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Russo ML, Ayala G, Neal D, Rogalsky AE, Ahmad S, Musial TF, Pearlman M, Bean LA, Farooqi AK, Ahmed A, Castaneda A, Patel A, Parduhn Z, Haddad LG, Gabriel A, Disterhoft JF, Nicholson DA. Alzheimer's-linked axonal changes accompany elevated antidromic action potential failure rate in aged mice. Brain Res 2024; 1841:149083. [PMID: 38866308 PMCID: PMC11323114 DOI: 10.1016/j.brainres.2024.149083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 04/22/2024] [Accepted: 06/09/2024] [Indexed: 06/14/2024]
Abstract
Alzheimer's disease (AD) affects both grey and white matter (WM), but considerably more is known about the former. Interestingly, WM disruption has been consistently observed and thoroughly described using imaging modalities, particularly MRI which has shown WM functional disconnections between the hippocampus and other brain regions during AD pathogenesis when early neurodegeneration and synapse loss are also evident. Nonetheless, high-resolution structural and functional analyses of WM during AD pathogenesis remain scarce. Given the importance of the myelinated axons in the WM for conveying information across brain regions, such studies will provide valuable information on the cellular drivers and consequences of WM disruption that contribute to the characteristic cognitive decline of AD. Here, we employed a multi-scale approach to investigate hippocampal WM disruption during AD pathogenesis and determine whether hippocampal WM changes accompany the well-documented grey matter losses. Our data indicate that ultrastructural myelin disruption is elevated in the alveus in human AD cases and increases with age in 5xFAD mice. Unreliable action potential propagation and changes to sodium channel expression at the node of Ranvier co-emerged with this deterioration. These findings provide important insight to the neurobiological substrates and functional consequences of decreased WM integrity and are consistent with the notion that hippocampal disconnection contributes to cognitive changes in AD.
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Affiliation(s)
- Matthew L Russo
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA.
| | - Gelique Ayala
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Demetria Neal
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Annalise E Rogalsky
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Suzan Ahmad
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Timothy F Musial
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Morgan Pearlman
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Linda A Bean
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Anise K Farooqi
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Aysha Ahmed
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Adrian Castaneda
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Aneri Patel
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Zachary Parduhn
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Loreece G Haddad
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - Ashley Gabriel
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
| | - John F Disterhoft
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Daniel A Nicholson
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL 60612, USA
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2
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Wen C, Zeng Q, Zhou R, Xie L, Yu J, Zhang C, Wang J, Yu Y, Gu Y, Cao G, Feng Y, Wang M. Characterization of local white matter microstructural alterations in Alzheimer's disease: A reproducible study. Comput Biol Med 2024; 179:108750. [PMID: 38996551 DOI: 10.1016/j.compbiomed.2024.108750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 05/24/2024] [Accepted: 06/08/2024] [Indexed: 07/14/2024]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease with a close association with microstructural alterations in white matter (WM). Current studies lack the characterization and further validation of specific regions in WM fiber tracts in AD. This study subdivided fiber tracts into multiple fiber clusters on the basis of automated fiber clustering and performed quantitative analysis along the fiber clusters to identify local WM microstructural alterations in AD. Diffusion tensor imaging data from a public dataset (53 patients with AD and 70 healthy controls [HCs]) and a clinical dataset (27 patients with AD and 19 HCs) were included for mutual validation. Whole-brain tractograms were automatically subdivided into 800 clusters through the automatic fiber clustering approach. Then, 100 segments were divided along the clusters, and the diffusion properties of each segment were calculated. Results showed that patients with AD had significantly lower fraction anisotropy (FA) and significantly higher mean diffusivity (MD) in some regions of the fiber clusters in the cingulum bundle, uncinate fasciculus, external capsule, and corpus callosum than HCs. Importantly, these changes were reproducible across the two datasets. Correlation analysis revealed a positive correlation between FA and Mini-Mental State Examination (MMSE) scores and a negative correlation between MD and MMSE in these clusters. The accuracy of the constructed classifier reached 89.76% with an area under the curve of 0.93. This finding indicates that this study can effectively identify local WM microstructural changes in AD and provides new insight into the analysis and diagnosis of WM abnormalities in patients with AD.
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Affiliation(s)
- Caiyun Wen
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China
| | - Qingrun Zeng
- College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Ronghui Zhou
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China
| | - Lei Xie
- College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Jiangli Yu
- College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Chengzhe Zhang
- College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Jingqiang Wang
- College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Yan Yu
- College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Yixin Gu
- College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Guoquan Cao
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China
| | - Yuanjing Feng
- College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China
| | - Meihao Wang
- Department of Radiology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
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3
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Chandio BQ, Villalon-Reina JE, Nir TM, Thomopoulos SI, Feng Y, Benavidez S, Jahanshad N, Harezlak J, Garyfallidis E, Thompson PM. Amyloid, Tau, and APOE in Alzheimer's Disease: Impact on White Matter Tracts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.05.606560. [PMID: 39149378 PMCID: PMC11326207 DOI: 10.1101/2024.08.05.606560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Alzheimer's disease (AD) is characterized by cognitive decline and memory loss due to the abnormal accumulation of amyloid-beta (Aβ) plaques and tau tangles in the brain; its onset and progression also depend on genetic factors such as the apolipoprotein E (APOE) genotype. Understanding how these factors affect the brain's neural pathways is important for early diagnostics and interventions. Tractometry is an advanced technique for 3D quantitative assessment of white matter tracts, localizing microstructural abnormalities in diseased populations in vivo. In this work, we applied BUAN (Bundle Analytics) tractometry to 3D diffusion MRI data from 730 participants in ADNI3 (phase 3 of the Alzheimer's Disease Neuroimaging Initiative; age range: 55-95 years, 349M/381F, 214 with mild cognitive impairment, 69 with AD, and 447 cognitively healthy controls). Using along-tract statistical analysis, we assessed the localized impact of amyloid, tau, and APOE genetic variants on the brain's neural pathways. BUAN quantifies microstructural properties of white matter tracts, supporting along-tract statistical analyses that identify factors associated with brain microstructure. We visualize the 3D profile of white matter tract associations with tau and amyloid burden in Alzheimer's disease; strong associations near the cortex may support models of disease propagation along neural pathways. Relative to the neutral genotype, APOE ϵ3/ϵ3, carriers of the AD-risk conferring APOE ϵ4 genotype show microstructural abnormalities, while carriers of the protective ϵ2 genotype also show subtle differences. Of all the microstructural metrics, mean diffusivity (MD) generally shows the strongest associations with AD pathology, followed by axial diffusivity (AxD) and radial diffusivity (RD), while fractional anisotropy (FA) is typically the least sensitive metric. Along-tract microstructural metrics are sensitive to tau and amyloid accumulation, showing the potential of diffusion MRI to track AD pathology and map its impact on neural pathways.
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Affiliation(s)
- Bramsh Qamar Chandio
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Julio E. Villalon-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Talia M. Nir
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Yixue Feng
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sebastian Benavidez
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | | | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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Malla S, Bryant AG, Jayakumar R, Woost B, Wolf N, Li A, Das S, van Veluw SJ, Bennett RE. Molecular profiling of frontal and occipital subcortical white matter hyperintensities in Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.13.598845. [PMID: 38915516 PMCID: PMC11195168 DOI: 10.1101/2024.06.13.598845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
White matter hyperintensities (WMHs) are commonly detected on T2-weighted magnetic resonance imaging (MRI) scans, occurring in both typical aging and Alzheimer's disease. Despite their frequent appearance and their association with cognitive decline, the molecular factors contributing to WMHs remain unclear. In this study, we investigated the transcriptomic profiles of two commonly affected brain regions with coincident AD pathology-frontal subcortical white matter (frontal-WM) and occipital subcortical white matter (occipital-WM)-and compared with age-matched healthy controls. Through RNA-sequencing in frontal- and occipital-WM bulk tissues, we identified an upregulation of genes associated with brain vasculature function in AD white matter. To further elucidate vasculature-specific transcriptomic features, we performed RNA-seq analysis on blood vessels isolated from these white matter regions, which revealed an upregulation of genes related to protein folding pathways. Finally, comparing gene expression profiles between AD individuals with high- versus low-WMH burden showed an increased expression of pathways associated with immune function. Taken together, our study characterizes the diverse molecular profiles of white matter changes in AD compared to normal aging and provides new mechanistic insights processes underlying AD-related WMHs.
