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McAleese KE, Miah M, Graham S, Hadfield GM, Walker L, Johnson M, Colloby SJ, Thomas AJ, DeCarli C, Koss D, Attems J. Frontal white matter lesions in Alzheimer's disease are associated with both small vessel disease and AD-associated cortical pathology. Acta Neuropathol 2021; 142:937-950. [PMID: 34608542 PMCID: PMC8568857 DOI: 10.1007/s00401-021-02376-2] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 09/26/2021] [Accepted: 09/27/2021] [Indexed: 12/22/2022]
Abstract
Cerebral white matter lesions (WML) encompass axonal loss and demyelination and are assumed to be associated with small vessel disease (SVD)-related ischaemia. However, our previous study in the parietal lobe white matter revealed that WML in Alzheimer's disease (AD) are linked with degenerative axonal loss secondary to the deposition of cortical AD pathology. Furthermore, neuroimaging data suggest that pathomechanisms for the development of WML differ between anterior and posterior lobes with AD-associated degenerative mechanism driving posterior white matter disruption, and both AD-associated degenerative and vascular mechanisms contributed to anterior matter disruption. In this pilot study, we used human post-mortem brain tissue to investigate the composition and aetiology of frontal WML from AD and non-demented controls to determine if frontal WML are SVD-associated and to reveal any regional differences in the pathogenesis of WML. Frontal WML tissue sections from 40 human post-mortem brains (AD, n = 19; controls, n = 21) were quantitatively assessed for demyelination, axonal loss, cortical hyperphosphorylated tau (HPτ) and amyloid-beta (Aβ) burden, and arteriolosclerosis as a measure of SVD. Biochemical assessment included Wallerian degeneration-associated protease calpain and the myelin-associated glycoprotein to proteolipid protein ratio as a measure of ante-mortem ischaemia. Arteriolosclerosis severity was found to be associated with and a significant predictor of frontal WML severity in both AD and non-demented controls. Interesting, frontal axonal loss was also associated with HPτ and calpain levels were associated with increasing Aβ burden in the AD group, suggestive of an additional degenerative influence. To conclude, this pilot data suggest that frontal WML in AD may result from both increased arteriolosclerosis and AD-associated degenerative changes. These preliminary findings in combination with previously published data tentatively indicate regional differences in the aetiology of WML in AD, which should be considered in the clinical diagnosis of dementia subtypes: posterior WML maybe associated with degenerative mechanisms secondary to AD pathology, while anterior WML could be associated with both SVD-associated and degenerative mechanisms.
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Affiliation(s)
- Kirsty E McAleese
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK.
| | - Mohi Miah
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sophie Graham
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Georgina M Hadfield
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Lauren Walker
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Mary Johnson
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sean J Colloby
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Alan J Thomas
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, CA, USA
| | - David Koss
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Johannes Attems
- Translation and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
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52
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Shirazi Y, Oghabian MA, Batouli SAH. Along-tract analysis of the white matter is more informative about brain ageing, compared to whole-tract analysis. Clin Neurol Neurosurg 2021; 211:107048. [PMID: 34826755 DOI: 10.1016/j.clineuro.2021.107048] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 10/25/2021] [Accepted: 11/14/2021] [Indexed: 11/30/2022]
Abstract
Diffusion Tensor Imaging (DTI) enabled the investigation of brain White Matter (WM), both qualitatively to study the macrostructure, and quantitatively to study the microstructure. The quantitative analyses are mostly performed at the whole-tract level, i.e., providing one measure of interest per tract; however, along-tract approaches may provide finer details of the quality of the WM tracts. In this study, using the DWI data collected from 40 young and 40 old individuals, we compared the DTI measures of FA, MD, AD, and RD, estimated by both whole-tract and along-tract approaches in 18 WM bundles, between the two groups. The results of the whole-tract quantitative analysis showed a statistically significant (p-FWER < 0.05) difference between the old and young groups in 6 tracts for FA, 8 tracts for MD, 1 tract for AD, and 7 tracts for RD. On the contrary, the along-tract approach showed differences between the two groups in 10 tracts for FA, 14 tracts for MD, 8 tracts for AD, and 11 tracts for RD. All the differences between the along-tract measures of the two groups had a large effect size (Cohen'd > 0.80). This study showed that the along-tract approach for the analysis of brain WM reveals changes in some WM tracts which had not shown any changes in the whole-tract approach, and therefore this finding emphasizes the utilization of the along-tract approach along with the whole-tract method for a more accurate study of the brain WM.
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Affiliation(s)
- Yasin Shirazi
- Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Oghabian
- Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran; Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Amir Hossein Batouli
- Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran; Department of Neuroscience and addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.
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53
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Liang L, Chen Z, Wei Y, Tang F, Nong X, Li C, Yu B, Duan G, Su J, Mai W, Zhao L, Zhang Z, Deng D. Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA. Neuroimage Clin 2021; 32:102874. [PMID: 34911186 PMCID: PMC8605254 DOI: 10.1016/j.nicl.2021.102874] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 10/30/2021] [Accepted: 11/01/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Previous multimodal neuroimaging studies analyzed each dataset independently in subjective cognitive decline (SCD) and mild cognitive impairment (MCI), missing the cross-information. Multi-modal fusion analysis can provide more integral and comprehensive information regarding the brain. There has been a paucity of research on fusion analysis of sMRI and DTI in SCD and MCI. MATERIALS AND METHODS In the present study, we conducted fusion analysis of structural MRI and DTI by applying multimodal canonical correlation analysis with joint independent component analysis (mCCA-jICA) to capture the cross-information of gray matter (GM) and white matter (WM) in 62 SCD patients, 99 MCI patients, and 70 healthy controls (HCs). We further analyzed correlations between the mixing coefficients of mCCA-jICA and neuropsychological scores among the three groups. RESULTS A set of joint-discriminative independent components of GM and fractional anisotropy (FA) exhibited significant links between SCD and HCs, as well as between MCI and HCs. The covariant abnormalities primarily involved the frontal lobe/middle temporal gyrus/calcarine sulcus-anterior thalamic radiation/superior longitudinal fasciculus in SCD, and middle temporal gyrus/ fusiform gyrus/caudate necleus-forceps minor/anterior thalamic radiation in MCI. There was no significant difference between SCD and MCI groups. CONCLUSIONS The covariant GM-WM abnormalities in SCD and MCI were found in specific brain regions involved in cognitive processing, which confirms the simultaneous GM and WM changes underlying cognitive decline. These findings suggest that multimodal fusion analysis allows for a more comprehensive understanding of the association among different types of brain tissues and its crucial role in the neuropathological mechanism of SCD and MCI.
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Affiliation(s)
- Lingyan Liang
- The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, Guangxi, China
| | - Zaili Chen
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Department of Medical Instrument Measurement, Shenzhen Academy of Metrology and Quality Inspection, Shenzhen 518055, China.
| | - Yichen Wei
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Fei Tang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Department of Medical Instrument Measurement, Shenzhen Academy of Metrology and Quality Inspection, Shenzhen 518055, China.
| | - Xiucheng Nong
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Chong Li
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Bihan Yu
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Gaoxiong Duan
- The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, Guangxi, China
| | - Jiahui Su
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Wei Mai
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Lihua Zhao
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine, Nanning 530023, Guangxi, China
| | - Zhiguo Zhang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China; Peng Cheng Laboratory, Shenzhen 518055, China.
| | - Demao Deng
- The People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, Guangxi, China.
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54
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Zhang Y, Ma M, Xie Z, Wu H, Zhang N, Shen J. Bridging the Gap Between Morphometric Similarity Mapping and Gene Transcription in Alzheimer's Disease. Front Neurosci 2021; 15:731292. [PMID: 34671240 PMCID: PMC8522649 DOI: 10.3389/fnins.2021.731292] [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: 06/26/2021] [Accepted: 09/03/2021] [Indexed: 11/13/2022] Open
Abstract
Disruptions in brain connectivity have been widely reported in Alzheimer’s disease (AD). Morphometric similarity (MS) mapping provides a new way of estimating structural connectivity by interregional correlation of T1WI- and DTI-derived parameters within individual brains. Here, we aimed to identify AD-related MS changing patterns and genes related to the changes and further explored the molecular and cellular mechanism underlying MS changes in AD. Both 3D-T1WI and DTI data of 106 AD patients and 106 well-matched healthy elderly individuals from the ADNI database were included in our study. Cortical regions with significantly decreased MS were found in the temporal and parietal cortex, increased MS was found in the frontal cortex and variant changes were found in the occipital cortex in AD patients. Mean MS in regions with significantly changed MS was positively or negatively associated with memory function. Negative MS-related genes were significantly downregulated in AD, specifically enriched in neurons, and participated in biological processes, with the most significant term being synaptic transmission. This study revealed AD-related cortical MS changes associated with memory function. Linking gene expression to cortical MS changes may provide a possible molecular and cellular substrate for MS abnormality and cognitive decline in AD.
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Affiliation(s)
- Yang Zhang
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Min Ma
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhonghua Xie
- Department of Mathematics, School of Science, Tianjin University of Science and Technology, Tianjin, China
| | - Heng Wu
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Nan Zhang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Junlin Shen
- Department of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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55
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Piersson AD, Ibrahim B, Suppiah S, Mohamad M, Hassan HA, Omar NF, Ibrahim MI, Yusoff AN, Ibrahim N, Saripan MI, Razali RM. Multiparametric MRI for the improved diagnostic accuracy of Alzheimer's disease and mild cognitive impairment: Research protocol of a case-control study design. PLoS One 2021; 16:e0252883. [PMID: 34547018 PMCID: PMC8454976 DOI: 10.1371/journal.pone.0252883] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 05/18/2021] [Indexed: 11/19/2022] Open
Abstract
Background Alzheimer’s disease (AD) is a major neurocognitive disorder identified by memory loss and a significant cognitive decline based on previous level of performance in one or more cognitive domains that interferes in the independence of everyday activities. The accuracy of imaging helps to identify the neuropathological features that differentiate AD from its common precursor, mild cognitive impairment (MCI). Identification of early signs will aid in risk stratification of disease and ensures proper management is instituted to reduce the morbidity and mortality associated with AD. Magnetic resonance imaging (MRI) using structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (1H-MRS) performed alone is inadequate. Thus, the combination of multiparametric MRI is proposed to increase the accuracy of diagnosing MCI and AD when compared to elderly healthy controls. Methods This protocol describes a non-interventional case control study. The AD and MCI patients and the healthy elderly controls will undergo multi-parametric MRI. The protocol consists of sMRI, fMRI, DTI, and single-voxel proton MRS sequences. An eco-planar imaging (EPI) will be used to perform resting-state fMRI sequence. The structural images will be analysed using Computational Anatomy Toolbox-12, functional images will be analysed using Statistical Parametric Mapping-12, DPABI (Data Processing & Analysis for Brain Imaging), and Conn software, while DTI and 1H-MRS will be analysed using the FSL (FMRIB’s Software Library) and Tarquin respectively. Correlation of the MRI results and the data acquired from the APOE genotyping, neuropsychological evaluations (i.e. Montreal Cognitive Assessment [MoCA], and Mini–Mental State Examination [MMSE] scores) will be performed. The imaging results will also be correlated with the sociodemographic factors. The diagnosis of AD and MCI will be standardized and based on the DSM-5 criteria and the neuropsychological scores. Discussion The combination of sMRI, fMRI, DTI, and MRS sequences can provide information on the anatomical and functional changes in the brain such as regional grey matter volume atrophy, impaired functional connectivity among brain regions, and decreased metabolite levels specifically at the posterior cingulate cortex/precuneus. The combination of multiparametric MRI sequences can be used to stratify the management of MCI and AD patients. Accurate imaging can decide on the frequency of follow-up at memory clinics and select classifiers for machine learning that may aid in the disease identification and prognostication. Reliable and consistent quantification, using standardised protocols, are crucial to establish an optimal diagnostic capability in the early detection of Alzheimer’s disease.
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Affiliation(s)
- Albert Dayor Piersson
- Diagnostic Imaging and Radiotherapy Programme, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
- Department of Imaging Technology & Sonography, School of Allied Health Sciences, University of Cape Coast, Cape Coast, Ghana
| | - Buhari Ibrahim
- Faculty of Medicine and Health Sciences, Department of Radiology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Faculty of Medicine and Health Sciences, Neuroscience Laboratory for Cognitive Function and Behavioural Imaging (NeuroCoB), Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Faculty of Basic Medical Sciences, Department of Physiology, Bauchi State University PMB 65, Gadau, Nigeria
| | - Subapriya Suppiah
- Faculty of Medicine and Health Sciences, Department of Radiology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Faculty of Medicine and Health Sciences, Neuroscience Laboratory for Cognitive Function and Behavioural Imaging (NeuroCoB), Universiti Putra Malaysia, Seri Kembangan, Malaysia
- * E-mail:
| | - Mazlyfarina Mohamad
- Diagnostic Imaging and Radiotherapy Programme, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Hasyma Abu Hassan
- Faculty of Medicine and Health Sciences, Department of Radiology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Nur Farhayu Omar
- Faculty of Medicine and Health Sciences, Department of Radiology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Mohd Izuan Ibrahim
- Diagnostic Imaging and Radiotherapy Programme, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Ahmad Nazlim Yusoff
- Diagnostic Imaging and Radiotherapy Programme, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Normala Ibrahim
- Faculty of Medicine and Health Sciences, Department of Psychiatry, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - M. Iqbal Saripan
- Faculty of Engineering, Department of Computer & Communication Systems, University Putra Malaysia, Seri Kembangan, Malaysia
| | - Rizah Mazzuin Razali
- Gerontology Unit, Department of Medicine, Hospital Kuala Lumpur, Kuala Lumpur, Malaysia
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56
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Hall Z, Chien B, Zhao Y, Risacher SL, Saykin AJ, Wu YC, Wen Q. Tau deposition and structural connectivity demonstrate differential association patterns with neurocognitive tests. Brain Imaging Behav 2021; 16:702-714. [PMID: 34533771 PMCID: PMC8935446 DOI: 10.1007/s11682-021-00531-7] [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] [Accepted: 07/28/2021] [Indexed: 11/25/2022]
Abstract
Tau neurofibrillary tangles have a central role in the pathogenesis of Alzheimer’s Disease (AD). Mounting evidence indicates that the propagation of tau is assisted by brain connectivity with weakened white-matter integrity along the propagation pathways. Recent advances in tau positron emission tomography tracers and diffusion magnetic resonance imaging allow the visualization of tau pathology and white-matter connectivity of the brain in vivo. The current study aims to investigate how tau deposition and structural connectivity are associated with memory function in prodromal AD. In this study, tau accumulation and structural connectivity data from 83 individuals (57 cognitively normal participants and 26 participants with mild cognitive impairment) were associated with neurocognitive test scores. Statistical analyses were performed in 70 cortical/subcortical brain regions to determine: 1. the level of association between tau and network metrics extracted from structural connectivity and 2. the association patterns of brain memory function with tau accumulation and network metrics. The results showed that tau accumulation and network metrics were correlated in early tau deposition regions. Furthermore, tau accumulation was associated with worse performance in almost all neurocognitive tests performance evaluated in the study. In comparison, decreased network connectivity was associated with declines in the delayed memory recall in Craft Stories and Benson Figure Copy. Interaction analysis indicates that tau deposition and dysconnectivity have a synergistic effect on the delayed Benson Figure Recall. Overall, our findings indicate that both tau deposition and structural dysconnectivity are associated with neurocognitive dysfunction. They also suggest that tau-PET may have better sensitivity to neurocognitive performance than diffusion MRI-derived measures of white-matter connectivity.
