weighted imaging and neurite orientation dispersion and density imaging (NODDI) now provide in vivo biophysical measurements that explain these biological processes in the cortex and white matter. In this study, neurite distributions were evaluated in the cortex and white matter in healthy older adults and patients with amnestic mild cognitive impairment (aMCI) that provides fundamental contributions regarding healthy aging and neurodegeneration. Older age was associated with reduced neurite density and neurite orientation dispersion (ODI) in widespread cortical regions. In contrast, increased ODI was only observed in the right thalamus and hippocampus with age. For the first time, we also reported a widespread age-associated decrease in neurite density along major white matter tracts correlated with decreased cortical neurite density in the tract endpoints in healthy older adults. We further examined alterations in cortical and white matter neurite microstructures in aMCI patients and found significant neurite morphology deficits in memory networks correlated with memory performance. Our findings indicate that neurite parameters provide valuable information regarding cortical and white matter microstructure and complement myeloarchitectural information in healthy aging and aMCI.
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Affiliation(s)
- Elveda Gozdas
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Hannah Fingerhut
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Lauren Dacorro
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Jennifer L Bruno
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - S M Hadi Hosseini
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
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