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Affiliation(s)
- Sulochan Malla
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Annie G Bryant
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- School of Physics, The University of Sydney, Sydney, Australia
| | - Rojashree Jayakumar
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Benjamin Woost
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Nina Wolf
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Andrew Li
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Sudeshna Das
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Susanne J van Veluw
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Rachel E Bennett
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
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Sakaie K, Koenig K, Lerner A, Appleby B, Ogrocki P, Pillai JA, Rao S, Leverenz JB, Lowe MJ. Multi-shell diffusion MRI of the fornix as a biomarker for cognition in Alzheimer's disease. Magn Reson Imaging 2024; 109:221-226. [PMID: 38521367 DOI: 10.1016/j.mri.2024.03.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 03/05/2024] [Accepted: 03/19/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND AND PURPOSE A substantial fraction of those who had Alzheimer's Disease (AD) pathology on autopsy did not have dementia in life. While biomarkers for AD pathology are well-developed, biomarkers specific to cognitive domains affected by early AD are lagging. Diffusion MRI (dMRI) of the fornix is a candidate biomarker for early AD-related cognitive changes but is susceptible to bias due to partial volume averaging (PVA) with cerebrospinal fluid. The purpose of this work is to leverage multi-shell dMRI to correct for PVA and to evaluate PVA-corrected dMRI measures in fornix as a biomarker for cognition in AD. METHODS Thirty-three participants in the Cleveland Alzheimer's Disease Research Center (CADRC) (19 with normal cognition (NC), 10 with mild cognitive impairment (MCI), 4 with dementia due to AD) were enrolled in this study. Multi-shell dMRI was acquired, and voxelwise fits were performed with two models: 1) diffusion tensor imaging (DTI) that was corrected for PVA and 2) neurite orientation dispersion and density imaging (NODDI). Values of tissue integrity in fornix were correlated with neuropsychological scores taken from the Uniform Data Set (UDS), including the UDS Global Composite 5 score (UDSGC5). RESULTS Statistically significant correlations were found between the UDSGC5 and PVA-corrected measure of mean diffusivity (MDc, r = -0.35, p < 0.05) from DTI and the intracelluar volume fraction (ficvf, r = 0.37, p < 0.04) from NODDI. A sensitivity analysis showed that the relationship to MDc was driven by episodic memory, which is often affected early in AD, and language. CONCLUSION This cross-sectional study suggests that multi-shell dMRI of the fornix that has been corrected for PVA is a potential biomarker for early cognitive domain changes in AD. A longitudinal study will be necessary to determine if the imaging measure can predict cognitive decline.
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Affiliation(s)
- Ken Sakaie
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA.
| | - Katherine Koenig
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
| | - Alan Lerner
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Brian Appleby
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Paula Ogrocki
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Jagan A Pillai
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - Stephen Rao
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-10, Cleveland, OH 44195, USA
| | - Mark J Lowe
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
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6
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Heo S, Yoon CW, Kim SY, Kim WR, Na DL, Noh Y. Alterations of Structural Network Efficiency in Early-Onset and Late-Onset Alzheimer's Disease. J Clin Neurol 2024; 20:265-275. [PMID: 38330417 PMCID: PMC11076196 DOI: 10.3988/jcn.2023.0092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 08/17/2023] [Accepted: 10/05/2023] [Indexed: 02/10/2024] Open
Abstract
BACKGROUND AND PURPOSE Early- and late-onset Alzheimer's disease (EOAD and LOAD, respectively) share the same neuropathological hallmarks of amyloid and neurofibrillary tangles but have distinct cognitive features. We compared structural brain connectivity between the EOAD and LOAD groups using structural network efficiency and evaluated the association of structural network efficiency with the cognitive profile and pathological markers of Alzheimer's disease (AD). METHODS The structural brain connectivity networks of 80 AD patients (47 with EOAD and 33 with LOAD) and 57 healthy controls were reconstructed using diffusion-tensor imaging. Graph-theoretic indices were calculated and intergroup differences were evaluated. Correlations between network parameters and neuropsychological test results were analyzed. The correlations of the amyloid and tau burdens with network parameters were evaluated for the patients and controls. RESULTS Compared with the age-matched control group, the EOAD patients had increased global path length and decreased global efficiency, averaged local efficiency, and averaged clustering coefficient. In contrast, no significant differences were found in the LOAD patients. Locally, the EOAD patients showed decreases in local efficiency and the clustering coefficient over a wide area compared with the control group, whereas LOAD patients showed such decreases only within a limited area. Changes in network parameters were significantly correlated with multiple cognitive domains in EOAD patients, but only with Clinical Dementia Rating Sum-of-Boxes scores in LOAD patients. Finally, the tau burden was correlated with changes in network parameters in AD signature areas in both patient groups, while there was no correlation with the amyloid burden. CONCLUSIONS The impairment of structural network efficiency and its effects on cognition may differ between EOAD and LOAD.
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Affiliation(s)
- Suyeon Heo
- Gachon University, College of Medicine, Incheon, Korea
| | - Cindy W Yoon
- Department of Neurology, Inha University School of Medicine, Incheon, Korea
| | - Sang-Young Kim
- Neuroscience Research Institute, Gachon University, Incheon, Korea
- MR Clinical Science, Health Systems, Philips Healthcare, Seoul, Korea
| | - Woo-Ram Kim
- Neuroscience Research Institute, Gachon University, Incheon, Korea
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Happymind Clinic, Seoul, Korea
| | - Young Noh
- Neuroscience Research Institute, Gachon University, Incheon, Korea
- Department of Neurology, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea.
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Warner NS, Hanson AC, Schulte PJ, Kara F, Reid RI, Schwarz CG, Benarroch EE, Graff-Radford J, Vemuri P, Jack CR, Petersen RC, Warner DO, Mielke MM, Kantarci K. Prescription Opioids and Brain Structure in Community-Dwelling Older Adults. Mayo Clin Proc 2024; 99:716-726. [PMID: 38702125 PMCID: PMC11081533 DOI: 10.1016/j.mayocp.2024.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 12/22/2023] [Accepted: 01/30/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE To evaluate the associations between prescription opioid exposures in community-dwelling older adults and gray and white matter structure by magnetic resonance imaging. METHODS Secondary analysis was conducted of a prospective, longitudinal population-based cohort study employing cross-sectional imaging of older adult (≥65 years) enrollees between November 1, 2004, and December 31, 2017. Gray matter outcomes included cortical thickness in 41 structures and subcortical volumes in 6 structures. White matter outcomes included fractional anisotropy in 40 tracts and global white matter hyperintensity volumes. The primary exposure was prescription opioid availability expressed as the per-year rate of opioid days preceding magnetic resonance imaging, with a secondary exposure of per-year total morphine milligram equivalents (MME). Multivariable models assessed associations between opioid exposures and brain structures. RESULTS The study included 2185 participants; median (interquartile range) age was 80 (75 to 85) years, 47% were women, and 1246 (57%) received opioids. No significant associations were found between opioids and gray matter. Increased opioid days and MME were associated with decreased white matter fractional anisotropy in 15 (38%) and 16 (40%) regions, respectively, including the corpus callosum, posterior thalamic radiation, and anterior limb of the internal capsule, among others. Opioid days and MME were also associated with greater white matter hyperintensity volume (1.02 [95% CI, 1.002 to 1.036; P=.029] and 1.01 [1.001 to 1.024; P=.032] increase in the geometric mean, respectively). CONCLUSION The duration and dose of prescription opioids were associated with decreased white matter integrity but not with gray matter structure. Future studies with longitudinal imaging and clinical correlation are warranted to further evaluate these relationships.
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Affiliation(s)
- Nafisseh S Warner
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN.
| | - Andrew C Hanson
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | - Firat Kara
- Department of Radiology, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | | | - David O Warner
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC
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Mak E, Reid RI, Przybelski SA, Lesnick TG, Schwarz CG, Senjem ML, Raghavan S, Vemuri P, Jack CR, Min HK, Jain MK, Miyagawa T, Forsberg LK, Fields JA, Savica R, Graff-Radford J, Jones DT, Botha H, St Louis EK, Knopman DS, Ramanan VK, Dickson DW, Graff-Radford NR, Ferman TJ, Petersen RC, Lowe VJ, Boeve BF, O'Brien JT, Kantarci K. Influences of amyloid-β and tau on white matter neurite alterations in dementia with Lewy bodies. NPJ Parkinsons Dis 2024; 10:76. [PMID: 38570511 PMCID: PMC10991290 DOI: 10.1038/s41531-024-00684-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 03/13/2024] [Indexed: 04/05/2024] Open
Abstract
Dementia with Lewy bodies (DLB) is a neurodegenerative condition often co-occurring with Alzheimer's disease (AD) pathology. Characterizing white matter tissue microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) may help elucidate the biological underpinnings of white matter injury in individuals with DLB. In this study, diffusion tensor imaging (DTI) and NODDI metrics were compared in 45 patients within the dementia with Lewy bodies spectrum (mild cognitive impairment with Lewy bodies (n = 13) and probable dementia with Lewy bodies (n = 32)) against 45 matched controls using conditional logistic models. We evaluated the associations of tau and amyloid-β with DTI and NODDI parameters and examined the correlations of AD-related white matter injury with Clinical Dementia Rating (CDR). Structural equation models (SEM) explored relationships among age, APOE ε4, amyloid-β, tau, and white matter injury. The DLB spectrum group exhibited widespread white matter abnormalities, including reduced fractional anisotropy, increased mean diffusivity, and decreased neurite density index. Tau was significantly associated with limbic and temporal white matter injury, which was, in turn, associated with worse CDR. SEM revealed that amyloid-β exerted indirect effects on white matter injury through tau. We observed widespread disruptions in white matter tracts in DLB that were not attributed to AD pathologies, likely due to α-synuclein-related injury. However, a fraction of the white matter injury could be attributed to AD pathology. Our findings underscore the impact of AD pathology on white matter integrity in DLB and highlight the utility of NODDI in elucidating the biological basis of white matter injury in DLB.