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Affiliation(s)
- Zack Hall
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Billy Chien
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yi Zhao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA.,Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA.,Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Clinical Psychology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA. .,Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA. .,Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA. .,Indiana Institute for Biomedical Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA.
| | - Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 West 16th Street, Suite 4100, Indianapolis, IN, 46202, USA. .,Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
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57
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Zhuang XM, Kuo LW, Lin SY, Yang JJ, Tu MC, Hsu YH. Prospective Memory and Regional Functional Connectivity in Subcortical Ischemic Vascular Disease. Front Aging Neurosci 2021; 13:686040. [PMID: 34489671 PMCID: PMC8417716 DOI: 10.3389/fnagi.2021.686040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 07/22/2021] [Indexed: 12/21/2022] Open
Abstract
Objectives: Patients with subcortical ischemic vascular disease (SIVD) often have prominent frontal dysfunction. However, it remains unclear how SIVD affects prospective memory (PM), which strongly relies on the frontoparietal network. The present study aimed to investigate PM performance in patients with early stage SIVD as compared to those with Alzheimer's disease (AD) and to older adults with normal cognition, and to explore the neural correlates of PM deficits. Method: Patients with very-mild to mild dementia due to SIVD or AD and normal controls (NC) aged above 60 years were recruited. Seventy-three participants (20 SIVD, 22 AD, and 31 NC) underwent structural magnetic resonance imaging (MRI), cognitive screening tests, and a computerized PM test. Sixty-five of these participants (19 SIVD, 20 AD, and 26 NC) also received resting-state functional MRI. Results: The group with SIVD had significantly fewer PM hits than the control group on both time-based and non-focal event-based PM tasks. Among patients in the very early stage, only those with SIVD but not AD performed significantly worse than the controls. Correlational analyses showed that non-focal event-based PM in SIVD was positively correlated with regional homogeneity in bilateral superior and middle frontal gyri, while time-based PM was not significantly associated with regional homogeneity in any of the regions of interest within the dorsal frontoparietal regions. Conclusions: The findings of this study highlight the vulnerability of non-focal event-based PM to the disruption of regional functional connectivity in bilateral superior and middle frontal gyri in patients with SIVD.
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Affiliation(s)
- Xuan-Miao Zhuang
- Department of Psychology, National Chung Cheng University, Chiayi, Taiwan
| | - Li-Wei Kuo
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan.,Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Shih-Yen Lin
- Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan
| | - Jir-Jei Yang
- Department of Medical Imaging, Taichung Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Taichung, Taiwan
| | - Min-Chien Tu
- Department of Neurology, Taichung Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Taichung, Taiwan.,Department of Neurology, School of Medicine, Tzu Chi University, Hualien, Taiwan
| | - Yen-Hsuan Hsu
- Department of Psychology, National Chung Cheng University, Chiayi, Taiwan.,Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, Chiayi, Taiwan
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Shu P, Zhu H, Jin W, Zhou J, Tong S, Sun J. The Resilience and Vulnerability of Human Brain Networks Across the Lifespan. IEEE Trans Neural Syst Rehabil Eng 2021; 29:1756-1765. [PMID: 34410925 DOI: 10.1109/tnsre.2021.3105991] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Resilience, the ability for a system to maintain its basic functionality when suffering from lesions, is a critical property for human brain, especially in the brain aging process. This study adopted a novel metric of network resilience, the Resilience Index (RI), to assess human brain resilience with three different lifespan datasets. Based on the structural brain networks constructed from diffusion tensor imaging (DTI), we observed an inverted-U relationship between RI and age, that is, RI increased during development and early adulthood, reached a peak at about 35 years old, and then decreased during aging, which suggested that brain resilience could be quantified by RI. Furthermore, we studied brain network vulnerability by the decreases in RI when virtual lesions occurred to nodes (i.e., brain regions) or edges (i.e., structural brain connectivity). We found that the strong edges were markedly vulnerable, and the homotopic edges were the most prominent representatives of vulnerable edges. In other words, an arbitrary attack on homotopic edges would have a high probability to degrade brain network resilience. These findings suggest the change of human brain resilience across the lifespan and provide a new perspective for exploring human brain vulnerability.
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Yu M, Sporns O, Saykin AJ. The human connectome in Alzheimer disease - relationship to biomarkers and genetics. Nat Rev Neurol 2021; 17:545-563. [PMID: 34285392 PMCID: PMC8403643 DOI: 10.1038/s41582-021-00529-1] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Bloomington, IN, USA.
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Ramírez-Toraño F, Abbas K, Bruña R, Marcos de Pedro S, Gómez-Ruiz N, Barabash A, Pereda E, Marcos A, López-Higes R, Maestu F, Goñi J. A Structural Connectivity Disruption One Decade before the Typical Age for Dementia: A Study in Healthy Subjects with Family History of Alzheimer's Disease. Cereb Cortex Commun 2021; 2:tgab051. [PMID: 34647029 PMCID: PMC8501268 DOI: 10.1093/texcom/tgab051] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/23/2021] [Accepted: 07/26/2021] [Indexed: 11/23/2022] Open
Abstract
The concept of the brain has shifted to a complex system where different subnetworks support the human cognitive functions. Neurodegenerative diseases would affect the interactions among these subnetworks and, the evolution of impairment and the subnetworks involved would be unique for each neurodegenerative disease. In this study, we seek for structural connectivity traits associated with the family history of Alzheimer's disease, that is, early signs of subnetworks impairment due to Alzheimer's disease. The sample in this study consisted of 123 first-degree Alzheimer's disease relatives and 61 nonrelatives. For each subject, structural connectomes were obtained using classical diffusion tensor imaging measures and different resolutions of cortical parcellation. For the whole sample, independent structural-connectome-traits were obtained under the framework of connICA. Finally, we tested the association of the structural-connectome-traits with different factors of relevance for Alzheimer's disease by means of a multiple linear regression. The analysis revealed a structural-connectome-trait obtained from fractional anisotropy associated with the family history of Alzheimer's disease. The structural-connectome-trait presents a reduced fractional anisotropy pattern in first-degree relatives in the tracts connecting posterior areas and temporal areas. The family history of Alzheimer's disease structural-connectome-trait presents a posterior-posterior and posterior-temporal pattern, supplying new evidences to the cascading network failure model.
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Affiliation(s)
- F Ramírez-Toraño
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid 28223, Comunidad de Madrid, Spain
| | - Kausar Abbas
- Purdue Institute for Integrative Neuroscience, Purdue University, West-Lafayette, IN 46202, USA
- School of Industrial Engineering, Purdue University, West Lafayette, IN 46202, USA
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid 28223, Comunidad de Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN), Madrid 28029, Comunidad de Madrid, Spain
| | - Silvia Marcos de Pedro
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain
- Facultad de Educación y Salud, Universidad Camilo José Cela, Madrid 28010, Comunidad de Madrid, Spain
| | - Natividad Gómez-Ruiz
- Sección Neurorradiología, Servicio de Diagnóstico por Imagen, Hospital Clínico San Carlos, Madrid 28040, Comunidad de Madrid, Spain
| | - Ana Barabash
- Endocrinology and Nutrition Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid 28040, Comunidad de Madrid, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Madrid 28029, Comunidad de Madrid, Spain
| | - Ernesto Pereda
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain
- Electrical Engineering and Bioengineering Group, Department of Industrial Engineering & IUNE & ITB, Universidad de La Laguna, Santa Cruz de Tenerife 38205, Spain
| | - Alberto Marcos
- Neurology Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid 28040, Comunidad de Madrid, Spain
| | - Ramón López-Higes
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid 28223, Comunidad de Madrid, Spain
| | - Fernando Maestu
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Politécnica de Madrid, Madrid 28223, Comunidad de Madrid, Spain
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid 28223, Comunidad de Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN), Madrid 28029, Comunidad de Madrid, Spain
| | - Joaquín Goñi
- Purdue Institute for Integrative Neuroscience, Purdue University, West-Lafayette, IN 46202, USA
- School of Industrial Engineering, Purdue University, West Lafayette, IN 46202, USA
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 46202, USA
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61
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Toniolo S, Serra L, Olivito G, Caltagirone C, Mercuri NB, Marra C, Cercignani M, Bozzali M. Cerebellar White Matter Disruption in Alzheimer's Disease Patients: A Diffusion Tensor Imaging Study. J Alzheimers Dis 2021; 74:615-624. [PMID: 32065792 DOI: 10.3233/jad-191125] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The cognitive role of the cerebellum has recently gained much attention, and its pivotal role in Alzheimer's disease (AD) has now been widely recognized. Diffusion tensor imaging (DTI) has been used to evaluate the disruption of the microstructural milieu in AD, and though several white matter (WM) tracts such as corpus callosum, inferior and superior longitudinal fasciculus, cingulum, fornix, and uncinate fasciculus have been evaluated in AD, data on cerebellar WM tracts are currently lacking. We performed a tractography-based DTI reconstruction of the middle cerebellar peduncle (MCP), and the left and right superior cerebellar peduncles separately (SCPL and SCPR) and addressed the differences in fractional anisotropy (FA), axial diffusivity (Dax), radial diffusivity (RD), and mean diffusivity (MD) in the three tracts between 50 patients with AD and 25 healthy subjects. We found that AD patients showed a lower FA and a higher RD compared to healthy subjects in MCP, SCPL, and SCPR. Moreover, higher MD was found in SCPR and SCPL and higher Dax in SCPL. This result is important as it challenges the traditional view that WM bundles in the cerebellum are unaffected in AD and might identify new targets for therapeutic interventions.
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Affiliation(s)
- Sofia Toniolo
- Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Rome, Italy.,Department of Neuroscience, University of Rome 'Tor Vergata', Rome, Italy
| | - Laura Serra
- Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Rome, Italy
| | - Giusy Olivito
- Department of Psychology, Sapienza University of Rome, Rome, Italy.,Ataxia Research Laboratory-Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Carlo Caltagirone
- Department of Neuroscience, University of Rome 'Tor Vergata', Rome, Italy.,Ataxia Research Laboratory-Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | | | - Camillo Marra
- Department of Clinical and Behavioural Neurology, Fondazione Santa Lucia, IRCCS, Rome, Italy
| | | | - Marco Bozzali
- Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Rome, Italy.,Institute of Neurology, Catholic University, Rome, Italy
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62
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King-Robson J, Wilson H, Politis M. Associations Between Amyloid and Tau Pathology, and Connectome Alterations, in Alzheimer's Disease and Mild Cognitive Impairment. J Alzheimers Dis 2021; 82:541-560. [PMID: 34057079 DOI: 10.3233/jad-201457] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND The roles of amyloid-β and tau in the degenerative process of Alzheimer's disease (AD) remain uncertain. [18F]AV-45 and [18F]AV-1451 PET quantify amyloid-β and tau pathology, respectively, while diffusion tractography enables detection of their microstructural consequences. OBJECTIVE Examine the impact of amyloid-β and tau pathology on the structural connectome and cognition, in mild cognitive impairment (MCI) and AD. METHODS Combined [18F]AV-45 and [18F]AV-1451 PET, diffusion tractography, and cognitive assessment in 28 controls, 32 MCI, and 26 AD patients. RESULTS Hippocampal connectivity was reduced to the thalami, right lateral orbitofrontal, and right amygdala in MCI; alongside the insula, posterior cingulate, right entorhinal, and numerous cortical regions in AD (all p < 0.05). Hippocampal strength inversely correlated with [18F]AV-1451 SUVr in MCI (r = -0.55, p = 0.049) and AD (r = -0.57, p = 0.046), while reductions in hippocampal connectivity to ipsilateral brain regions correlated with increased [18F]AV-45 SUVr in those same regions in MCI (r = -0.33, p = 0.003) and AD (r = -0.31, p = 0.006). Cognitive scores correlated with connectivity of the right temporal pole in MCI (r = -0.60, p = 0.035) and left hippocampus in AD (r = 0.69, p = 0.024). Clinical Dementia Rating Scale scores correlated with [18F]AV-1451 SUVr in multiple areas reflecting Braak stages I-IV, including the right (r = 0.65, p = 0.004) entorhinal cortex in MCI; and Braak stages III-VI, including the right (r = 0.062, p = 0.009) parahippocampal gyrus in AD. CONCLUSION Reductions in hippocampal connectivity predominate in the AD connectome, correlating with hippocampal tau in MCI and AD, and with amyloid-β in the target regions of those connections. Cognitive scores correlate with microstructural changes and reflect the accumulation of tau pathology.
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Affiliation(s)
- Josh King-Robson
- Neurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
| | - Heather Wilson
- Neurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK.,Neurodegeneration Imaging Group, University of Exeter Medical School, London, UK
| | - Marios Politis
- Neurodegeneration Imaging Group, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK.,Neurodegeneration Imaging Group, University of Exeter Medical School, London, UK
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63
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Tao W, Li H, Li X, Huang R, Shao W, Guan Q, Zhang Z. Progressive Brain Degeneration From Subjective Cognitive Decline to Amnestic Mild Cognitive Impairment: Evidence From Large-Scale Anatomical Connection Classification Analysis. Front Aging Neurosci 2021; 13:687530. [PMID: 34322011 PMCID: PMC8312851 DOI: 10.3389/fnagi.2021.687530] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 06/07/2021] [Indexed: 11/13/2022] Open
Abstract
People with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) are both at high risk for Alzheimer’s disease (AD). Behaviorally, both SCD and aMCI have subjective reports of cognitive decline, but the latter suffers a more severe objective cognitive impairment than the former. However, it remains unclear how the brain develops from SCD to aMCI. In the current study, we aimed to investigate the topological characteristics of the white matter (WM) network that can successfully identify individuals with SCD or aMCI from healthy control (HC) and to describe the relationship of pathological changes between these two stages. To this end, three groups were recruited, including 22 SCD, 22 aMCI, and 22 healthy control (HC) subjects. We constructed WM network for each subject and compared large-scale topological organization between groups at both network and nodal levels. At the network level, the combined network indexes had the best performance in discriminating aMCI from HC. However, no indexes at the network level can significantly identify SCD from HC. These results suggested that aMCI but not SCD was associated with anatomical impairments at the network level. At the nodal level, we found that the short-path length can best differentiate between aMCI and HC subjects, whereas the global efficiency has the best performance in differentiating between SCD and HC subjects, suggesting that both SCD and aMCI had significant functional integration alteration compared to HC subjects. These results converged on the idea that the neural degeneration from SCD to aMCI follows a gradual process, from abnormalities at the nodal level to those at both nodal and network levels.
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Affiliation(s)
- Wuhai Tao
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China.,Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Hehui Li
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Rong Huang
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Wen Shao
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Qing Guan
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China.,Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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64
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Buyanova IS, Arsalidou M. Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review. Front Hum Neurosci 2021; 15:662031. [PMID: 34295229 PMCID: PMC8290169 DOI: 10.3389/fnhum.2021.662031] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/02/2021] [Indexed: 12/22/2022] Open
Abstract
White matter makes up about fifty percent of the human brain. Maturation of white matter accompanies biological development and undergoes the most dramatic changes during childhood and adolescence. Despite the advances in neuroimaging techniques, controversy concerning spatial, and temporal patterns of myelination, as well as the degree to which the microstructural characteristics of white matter can vary in a healthy brain as a function of age, gender and cognitive abilities still exists. In a selective review we describe methods of assessing myelination and evaluate effects of age and gender in nine major fiber tracts, highlighting their role in higher-order cognitive functions. Our findings suggests that myelination indices vary by age, fiber tract, and hemisphere. Effects of gender were also identified, although some attribute differences to methodological factors or social and learning opportunities. Findings point to further directions of research that will improve our understanding of the complex myelination-behavior relation across development that may have implications for educational and clinical practice.
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Affiliation(s)
- Irina S. Buyanova
- Neuropsy Lab, HSE University, Moscow, Russia
- Center for Language and Brain, HSE University, Moscow, Russia
| | - Marie Arsalidou
- Neuropsy Lab, HSE University, Moscow, Russia
- Cognitive Centre, Sirius University of Science and Technology, Sochi, Russia
- Department of Psychology, York University, Toronto, ON, Canada
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65
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Gyori NG, Clark CA, Alexander DC, Kaden E. On the potential for mapping apparent neural soma density via a clinically viable diffusion MRI protocol. Neuroimage 2021; 239:118303. [PMID: 34174390 PMCID: PMC8363942 DOI: 10.1016/j.neuroimage.2021.118303] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 06/16/2021] [Accepted: 06/22/2021] [Indexed: 12/14/2022] Open
Abstract
B-tensor encoding enables estimation of spherical cellular structures in the brain. Spherical compartments may provide markers for apparent neural soma density. Model parameters can be estimated in a fast and robust way using deep learning. Practical acquisition times are achievable on widely available clinical scanners.
Diffusion MRI is a valuable tool for probing tissue microstructure in the brain noninvasively. Today, model-based techniques are widely available and used for white matter characterisation where their development is relatively mature. Conversely, tissue modelling in grey matter is more challenging, and no generally accepted models exist. With advances in measurement technology and modelling efforts, a clinically viable technique that reveals salient features of grey matter microstructure, such as the density of quasi-spherical cell bodies and quasi-cylindrical cell projections, is an exciting prospect. As a step towards capturing the microscopic architecture of grey matter in clinically feasible settings, this work uses a biophysical model that is designed to disentangle the diffusion signatures of spherical and cylindrical structures in the presence of orientation heterogeneity, and takes advantage of B-tensor encoding measurements, which provide additional sensitivity compared to standard single diffusion encoding sequences. For the fast and robust estimation of microstructural parameters, we leverage recent advances in machine learning and replace conventional fitting techniques with an artificial neural network that fits complex biophysical models within seconds. Our results demonstrate apparent markers of spherical and cylindrical geometries in healthy human subjects, and in particular an increased volume fraction of spherical compartments in grey matter compared to white matter. We evaluate the extent to which spherical and cylindrical geometries may be interpreted as correlates of neural soma and neural projections, respectively, and quantify parameter estimation errors in the presence of various departures from the modelling assumptions. While further work is necessary to translate the ideas presented in this work to the clinic, we suggest that biomarkers focussing on quasi-spherical cellular geometries may be valuable for the enhanced assessment of neurodevelopmental disorders and neurodegenerative diseases.
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Affiliation(s)
- Noemi G Gyori
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.
| | - Christopher A Clark
- Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Enrico Kaden
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
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66
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Radhakrishnan H, Ubele MF, Krumholz SM, Boaz K, Mefford JL, Jones ED, Meacham B, Smiley J, Puskás LG, Powell DK, Norris CM, Stark CEL, Head E. Tacrolimus Protects against Age-Associated Microstructural Changes in the Beagle Brain. J Neurosci 2021; 41:5124-5133. [PMID: 33952632 PMCID: PMC8197636 DOI: 10.1523/jneurosci.0361-21.2021] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/09/2021] [Accepted: 04/16/2021] [Indexed: 11/21/2022] Open
Abstract
The overexpression of calcineurin leads to astrocyte hyperactivation, neuronal death, and inflammation, which are characteristics often associated with pathologic aging and Alzheimer's disease. In this study, we tested the hypothesis that tacrolimus, a calcineurin inhibitor, prevents age-associated microstructural atrophy, which we measured using higher-order diffusion MRI, in the middle-aged beagle brain (n = 30, male and female). We find that tacrolimus reduces hippocampal (p = 0.001) and parahippocampal (p = 0.002) neurite density index, as well as protects against an age-associated increase in the parahippocampal (p = 0.007) orientation dispersion index. Tacrolimus also protects against an age-related decrease in fractional anisotropy in the prefrontal cortex (p < 0.0001). We also show that these microstructural alterations precede cognitive decline and gross atrophy. These results support the idea that calcineurin inhibitors may have the potential to prevent aging-related pathology if administered at middle age.SIGNIFICANCE STATEMENT Hyperactive calcineurin signaling causes neuroinflammation and other neurobiological changes often associated with pathologic aging and Alzheimer's disease (AD). Controlling the expression of calcineurin before gross cognitive deficits are observable might serve as a promising avenue for preventing AD pathology. In this study, we show that the administration of the calcineurin inhibitor, tacrolimus, over 1 year prevents age- and AD-associated microstructural changes in the hippocampus, parahippocampal cortex, and prefrontal cortex of the middle-aged beagle brain, with no noticeable adverse effects. Tacrolimus is already approved by the Food and Drug Administration for use in humans to prevent solid organ transplant rejection, and our results bolster the promise of this drug to prevent AD and aging-related pathology.
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Affiliation(s)
- Hamsanandini Radhakrishnan
- Mathematical, Computational and Systems Biology, University of California, Irvine, Irvine, California 92697
| | - Margo F Ubele
- Sanders Brown Center on Aging, Department of Pharmacology and Nutritional Sciences, College of Medicine, University of Kentucky, Lexington, Kentucky 40506
| | - Stephanie M Krumholz
- Sanders Brown Center on Aging, Department of Pharmacology and Nutritional Sciences, College of Medicine, University of Kentucky, Lexington, Kentucky 40506
| | - Kathy Boaz
- Sanders Brown Center on Aging, Department of Pharmacology and Nutritional Sciences, College of Medicine, University of Kentucky, Lexington, Kentucky 40506
| | - Jennifer L Mefford
- Division of Laboratory Animal Resources, University of Kentucky, Lexington, Kentucky 40506
| | - Erin Denhart Jones
- Division of Laboratory Animal Resources, University of Kentucky, Lexington, Kentucky 40506
| | - Beverly Meacham
- Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, Kentucky 40506
| | - Jeffrey Smiley
- Division of Laboratory Animal Resources, University of Kentucky, Lexington, Kentucky 40506
| | | | - David K Powell
- Magnetic Resonance Imaging and Spectroscopy Center, University of Kentucky, Lexington, Kentucky 40506
| | - Christopher M Norris
- Sanders Brown Center on Aging, Department of Pharmacology and Nutritional Sciences, College of Medicine, University of Kentucky, Lexington, Kentucky 40506
| | - Craig E L Stark
- Mathematical, Computational and Systems Biology, University of California, Irvine, Irvine, California 92697
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, California 92697
| | - Elizabeth Head
- Department of Pathology & Laboratory Medicine, University of California, Irvine, Irvine, California 92697
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67
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Kara F, Belloy ME, Voncken R, Sarwari Z, Garima Y, Anckaerts C, Langbeen A, Leysen V, Shah D, Jacobs J, Hamaide J, Bols P, Van Audekerke J, Daans J, Guglielmetti C, Kantarci K, Prevot V, Roßner S, Ponsaerts P, Van der Linden A, Verhoye M. Long-term ovarian hormone deprivation alters functional connectivity, brain neurochemical profile and white matter integrity in the Tg2576 amyloid mouse model of Alzheimer's disease. Neurobiol Aging 2021; 102:139-150. [PMID: 33765427 PMCID: PMC8312737 DOI: 10.1016/j.neurobiolaging.2021.02.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 02/05/2021] [Accepted: 02/16/2021] [Indexed: 01/18/2023]
Abstract
Premenopausal bilateral ovariectomy is considered to be one of the risk factors of Alzheimer's disease (AD). However, the underlying mechanisms remain unclear. Here, we aimed to investigate long-term neurological consequences of ovariectomy in a rodent AD model, TG2576 (TG), and wild-type mice (WT) that underwent an ovariectomy or sham-operation, using in vivo MRI biomarkers. An increase in osmoregulation and energy metabolism biomarkers in the hypothalamus, a decrease in white matter integrity, and a decrease in the resting-state functional connectivity was observed in ovariectomized TG mice compared to sham-operated TG mice. In addition, we observed an increase in functional connectivity in ovariectomized WT mice compared to sham-operated WT mice. Furthermore, genotype (TG vs. WT) effects on imaging markers and GFAP immunoreactivity levels were observed, but there was no effect of interaction (Genotype × Surgery) on amyloid-beta-and GFAP immunoreactivity levels. Taken together, our results indicated that both genotype and ovariectomy alters imaging biomarkers associated with AD.
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Affiliation(s)
- Firat Kara
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
| | - Michael E Belloy
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Rick Voncken
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Zahra Sarwari
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Yadav Garima
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Cynthia Anckaerts
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - An Langbeen
- Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, Antwerp, Belgium
| | - Valerie Leysen
- Univ. Lille, Inserm, CHU Lille, Development and Plasticity of the Neuroendocrine Brain, Lille Neurosciences and Cognition, UMR-S1172, DistalZ, Lille, France
| | - Disha Shah
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Jules Jacobs
- University of Nijmegen, Nijmegen, the Netherlands
| | - Julie Hamaide
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Peter Bols
- Veterinary Physiology and Biochemistry, Department of Veterinary Sciences, University of Antwerp, Antwerp, Belgium
| | - Johan Van Audekerke
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Jasmijn Daans
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (Vaxinfectio), University of Antwerp, Antwerp, Belgium
| | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Vincent Prevot
- Univ. Lille, Inserm, CHU Lille, Development and Plasticity of the Neuroendocrine Brain, Lille Neurosciences and Cognition, UMR-S1172, DistalZ, Lille, France
| | - Steffen Roßner
- Paul Flechsig Institute of Brain Research, Leipzig University, Leipzig, Germany
| | - Peter Ponsaerts
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (Vaxinfectio), University of Antwerp, Antwerp, Belgium
| | - Annemie Van der Linden
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Marleen Verhoye
- Bio-imaging Lab- Member of INMIND consortium, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
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68
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Lee J, Ju G, Son JW, Shin CJ, Lee SI, Park H, Kim S. White matter integrity in alcohol-dependent patients with long-term abstinence. Medicine (Baltimore) 2021; 100:e26078. [PMID: 34032740 PMCID: PMC8154411 DOI: 10.1097/md.0000000000026078] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 05/05/2021] [Indexed: 11/26/2022] Open
Abstract
Based on association studies on amounts of alcohol consumed and cortical and subcortical structural shrinkage, we investigated the effect of chronic alcohol consumption on white matter pathways using probabilistic tractography.Twenty-three alcohol-dependent men (with an average sobriety of 13.1 months) from a mental health hospital and 22 age-matched male healthy social drinkers underwent 3T magnetic resonance imaging. Eighteen major white matter pathways were reconstructed using the TRActs Constrained by UnderLying Anatomy tool (provided by the FreeSurfer). The hippocampal volumes were estimated using an automated procedure. The lifetime drinking history interview, Alcohol Use Disorder Identification Test, Brief Michigan Alcoholism Screening Test, and pack-years of smoking were also evaluated.Analysis of covariance controlling for age, cigarette smoking, total motion index indicated that there was no definite difference of diffusion parameters between the 2 groups after multiple comparison correction. As hippocampal volume decreased, the fractional anisotropy of the right cingulum-angular bundle decreased. Additionally, the axial diffusivity of right cingulum-angular bundle was positively correlated with the alcohol abstinence period.The results imply resilience of white matter in patients with alcohol dependence. Additional longitudinal studies with multimodal methods and neuropsychological tests may improve our findings of the changes in white matter pathways in patients with alcohol dependence.
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Affiliation(s)
- Jeonghwan Lee
- Department of Psychiatry, Chungbuk National University Hospital
- Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, South Korea
| | - Gawon Ju
- Department of Psychiatry, Chungbuk National University Hospital
- Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, South Korea
| | - Jung-Woo Son
- Department of Psychiatry, Chungbuk National University Hospital
- Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, South Korea
| | - Chul-Jin Shin
- Department of Psychiatry, Chungbuk National University Hospital
- Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, South Korea
| | - Sang Ick Lee
- Department of Psychiatry, Chungbuk National University Hospital
- Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, South Korea
| | - Hyemi Park
- Department of Psychiatry, Chungbuk National University Hospital
- Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, South Korea
| | - Siekyeong Kim
- Department of Psychiatry, Chungbuk National University Hospital
- Department of Psychiatry, Chungbuk National University College of Medicine, Cheongju, South Korea
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69
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Raghavan S, Reid RI, Przybelski SA, Lesnick TG, Graff-Radford J, Schwarz CG, Knopman DS, Mielke MM, Machulda MM, Petersen RC, Jack CR, Vemuri P. Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition. Brain Commun 2021; 3:fcab106. [PMID: 34136811 PMCID: PMC8202149 DOI: 10.1093/braincomms/fcab106] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 03/24/2021] [Accepted: 04/12/2021] [Indexed: 01/20/2023] Open
Abstract
White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to demographics, common age-related pathological processes (amyloid, tau and white matter hyperintensities) and cognition. We also compared Neurite Orientation Dispersion and Density Imaging findings to the older Diffusion Tensor Imaging model-based findings. Three hundred and twenty-eight participants (264 cognitively unimpaired, 57 mild cognitive impairment and 7 dementia with a mean age of 68.3 ± 13.1 years) from the Mayo Clinic Study of Aging with multi-shell diffusion imaging, fluid attenuated inversion recovery MRI as well as amyloid and tau PET scans were included in this study. White matter tract level diffusion measures were calculated from Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, white matter hyperintensities, amyloid and tau as predictors. Analyses were also performed with each diffusion MRI measure as a predictor of cognitive outcomes. Age and white matter hyperintensities were the strongest predictors of all white matter diffusion measures with low associations with amyloid and tau. However, neurite density decrease from Neurite Orientation Dispersion and Density Imaging was observed with amyloidosis specifically in the temporal lobes. White matter integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures. All diffusion measures provided information about white matter ageing and white matter changes due to age-related pathological processes and were associated with cognition. Neurite orientation dispersion and density imaging and diffusion tensor imaging are two different diffusion models that provide distinct information about variation in white matter microstructural integrity. Neurite Orientation Dispersion and Density Imaging provides additional information about synaptic density, organization and free water content which may aid in providing mechanistic insights into disease progression.