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Affiliation(s)
- Elijah Mak
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Robert I Reid
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | - Hoon Ki Min
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Manoj K Jain
- Department of Radiology, Mayo Clinic, Jacksonville, FL, USA
| | - Toji Miyagawa
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Rodolfo Savica
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Erik K St Louis
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
- Center for Sleep Medicine, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | | | | | - Dennis W Dickson
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL, USA
| | | | - Tanis J Ferman
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Ronald C Petersen
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.
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9
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Jäger HR. The connection between cerebral amyloid angiopathy and Alzheimer's disease. Eur Radiol 2024; 34:2171-2173. [PMID: 38062269 DOI: 10.1007/s00330-023-10462-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 10/31/2023] [Accepted: 11/11/2023] [Indexed: 03/22/2024]
Affiliation(s)
- Hans Rolf Jäger
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, Box 65, Queen Square, London, WC1N 3BG, UK.
- Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, London, UK.
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10
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Heise V, Offer A, Whiteley W, Mackay CE, Armitage JM, Parish S. A comprehensive analysis of APOE genotype effects on human brain structure in the UK Biobank. Transl Psychiatry 2024; 14:143. [PMID: 38472178 PMCID: PMC10933274 DOI: 10.1038/s41398-024-02848-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 02/14/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024] Open
Abstract
Alzheimer's disease (AD) risk is increased in carriers of the apolipoprotein E (APOE) ε4 allele and decreased in ε2 allele carriers compared with the ε3ε3 genotype. The aim of this study was to determine whether: the APOE genotype affects brain grey (GM) or white matter (WM) structure; and if differences exist, the age when they become apparent and whether there are differential effects by sex. We used cross-sectional magnetic resonance imaging data from ~43,000 (28,494 after pre-processing) white British cognitively healthy participants (7,446 APOE ε4 carriers) aged 45-80 years from the UK Biobank cohort and investigated image-derived phenotypes (IDPs). We observed no statistically significant effects of APOE genotype on GM structure volumes or median T2* in subcortical structures, a measure related to iron content. The volume of white matter hyperintensities differed significantly between APOE genotype groups with higher volumes in APOE ε4ε4 (effect size 0.14 standard deviations [SD]) and ε3ε4 carriers (effect size 0.04 SD) but no differences in ε2 carriers compared with ε3ε3 carriers. WM integrity measures in the dorsal (mean diffusivity [MD]) and ventral cingulum (MD and intracellular volume fraction), posterior thalamic radiation (MD and isotropic volume fraction) and sagittal stratum (MD) indicated lower integrity in APOE ε4ε4 carriers (effect sizes around 0.2-0.3 SD) and ε3ε4 (effect sizes around 0.05 SD) carriers but no differences in ε2 carriers compared with the APOE ε3ε3 genotype. Effects did not differ between men and women. APOE ε4 homozygotes had lower WM integrity specifically at older ages with a steeper decline of WM integrity from the age of 60 that corresponds to around 5 years greater "brain age". APOE genotype affects various white matters measures, which might be indicative of preclinical AD processes. This hypothesis can be assessed in future when clinical outcomes become available.
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Affiliation(s)
- Verena Heise
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Alison Offer
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - William Whiteley
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Clare E Mackay
- Department of Psychiatry, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, University of Oxford, Oxford, UK
| | - Jane M Armitage
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Sarah Parish
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
- Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
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11
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Cha WJ, Yi D, Ahn H, Byun MS, Chang YY, Choi JM, Kim K, Choi H, Jung G, Kang KM, Sohn CH, Lee YS, Kim YK, Lee DY. Association between brain amyloid deposition and longitudinal changes of white matter hyperintensities. Alzheimers Res Ther 2024; 16:50. [PMID: 38454444 PMCID: PMC10918927 DOI: 10.1186/s13195-024-01417-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 02/20/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Growing evidence suggests that not only cerebrovascular disease but also Alzheimer's disease (AD) pathological process itself cause cerebral white matter degeneration, resulting in white matter hyperintensities (WMHs). Some preclinical evidence also indicates that white matter degeneration may precede or affect the development of AD pathology. This study aimed to clarify the direction of influence between in vivo AD pathologies, particularly beta-amyloid (Aβ) and tau deposition, and WMHs through longitudinal approach. METHODS Total 282 older adults including cognitively normal and cognitively impaired individuals were recruited from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE) cohort. The participants underwent comprehensive clinical and neuropsychological assessment, [11C] Pittsburgh Compound B PET for measuring Aβ deposition, [18F] AV-1451 PET for measuring tau deposition, and MRI scans with fluid-attenuated inversion recovery image for measuring WMH volume. The relationships between Aβ or tau deposition and WMH volume were examined using multiple linear regression analysis. In this analysis, baseline Aβ or tau were used as independent variables, and change of WMH volume over 2 years was used as dependent variable to examine the effect of AD pathology on increase of WMH volume. Additionally, we set baseline WMH volume as independent variable and longitudinal change of Aβ or tau deposition for 2 years as dependent variables to investigate whether WMH volume could precede AD pathologies. RESULTS Baseline Aβ deposition, but not tau deposition, had significant positive association with longitudinal change of WMH volume over 2 years. Baseline WMH volume was not related with any of longitudinal change of Aβ or tau deposition for 2 years. We also found a significant interaction effect between baseline Aβ deposition and sex on longitudinal change of WMH volume. Subsequent subgroup analyses showed that high baseline Aβ deposition was associated with increase of WMH volume over 2 years in female, but not in male. CONCLUSIONS Our findings suggest that Aβ deposition accelerates cerebral WMHs, particularly in female, whereas white matter degeneration appears not influence on longitudinal Aβ increase. The results also did not support any direction of influence between tau deposition and WMHs.
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Affiliation(s)
- Woo-Jin Cha
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Hyejin Ahn
- Interdisciplinary program of cognitive science, Seoul National University College of Humanities, Seoul, Republic of Korea
| | - Min Soo Byun
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yoon Young Chang
- Department of Psychiatry, Inje University Sanggye Paik Hospital, Seoul, Republic of Korea
| | - Jung-Min Choi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Kyungtae Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyeji Choi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Gijung Jung
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yun-Sang Lee
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea.
- Interdisciplinary program of cognitive science, Seoul National University College of Humanities, Seoul, Republic of Korea.
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
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12
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To XV, Mohamed AZ, Cumming P, Nasrallah FA. Diffusion tensor imaging and plasma immunological biomarker panel in a rat traumatic brain injury (TBI) model and in human clinical TBI. Front Immunol 2024; 14:1293471. [PMID: 38259455 PMCID: PMC10800599 DOI: 10.3389/fimmu.2023.1293471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 12/11/2023] [Indexed: 01/24/2024] Open
Abstract
Introduction Neuroinflammatory reactions play a significant role in the pathology and long-term consequences of traumatic brain injury (TBI) and may mediate salutogenic processes that white matter integrity. This study aimed to investigate the relationship between inflammatory markers and white matter integrity following TBI in both a rat TBI model and clinical TBI cases. Methods In the rat model, blood samples were collected following a controlled cortical impact (CCI) to assess a panel of inflammatory markers; MR-based diffusion tensor imaging (DTI) was employed to evaluate white matter integrity 60 days post-injury. 15 clinical TBI patients were similarly assessed for a panel of inflammatory markers and DTI post-intensive care unit discharge. Blood samples from healthy controls were used for comparison of the inflammatory markers. Results Time-dependent elevations in immunological markers were observed in TBI rats, with a correlation to preserved fractional anisotropy (FA) in white matter. Specifically, TBI-induced increased plasma levels of IL-1β, IL-6, G-CSF, CCL3, CCL5, and TNF-α were associated with higher white matter integrity, as measured by FA. Clinical cases had similar findings: elevated inflammatory markers (relative to controls) were associated with preservation of FA in vulnerable white matter regions. Discussion Inflammatory markers in post-TBI plasma samples are ambivalent with respect to prediction of favourable outcome versus a progression to more pervasive pathology and morbidity.
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Affiliation(s)
- Xuan Vinh To
- The Queensland Brain Institute, The University of Queensland, Queensland, Australia
| | - Abdalla Z. Mohamed
- The Queensland Brain Institute, The University of Queensland, Queensland, Australia
- Thompson Institute, University of the Sunshine Coast, Queensland, Australia
| | - Paul Cumming
- Department of Nuclear Medicine, Bern University Hospital, Bern, Switzerland
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Fatima A. Nasrallah
- The Queensland Brain Institute, The University of Queensland, Queensland, Australia
- The Centre for Advanced Imaging, The University of Queensland, Queensland, Australia
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13
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Mu S, Lu W, Yu G, Zheng L, Qiu J. Deep learning-based grading of white matter hyperintensities enables identification of potential markers in multi-sequence MRI data. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 243:107904. [PMID: 37924768 DOI: 10.1016/j.cmpb.2023.107904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 10/06/2023] [Accepted: 10/27/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND White matter hyperintensities (WMHs) are widely-seen in the aging population, which are associated with cerebrovascular risk factors and age-related cognitive decline. At present, structural atrophy and functional alterations coexisted with WMHs lacks comprehensive investigation. This study developed a WMHs risk prediction model to evaluate WHMs according to Fazekas scales, and to locate potential regions with high risks across the entire brain. METHODS We developed a WMHs risk prediction model, which consisted of the following steps: T2 fluid attenuated inversion recovery (T2-FLAIR) image of each participant was firstly segmented into 1000 tiles with the size of 32 × 32 × 1, features from the tiles were extracted using the ResNet18-based feature extractor, and then a 1D convolutional neural network (CNN) was used to score all tiles based on the extracted features. Finally, a multi-layer perceptron (MLP) was constructed to predict the Fazekas scales based on the tile scores. The proposed model was trained using T2-FLAIR images, we selected tiles with abnormal scores in the test set after prediction, and evaluated their corresponding gray matter (GM) volume, white matter (WM) volume, fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF) via longitudinal and multi-sequence Magnetic Resonance Imaging (MRI) data analysis. RESULTS The proposed WMHs risk prediction model could accurately predict the Fazekas ratings based on the tile scores from T2-FLAIR MRI images with accuracy of 0.656, 0.621 in training data set and test set, respectively. The longitudinal MRI validation revealed that most of the high-risk tiles predicted by the WMHs risk prediction model in the baseline images had WMHs in the corresponding positions in the longitudinal images. The validation on multi-sequence MRI demonstrated that WMHs were associated with GM and WM atrophies, WM micro-structural and perfusion alterations in high-risk tiles, and multi-modal MRI measures of most high-risk tiles showed significant associations with Mini Mental State Examination (MMSE) score. CONCLUSION Our proposed WMHs risk prediction model can not only accurately evaluate WMH severities according to Fazekas scales, but can also uncover potential markers of WMHs across modalities. The WMHs risk prediction model has the potential to be used for the early detection of WMH-related alterations in the entire brain and WMH-induced cognitive decline.