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Affiliation(s)
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - David S Knopman
- Department of Neurology, Mayo Clinic, 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 Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
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70
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Pichet Binette A, Theaud G, Rheault F, Roy M, Collins DL, Levin J, Mori H, Lee JH, Farlow MR, Schofield P, Chhatwal JP, Masters CL, Benzinger T, Morris J, Bateman R, Breitner JC, Poirier J, Gonneaud J, Descoteaux M, Villeneuve S. Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer's disease. eLife 2021; 10:62929. [PMID: 33983116 PMCID: PMC8169107 DOI: 10.7554/elife.62929] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 05/12/2021] [Indexed: 12/12/2022] Open
Abstract
Beta-amyloid (Aβ) and tau proteins, the pathological hallmarks of Alzheimer's disease (AD), are believed to spread through connected regions of the brain. Combining diffusion imaging and positron emission tomography, we investigated associations between white matter microstructure specifically in bundles connecting regions where Aβ or tau accumulates and pathology. We focused on free-water-corrected diffusion measures in the anterior cingulum, posterior cingulum, and uncinate fasciculus in cognitively normal older adults at risk of sporadic AD and presymptomatic mutation carriers of autosomal dominant AD. In Aβ-positive or tau-positive groups, lower tissue fractional anisotropy and higher mean diffusivity related to greater Aβ and tau burden in both cohorts. Associations were found in the posterior cingulum and uncinate fasciculus in preclinical sporadic AD, and in the anterior and posterior cingulum in presymptomatic mutation carriers. These results suggest that microstructural alterations accompany pathological accumulation as early as the preclinical stage of both sporadic and autosomal dominant AD.
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Affiliation(s)
- Alexa Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Guillaume Theaud
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - François Rheault
- Electrical Engineering, Vanderbilt University, Nashville, United States
| | - Maggie Roy
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - D Louis Collins
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Hiroshi Mori
- Department of Clinical Neuroscience, Osaka City University Medical School, Osaka, Japan
| | - Jae Hong Lee
- Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | | | - Peter Schofield
- Neuroscience Research Australia, Sydney, Australia.,School of Medical Sciences, UNSW Sydney, Sydney, Australia
| | - Jasmeer P Chhatwal
- Harvard Medical School, Massachusetts General Hospital, Boston, United States
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
| | - Tammie Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - John Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - Randall Bateman
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, United States.,Department of Neurology, Washington University School of Medicine, St. Louis, United States
| | - John Cs Breitner
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Judes Poirier
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada
| | - Julie Gonneaud
- Douglas Mental Health University Institute, Montreal, Canada.,Normandie Univ, UNICAEN, INSERM, U1237, Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Sylvia Villeneuve
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Canada.,Douglas Mental Health University Institute, Montreal, Canada.,McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
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71
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Massalimova A, Ni R, Nitsch RM, Reisert M, von Elverfeldt D, Klohs J. Diffusion Tensor Imaging Reveals Whole-Brain Microstructural Changes in the P301L Mouse Model of Tauopathy. NEURODEGENER DIS 2021; 20:173-184. [PMID: 33975312 DOI: 10.1159/000515754] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 03/05/2021] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Increased expression of hyperphosphorylated tau and the formation of neurofibrillary tangles are associated with neuronal loss and white matter damage. Using high-resolution ex vivo diffusion tensor imaging (DTI), we investigated microstructural changes in the white and grey matter in the P301L mouse model of human tauopathy at 8.5 months of age. For unbiased computational analysis, we implemented a pipeline for voxel-based analysis (VBA) and atlas-based analysis (ABA) of DTI mouse brain data. METHODS Hemizygous and homozygous transgenic P301L mice and non-transgenic littermates were used. DTI data were acquired for generation of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) maps. VBA on the entire brain was performed using SPM8 and the SPM Mouse toolbox. Initially, all DTI maps were coregistered with the Allen mouse brain atlas to bring them to one common coordinate space. In VBA, coregistered DTI maps were normalized and smoothed in order to perform two-sample and unpaired t tests with false discovery rate correction to compare hemizygotes with non-transgenic littermates, homozygotes with non-transgenic littermates, and hemizygotes with homozygotes on each DTI parameter map. In ABA, the average values for selected regions of interests were computed with coregistered DTI maps and labels in Allen mouse brain atlas. Afterwards, a Kruskal-Wallis one-way ANOVA on ranks with a Tukey post hoc test was executed on the estimated average values. RESULTS With VBA, we found pronounced and brain-wide spread changes when comparing homozygous, P301L mice with non-transgenic littermates, which were not seen when comparing hemizygous P301L with non-transgenic animals. Statistical comparison of DTI metrics in selected brain regions by ABA corroborated findings from VBA. FA was found to be decreased in most brain regions, while MD, RD, and AD were increased in homozygotes compared to hemizygotes and non-transgenic littermates. DISCUSSION/CONCLUSION High-resolution ex vivo DTI demonstrated brain-wide microstructural and gene-dose-dependent changes in the P301L mouse model of human tauopathy. The DTI analysis pipeline may serve for the phenotyping of models of tauopathy and other brain diseases.
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Affiliation(s)
- Aidana Massalimova
- Institute for Biomedical Engineering, ETH & University of Zurich, Zurich, Switzerland
| | - Ruiqing Ni
- Institute for Biomedical Engineering, ETH & University of Zurich, Zurich, Switzerland
| | - Roger M Nitsch
- Zurich Neuroscience Center (ZNZ), Zurich, Switzerland.,Institute for Regenerative Medicine, University of Zurich, Schlieren, Switzerland
| | - Marco Reisert
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dominik von Elverfeldt
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jan Klohs
- Institute for Biomedical Engineering, ETH & University of Zurich, Zurich, Switzerland.,Zurich Neuroscience Center (ZNZ), Zurich, Switzerland
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72
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Wong D, Atiya S, Fogarty J, Montero-Odasso M, Pasternak SH, Brymer C, Borrie MJ, Bartha R. Reduced Hippocampal Glutamate and Posterior Cingulate N-Acetyl Aspartate in Mild Cognitive Impairment and Alzheimer's Disease Is Associated with Episodic Memory Performance and White Matter Integrity in the Cingulum: A Pilot Study. J Alzheimers Dis 2021; 73:1385-1405. [PMID: 31958093 DOI: 10.3233/jad-190773] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Identification of biological changes underlying the early symptoms of Alzheimer's disease (AD) will help to identify and stage individuals prior to symptom onset. The limbic system, which supports episodic memory and is impaired early in AD, is a primary target. In this study, brain metabolism and microstructure evaluated by high field (7 Tesla) proton magnetic resonance spectroscopy (1H-MRS) and diffusion tensor imaging (DTI) were evaluated in the limbic system of eight individuals with mild cognitive impairment (MCI), nine with AD, and sixteen normal elderly controls (NEC). Left hippocampal glutamate and posterior cingulate N-acetyl aspartate concentrations were reduced in MCI and AD compared to NEC. Differences in DTI metrics indicated volume and white matter loss along the cingulum in AD compared to NEC. Metabolic and microstructural changes were associated with episodic memory performance assessed using Craft Story 21 Recall and Benson Complex Figure Copy. The current study suggests that metabolite concentrations measured using 1H-MRS may provide insight into the underlying metabolic and microstructural processes of episodic memory impairment.
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Affiliation(s)
- Dickson Wong
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
| | - Samir Atiya
- Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Jennifer Fogarty
- Parkwood Institute Research Program, Lawson Health Research Institute, London, ON, Canada
| | - Manuel Montero-Odasso
- Parkwood Institute Research Program, Lawson Health Research Institute, London, ON, Canada.,Geriatric Medicine, University of Western Ontario, London, ON, Canada.,Gait and Brain Lab, Parkwood Institute, Lawson Health Research Institute, London, ON, Canada.,Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Stephen H Pasternak
- Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada.,Parkwood Institute Research Program, Lawson Health Research Institute, London, ON, Canada
| | - Chris Brymer
- Geriatric Medicine, University of Western Ontario, London, ON, Canada
| | - Michael J Borrie
- Parkwood Institute Research Program, Lawson Health Research Institute, London, ON, Canada.,Geriatric Medicine, University of Western Ontario, London, ON, Canada
| | - Robert Bartha
- Department of Medical Biophysics, University of Western Ontario, London, ON, Canada.,Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
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73
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Li X, Xia J, Ma C, Chen K, Xu K, Zhang J, Chen Y, Li H, Wei D, Zhang Z. Accelerating Structural Degeneration in Temporal Regions and Their Effects on Cognition in Aging of MCI Patients. Cereb Cortex 2021; 30:326-338. [PMID: 31169867 DOI: 10.1093/cercor/bhz090] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Revised: 03/06/2019] [Accepted: 03/28/2019] [Indexed: 12/20/2022] Open
Abstract
Age is the major risk factor for Alzheimer's disease (AD) and for mild cognitive impairment (MCI). However, there is limited evidence about MCI-specific aging-related simultaneous changes of the brain structure and their impact on cognition. We analyzed the brain imaging data from 269 subjects (97 MCI patients and 172 cognitively normal [CN] elderly) using voxel-based morphometry and tract-based spatial statistics procedures to explore the special structural pattern during aging. We found that the patients with MCI showed accelerated age-related reductions in gray matter volume in the left planum temporale, thalamus, and posterior cingulate gyrus. The similar age×group interaction effect was found in the fractional anisotropy of the bilateral parahippocampal cingulum white matter tract, which connects the temporal regions. Importantly, the age-related temporal gray matter and white matter alterations were more significantly related to performance in memory and attention tasks in MCI patients. The accelerated degeneration patterns in the brain structure provide evidence for different neural mechanisms underlying aging in MCI patients. Temporal structural degeneration may serve as a potential imaging marker for distinguishing the progression of the preclinical AD stage from normal aging.
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Affiliation(s)
- Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China
| | - Jianan Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China
| | - Chao Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China.,School of Electrical and Information Engineering, Tianjin University, Tianjin, P. R. China
| | - Kewei Chen
- BABRI Centre, Beijing Normal University, Beijing, P. R. China.,Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Kai Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China
| | - Junying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China.,Institute of Basic Research in Clinical Medicine, China Academy of Traditional Chinese Medicine, Beijing, P. R. China
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China
| | - He Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China.,Institute of Basic Research in Clinical Medicine, China Academy of Traditional Chinese Medicine, Beijing, P. R. China
| | - Dongfeng Wei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China.,Institute of Basic Research in Clinical Medicine, China Academy of Traditional Chinese Medicine, Beijing, P. R. China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, P. R. China.,BABRI Centre, Beijing Normal University, Beijing, P. R. China
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Mak E, Dounavi ME, Low A, Carter SF, McKiernan E, Williams GB, Jones PS, Carriere I, Muniz GT, Ritchie K, Ritchie C, Su L, O'Brien JT. Proximity to dementia onset and multi-modal neuroimaging changes: The prevent-dementia study. Neuroimage 2021; 229:117749. [PMID: 33454416 DOI: 10.1016/j.neuroimage.2021.117749] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 12/22/2020] [Accepted: 01/08/2021] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND First-degree relatives of people with dementia (FH+) are at increased risk of developing Alzheimer's disease (AD). Here, we investigate "estimated years to onset of dementia" (EYO) as a surrogate marker of preclinical disease progression and assess its associations with multi-modal neuroimaging biomarkers. METHODS 89 FH+ participants in the PREVENT-Dementia study underwent longitudinal MR imaging over 2 years. EYO was calculated as the difference between the parental age of dementia diagnosis and the current age of the participant (mean EYO = 23.9 years). MPRAGE, ASL and DWI data were processed using Freesurfer, FSL-BASIL and DTI-TK. White matter lesion maps were segmented from FLAIR scans. The SPM Sandwich Estimator Toolbox was used to test for the main effects of EYO and interactions between EYO, Time, and APOE-ε4+. Threshold free cluster enhancement and family wise error rate correction (TFCE FWER) was performed on voxelwise statistical maps. RESULTS There were no significant effects of EYO on regional grey matter atrophy or white matter hyperintensities. However, a shorter EYO was associated with lower white matter Fractional Anisotropy and elevated Mean/Radial Diffusivity, particularly in the corpus callosum (TFCEFWERp < 0.05). The influence of EYO on white matter deficits were significantly stronger compared to that of normal ageing. APOE-ε4 carriers exhibited hyperperfusion with nearer proximity to estimated onset in temporo-parietal regions. There were no interactions between EYO and time, suggesting that EYO was not associated with accelerated imaging changes in this sample. CONCLUSIONS Amongst cognitively normal midlife adults with a family history of dementia, a shorter hypothetical proximity to dementia onset may be associated with incipient brain abnormalities, characterised by white matter disruptions and perfusion abnormalities, particularly amongst APOE-ε4 carriers. Our findings also confer biological validity to the construct of EYO as a potential stage marker of preclinical progression in the context of sporadic dementia. Further clinical follow-up of our longitudinal sample would provide critical validation of these findings.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK.
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - Stephen F Carter
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - Elizabeth McKiernan
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - Guy B Williams
- Department of Clinical Neurosciences and Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - P Simon Jones
- Department of Clinical Neurosciences and Wolfson Brain Imaging Centre, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Isabelle Carriere
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | | | - Karen Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK; INSERM and University of Montpellier, Montpellier, France
| | - Craig Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
| | - John T O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SP, UK
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Wang X, Zhao M, Lin L, Han Y. Plasma β-Amyloid Levels Associated With Structural Integrity Based on Diffusion Tensor Imaging in Subjective Cognitive Decline: The SILCODE Study. Front Aging Neurosci 2021; 12:592024. [PMID: 33510631 PMCID: PMC7835390 DOI: 10.3389/fnagi.2020.592024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 12/11/2020] [Indexed: 11/26/2022] Open
Abstract
Background: Accumulating evidence has demonstrated that plasma β-amyloid (Aβ) levels are useful biomarkers to reflect brain amyloidosis and gray matter structure, but little is known about their correlation with subclinical white matter (WM) integrity in individuals at risk of Alzheimer's disease (AD). Here, we investigated the microstructural changes in WM between subjects with low and high plasma Aβ levels among individuals with subjective cognitive decline (SCD). Methods: This study included 142 cognitively normal individuals with SCD who underwent a battery of neuropsychological tests, plasma Aβ measurements, and diffusion tensor imaging (DTI) based on the Sino Longitudinal Study on Cognitive Decline (SILCODE). Using tract-based spatial statistics (TBSS), we compared fractional anisotropy (FA), and mean diffusivity (MD) in WM between subjects with low (N = 71) and high (N = 71) plasma Aβ levels (cut-off: 761.45 pg/ml for Aβ40 and 10.74 pg/ml for Aβ42). Results: We observed significantly decreased FA and increased MD in the high Aβ40 group compared to the low Aβ40 group in various regions, including the body, the genu, and the splenium of the corpus callosum; the superior longitudinal fasciculus; the corona radiata; the thalamic radiation; the external and internal capsules; the inferior fronto-occipital fasciculus; and the sagittal stratum [p < 0.05, familywise error (FWE) corrected]. Average FA values were associated with poor performance on executive and memory assessments. No significant differences were found in either MD or FA between the low and high Aβ42 groups. Conclusion: Our results suggest that a correlation exists between WM integrity and plasma Aβ40 levels in individuals with SCD.