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Affiliation(s)
- Si Mu
- College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai'an, Shandong, 271000, China
| | - Weizhao Lu
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, 271000, China
| | - Guanghui Yu
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, 271000, China
| | - Lei Zheng
- Department of Radiology, Rushan Hospital of Chinese Medicine, Rushan, Shandong, 264500, China.
| | - Jianfeng Qiu
- School of Radiology, Shandong First Medical University & Shandong Academy of Medicine Sciences, Tai'an, Shandong, 271000, China; Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250000, China.
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14
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Qiu D, Zhou S, Donnelly J, Xia D, Zhao L. Aerobic exercise attenuates abnormal myelination and oligodendrocyte differentiation in 3xTg-AD mice. Exp Gerontol 2023; 182:112293. [PMID: 37730187 DOI: 10.1016/j.exger.2023.112293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 09/10/2023] [Accepted: 09/17/2023] [Indexed: 09/22/2023]
Abstract
Pathological features of Alzheimer's Disease (AD) include alterations in the structure and function of neurons as well as of myelin sheaths. Accumulated evidence shows that aerobic type of exercise can enhance neuroplasticity in mouse models of AD. However, whether and how aerobic exercise can affect myelin sheath repair and neuroprotection in the AD models remains unclear. In this study we tested the hypotheses that 1) myelin structural alterations in 3xTg-AD mice would be related to abnormalities in oligodendrocyte lineage cells, resulting in impaired learning and memory, and 2) a 6-month aerobic exercise intervention would have beneficial effects on such alterations. Two-month-old male 3xTg-AD mice were randomly assigned to a control (AC) or an exercise (AE) group, and age-matched male C57BL/6;129 mice were also randomly assigned to a normal control (NC) or an exercise (NE) group, with n = 12 in each group. Mice in the exercise groups were trained on a motor-drive treadmill, 60 min per day, 5 days per week for 6 months. Cognitive function was assessed at the end of the intervention period. Then, brain specimens were obtained for assessments of morphological and oligodendrocyte lineage cell changes. The results of electron microscopy showed that myelin ultrastructure demonstrated a higher percentage of loose and granulated myelin sheath around axons in the temporal lobe in the AC, as compared with the NC group, along with greater cognitive dysfunction at 8-months of age. These differences were accompanied by significantly greater myelin basic protein (MBP) expression and less neuron-glial antigen-2 (NG2) protein and mRNA levels in the AC, compared to the NC. However, there were no significant between-group differences in the G-ratio (the ratio of axon diameter to axon plus myelin sheath diameter) and 2',3'-cyclic-nucleotide 3'-phosphodiesterase (CNPase) protein and mRNA levels. The aerobic exercise ameliorated cognitive deterioration and appeared to keep components of myelin sheath and oligodendrocyte precursor cells stabilized, resulting in a decrease in the percentage of loose and granulated myelin sheath and MBP protein, and an increase in NG2 protein and mRNA levels in the AE group. Therefore, the 6-month exercise intervention demonstrated beneficial effects on myelin lesions, abnormal differentiation of oligodendrocytes and general brain function in the 3xTg-AD mice, providing further insights into the role of aerobic exercise in management of neurodegeneration in AD by maintaining intact myelination.
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Affiliation(s)
- Dan Qiu
- Baotou Teachers' College, Inner Mongolia University of Science and Technology, Baotou 014030, China; Key Laboratory of Physical Fitness and Exercise, Ministry of Education, Beijing Sport University, Beijing, China; Physical Activity, Sport and Exercise Research Theme, Faculty of Health, Southern Cross University, Lismore, NSW, Australia
| | - Shi Zhou
- Physical Activity, Sport and Exercise Research Theme, Faculty of Health, Southern Cross University, Lismore, NSW, Australia.
| | | | - Dongdong Xia
- Key Laboratory of Physical Fitness and Exercise, Ministry of Education, Beijing Sport University, Beijing, China
| | - Li Zhao
- Key Laboratory of Physical Fitness and Exercise, Ministry of Education, Beijing Sport University, Beijing, China.
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15
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Shrestha S, Zhu X, Sullivan KJ, Blackshear C, Deal JA, Sharrett AR, Kamath V, Schneider ALC, Jack CR, Huang J, Palta P, Reid RI, Knopman DS, Gottesman RF, Chen H, Windham BG, Griswold ME, Mosley TH. Association of Olfaction and Microstructural Integrity of Brain Tissue in Community-Dwelling Adults: Atherosclerosis Risk in Communities Neurocognitive Study. Neurology 2023; 101:e1328-e1340. [PMID: 37541841 PMCID: PMC10558165 DOI: 10.1212/wnl.0000000000207636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 05/30/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Research on olfaction and brain neuropathology may help understand brain regions associated with normal olfaction and dementia pathophysiology. To identify early regional brain structures affected in poor olfaction, we examined cross-sectional associations of microstructural integrity of the brain with olfaction in the Atherosclerosis Risk in Communities Neurocognitive Study. METHODS Participants were selected from a prospective cohort study of community-dwelling adults; selection criteria included the following: evidence of cognitive impairment, participation in a previous MRI study, and a random sample of cognitively normal participants. Microstructural integrity was measured by 2 diffusion tensor imaging (DTI) measures, fractional anisotropy (FA) and mean diffusivity (MD), and olfaction by a 12-item odor identification test at the same visit. Higher FA and MD values indicate better and worse microstructural integrity, respectively, and higher odor identification scores indicate better olfaction. We used brain region-specific linear regression models to examine associations between DTI measures and olfaction, adjusting for potential confounders. RESULTS Among 1,418 participants (mean age 76 ± 5 years, 41% male, 21% Black race, 59% with normal cognition), the mean olfaction score was 9 ± 2.3. Relevant to olfaction, higher MD in the medial temporal lobe (MTL) regions, namely the hippocampus (β -0.79 [95% CI -0.94 to -0.65] units lower olfaction score per 1 SD higher MD), amygdala, entorhinal area, and some white matter (WM) tracts connecting to these regions, was associated with olfaction. We also observed associations with MD and WM FA in multiple atlas regions that were not previously implicated in olfaction. The associations between MD and olfaction were particularly stronger in the MTL regions among individuals with mild cognitive impairment (MCI) compared with those with normal cognition (e.g., βhippocampus -0.75 [95% CI -1.02 to -0.49] and -0.44 [95% CI -0.63 to -0.26] for MCI and normal cognition, respectively, p interaction = 0.004). DISCUSSION Neuronal microstructural integrity in multiple brain regions, particularly the MTL (the regions known to be affected in early Alzheimer disease), is associated with odor identification ability. Differential associations in the MTL regions among cognitively normal individuals compared with those with MCI may reflect the earlier vs later effects of the dementia pathogenesis. It is likely that some of the associated regions may not have any functional relevance to olfaction.
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Affiliation(s)
- Srishti Shrestha
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing.
| | - Xiaoqian Zhu
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Kevin J Sullivan
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Chad Blackshear
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Jennifer A Deal
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - A Richey Sharrett
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Vidyulata Kamath
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Andrea L C Schneider
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Clifford R Jack
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Juebin Huang
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Priya Palta
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Robert I Reid
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - David S Knopman
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Rebecca F Gottesman
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Honglei Chen
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - B Gwen Windham
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Michael E Griswold
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Thomas H Mosley
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
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Hari E, Kizilates-Evin G, Kurt E, Bayram A, Ulasoglu-Yildiz C, Gurvit H, Demiralp T. Functional and structural connectivity in the Papez circuit in different stages of Alzheimer's disease. Clin Neurophysiol 2023; 153:33-45. [PMID: 37451080 DOI: 10.1016/j.clinph.2023.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 04/12/2023] [Accepted: 06/16/2023] [Indexed: 07/18/2023]
Abstract
OBJECTIVE Alzheimer's disease (AD) is a progressive neurodegenerative continuum with memory impairment. We aimed to examine the detailed functional (FC) and structural connectivity (SC) pattern of the Papez circuit, known as the memory circuit, along the AD. METHODS MRI data of 15 patients diagnosed with AD dementia (ADD), 15 patients with the amnestic mild cognitive impairment (MCI), and 15 patients with subjective cognitive impairment were analyzed. The FC analyses were performed between main nodes of the Papez circuit, and the SC was quantified as fractional anisotropy (FA) of the main white matter pathways of the Papez circuit. RESULTS The FC between the retrosplenial (RSC) and parahippocampal cortices (PHC) was the earliest affected FC, while a manifest SC change in the ventral cingulum and fornix was observed in the later ADD stage. The RSC-PHC FC and the ventral cingulum FA efficiently predicted the memory performance of the non-demented participants. CONCLUSIONS Our findings revealed the importance of the Papez circuit as target regions along the AD. SIGNIFICANCE The ventral cingulum connecting the RSC and PHC, a critical overlap area between the Papez circuit and the default mode network, seems to be a target region associated with the earliest objective memory findings in AD.
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Affiliation(s)
- Emre Hari
- Graduate School of Health Sciences, Istanbul University, 34216 Istanbul, Turkey; Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Gozde Kizilates-Evin
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Elif Kurt
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Ali Bayram
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Cigdem Ulasoglu-Yildiz
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093 Istanbul, Turkey; Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey.
| | - Hakan Gurvit
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey; Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul Faculty of Medicine, Istanbul University, 34093 Istanbul, Turkey.
| | - Tamer Demiralp
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093 Istanbul, Turkey; Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, 34093 Istanbul, Turkey.
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Wang M, Wang Y, Wang Z, Ren Q. The Abnormal Alternations of Brain Imaging in Patients with Chronic Obstructive Pulmonary Disease: A Systematic Review. J Alzheimers Dis Rep 2023; 7:901-919. [PMID: 37662615 PMCID: PMC10473125 DOI: 10.3233/adr-220083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 07/11/2023] [Indexed: 09/05/2023] Open
Abstract
Background Cognitive impairment (CI) is an important extrapulmonary complication in patients with chronic obstructive pulmonary disease (COPD). Multimodal Neuroimaging Examination can display changes in brain structure and functions in patients with COPD. Objective The purpose of this systematic review is to provide an overview of the variations in brain imaging in patients with COPD and their potential relationship with CI. Furthermore, we aim to provide new ideas and directions for future research. Methods Literature searches were performed using the electronic databases PubMed, Scopus, and ScienceDirect. All articles published between January 2000 and November 2021 that met the eligibility criteria were included. Results Twenty of the 23 studies focused on changes in brain structure and function. Alterations in the brain's macrostructure are manifested in the bilateral frontal lobe, hippocampus, right temporal lobe, motor cortex, and supplementary motor area. The white matter microstructural changes initially appear in the bilateral frontal subcortical region. Regarding brain function, patients with COPD exhibited reduced frontal cerebral perfusion and abnormal alterations in intrinsic brain activity in the bilateral posterior cingulate cortex, precuneus, right lingual gyrus, and left anterior central gyrus. Currently, there is limited research related to brain networks. Conclusion CI in patients with COPD may present as a type of dementia different from Alzheimer's disease, which tends to manifest as frontal cognitive decline early in the disease. Further studies are required to clarify the neurobiological pathways of CI in patients with COPD from the perspective of brain connectomics based on the whole-brain system in the future.
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Affiliation(s)
- Mengxue Wang
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Yanjuan Wang
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
| | - Qingguo Ren
- Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, China
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18
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Garnier-Crussard A, Cotton F, Krolak-Salmon P, Chételat G. White matter hyperintensities in Alzheimer's disease: Beyond vascular contribution. Alzheimers Dement 2023; 19:3738-3748. [PMID: 37027506 DOI: 10.1002/alz.13057] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/15/2023] [Accepted: 03/03/2023] [Indexed: 04/09/2023]
Abstract
White matter hyperintensities (WMH), frequently seen in older adults, are usually considered vascular lesions, and participate in the vascular contribution to cognitive impairment and dementia. However, emerging evidence highlights the heterogeneity of WMH pathophysiology, suggesting that non-vascular mechanisms could also be involved, notably in Alzheimer's disease (AD). This led to the alternative hypothesis that in AD, part of WMH may be secondary to AD-related processes. The current perspective brings together the arguments from different fields of research, including neuropathology, neuroimaging and fluid biomarkers, and genetics, in favor of this alternative hypothesis. Possible underlying mechanisms leading to AD-related WMH, such as AD-related neurodegeneration or neuroinflammation, are discussed, as well as implications for diagnostic criteria and management of AD. We finally discuss ways to test this hypothesis and remaining challenges. Acknowledging the heterogeneity of WMH and the existence of AD-related WMH may improve personalized diagnosis and care of patients.
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Affiliation(s)
- Antoine Garnier-Crussard
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders," Neuropresage Team, Cyceron, Caen, France
- Clinical and Research Memory Center of Lyon, Lyon Institute For Aging, Hospices Civils de Lyon, Villeurbanne, France
- Eduwell team, Lyon Neuroscience Research Center (CRNL), INSERM U1028, CNRS UMR5292, UCBL1, Lyon, France
| | - François Cotton
- Radiology Department, Centre Hospitalier Lyon-Sud, Hospices Civils de Lyon, Pierre-Bénite, France
- CREATIS, INSERM U1044, CNRS UMR 5220, UCBL1, Villeurbanne, France
| | - Pierre Krolak-Salmon
- Clinical and Research Memory Center of Lyon, Lyon Institute For Aging, Hospices Civils de Lyon, Villeurbanne, France
- Eduwell team, Lyon Neuroscience Research Center (CRNL), INSERM U1028, CNRS UMR5292, UCBL1, Lyon, France
| | - Gaël Chételat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders," Neuropresage Team, Cyceron, Caen, France
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Mohamed AZ, Lagopoulos J, Nasrallah FA, Shan Z. Self-reported Fatigue was Associated with Increased White-matter Alterations in Long-term Traumatic Brain Injury and Posttraumatic Stress Disorder Patients. Neuroscience 2023; 520:46-57. [PMID: 37080447 PMCID: PMC10357124 DOI: 10.1016/j.neuroscience.2023.03.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/12/2023] [Accepted: 03/28/2023] [Indexed: 04/22/2023]
Abstract
Fatigue is a long-lasting problem in traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD), with limited research that investigated the fatigue-related white-matter changes within TBI and/or PTSD cohorts. This exploratory cross-sectional study used diffusion tensor imaging (DTI) and neuropsychological data collected from 153 male Vietnam War veterans, as part of the Alzheimer's Disease Neuroimaging Initiative - Department of Defense, and were divided clinically into control veterans, PTSD, TBI, and with both TBI and PTSD (TBI + PTSD). The existence of fatigue was defined by the question "Do you often feel tired, fatigued, or sleepy during the daytime?". DTI data were compared between fatigue and non-fatigue subgroups in each clinical group using tract-based spatial statistics voxel-based differences. Fatigue was reported in controls (29.55%), slightly higher in TBI (52.17%, PBenf = 0.06), and significantly higher in both TBI + PTSD (66.67%, PBenf = 0.001) and PTSD groups (79.25%, PBenf < 0.001). Compared to non-fatigued subgroups, no white-matter differences were observed in the fatigued subgroups of control or TBI, while the fatigued PTSD subgroup only showed increased diffusivity measures (i.e., radial and axial), and the fatigued TBI + PTSD subgroup showed decreased fractional anisotropy and increased diffusivity measures (PFWE ≤ 0.05). The results act as preliminary findings suggesting fatigue to be significantly reported in TBI + PTSD and PTSD decades post-trauma with a possible link to white-matter microstructural differences in both PTSD and TBI + PTSD. Future studies with larger cohorts and detailed fatigue assessments would be required to identify the white-matter changes associated with fatigue in these cohorts.