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Affiliation(s)
- Xiaoni Wang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Mingyan Zhao
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Li Lin
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.,National Clinical Research Center for Geriatric Disorders, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
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76
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To XV, Nasrallah FA. A roadmap of brain recovery in a mouse model of concussion: insights from neuroimaging. Acta Neuropathol Commun 2021; 9:2. [PMID: 33407949 PMCID: PMC7789702 DOI: 10.1186/s40478-020-01098-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 12/01/2020] [Indexed: 12/17/2022] Open
Abstract
Concussion or mild traumatic brain injury is the most common form of traumatic brain injury with potentially long-term consequences. Current objective diagnosis and treatment options are limited to clinical assessment, cognitive rest, and symptom management, which raises the real danger of concussed patients being released back into activities where subsequent and cumulative injuries may cause disproportionate damages. This study conducted a cross-sectional multi-modal examination investigation of the temporal changes in behavioural and brain changes in a mouse model of concussion using magnetic resonance imaging. Sham and concussed mice were assessed at day 2, day 7, and day 14 post-sham or injury procedures following a single concussion event for motor deficits, psychological symptoms with open field assessment, T2-weighted structural imaging, diffusion tensor imaging (DTI), neurite orientation density dispersion imaging (NODDI), stimulus-evoked and resting-state functional magnetic resonance imaging (fMRI). Overall, a mismatch in the temporal onsets and durations of the behavioural symptoms and structural/functional changes in the brain was seen. Deficits in behaviour persisted until day 7 post-concussion but recovered at day 14 post-concussion. DTI and NODDI changes were most extensive at day 7 and persisted in some regions at day 14 post-concussion. A persistent increase in connectivity was seen at day 2 and day 14 on rsfMRI. Stimulus-invoked fMRI detected increased cortical activation at day 7 and 14 post-concussion. Our results demonstrate the capabilities of advanced MRI in detecting the effects of a single concussive impact in the brain, and highlight a mismatch in the onset and temporal evolution of behaviour, structure, and function after a concussion. These results have significant translational impact in developing methods for the detection of human concussion and the time course of brain recovery.
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78
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Batouli SAH, Sisakhti M, Haghshenas S, Dehghani H, Sachdev P, Ekhtiari H, Kochan N, Wen W, Leemans A, Kohanpour M, Oghabian MA. Iranian Brain Imaging Database: A Neuropsychiatric Database of Healthy Brain. Basic Clin Neurosci 2021; 12:115-132. [PMID: 33995934 PMCID: PMC8114860 DOI: 10.32598/bcn.12.1.1774.2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 06/19/2019] [Indexed: 12/11/2022] Open
Abstract
INTRODUCTION The Iranian Brain Imaging Database (IBID) was initiated in 2017, with 5 major goals: provide researchers easy access to a neuroimaging database, provide normative quantitative measures of the brain for clinical research purposes, study the aging profile of the brain, examine the association of brain structure and function, and join the ENIGMA consortium. Many prestigious databases with similar goals are available. However, they were not done on an Iranian population, and the battery of their tests (e.g. cognitive tests) is selected based on their specific questions and needs. METHODS The IBID will include 300 participants (50% female) in the age range of 20 to 70 years old, with an equal number of participants (#60) in each age decade. It comprises a battery of cognitive, lifestyle, medical, and mental health tests, in addition to several Magnetic Resonance Imaging (MRI) protocols. Each participant completes the assessments on two referral days. RESULTS The study currently has a cross-sectional design, but longitudinal assessments are considered for the future phases of the study. Here, details of the methodology and the initial results of assessing the first 152 participants of the study are provided. CONCLUSION IBID is established to enable research into human brain function, to aid clinicians in disease diagnosis research, and also to unite the Iranian researchers with interests in the brain.
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Affiliation(s)
- Seyed Amir Hossein Batouli
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
- Departmen of Neuroimaging and Analysis, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Minoo Sisakhti
- Departmen of Neuroimaging and Analysis, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Institute for Cognitive Sciences Studies, Tehran, Iran
| | - Shirin Haghshenas
- Departmen of Neuroimaging and Analysis, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Hamed Dehghani
- Departmen of Neuroimaging and Analysis, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Perminder Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, Australia
| | | | - Nicole Kochan
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Mohsen Kohanpour
- Departmen of Neuroimaging and Analysis, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Oghabian
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
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79
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Zeng HM, Han HB, Zhang QF, Bai H. Application of modern neuroimaging technology in the diagnosis and study of Alzheimer's disease. Neural Regen Res 2021; 16:73-79. [PMID: 32788450 PMCID: PMC7818875 DOI: 10.4103/1673-5374.286957] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Neurological abnormalities identified via neuroimaging are common in patients with Alzheimer’s disease. However, it is not yet possible to easily detect these abnormalities using head computed tomography in the early stages of the disease. In this review, we evaluated the ways in which modern imaging techniques such as positron emission computed tomography, single photon emission tomography, magnetic resonance spectrum imaging, structural magnetic resonance imaging, magnetic resonance diffusion tensor imaging, magnetic resonance perfusion weighted imaging, magnetic resonance sensitive weighted imaging, and functional magnetic resonance imaging have revealed specific changes not only in brain structure, but also in brain function in Alzheimer’s disease patients. The reviewed literature indicated that decreased fluorodeoxyglucose metabolism in the temporal and parietal lobes of Alzheimer’s disease patients is frequently observed via positron emission computed tomography. Furthermore, patients with Alzheimer’s disease often show a decreased N-acetylaspartic acid/creatine ratio and an increased myoinositol/creatine ratio revealed via magnetic resonance imaging. Atrophy of the entorhinal cortex, hippocampus, and posterior cingulate gyrus can be detected early using structural magnetic resonance imaging. Magnetic resonance sensitive weighted imaging can show small bleeds and abnormal iron metabolism. Task-related functional magnetic resonance imaging can display brain function activity through cerebral blood oxygenation. Resting functional magnetic resonance imaging can display the functional connection between brain neural networks. These are helpful for the differential diagnosis and experimental study of Alzheimer’s disease, and are valuable for exploring the pathogenesis of Alzheimer’s disease.
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Affiliation(s)
- Hong-Mei Zeng
- Department of Neurology, Third Affiliated Hospital of Guizhou Medical University, Duyun; Department of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, China
| | - Hua-Bo Han
- Department of Radiology, Third Affiliated Hospital of Guizhou Medical University, Duyun, Guizhou Province, China
| | - Qi-Fang Zhang
- Key Laboratory of Endemic and Ethnic Diseases of Ministry of Education, and Key Laboratory of Medical Molecular Biology, Guizhou Medical University, Guiyang, Guizhou Province, China
| | - Hua Bai
- Department of Neurology, Third Affiliated Hospital of Guizhou Medical University, Duyun; Department of Neurology, Affiliated Hospital of Guizhou Medical University, Guiyang; Medical Experiment Center, Third Affiliated Hospital of Guizhou Medical University, Duyun, Guizhou Province, China
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80
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Wen Q, Risacher SL, Xie L, Li J, Harezlak J, Farlow MR, Unverzagt FW, Gao S, Apostolova LG, Saykin AJ, Wu YC. Tau-related white-matter alterations along spatially selective pathways. Neuroimage 2020; 226:117560. [PMID: 33189932 PMCID: PMC8364310 DOI: 10.1016/j.neuroimage.2020.117560] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 11/08/2020] [Indexed: 01/07/2023] Open
Abstract
Progressive accumulation of tau neurofibrillary tangles in the brain is a defining pathologic feature of Alzheimer’s disease (AD). Tau pathology exhibits a predictable spatiotemporal spreading pattern, but the underlying mechanisms of this spread are poorly understood. Although AD is conventionally considered a disease of the gray matter, it is also associated with pronounced and progressive deterioration of the white matter (WM). A link between abnormal tau and WM degeneration is suggested by findings from both animal and postmortem studies, but few studies demonstrated their interplay in vivo. Recent advances in diffusion magnetic resonance imaging and the availability of tau positron emission tomography (PET) have made it possible to evaluate the association of tau and WM degeneration (tau-WM) in vivo. In this study, we explored the spatial pattern of tau-WM associations across the whole brain to evaluate the hypothesis that tau deposition is associated with WM microstructural alterations not only in isolated tracts, but in continuous structural connections in a stereotypic pattern. Sixty-two participants, including 22 cognitively normal subjects, 22 individuals with subjective cognitive decline, and 18 with mild cognitive impairment were included in the study. WM characteristics were inferred by classic diffusion tensor imaging (DTI) and a complementary diffusion compartment model – neurite orientation dispersion and density imaging (NODDI) that provides a proxy for axonal density. A data-driven iterative searching (DDIS) approach, coupled with whole-brain graph theory analyses, was developed to continuously track tau-WM association patterns. Without applying prior knowledge of the tau spread, we observed a distinct spatial pattern that resembled the typical propagation of tau pathology in AD. Such association pattern was not observed between diffusion and amyloid-β PET signal. Tau-related WM degeneration is characterized by an increase in the mean diffusivity (with a dominant change in the radial direction) and a decrease in the intra-axonal volume fraction. These findings suggest that cortical tau deposition (as measured in tau PET) is associated with a lower axonal packing density and greater diffusion freedom. In conclusion, our in vivo findings using a data-driven method on cross-sectional data underline the important role of WM alterations in the AD pathological cascade with an association pattern similar to the postmortem Braak staging of AD. Future studies will focus on longitudinal analyses to provide in vivo evidence of tau pathology spreads along neuroanatomically connected brain areas.
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Affiliation(s)
- Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine,, Indianapolis, IN 46202, USA; Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine,, Indianapolis, IN 46202, USA; Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Linhui Xie
- Department of Electrical and Computer Engineering, Indiana University Purdue University Indianapolis, IN, USA
| | - Junjie Li
- University Information Technology Service - Research Technology, Indiana University, Indianapolis, IN, USA
| | - Jaroslaw Harezlak
- Department of Epidemiology and Biostatistics, School of Public Health, Indiana University, Bloomington, IN, USA
| | - Martin R Farlow
- Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Frederick W Unverzagt
- Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Clinical Psychology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sujuan Gao
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liana G Apostolova
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine,, Indianapolis, IN 46202, USA; Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine,, Indianapolis, IN 46202, USA; Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Clinical Psychology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine,, Indianapolis, IN 46202, USA; Indiana Alzheimer Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
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81
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Finsterwalder S, Vlegels N, Gesierich B, Caballero MÁA, Weaver NA, Franzmeier N, Georgakis MK, Konieczny MJ, Koek HL, Karch CM, Graff-Radford NR, Salloway S, Oh H, Allegri RF, Chhatwal JP, Jessen F, Düzel E, Dobisch L, Metzger C, Peters O, Incesoy EI, Priller J, Spruth EJ, Schneider A, Fließbach K, Buerger K, Janowitz D, Teipel SJ, Kilimann I, Laske C, Buchmann M, Heneka MT, Brosseron F, Spottke A, Roy N, Ertl-Wagner B, Scheffler K, Seo SW, Kim Y, Na DL, Kim HJ, Jang H, Ewers M, Levin J, Schmidt R, Pasternak O, Dichgans M, Biessels GJ, Duering M. Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients. Alzheimers Dement 2020; 16:1504-1514. [PMID: 32808747 PMCID: PMC8102202 DOI: 10.1002/alz.12150] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 06/25/2020] [Accepted: 06/25/2020] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Microstructural alterations as assessed by diffusion tensor imaging (DTI) are key findings in both Alzheimer's disease (AD) and small vessel disease (SVD). We determined the contribution of each of these conditions to diffusion alterations. METHODS We studied six samples (N = 365 participants) covering the spectrum of AD and SVD, including genetically defined samples. We calculated diffusion measures from DTI and free water imaging. Simple linear, multivariable random forest, and voxel-based regressions were used to evaluate associations between AD biomarkers (amyloid beta, tau), SVD imaging markers, and diffusion measures. RESULTS SVD markers were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analysis across all memory clinic samples. Voxel-wise analyses between tau and diffusion measures were not significant. DISCUSSION In memory clinic patients, the effect of SVD on diffusion alterations largely exceeds the effect of AD, supporting the value of diffusion measures as markers of SVD.
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Affiliation(s)
- Sofia Finsterwalder
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Naomi Vlegels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Benno Gesierich
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Miguel Á. Araque Caballero
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Nick A. Weaver
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Marios K. Georgakis
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Marek J. Konieczny
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Huiberdina L. Koek
- Department of Geriatrics, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Celeste M. Karch
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
| | | | | | - Hwamee Oh
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Ricardo F. Allegri
- Department of Cognitive Neurology, FLENI Institute for Neurological Research, Buenos Aires, Argentina
| | | | | | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry, University of Cologne, Medical Faculty, Cologne, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Coraline Metzger
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, Magdeburg, Germany
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Enise I. Incesoy
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Eike J. Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Klaus Fließbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Katharina Buerger
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Stefan J. Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Martina Buchmann
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Michael T. Heneka
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Frederic Brosseron
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Birgit Ertl-Wagner
- Institute of Clinical Radiology, University Hospital, LMU Munich, Munich, Germany
- Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | | | | | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Korea
- Department of Clinical Research Design and Evaluation, Samsung Advanced Institute of Health Sciences and Technology, Sungkyunkwan University, Seoul, Korea
- Center for Imaging of Neurodegenerative Diseases, University of California, San Francisco
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea
| | - Yeshin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Korea
- Department of Neurology, Kangwon National University Hospital, Kangwon National University College of Medicine Chuncheon, Republic of Korea
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute of Health Sciences and Technology, Sungkyunkwan University, Seoul, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Neuroscience Center, Samsung Medical Center, Seoul, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul, Korea
| | - Michael Ewers
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Neurology, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Ofer Pasternak
- Department of Psychiatry and Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
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82
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Luo C, Li M, Qin R, Chen H, Huang L, Yang D, Ye Q, Liu R, Xu Y, Zhao H, Bai F. Long Longitudinal Tract Lesion Contributes to the Progression of Alzheimer's Disease. Front Neurol 2020; 11:503235. [PMID: 33178095 PMCID: PMC7597387 DOI: 10.3389/fneur.2020.503235] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 08/13/2020] [Indexed: 11/16/2022] Open
Abstract
Background: The degenerative pattern of white matter (WM) microstructures during Alzheimer's disease (AD) and its relationship with cognitive function have not yet been clarified. The present research aimed to explore the alterations of the WM microstructure and its impact on amnestic mild cognitive (aMCI) and AD patients. Mechanical learning methods were used to explore the validity of WM microstructure lesions on the classification in AD spectrum disease. Methods: Neuropsychological data and diffusion tensor imaging (DTI) images were collected from 28 AD subjects, 31 aMCI subjects, and 27 normal controls (NC). Tract-based spatial statistics (TBSS) were used to extract diffusion parameters in WM tracts. We performed ANOVA analysis to compare diffusion parameters and clinical features among the three groups. Partial correlation analysis was used to explore the relationship between diffusion metrics and cognitive functions controlling for age, gender, and years of education. Additionally, we performed the support vector machine (SVM) classification to determine the discriminative ability of DTI metrics in the differentiation of aMCI and AD patients from controls. Results: As compared to controls or aMCI patients, AD patients displayed widespread WM lesions, including in the inferior longitudinal fasciculus, inferior fronto-occipital fasciculi, and superior longitudinal fasciculus. Significant correlations between fractional anisotropy (FA), mean diffusivity (MD), and radial diffusion (RD) of the long longitudinal tract and memory deficits were found in aMCI and AD groups, respectively. Furthermore, through SVM classification, we found DTI indicators generated by FA and MD parameters can effectively distinguish AD patients from the control group with accuracy rates of up to 89 and 85%, respectively. Conclusion: The WM microstructure is extensively disrupted in AD patients, and the WM integrity of the long longitudinal tract is closely related to memory, which would hold potential value for monitoring the progression of AD. The method of classification based on SVM and WM damage features may be objectively helpful to the classification of AD diseases.
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Affiliation(s)
- Caimei Luo
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Mengchun Li
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Ruomeng Qin
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Haifeng Chen
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Lili Huang
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Dan Yang
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Qing Ye
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Renyuan Liu
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Hui Zhao
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- The State Key Laboratory of Pharmaceutical Biotechnology, Department of Neurology, Affiliated Drum Tower Hospital of Medical School, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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83
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Li K, Wang S, Luo X, Zeng Q, Jiaerken Y, Xu X, Wang C, Liu X, Li Z, Zhao S, Zhang T, Fu Y, Chen Y, Liu Z, Zhou J, Huang P, Zhang M. Progressive Memory Circuit Impairments along with Alzheimer's Disease Neuropathology Spread: Evidence from in vivo Neuroimaging. Cereb Cortex 2020; 30:5863-5873. [PMID: 32537637 DOI: 10.1093/cercor/bhaa162] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 05/04/2020] [Accepted: 05/21/2020] [Indexed: 01/04/2023] Open
Abstract
During the progression of Alzheimer's disease (AD), neuropathology may propagate transneuronally, cause disruption in memory circuit, and lead to memory impairment. However, there is a lack of in vivo evidence regarding this process. Thus, we aim to simulate and observe the progression of neuropathology in AD continuum. We included cognitively normal (CN), mild cognitive impairments (MCI), and AD subjects, and further classified them using the A/T/N scheme (Group 0: CN, A - T-; Group 1: CN, A + T-; Group 2: CN, A + T+; Group 3: MCI, A + T+; Group 4: AD, A + T+). We investigated alterations of three core memory circuit structures: hippocampus (HP) subfields volume, cingulum-angular bundles (CAB) fiber integrity, and precuneus cortex volume. HP subfields volume showed the trend of initially increased and then decreased (starting from Group 2), while precuneus volume decreased in Groups 3 and 4. The CAB integrity degenerated in Groups 3 and 4 and aggravated with higher disease stages. Further, memory circuit impairments were correlated with neuropathology biomarkers and memory performance. Conclusively, our results demonstrated a pattern of memory circuit impairments along with AD progression: starting from the HP, then propagating to the downstream projection fiber tract and cortex. These findings support the tau propagation theory to some extent.
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Affiliation(s)
- Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Yerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Xiaopei Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Chao Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Zheyu Li
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Shuai Zhao
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Tianyi Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Yanv Fu
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Yanxing Chen
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Zhirong Liu
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Jiong Zhou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310009, China
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Archer DB, Moore EE, Shashikumar N, Dumitrescu L, Pechman KR, Landman BA, Gifford KA, Jefferson AL, Hohman TJ. Free-water metrics in medial temporal lobe white matter tract projections relate to longitudinal cognitive decline. Neurobiol Aging 2020; 94:15-23. [PMID: 32502831 PMCID: PMC7483422 DOI: 10.1016/j.neurobiolaging.2020.05.001] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 04/24/2020] [Accepted: 05/03/2020] [Indexed: 12/12/2022]
Abstract
Although hippocampal volume has served as a long-standing predictor of cognitive decline, diffusion magnetic resonance imaging studies of white matter have shown similar relationships. Still, it remains unclear if gray matter and white matter interact to predict cognitive impairment and longitudinal decline. Here, we investigate whether free-water (FW) and FW-corrected fractional anisotropy (FAT) within medial temporal lobe white matter tracts provides meaningful contribution to cognition and cognitive decline beyond hippocampal volume. Using data from the Vanderbilt Memory & Aging Project (n = 319), we found that FW was associated with baseline memory and executive function beyond that of hippocampal volume and other comorbidities. Longitudinal analyses demonstrated significant interactions of hippocampal volume and inferior longitudinal fasciculus (p = 0.043) and cingulum bundle (p = 0.025) FAT on memory decline and with fornix FAT (p = 0.025) on decline in executive function. Results suggest that FW metrics of white matter have a unique role in cognitive decline and should be included in theoretical models of aging, cerebrovascular disease, and Alzheimer's disease.
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Affiliation(s)
- Derek B Archer
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA; Department of Neurology, Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Elizabeth E Moore
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA; Department of Neurology, Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Kimberly R Pechman
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Katherine A Gifford
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Angela L Jefferson
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA.
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt University School of Medicine, Nashville, TN, USA; Department of Neurology, Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
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85
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Chen H, Sheng X, Qin R, Luo C, Li M, Liu R, Zhang B, Xu Y, Zhao H, Bai F. Aberrant White Matter Microstructure as a Potential Diagnostic Marker in Alzheimer's Disease by Automated Fiber Quantification. Front Neurosci 2020; 14:570123. [PMID: 33071742 PMCID: PMC7541946 DOI: 10.3389/fnins.2020.570123] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Accepted: 08/19/2020] [Indexed: 12/22/2022] Open
Abstract
Neuroimaging evidence has suggested white matter microstructure are heavily affected in Alzheimer's disease (AD). However, whether white matter dysfunction is localized at the specific regions of fiber tracts and whether they would be a potential biomarker for AD remain unclear. By automated fiber quantification (AFQ), we applied diffusion tensor images from 25 healthy controls (HC), 24 amnestic mild cognitive impairment (aMCI) patients and 18 AD patients to create tract profiles along 16 major white matter fibers. We compared diffusion metrics [Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR)] between groups. To assess the diagnostic value, we applied a random forest (RF) classifier, a type of machine learning method. In the global tract level, we found that aMCI and AD patients showed higher MD, DA, and DR values in some fiber tracts mostly in the left hemisphere compared to HC. In the point-wise level, widespread disruption were distributed on specific locations of different tracts. The point-wise MD measurements presented the best classification performance with respect to differentiating AD from HC. The two most important variables were localized in the prefrontal potion of left uncinate fasciculus and anterior thalamic radiation. In addition, the point-wise DA in the posterior component of the left cingulum cingulate displayed the most robust discriminative ability to identify AD from aMCI. Our findings provide evidence that white matter abnormalities based on the AFQ method could be as a diagnostic biomarker in AD.
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Affiliation(s)
- Haifeng Chen
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Xiaoning Sheng
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Caimei Luo
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Mengchun Li
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Renyuan Liu
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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86
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Stephen R, Solomon A, Ngandu T, Levälahti E, Rinne JO, Kemppainen N, Parkkola R, Antikainen R, Strandberg T, Kivipelto M, Soininen H, Liu Y. White Matter Changes on Diffusion Tensor Imaging in the FINGER Randomized Controlled Trial. J Alzheimers Dis 2020; 78:75-86. [PMID: 32925045 PMCID: PMC7683078 DOI: 10.3233/jad-200423] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Background: Early pathological changes in white matter microstructure can be studied using the diffusion tensor imaging (DTI). It is not only important to study these subtle pathological changes leading to cognitive decline, but also to ascertain how an intervention would impact the white matter microstructure and cognition in persons at-risk of dementia. Objectives: To study the impact of a multidomain lifestyle intervention on white matter and cognitive changes during the 2-year Finnish Geriatric Intervention Study to prevent Cognitive Impairment and Disability (FINGER), a randomized controlled trial in at-risk older individuals (age 60–77 years) from the general population. Methods: This exploratory study consisted of a subsample of 60 FINGER participants. Participants were randomized to either a multidomain intervention (diet, exercise, cognitive training, and vascular risk management, n = 34) or control group (general health advice, n = 26). All underwent baseline and 2-year brain DTI. Changes in fractional anisotropy (FA), diffusivity along domain (F1) and non-domain (F2) diffusion orientations, mean diffusivity (MD), axial diffusivity (AxD), radial diffusivity (RD), and their correlations with cognitive changes during the 2-year multidomain intervention were analyzed. Results: FA decreased, and cognition improved more in the intervention group compared to the control group (p < 0.05), with no significant intergroup differences for changes in F1, F2, MD, AxD, or RD. The cognitive changes were significantly positively related to FA change, and negatively related to RD change in the control group, but not in the intervention group. Conclusion: The 2-year multidomain FINGER intervention may modulate white matter microstructural alterations.
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Affiliation(s)
- Ruth Stephen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland
| | - Alina Solomon
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, NVS, Karolinska Institutet, Stockholm, Sweden
| | - Tiia Ngandu
- Division of Clinical Geriatrics, Center for Alzheimer Research, NVS, Karolinska Institutet, Stockholm, Sweden.,Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Esko Levälahti
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Juha O Rinne
- Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland.,Turku PET Centre, University of Turku, Turku, Finland
| | - Nina Kemppainen
- Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland.,Turku PET Centre, University of Turku, Turku, Finland
| | - Riitta Parkkola
- Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland
| | - Riitta Antikainen
- Center for Life Course Health Research/Geriatrics, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and Oulu City Hospital, Oulu, Finland
| | - Timo Strandberg
- Center for Life Course Health Research/Geriatrics, University of Oulu, Oulu, Finland.,Department of Medicine, Geriatric Clinic, University of Helsinki, Helsinki University Central Hospital, Helsinki, Finland
| | - Miia Kivipelto
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Division of Clinical Geriatrics, Center for Alzheimer Research, NVS, Karolinska Institutet, Stockholm, Sweden.,Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.,Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, United Kingdom
| | - Hilkka Soininen
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Neurocenter, Neurology, Kuopio University Hospital, Kuopio, Finland
| | - Yawu Liu
- Institute of Clinical Medicine/Neurology, University of Eastern Finland, Kuopio, Finland.,Department of Clinical Radiology, Kuopio University Hospital, Kuopio, Finland
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87
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Donaghy PC, Firbank M, Petrides G, Lloyd J, Barnett N, Olsen K, Thomas AJ, O'Brien JT. Diffusion imaging in dementia with Lewy bodies: Associations with amyloid burden, atrophy, vascular factors and clinical features. Parkinsonism Relat Disord 2020; 78:109-115. [PMID: 32814228 DOI: 10.1016/j.parkreldis.2020.07.025] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 07/03/2020] [Accepted: 07/25/2020] [Indexed: 01/08/2023]
Abstract
INTRODUCTION White matter disruption in dementia has been linked to a variety of factors including vascular disease and cortical pathology. We aimed to examine the relationship between white matter changes on diffusion tensor imaging (DTI) in DLB and factors including vascular disease, structural atrophy and amyloid burden. METHODS Participants with DLB (n = 29), Alzheimer's disease (AD, n = 17) and healthy controls (n = 20) had clinical and neuropsychological assessments followed by structural and diffusion tensor 3T MRI and 18F-Florbetapir PET-CT imaging. Voxelwise statistical analysis of white matter fractional anisotropy (FA) and mean diffusivity (MD) was carried out using Tract-Based Spatial Statistics with family-wise error correction (p < 0.05). RESULTS DLB and AD groups demonstrated widespread increased MD and decreased FA when compared with controls. There were no differences between the DLB and AD groups. In DLB, increased MD and decreased FA correlated with decreased grey matter and hippocampal volumes as well as vascular disease. There was no correlation with cortical florbetapir SUVR. The relationship between DTI changes and grey matter/hippocampal volumes remained after including Cumulative Illness Rating Scale-Geriatric vascular score as a covariate. CONCLUSIONS Widespread disruption of white matter tracts is present in DLB and is associated with vascular disease, reduced hippocampal volume and reduced grey matter volume, but not with cortical amyloid deposition. The mechanism behind the correlation observed between hippocampal volume and white matter tract disruption should be investigated in future cohorts using tau imaging, as hippocampal atrophy has been shown to correlate with tau deposition in DLB.
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Affiliation(s)
- Paul C Donaghy
- Translational and Clinical Research Institute, Newcastle University, UK.
| | - Michael Firbank
- Translational and Clinical Research Institute, Newcastle University, UK
| | - George Petrides
- Nuclear Medicine Department, Newcastle upon Tyne Hospitals NHS Foundation Trust, UK
| | - Jim Lloyd
- Nuclear Medicine Department, Newcastle upon Tyne Hospitals NHS Foundation Trust, UK
| | - Nicola Barnett
- Translational and Clinical Research Institute, Newcastle University, UK
| | - Kirsty Olsen
- Translational and Clinical Research Institute, Newcastle University, UK
| | - Alan J Thomas
- Translational and Clinical Research Institute, Newcastle University, UK
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88
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Disrupted white matter functional connectivity in aMCI APOEε4 carriers: a resting-state study. Brain Imaging Behav 2020; 15:1739-1747. [PMID: 32715396 DOI: 10.1007/s11682-020-00367-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The ε4 allele of the APOE gene is thought to increase risk from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease. Cognitive decline in the condition is increasingly considered to worsen functional disconnections in brain network composed of gray matter and white matter. Nevertheless, Whether APOEε4 targets specific white matter functional connectivity in patients with aMCI remains mostly unexplored, mainly due to the challenges of detecting BOLD signals in white matter. Here, we applied a novel approach to investigate APOEε4-related specific bundles and cortical area alterations in aMCI subjects, in order to characterize white matter-gray matter functional connectivity differences throughout the brain. We analyzed 75 patients with aMCI and 76 demographically matched normal controls. The aMCI APOEε4 carriers showed decreased functional connectivity located at left corticospinal tract, bilateral posterior limb of internal capsule, and right temporopolaris, which was different from the regions of aMCI-related changes. We further found that recognition scores were positively associated with the right temporopolaris in aMCI APOEε4 carriers. Collectively, the data provide new evidence that APOEε4 genotype exerts a negative impact on neural activity in both gray and white matter in aMCI, which potentially contributes to functional disconnection and memory decline. A novel method provides full-scale measuring effect of disease conditions on functional architecture throughout the brain. Trial registration: https://www.ClinicalTrials.gov (Identifier: NCT02225964). Registered January 2014.