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Affiliation(s)
- Abdalla Z Mohamed
- Thompson Institute, University of the Sunshine Coast, Sunshine Coast, QLD 4575, Australia.
| | - Jim Lagopoulos
- Thompson Institute, University of the Sunshine Coast, Sunshine Coast, QLD 4575, Australia
| | - Fatima A Nasrallah
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Zack Shan
- Thompson Institute, University of the Sunshine Coast, Sunshine Coast, QLD 4575, Australia
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Tian J, Raghavan S, Reid RI, Przybelski SA, Lesnick TG, Gebre RK, Graff-Radford J, Schwarz CG, Lowe VJ, Kantarci K, Knopman DS, Petersen RC, Jack CR, Vemuri P. White Matter Degeneration Pathways Associated With Tau Deposition in Alzheimer Disease. Neurology 2023; 100:e2269-e2278. [PMID: 37068958 PMCID: PMC10259272 DOI: 10.1212/wnl.0000000000207250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 02/16/2023] [Indexed: 04/19/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The dynamics of white matter (WM) changes are understudied in Alzheimer disease (AD). Our goal was to study the association between flortaucipir PET and WM health using neurite orientation dispersion and density imaging (NODDI) and evaluate its association with cognitive performance. Specifically, we focused on NODDI's Neurite Density Index (NDI), which aids in capturing axonal degeneration in WM and has greater specificity than single-shell diffusion MRI methods. METHOD We estimated regional flortaucipir PET standard uptake value ratios (SUVRs) from 3 regions corresponding to Braak stage I, III/IV, and V/VI to capture the spatial distribution pattern of the 3R/4R tau in AD. Then, we evaluated the associations between these measurements and NDIs in 29 candidate WM tracts using Pearson correlation and multiple regression models. RESULTS Based on 223 participants who were amyloid positive (mean age of 78 years and 57.0% male, 119 cognitively unimpaired, 56 mild cognitive impairment, and 48 dementia), the results showed that WM tracts NDI decreased with increasing regional Braak tau SUVRs. Of all the significant WM tracts, the uncinate fasciculus (r = -0.274 for Braak I, -0.311 for Braak III/IV, and -0.292 for Braak V/VI, p < 0.05) and cingulum adjoining hippocampus (r = -0.274, -0.288, -0.233, p < 0.05), both tracts anatomically connected to areas of early tau deposition, were consistently found to be within the top 5 distinguishing WM tracts associated with flortaucipir SUVRs. The increase in tau deposition measurable outside the medial temporal lobes in Braak III-VI was associated with a decrease in NDI in the middle and inferior temporal WM tracts. For cognitive performance, WM NDI had similar coefficients of determination (r 2 = 31%) as regional Braak flortaucipir SUVRs (29%), and together WM NDI and regional Braak flortaucipir SUVRs explained 46% of the variance in cognitive performance. DISCUSSION We found spatially dependent WM degeneration associated with regional flortaucipir SUVRs in Braak stages, suggesting a spatial pattern in WM damage. NDI, a specific marker of axonal density, provides complementary information about disease staging and progression in addition to tau deposition. Measurements of WM changes are important for the mechanistic understanding of multifactorial pathways through which AD causes cognitive dysfunction.
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Affiliation(s)
- Jianqiao Tian
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Sheelakumari Raghavan
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Robert I Reid
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Scott A Przybelski
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Timothy G Lesnick
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Robel K Gebre
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Jonathan Graff-Radford
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Christopher G Schwarz
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Val J Lowe
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Kejal Kantarci
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - David S Knopman
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Ronald C Petersen
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN
| | - Prashanthi Vemuri
- From the Department of Radiology (J.T., S.R., R.K.G., C.G.S., V.J.L., K.K., C.R.J., P.V.), Mayo Clinic; Mayo Clinic Graduate School of Biomedical Sciences (J.T.); and Department of Information Technology (R.I.R.), Department of Quantitative Health Sciences (S.A.P., T.G.L.), and Department of Neurology (J.G.-R., D.S.K., R.C.P.), Mayo Clinic, Rochester, MN.
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21
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Cogswell PM, Lundt ES, Therneau TM, Mester CT, Wiste HJ, Graff-Radford J, Schwarz CG, Senjem ML, Gunter JL, Reid RI, Przybelski SA, Knopman DS, Vemuri P, Petersen RC, Jack CR. Evidence against a temporal association between cerebrovascular disease and Alzheimer's disease imaging biomarkers. Nat Commun 2023; 14:3097. [PMID: 37248223 PMCID: PMC10226977 DOI: 10.1038/s41467-023-38878-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 05/15/2023] [Indexed: 05/31/2023] Open
Abstract
Whether a relationship exists between cerebrovascular disease and Alzheimer's disease has been a source of controversy. Evaluation of the temporal progression of imaging biomarkers of these disease processes may inform mechanistic associations. We investigate the relationship of disease trajectories of cerebrovascular disease (white matter hyperintensity, WMH, and fractional anisotropy, FA) and Alzheimer's disease (amyloid and tau PET) biomarkers in 2406 Mayo Clinic Study of Aging and Mayo Alzheimer's Disease Research Center participants using accelerated failure time models. The model assumes a common pattern of progression for each biomarker that is shifted earlier or later in time for each individual and represented by a per participant age adjustment. An individual's amyloid and tau PET adjustments show very weak temporal association with WMH and FA adjustments (R = -0.07 to 0.07); early/late amyloid or tau timing explains <1% of the variation in WMH and FA adjustment. Earlier onset of amyloid is associated with earlier onset of tau (R = 0.57, R2 = 32%). These findings support a strong mechanistic relationship between amyloid and tau aggregation, but not between WMH or FA and amyloid or tau PET.
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Affiliation(s)
- Petrice M Cogswell
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
| | - Emily S Lundt
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Carly T Mester
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | | | | | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
- Department of Information Technology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Jeffrey L Gunter
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Ronald C Petersen
- Department of Quantitative Health Sciences, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
- Department of Neurology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
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22
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Beach TG, Sue LI, Scott S, Intorcia AJ, Walker JE, Arce RA, Glass MJ, Borja CI, Cline MP, Hemmingsen SJ, Qiji S, Stewart A, Martinez KN, Krupp A, McHattie R, Mariner M, Lorenzini I, Kuramoto A, Long KE, Tremblay C, Caselli RJ, Woodruff BK, Rapscak SZ, Belden CM, Goldfarb D, Choudhury P, Driver-Dunckley ED, Mehta SH, Sabbagh MN, Shill HA, Atri A, Adler CH, Serrano GE. Cerebral white matter rarefaction has both neurodegenerative and vascular causes and may primarily be a distal axonopathy. J Neuropathol Exp Neurol 2023; 82:457-466. [PMID: 37071794 PMCID: PMC10209646 DOI: 10.1093/jnen/nlad026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023] Open
Abstract
Cerebral white matter rarefaction (CWMR) was considered by Binswanger and Alzheimer to be due to cerebral arteriolosclerosis. Renewed attention came with CT and MR brain imaging, and neuropathological studies finding a high rate of CWMR in Alzheimer disease (AD). The relative contributions of cerebrovascular disease and AD to CWMR are still uncertain. In 1181 autopsies by the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND), large-format brain sections were used to grade CWMR and determine its vascular and neurodegenerative correlates. Almost all neurodegenerative diseases had more severe CWMR than the normal control group. Multivariable logistic regression models indicated that Braak neurofibrillary stage was the strongest predictor of CWMR, with additional independently significant predictors including age, cortical and diencephalic lacunar and microinfarcts, body mass index, and female sex. It appears that while AD and cerebrovascular pathology may be additive in causing CWMR, both may be solely capable of this. The typical periventricular pattern suggests that CWMR is primarily a distal axonopathy caused by dysfunction of the cell bodies of long-association corticocortical projection neurons. A consequence of these findings is that CWMR should not be viewed simply as "small vessel disease" or as a pathognomonic indicator of vascular cognitive impairment or vascular dementia.
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Affiliation(s)
- Thomas G Beach
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Lucia I Sue
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Sarah Scott
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | | | - Richard A Arce
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Michael J Glass
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | - Madison P Cline
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | - Sanaria Qiji
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Analisa Stewart
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | - Addison Krupp
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Rylee McHattie
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Monica Mariner
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | - Angela Kuramoto
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Kathy E Long
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | | | | | | | | | | | | | | | - Shyamal H Mehta
- Department of Neurology, Mayo Clinic, Scottsdale, Arizona, USA
| | | | - Holly A Shill
- Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
- Harvard Medical School & Brigham & Women’s Hospital, Boston, Massachusetts, USA
| | - Charles H Adler
- Department of Neurology, Mayo Clinic, Scottsdale, Arizona, USA
| | - Geidy E Serrano
- Banner Sun Health Research Institute, Sun City, Arizona, USA
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23
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Bergamino M, Nelson MR, Numani A, Scarpelli M, Healey D, Fuentes A, Turner G, Stokes AM. Assessment of complementary white matter microstructural changes and grey matter atrophy in a preclinical model of Alzheimer's disease. Magn Reson Imaging 2023; 101:57-66. [PMID: 37028608 DOI: 10.1016/j.mri.2023.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 04/08/2023]
Abstract
Alzheimer's disease (AD) has been associated with amyloid and tau pathology, as well as neurodegeneration. Beyond these hallmark features, white matter microstructural abnormalities have been observed using MRI. The objective of this study was to assess grey matter atrophy and white matter microstructural changes in a preclinical mouse model of AD (3xTg-AD) using voxel-based morphometry (VBM) and free-water (FW) diffusion tensor imaging (FW-DTI). Compared to controls, lower grey matter density was observed in the 3xTg-AD model, corresponding to the small clusters in the caudate-putamen, hypothalamus, and cortex. DTI-based fractional anisotropy (FA) was decreased in the 3xTg model, while the FW index was increased. Notably, the largest clusters for both FW-FA and FW index were in the fimbria, with other regions including the anterior commissure, corpus callosum, forebrain septum, and internal capsule. Additionally, the presence of amyloid and tau in the 3xTg model was confirmed with histopathology, with significantly higher levels observed across many regions of the brain. Taken together, these results are consistent with subtle neurodegenerative and white matter microstructural changes in the 3xTg-AD model that manifest as increased FW, decreased FW-FA, and decreased grey matter density.
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Affiliation(s)
- Maurizio Bergamino
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Megan R Nelson
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Asfia Numani
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Matthew Scarpelli
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Deborah Healey
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Alberto Fuentes
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Gregory Turner
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | - Ashley M Stokes
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ 85013, USA.