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89
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Benear SL, Ngo CT, Olson IR. Dissecting the Fornix in Basic Memory Processes and Neuropsychiatric Disease: A Review. Brain Connect 2020; 10:331-354. [PMID: 32567331 DOI: 10.1089/brain.2020.0749] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: The fornix is the primary axonal tract of the hippocampus, connecting it to modulatory subcortical structures. This review reveals that fornix damage causes cognitive deficits that closely mirror those resulting from hippocampal lesions. Methods: We reviewed the literature on the fornix, spanning non-human animal lesion research, clinical case studies of human patients with fornix damage, as well as diffusion-weighted imaging (DWI) work that evaluates fornix microstructure in vivo. Results: The fornix is essential for memory formation because it serves as the conduit for theta rhythms and acetylcholine, as well as providing mnemonic representations to deep brain structures that guide motivated behavior, such as when and where to eat. In rodents and non-human primates, fornix lesions lead to deficits in conditioning, reversal learning, and navigation. In humans, damage to the fornix manifests as anterograde amnesia. DWI research reveals that the fornix plays a key role in mild cognitive impairment and Alzheimer's Disease, and can potentially predict conversion from the former to the latter. Emerging DWI findings link perturbations in this structure to schizophrenia, mood disorders, and eating disorders. Cutting-edge research has investigated how deep brain stimulation of the fornix can potentially attenuate memory loss, control epileptic seizures, and even improve mood. Conclusions: The fornix is essential to a fully functioning memory system and is implicated in nearly all neurological functions that rely on the hippocampus. Future research needs to use optimized DWI methods to study the fornix in vivo, which we discuss, given the difficult nature of fornix reconstruction. Impact Statement The fornix is a white matter tract that connects the hippocampus to several subcortical brain regions and is pivotal for episodic memory functioning. Functionally, the fornix transmits essential neurotransmitters, as well as theta rhythms, to the hippocampus. In addition, it is the conduit by which memories guide decisions. The fornix is biomedically important because lesions to this tract result in irreversible anterograde amnesia. Research using in vivo imaging methods has linked fornix pathology to cognitive aging, mild cognitive impairment, psychosis, epilepsy, and, importantly, Alzheimer's Disease.
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Affiliation(s)
- Susan L Benear
- Department of Psychology, Temple University, Philadelphia, Pennsylvania, USA
| | - Chi T Ngo
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Ingrid R Olson
- Department of Psychology, Temple University, Philadelphia, Pennsylvania, USA
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90
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To XV, Benetatos J, Soni N, Liu D, Mehari Abraha H, Yan W, Panagiotopoulou O, Nasrallah FA. Ultra-High-Field Diffusion Tensor Imaging Identifies Discrete Patterns of Concussive Injury in the Rodent Brain. J Neurotrauma 2020; 38:967-982. [PMID: 32394788 DOI: 10.1089/neu.2019.6944] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Although concussions can result in persistent neurological post-concussion symptoms, they are typically invisible on routine magnetic resonance imaging (MRI) scans. Our study aimed to investigate the use of ultra-high-field diffusion tensor imaging (UHF-DTI) in discerning severity-dependent microstructural changes in the mouse brain following a concussion. Twenty-three C57BL/6 mice were randomly allocated into three groups: the low concussive (LC, n = 9) injury group, the high concussive (HC, n = 6) injury group, and the sham control (SC, n = 7) group. Mice were perfused on day 2 post-injury, and the brains were scanned on a 16.4T MRI scanner with UHF-DTI and neurite orientation dispersion imaging (NODDI). Finite element analysis (FEA) was performed to determine the pattern and extent of the physical impact on the brain tissue. MRI findings were correlated with histopathological analysis in a subset of mice. In the LC group, increased fractional anisotropy (FA) and decreased orientation dispersion index (ODI) but limited neurite density index (NDI) changes were found in the gray matter, and minimal changes to white matter (WM) were observed. The HC group presented increased mean diffusivity (MD), decreased NDI, and decreased ODI in the WM and gray matter (GM); decreased FA was also found in a small area of the WM. WM changes were associated with WM degeneration and neuroinflammation. FEA showed varying region-dependent degrees of stress, in line with the different imaging findings. This study provides evidence that UHF-DTI combined with NODDI can detect concussions of variable intensities. This has significant implications for the diagnosis of concussion in humans.
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Affiliation(s)
- Xuan Vinh To
- The Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Joseph Benetatos
- The Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Neha Soni
- The Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Dedao Liu
- Department of Mechanical and Aerospace Engineering, Faculty of Engineering, Department of Anatomy and Developmental Biology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Hyab Mehari Abraha
- Monash Biomedicine Discovery Institute, Department of Anatomy and Developmental Biology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Wenyi Yan
- Department of Mechanical and Aerospace Engineering, Faculty of Engineering, Department of Anatomy and Developmental Biology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Olga Panagiotopoulou
- Monash Biomedicine Discovery Institute, Department of Anatomy and Developmental Biology, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - Fatima A Nasrallah
- The Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia.,The Center for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
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91
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Teipel SJ, Fritz HC, Grothe MJ. Neuropathologic features associated with basal forebrain atrophy in Alzheimer disease. Neurology 2020; 95:e1301-e1311. [PMID: 32631924 PMCID: PMC7538215 DOI: 10.1212/wnl.0000000000010192] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 03/09/2020] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE To study the neuropathologic correlates of cholinergic basal forebrain (BF) atrophy as determined using antemortem MRI in the Alzheimer disease (AD) spectrum. METHODS We determined associations between BF volume from antemortem MRI brain scans and postmortem assessment of neuropathologic features, including neuritic plaques, neurofibrillary tangles (NFTs), Lewy body (LB) pathology, and TDP-43, in 64 cases of the Alzheimer's Disease Neuroimaging Initiative cohort. For comparison, we assessed neuropathologic features associated with hippocampal and parahippocampal gyrus atrophy. In addition to region of interest-based analysis, we determined the association of neuropathologic features with whole brain gray matter volume using regionally unbiased voxel-based volumetry. RESULTS BF atrophy was associated with Thal amyloid phases (95% confidence interval [CI] -0.49 to -0.01, p = 0.049) and presence of LB pathology (95% CI -0.54 to -0.06, p = 0.015), as well as with the degree of LB pathology within the nucleus basalis Meynert (95% CI -0.54 to -0.07, p = 0.025). These effects were no longer significant after false discovery rate (FDR) correction. Hippocampal atrophy was significantly associated with the presence of TDP-43 pathology (95% CI -0.61 to -0.17, p = 0.003; surviving FDR correction), in addition to dentate gyrus NFT load (95% CI -0.49 to -0.01, p = 0.044; uncorrected). Voxel-based analysis confirmed spatially restricted effects of Thal phases and presence of LB pathology on BF volume. CONCLUSIONS These findings indicate that neuropathologic correlates of regional atrophy differ substantially between different brain regions that are typically involved in AD-related neurodegeneration, including different susceptibilities to common comorbid pathologies.
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Affiliation(s)
- Stefan J Teipel
- From the German Center for Neurodegenerative Diseases (DZNE) (S.J.T., M.J.G.); Department of Psychosomatic Medicine (S.J.T., H.-C.F.), University Medicine Rostock, Germany; and Instituto de Biomedicina de Sevilla (IBiS) (M.J.G.), Unidad de Trastornos del Movimiento, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Spain.
| | - H-Christian Fritz
- From the German Center for Neurodegenerative Diseases (DZNE) (S.J.T., M.J.G.); Department of Psychosomatic Medicine (S.J.T., H.-C.F.), University Medicine Rostock, Germany; and Instituto de Biomedicina de Sevilla (IBiS) (M.J.G.), Unidad de Trastornos del Movimiento, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Spain
| | - Michel J Grothe
- From the German Center for Neurodegenerative Diseases (DZNE) (S.J.T., M.J.G.); Department of Psychosomatic Medicine (S.J.T., H.-C.F.), University Medicine Rostock, Germany; and Instituto de Biomedicina de Sevilla (IBiS) (M.J.G.), Unidad de Trastornos del Movimiento, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Spain
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92
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Gunbey HP, Has AC, Aslan K, Saglam D, Avcı U, Sayıt AT, Incesu L. Microstructural white matter abnormalities in hypothyroidism evaluation with diffusion tensor imaging tract-based spatial statistical analysis. Radiol Med 2020; 126:283-290. [PMID: 32524282 DOI: 10.1007/s11547-020-01234-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 05/25/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE Hypothyroidism is presented in a wide range from neuropsychiatric problems including depression, memory and cognitive disorders to poor motor coordination. Against the background of morphologic, functional and molecular changes on the white and grey matter of the brain, we aimed to investigate the effects of hypothyroidism on white matter (WM) integrity using tract-based spatial statistics (TBSS). METHODS Eighteen patients with hyperthyroidism and 14 age-sex-matched healthy control subjects were included in this study. TBSS was used in the diffusion tensor imaging study for whole-brain voxel wise analysis of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) of WM. RESULTS When compared to the control group, the whole brain TBSS revealed extensive reductions of FA in the supratentorial WM including corticospinal tract, posterior limb of the internal capsule (PLIC), uncinate fasciculus, inferior longitudinal fasciculus (p < 0.005). The ROI analyses showed RD increment of superior longitudinal fasciculus, AD decrement of cingulum (CIN), external capsule, PLIC and corpus callosum (CC) in patients with hypothyroidism (p < 0.005). Autoimmune and non-autoimmune hypothyroidism patient subgroups showed a significant difference in terms of hippocampus FA, CIN MD, CC MD, CC AD, CIN RD, SLF RD, CC RD (p < 0.005). CIN FA values showed a negative correlation with the Beck Depression Inventory (p = 0.007, r = - 852). CONCLUSIONS These preliminary results of TBSS analyses represented FA and AD decrement, and RD increment in several WM tracts and indicates the demyelination process underlying pathophysiology of clinical aspects of hypothyroidism.
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Affiliation(s)
- Hediye Pınar Gunbey
- Department of Radiology, University of Health Sciences Kartal Lutfi Kırdar Training and Research Hospital, 34890, Kartal/Istanbul, Turkey.
| | - Arzu Ceylan Has
- Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kerim Aslan
- Department of Radiology, Ondokuz Mayıs University Faculty of Medicine, Samsun, Turkey
| | - Dilek Saglam
- Departmant of Radiology, University of Health Sciences Malatya Training and Research Hospital, Malatya, Turkey
| | - Ugur Avcı
- Department of Endocrinology, Recep Tayyip Erdogan University, Rize, Turkey
| | | | - Lutfi Incesu
- Department of Radiology, Ondokuz Mayıs University Faculty of Medicine, Samsun, Turkey
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93
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Mitelman SA, Buchsbaum MS, Christian BT, Merrill BM, Adineh M, DeCastro A, Buchsbaum BR, Lehrer DS. Relationship between white matter glucose metabolism and fractional anisotropy in healthy and schizophrenia subjects. Psychiatry Res Neuroimaging 2020; 299:111060. [PMID: 32135405 DOI: 10.1016/j.pscychresns.2020.111060] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Revised: 02/15/2020] [Accepted: 02/21/2020] [Indexed: 01/05/2023]
Abstract
Decreased fractional anisotropy and increased glucose utilization in the white matter have been reported in schizophrenia. These findings may be indicative of an inverse relationship between these measures of white matter integrity and metabolism. We used 18F-fluorodeoxyglucose positron emission tomography and diffusion-tensor imaging in 19 healthy and 25 schizophrenia subjects to assess and compare coterritorial correlation patterns between glucose utilization and fractional anisotropy on a voxel-by-voxel basis and across a range of automatically placed representative white matter regions of interest. We found a pattern of predominantly negative correlations between white matter metabolism and fractional anisotropy in both healthy and schizophrenia subjects. The overall strength of the relationship was attenuated in subjects with schizophrenia, who displayed significantly fewer and weaker correlations in all regions assessed with the exception of the corpus callosum. This attenuation was most prominent in the left prefrontal white matter and this region also best predicted the diagnosis of schizophrenia. There exists an inverse relationship between the measures of white matter integrity and metabolism, which may therefore be physiologically linked. In subjects with schizophrenia, hypermetabolism in the white matter may be a function of lower white matter integrity, with lower efficiency and increased energetic cost of task-related computations.
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Affiliation(s)
- Serge A Mitelman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, United States; Department of Psychiatry, Division of Child and Adolescent Psychiatry, Elmhurst Hospital Center, 79-01 Broadway, Elmhurst, NY 11373, United States.
| | - Monte S Buchsbaum
- NeuroPET Center, Departments of Psychiatry and Radiology, University of California, San Diego, 11388 Sorrento Valley Road, San Diego, CA 92121, United States
| | - Bradley T Christian
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, 1500 Highland Avenue, Room T231, Madison, WI 53705, United States
| | - Brian M Merrill
- Department of Psychiatry, Boonshoft School of Medicine, Wright State University, East Medical Plaza, Dayton, OH 45408, United States
| | - Mehdi Adineh
- Wallace-Kettering Neuroscience Institute, Kettering Medical Center, Kettering, OH 45429
| | - Alex DeCastro
- NeuroPET Center, Departments of Psychiatry and Radiology, University of California, San Diego, 11388 Sorrento Valley Road, San Diego, CA 92121, United States
| | - Bradley R Buchsbaum
- The Rotman Research Institute, Baycrest Centre for Geriatric Care and Department of Psychiatry, University of Toronto, 3560 Bathurst St., Toronto, Ontario, Canada, M6A 2E1
| | - Douglas S Lehrer
- Department of Psychiatry, Boonshoft School of Medicine, Wright State University, East Medical Plaza, Dayton, OH 45408, United States
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94
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Dou X, Yao H, Feng F, Wang P, Zhou B, Jin D, Yang Z, Li J, Zhao C, Wang L, An N, Liu B, Zhang X, Liu Y. Characterizing white matter connectivity in Alzheimer's disease and mild cognitive impairment: An automated fiber quantification analysis with two independent datasets. Cortex 2020; 129:390-405. [PMID: 32574842 DOI: 10.1016/j.cortex.2020.03.032] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 12/13/2019] [Accepted: 03/31/2020] [Indexed: 12/28/2022]
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive dementia. Diffusion tensor imaging (DTI) has been widely used to show structural integrity and delineate white matter (WM) degeneration in AD. The automated fiber quantification (AFQ) method is a fully automated approach that can rapidly and reliably identify major WM fiber tracts and evaluate WM properties. The main aim of this study was to assess WM integrity and abnormities in a cohort of patients with amnestic mild cognitive impairment (aMCI) and AD as well as normal controls (NCs). For this purpose, we first used AFQ to identify 20 major WM tracts and assessed WM integrity and abnormalities in a cohort of 120 subjects (39 NCs, 34 aMCI patients and 47 AD patients) in a discovery dataset and 122 subjects (43 NCs, 37 aMCI patients and 42 AD patients) in a replicated dataset. Pointwise differences along WM tracts were identified in the discovery dataset and simultaneously confirmed in the replicated dataset. Next, we investigated the utility of DTI measures along WM tracts as features to distinguish patients with AD from NCs via multilevel cross validation using a support vector machine. Correlation analysis revealed the identified microstructural WM alterations and classification output to be highly associated with cognitive ability in the patient groups, suggesting that they may be a robust biomarker of AD. This systematic study provides a pipeline to examine WM integrity and its potential clinical application in AD and may be useful for studying other neurological and psychiatric disorders.
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Affiliation(s)
- Xuejiao Dou
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Hongxiang Yao
- Department of Radiology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Feng Feng
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin, 300350, China; Department of Neurology, Nankai University Huanhu Hospital, Tianjin, China
| | - Bo Zhou
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Dan Jin
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, China
| | - Zhengyi Yang
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jin Li
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Cui Zhao
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Luning Wang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Ningyu An
- Department of Radiology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China
| | - Bing Liu
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Xi Zhang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, China.
| | - Yong Liu
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
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95
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Silva PHRD, Secchinato KF, Rondinoni C, Leoni RF. Brain Structural–Functional Connectivity Relationship Underlying the Information Processing Speed. Brain Connect 2020; 10:143-154. [DOI: 10.1089/brain.2019.0726] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Affiliation(s)
| | | | - Carlo Rondinoni
- InBrain, Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, Brazil
| | - Renata Ferranti Leoni
- InBrain, Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, Brazil
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96
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Berron D, van Westen D, Ossenkoppele R, Strandberg O, Hansson O. Medial temporal lobe connectivity and its associations with cognition in early Alzheimer's disease. Brain 2020; 143:1233-1248. [PMID: 32252068 PMCID: PMC7174043 DOI: 10.1093/brain/awaa068] [Citation(s) in RCA: 149] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 01/15/2020] [Accepted: 01/26/2020] [Indexed: 12/12/2022] Open
Abstract
Human episodic memory critically depends on subregions of the medial temporal lobe, which are part of functional brain systems such as the anterior-temporal and the posterior-medial system. Here we analysed how Alzheimer's pathology affects functional connectivity within these systems. Data from 256 amyloid-β-negative cognitively unimpaired, 103 amyloid-β-positive cognitively unimpaired, and 83 amyloid-β-positive individuals with mild cognitive impairment were analysed. Amyloid-β and tau pathology were measured using the CSF amyloid-β42/40 ratio and phosphorylated tau, respectively. We found that amyloid-β-positive cognitively unimpaired individuals were mainly characterized by decreased functional connectivity between the medial temporal lobe and regions in the anterior-temporal system, most prominently between left perirhinal/entorhinal cortices and medial prefrontal cortex. Furthermore, correlation analysis in this group revealed decreasing functional connectivity between bilateral perirhinal/entorhinal cortices, anterior hippocampus and posterior-medial regions with increasing levels of phosphorylated tau. The amyloid-β-positive individuals with mild cognitive impairment mostly exhibited reduced connectivity between the medial temporal lobe and posterior-medial regions, predominantly between the anterior hippocampus and posterior cingulate cortex. In addition, they showed hyperconnectivity within the medial temporal lobe and its immediate proximity. Lower medial temporal-cortical functional connectivity networks resulting from the group comparisons of cognitively unimpaired individuals were associated with reduced memory performance and more rapid longitudinal memory decline as shown by linear mixed-effects regression analysis. Finally, we found that reduced medial temporal-cortical connectivity in mildly cognitively impaired individuals was related to reduced entorhinal thickness and white matter integrity of the parahippocampal cingulum and the fornix. No such relationships were found in cognitively unimpaired individuals. In conclusion, our findings show that the earliest changes in preclinical Alzheimer's disease might involve decreased connectivity within the anterior-temporal system, and early changes in connectivity might be related to memory impairment, but not to structural changes. With disease progression and increased tau pathology, medial temporal functional connectivity with posterior-medial regions seems to be increasingly impaired. In individuals with mild cognitive impairment, reduced functional connectivity is associated with structural brain changes as well as the emergence of locally increased connectivity patterns. Thus, functional connectivity between the medial temporal lobe and the anterior-temporal and posterior-medial system could serve as stage-specific functional markers in early Alzheimer's disease.
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Affiliation(s)
- David Berron
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Danielle van Westen
- Diagnostic Radiology, Lund University, Lund, Sweden
- Image and Function, Skane University Hospital, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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97
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Trigiani LJ, Lacalle-Aurioles M, Bourourou M, Li L, Greenhalgh AD, Zarruk JG, David S, Fehlings MG, Hamel E. Benefits of physical exercise on cognition and glial white matter pathology in a mouse model of vascular cognitive impairment and dementia. Glia 2020; 68:1925-1940. [PMID: 32154952 DOI: 10.1002/glia.23815] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 02/06/2020] [Accepted: 02/24/2020] [Indexed: 12/16/2022]
Abstract
White matter (WM) pathology is a clinically predictive feature of vascular cognitive impairment and dementia (VCID). Mice overexpressing transforming growth factor-β1 (TGF) with an underlying cerebrovascular pathology when fed a high cholesterol diet (HCD) develop cognitive deficits (VCID mice) that we recently found could be prevented by physical exercise (EX). Here, we further investigated cognitive and WM pathology in VCID mice and examined the cellular substrates of the protective effects of moderate aerobic EX focusing on WM alterations. Six groups were studied: Wild-type (WT) and TGF mice (n = 20-24/group) fed standard lab chow or a 2% HCD, with two HCD-fed groups given concurrent access to running wheels. HCD had a significant negative effect in TGF mice that was prevented by EX on working and object recognition memory, the latter also altered in WT HCD mice. Whisker-evoked increases in cerebral blood flow (CBF) were reduced in HCD-fed mice, deficits that were countered by EX, and baseline WM CBF was similarly affected. VCID mice displayed WM functional deficits characterized by lower compound action potential amplitude not found in EX groups. Moreover, there was an increased number of collapsing capillaries, galectin-3-expressing microglial cells, as well as a reduced number of oligodendrocytes in the WM of VCID mice; all of which were prevented by EX. Our findings indicate that a compromised cerebral circulation precedes reduced WM vascularization, enhanced WM inflammation and impaired oligodendrogenesis that all likely account for the increased susceptibility to memory impairments in VCID mice, which can be prevented by EX. MAIN POINTS: A compromised cerebral circulation increases susceptibility to anatomical and functional white matter changes that develop alongside cognitive deficits when challenged with a high cholesterol diet; preventable by a translational regimen of exercise.
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Affiliation(s)
- Lianne J Trigiani
- Laboratory of Cerebrovascular Research, Montreal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - María Lacalle-Aurioles
- Laboratory of Cerebrovascular Research, Montreal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Miled Bourourou
- Laboratory of Cerebrovascular Research, Montreal Neurological Institute, McGill University, Montréal, Quebec, Canada
| | - Lijun Li
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Andrew D Greenhalgh
- Center for Research in Neuroscience, The Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
| | - Juan G Zarruk
- Center for Research in Neuroscience, The Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
| | - Samuel David
- Center for Research in Neuroscience, The Research Institute of the McGill University Health Center, Montreal, Quebec, Canada
| | - Michael G Fehlings
- Division of Genetics and Development, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Edith Hamel
- Laboratory of Cerebrovascular Research, Montreal Neurological Institute, McGill University, Montréal, Quebec, Canada
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98
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Conway ME. Alzheimer's disease: targeting the glutamatergic system. Biogerontology 2020; 21:257-274. [PMID: 32048098 PMCID: PMC7196085 DOI: 10.1007/s10522-020-09860-4] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 01/29/2020] [Indexed: 12/21/2022]
Abstract
Alzheimer’s disease (AD) is a debilitating neurodegenerative disease that causes a progressive decline in memory, language and problem solving. For decades mechanism-based therapies have primarily focused on amyloid β (Aβ) processing and pathways that govern neurofibrillary tangle generation. With the potential exception to Aducanumab, a monotherapy to target Aβ, clinical trials in these areas have been challenging and have failed to demonstrate efficacy. Currently, the prescribed therapies for AD are those that target the cholinesterase and glutamatergic systems that can moderately reduce cognitive decline, dependent on the individual. In the brain, over 40% of neuronal synapses are glutamatergic, where the glutamate level is tightly regulated through metabolite exchange in neuronal, astrocytic and endothelial cells. In AD brain, Aβ can interrupt effective glutamate uptake by astrocytes, which evokes a cascade of events that leads to neuronal swelling, destruction of membrane integrity and ultimately cell death. Much work has focussed on the post-synaptic response with little insight into how glutamate is regulated more broadly in the brain and the influence of anaplerotic pathways that finely tune these mechanisms. The role of blood branched chain amino acids (BCAA) in regulating neurotransmitter profiles under disease conditions also warrant discussion. Here, we review the importance of the branched chain aminotransferase proteins in regulating brain glutamate and the potential consequence of dysregulated metabolism in the context of BCAA or glutamate accumulation. We explore how the reported benefits of BCAA supplementation or restriction in improving cognitive function in other neurological diseases may have potential application in AD. Given that memantine, the glutamate receptor agonist, shows clinical relevance it is now timely to research related pathways, an understanding of which could identify novel approaches to treatment of AD.
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Affiliation(s)
- Myra E Conway
- Faculty of Health and Applied Sciences, University of the West of England, Coldharbour Lane, Bristol, BS16 1QY, UK. .,Faculty of Health and Life Sciences, University of the West of England, Coldharbour Lane, Bristol, BS16 1QY, UK.
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99
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Nicastro N, Mak E, Williams GB, Surendranathan A, Bevan-Jones WR, Passamonti L, Vàzquez Rodrìguez P, Su L, Arnold R, Fryer TD, Hong YT, Aigbirhio FI, Rowe JB, O'Brien JT. Correlation of microglial activation with white matter changes in dementia with Lewy bodies. Neuroimage Clin 2020; 25:102200. [PMID: 32032816 PMCID: PMC7005463 DOI: 10.1016/j.nicl.2020.102200] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 01/26/2020] [Accepted: 01/27/2020] [Indexed: 02/02/2023]
Abstract
Dementia with Lewy bodies (DLB) is characterized by alpha-synuclein protein deposition with variable degree of concurrent Alzheimer's pathology. Neuroinflammation is also increasingly recognized as a significant contributor to degeneration. We aimed to examine the relationship between microglial activation as measured with [11C]-PK11195 brain PET, MR diffusion tensor imaging (DTI) and grey matter atrophy in DLB. Nineteen clinically probable DLB and 20 similarly aged controls underwent 3T structural MRI (T1-weighted) and diffusion-weighted imaging. Eighteen DLB subjects also underwent [11C]-PK11195 PET imaging and 15 had [11C]-Pittsburgh compound B amyloid PET, resulting in 9/15 being amyloid-positive. We used Computational Anatomy Toolbox (CAT12) for volume-based morphometry (VBM) and Tract-Based Spatial Statistics (TBSS) for DTI to assess group comparisons between DLB and controls and to identify associations of [11C]-PK11195 binding with grey/white matter changes and cognitive score in DLB patients. VBM analyses showed that DLB had extensive reduction of grey matter volume in superior frontal, temporal, parietal and occipital cortices (family-wise error (FWE)-corrected p < 0.05). TBSS showed widespread changes in DLB for all DTI parameters (reduced fractional anisotropy, increased diffusivity), involving the corpus callosum, corona radiata and superior longitudinal fasciculus (FWE-corrected p < 0.05). Higher [11C]-PK11195 binding in parietal cortices correlated with widespread lower mean and radial diffusivity in DLB patients (FWE-corrected p < 0.05). Furthermore, preserved cognition in DLB (higher Addenbrookes Cognitive Evaluation revised score) also correlated with higher [11C]-PK11195 binding in frontal, temporal, and occipital lobes. However, microglial activation was not significantly associated with grey matter changes. Our study suggests that increased microglial activation is associated with a relative preservation of white matter and cognition in DLB, positioning neuroinflammation as a potential early marker of DLB etio-pathogenesis.
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Affiliation(s)
- Nicolas Nicastro
- Department of Psychiatry, University of Cambridge, UK,Department of Clinical Neurosciences, Geneva University Hospitals, Switzerland
| | - Elijah Mak
- Department of Psychiatry, University of Cambridge, UK
| | | | | | | | - Luca Passamonti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK,Consiglio Nazionale delle Ricerche (CNR), Istituto di Bioimmagini e Fisiologia Molecolare (IBFM), Milano, Italy
| | | | - Li Su
- Department of Psychiatry, University of Cambridge, UK,China-UK Centre for Cognition and Ageing Research, Southwest University, Chongqing, China
| | - Robert Arnold
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Tim D. Fryer
- Wolfson Brain Imaging Centre, University of Cambridge, UK,Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Young T. Hong
- Wolfson Brain Imaging Centre, University of Cambridge, UK,Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK,Medical Research Council Cognition and Brain Sciences Unit, Cambridge, UK
| | - John T. O'Brien
- Department of Psychiatry, University of Cambridge, UK,Corresponding author at: Department of Psychiatry, University of Cambridge School of Clinical Medicine, Box 189, Level E4 Cambridge Biomedical Campus, Cambridge CB2 0SP, United Kingdom.
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100
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Luo C, Li M, Qin R, Chen H, Yang D, Huang L, Liu R, Xu Y, Bai F, Zhao H. White Matter Microstructural Damage as an Early Sign of Subjective Cognitive Decline. Front Aging Neurosci 2020; 11:378. [PMID: 32047428 PMCID: PMC6997435 DOI: 10.3389/fnagi.2019.00378] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 12/23/2019] [Indexed: 01/21/2023] Open
Abstract
Background and Objective: Subjective cognitive decline (SCD) is considered a preclinical state of Alzheimer's disease (AD) and may represent a more advanced preclinical status than amnestic mild cognitive impairment (aMCI). Our aim was to explore changes in the white matter (WM) microstructure and their correlation with cognitive function in these AD-spectrum patients. Methods: Diffusion tensor images from 43 individuals with normal cognition (NC), 38 SCD patients, and 36 aMCI patients were compared using an atlas-based segmentation strategy. The correlation between diffusion parameters and cognitive function was further analyzed. Results: The anatomical pattern of WM impairment was generally similar between SCD and aMCI patients. However, aMCI patients showed significantly lower fractional anisotropy (i.e., corpus callosum forceps major and forceps minor) and increased mean diffusivity [i.e., bilateral anterior thalamic radiation (ATR), left corticospinal tract (CST), forceps minor, left cingulum (cingulate gyrus), left cingulum hippocampus, and left inferior fronto-occipital fasciculus (IFO)] in some tracts than did SCD subjects, indicating a disruption in WM microstructural integrity in the aMCI. Individuals with microstructural disruption in forceps minor, left cingulum (cingulate gyrus), and left cingulum hippocampus tracts performed worse in general cognition and memory function tests, as indicated by line regression analysis. Conclusion: SCD individuals had extensive WM microstructural damage in a pattern similar to that seen in aMCI, although presenting a cognitive performance comparable with that of cognitively healthy individuals. Our results suggest that WM integrity might precede objectively measurable memory decline and may be a potential early biomarker for AD.
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Affiliation(s)
- Caimei Luo
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Mengchun Li
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Haifeng Chen
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Dan Yang
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Lili Huang
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Renyuan Liu
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, China.,Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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