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24
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Hu Z, Wang L, Zhu D, Qin R, Sheng X, Ke Z, Shao P, Zhao H, Xu Y, Bai F. Retinal Alterations as Potential Biomarkers of Structural Brain Changes in Alzheimer’s Disease Spectrum Patients. Brain Sci 2023; 13:brainsci13030460. [PMID: 36979270 PMCID: PMC10046312 DOI: 10.3390/brainsci13030460] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 03/02/2023] [Accepted: 03/06/2023] [Indexed: 03/11/2023] Open
Abstract
Retinal imaging being a potential biomarker for Alzheimer’s disease is gradually attracting the attention of researchers. However, the association between retinal parameters and AD neuroimaging biomarkers, particularly structural changes, is still unclear. In this cross-sectional study, we recruited 25 cognitively impaired (CI) and 21 cognitively normal (CN) individuals. All subjects underwent retinal layer thickness and microvascular measurements with optical coherence tomography angiography (OCTA). Gray matter and white matter (WM) data such as T1-weighted magnetic resonance imaging and diffusion tensor imaging, respectively, were also collected. In addition, hippocampal subfield volumes and WM tract microstructural alterations were investigated as classical AD neuroimaging biomarkers. The microvascular and retinal features and their correlation with brain structural imaging markers were further analyzed. We observed a reduction in vessel density (VD) at the inferior outer (IO) sector (p = 0.049), atrophy in hippocampal subfield volumes, such as the subiculum (p = 0.012), presubiculum (p = 0.015), molecular_layer_HP (p = 0.033), GC-ML-DG (p = 0.043) and whole hippocampus (p = 0.033) in CI patients. Altered microstructural integrity of WM tracts in CI patients was also discovered in the cingulum hippocampal part (CgH). Importantly, we detected significant associations between retinal VD and gray matter volumes of the hippocampal subfield in CI patients. These findings suggested that the retinal microvascular measures acquired by OCTA may be markers for the early prediction of AD-related structural brain changes.
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Affiliation(s)
- Zheqi Hu
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Lianlian Wang
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing 210008, China
| | - Dandan Zhu
- Department of Ophthalmology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing University, Nanjing 210008, China
| | - Ruomeng Qin
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Xiaoning Sheng
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Zhihong Ke
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Pengfei Shao
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Hui Zhao
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing 210008, China
- Geriatric Medicine Center, Affiliated Taikang Xianlin Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
- Correspondence: ; Tel.: +86-25-83105960
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25
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Rashid T, Li K, Toledo JB, Nasrallah I, Pajewski NM, Dolui S, Detre J, Wolk DA, Liu H, Heckbert SR, Bryan RN, Williamson J, Davatzikos C, Seshadri S, Launer LJ, Habes M. Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers: Post Hoc Secondary Analysis of the SPRINT MIND Randomized Clinical Trial. JAMA Netw Open 2023; 6:e231055. [PMID: 36857053 PMCID: PMC9978954 DOI: 10.1001/jamanetworkopen.2023.1055] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2023] Open
Abstract
IMPORTANCE Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers. OBJECTIVE To investigate the regional associations of intensive vs standard BP control with small vessel disease biomarkers, such as white matter lesions (WMLs), fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF). DESIGN, SETTING, AND PARTICIPANTS The Systolic Blood Pressure Intervention Trial (SPRINT) is a multicenter randomized clinical trial that compared intensive systolic BP (SBP) control (SBP target <120 mm Hg) vs standard control (SBP target <140 mm Hg) among participants aged 50 years or older with hypertension and without diabetes or a history of stroke. The study began randomization on November 8, 2010, and stopped July 1, 2016, with a follow-up duration of approximately 4 years. A total of 670 and 458 participants completed brain magnetic resonance imaging at baseline and follow-up, respectively, and comprise the cohort for this post hoc analysis. Statistical analyses for this post hoc analysis were performed between August 2020 and October 2022. INTERVENTIONS At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment. MAIN OUTCOMES AND MEASURES The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest). RESULTS At baseline, 355 participants (mean [SD] age, 67.7 [8.0] years; 200 men [56.3%]) received intensive BP treatment and 315 participants (mean [SD] age, 67.0 [8.4] years; 199 men [63.2%]) received standard BP treatment. Intensive treatment was associated with smaller mean increases in WML volume compared with standard treatment (644.5 mm3 vs 1258.1 mm3). The smaller mean increases were observed specifically in the deep white matter regions of the left anterior corona radiata (intensive treatment, 30.3 mm3 [95% CI, 16.0-44.5 mm3]; standard treatment, 80.5 mm3 [95% CI, 53.8-107.2 mm3]), left tapetum (intensive treatment, 11.8 mm3 [95% CI, 4.4-19.2 mm3]; standard treatment, 27.2 mm3 [95% CI, 19.4-35.0 mm3]), left superior fronto-occipital fasciculus (intensive treatment, 3.2 mm3 [95% CI, 0.7-5.8 mm3]; standard treatment, 9.4 mm3 [95% CI, 5.5-13.4 mm3]), left posterior corona radiata (intensive treatment, 26.0 mm3 [95% CI, 12.9-39.1 mm3]; standard treatment, 52.3 mm3 [95% CI, 34.8-69.8 mm3]), left splenium of the corpus callosum (intensive treatment, 45.4 mm3 [95% CI, 25.1-65.7 mm3]; standard treatment, 83.0 mm3 [95% CI, 58.7-107.2 mm3]), left posterior thalamic radiation (intensive treatment, 53.0 mm3 [95% CI, 29.8-76.2 mm3]; standard treatment, 106.9 mm3 [95% CI, 73.4-140.3 mm3]), and right posterior thalamic radiation (intensive treatment, 49.5 mm3 [95% CI, 24.3-74.7 mm3]; standard treatment, 102.6 mm3 [95% CI, 71.0-134.2 mm3]). CONCLUSIONS AND RELEVANCE This study suggests that intensive BP treatment, compared with standard treatment, was associated with a slower increase of WMLs, improved diffusion tensor imaging, and FA and CBF changes in several brain regions that represent vulnerable areas that may benefit from more strict BP control. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01206062.
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Affiliation(s)
- Tanweer Rashid
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Karl Li
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Jon B. Toledo
- Department of Neurology, University of Florida, Gainesville
- Department of Neurology, Houston Methodist Hospital, Houston, Texas
| | - Ilya Nasrallah
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Sudipto Dolui
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
| | - John Detre
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Department of Neurology, University of Pennsylvania, Philadelphia
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia
| | - Hangfan Liu
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | | | - R. Nick Bryan
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
| | - Jeff Williamson
- Section of Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Christos Davatzikos
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Sudha Seshadri
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Lenore J. Launer
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland
| | - Mohamad Habes
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
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26
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Yao J, Tendler BC, Zhou Z, Lei H, Zhang L, Bao A, Zhong J, Miller KL, He H. Both noise-floor and tissue compartment difference in diffusivity contribute to FA dependence on b-value in diffusion MRI. Hum Brain Mapp 2023; 44:1371-1388. [PMID: 36264194 PMCID: PMC9921221 DOI: 10.1002/hbm.26121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 08/27/2022] [Accepted: 10/09/2022] [Indexed: 11/06/2022] Open
Abstract
Noninvasive diffusion magnetic resonance imaging (dMRI) has been widely employed in both clinical and research settings to investigate brain tissue microstructure. Despite the evidence that dMRI-derived fractional anisotropy (FA) correlates with white matter properties, the metric is not specific. Recent studies have reported that FA is dependent on the b-value, and its origin has primarily been attributed to either the influence of microstructure or the noise-floor effect. A systematic investigation into the inter-relationship of these two effects is however still lacking. This study aims to quantify contributions of the reported differences in intra- and extra-neurite diffusivity to the observed changes in FA, in addition to the noise in measurements. We used in-vivo and post-mortem human brain imaging, as well as numerical simulations and histological validation, for this purpose. Our investigations reveal that the percentage difference of FA between b-values (pdFA) has significant positive associations with neurite density index (NDI), which is derived from in-vivo neurite orientation dispersion and density imaging (NODDI), or Bielschowsky's silver impregnation (BIEL) staining sections of fixed post-mortem human brain samples. Furthermore, such an association is found to be varied with Signal-to-Noise Ratio (SNR) level, indicating a nonlinear interaction effect between tissue microstructure and noise. Finally, a multicompartment model simulation revealed that these findings can be driven by differing diffusivities of intra- and extra-neurite compartments in tissue, with the noise-floor further amplifying the effect. In conclusion, both the differences in intra- and extra-neurite diffusivity and noise-floor effects significantly contribute to the FA difference associated with the b-value.
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Affiliation(s)
- Junye Yao
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, Zhejiang, China
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Zihan Zhou
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hao Lei
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Lei Zhang
- Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University, Hangzhou, China.,National Human Brain Bank for Health and Disease, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
| | - Aimin Bao
- Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University, Hangzhou, China.,National Human Brain Bank for Health and Disease, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, Zhejiang, China.,Department of Imaging Sciences, University of Rochester, Rochester, New York, USA
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, Zhejiang, China
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27
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Leng F, Hinz R, Gentleman S, Hampshire A, Dani M, Brooks DJ, Edison P. Neuroinflammation is independently associated with brain network dysfunction in Alzheimer's disease. Mol Psychiatry 2023; 28:1303-1311. [PMID: 36474000 PMCID: PMC10005956 DOI: 10.1038/s41380-022-01878-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 09/17/2022] [Accepted: 11/08/2022] [Indexed: 12/12/2022]
Abstract
Brain network dysfunction is increasingly recognised in Alzheimer's disease (AD). However, the causes of brain connectivity disruption are still poorly understood. Recently, neuroinflammation has been identified as an important factor in AD pathogenesis. Microglia participate in the construction and maintenance of healthy neuronal networks, but pro-inflammatory microglia can also damage these circuits. We hypothesised that microglial activation is independently associated with brain connectivity disruption in AD. We performed a cross-sectional multimodal imaging study and interrogated the relationship between imaging biomarkers of neuroinflammation, Aβ deposition, brain connectivity and cognition. 42 participants (12 Aβ-positive MCI, 14 Aβ-positive AD and 16 Aβ-negative healthy controls) were recruited. Participants had 11C-PBR28 and 18F-flutemetamol PET to quantify Aβ deposition and microglial activation, T1-weighted, diffusion tensor and resting-state functional MRI to assess structural network and functional network. 11C-PBR28 uptake, structural network integrity and functional network orgnisation were compared across diagnostic groups and the relationship between neuroinflammation and brain network was tested in 26 Aβ-positive patients. Increased 11C-PBR28 uptake, decreased FA, network small-worldness and local efficiency were observed in AD patients. Cortical 11C-PBR28 uptake correlated negatively with structural integrity (standardised β = -0.375, p = 0.037) and network local efficiency (standardised β = -0.468, p < 0.001), independent of cortical thickness and Aβ deposition, while Aβ was not. Network structural integrity, small-worldness and local efficiency, and cortical thickness were positively associated with cognition. Our findings suggest cortical neuroinflammation coincide with structural and functional network disruption independent of Aβ and cortical atrophy. These findings link the brain connectivity change and pathological process in Alzheimer's disease, and suggest a pathway from neuroinflammation to systemic brain dysfunction.
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Affiliation(s)
- Fangda Leng
- Department of Brain Sciences, Imperial College London, London, UK
- Department of Neurology, Peking University First Hospital, Beijing, PR China
| | - Rainer Hinz
- Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
| | - Steve Gentleman
- Department of Brain Sciences, Imperial College London, London, UK
| | - Adam Hampshire
- Department of Brain Sciences, Imperial College London, London, UK
| | - Melanie Dani
- Department of Brain Sciences, Imperial College London, London, UK
| | - David J Brooks
- Department of Brain Sciences, Imperial College London, London, UK
- Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Institute of Translational and Clinical Research, University of Newcastle upon Tyne, Newcastle, UK
| | - Paul Edison
- Department of Brain Sciences, Imperial College London, London, UK.
- School of Medicine, Cardiff University, Wales, UK.
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28
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Chen Q, Abrigo J, Deng M, Shi L, Wang YX, Chu WCW. Diffusion Changes in Hippocampal Cingulum in Early Biologically Defined Alzheimer's Disease. J Alzheimers Dis 2023; 91:1007-1017. [PMID: 36530082 DOI: 10.3233/jad-220671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Diagnosis of Alzheimer's disease (AD) was recently shifted from clinical to biological construct to reflect underlying neuropathological status, where amyloid deposition designated patients to the Alzheimer's continuum, and additional tau positivity represented AD. OBJECTIVE To investigate white matter (WM) alteration in the brain of patients in the Alzheimer's continuum. METHODS A total of 236 subjects across the clinical and biological spectra of AD were included and stratified by normal/abnormal (-/+) amyloid (A) and tau (T) status based on positron emission tomography results, yielding five groups: A-T-cognitively normal (CN), A+T-CN, A+T+ CN, A+T+ mild cognitive impairment, and A+T+ AD. WM alteration was measured by diffusion tensor imaging (DTI). Group differences, correlation of DTI measures with amyloid and tau, and diagnostic performance of such measures were evaluated. RESULTS Compared with A-T-CN, widespread WM alteration was observed in the Alzheimer's continuum, including hippocampal cingulum (CGH), cingulum of the cingulate gyrus, and uncinate fasciculus. Diffusion changes measured by regional mean fractional anisotropy (FA) in the bilateral CGH were first detected in the A+T+ CN group and associated with tau burden in the Alzheimer's continuum (p < 0.001). For discrimination between A+T+ CN and A-T-CN groups, CGH FA achieved accuracy, sensitivity, and specificity of 74%, 58%, and 78% for right CGH and 57%, 83%, and 47% respectively for left CGH. CONCLUSION WM alteration is widespread in the Alzheimer's continuum. Diffusion alteration in CGH occurred early and was correlated with tau pathology, thus may be a promising biomarker in preclinical AD.
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Affiliation(s)
- Qianyun Chen
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jill Abrigo
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Min Deng
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yi-Xiang Wang
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Winnie Chiu Wing Chu
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
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Magalhães TNC, Casseb RF, Gerbelli CLB, Pimentel-Siva LR, Nogueira MH, Teixeira CVL, Carletti AFMK, de Rezende TJR, Joaquim HPG, Talib LL, Forlenza OV, Cendes F, Balthazar MLF. Whole-brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease. Brain Behav 2023; 13:e2863. [PMID: 36601694 PMCID: PMC9927845 DOI: 10.1002/brb3.2863] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 12/02/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Abstract
The causes of the neurodegenerative processes in Alzheimer's disease (AD) are not completely known. Recent studies have shown that white matter (WM) damage could be more severe and widespread than whole-brain cortical atrophy and that such damage may appear even before the damage to the gray matter (GM). In AD, Amyloid-beta (Aβ42 ) and tau proteins could directly affect WM, spreading across brain networks. Since hippocampal atrophy is common in the early phase of disease, it is reasonable to expect that hippocampal volume (HV) might be also related to WM integrity. Our study aimed to evaluate the integrity of the whole-brain WM, through diffusion tensor imaging (DTI) parameters, in mild AD and amnestic mild cognitive impairment (aMCI) due to AD (with Aβ42 alteration in cerebrospinal fluid [CSF]) in relation to controls; and possible correlations between those measures and the CSF levels of Aβ42 , phosphorylated tau protein (p-Tau) and total tau (t-Tau). We found a widespread WM alteration in the groups, and we also observed correlations between p-Tau and t-Tau with tracts directly linked to mesial temporal lobe (MTL) structures (fornix and hippocampal cingulum). However, linear regressions showed that the HV better explained the variation found in the DTI measures (with weak to moderate effect sizes, explaining from 9% to 31%) than did CSF proteins. In conclusion, we found widespread alterations in WM integrity, particularly in regions commonly affected by the disease in our group of early-stage disease and patients with Alzheimer's disease. Nonetheless, in the statistical models, the HV better predicted the integrity of the MTL tracts than the biomarkers in CSF.
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Affiliation(s)
- Thamires Naela Cardoso Magalhães
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | - Raphael Fernandes Casseb
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Seaman Family MR Research Center, University of Calgary, Calgary, Canada
| | - Christian Luiz Baptista Gerbelli
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | - Luciana Ramalho Pimentel-Siva
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | - Mateus Henrique Nogueira
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | - Camila Vieira Ligo Teixeira
- Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil.,National Institute on Aging, National Institute of Health, Baltimore, Maryland, USA
| | - Ana Flávia Mac Knight Carletti
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil
| | - Thiago Junqueira Ribeiro de Rezende
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | | | - Leda Leme Talib
- Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, University of Sao Paulo (USP), São Paulo, Brazil
| | - Orestes Vicente Forlenza
- Laboratory of Neuroscience (LIM-27), Department and Institute of Psychiatry, University of Sao Paulo (USP), São Paulo, Brazil
| | - Fernando Cendes
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
| | - Marcio Luiz Figueredo Balthazar
- Department of Neurology and Neuroimaging Laboratory, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, Brazil.,Brazilian Institute of Neuroscience and Neurotechnology, São Paulo, Brazil
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30
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Chen Z, Liu Y, Zhang Y, Li Q. Orthogonal latent space learning with feature weighting and graph learning for multimodal Alzheimer's disease diagnosis. Med Image Anal 2023; 84:102698. [PMID: 36462372 DOI: 10.1016/j.media.2022.102698] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 10/18/2022] [Accepted: 11/17/2022] [Indexed: 11/23/2022]
Abstract
Recent studies have shown that multimodal neuroimaging data provide complementary information of the brain and latent space-based methods have achieved promising results in fusing multimodal data for Alzheimer's disease (AD) diagnosis. However, most existing methods treat all features equally and adopt nonorthogonal projections to learn the latent space, which cannot retain enough discriminative information in the latent space. Besides, they usually preserve the relationships among subjects in the latent space based on the similarity graph constructed on original features for performance boosting. However, the noises and redundant features significantly corrupt the graph. To address these limitations, we propose an Orthogonal Latent space learning with Feature weighting and Graph learning (OLFG) model for multimodal AD diagnosis. Specifically, we map multiple modalities into a common latent space by orthogonal constrained projection to capture the discriminative information for AD diagnosis. Then, a feature weighting matrix is utilized to sort the importance of features in AD diagnosis adaptively. Besides, we devise a regularization term with learned graph to preserve the local structure of the data in the latent space and integrate the graph construction into the learning processing for accurately encoding the relationships among samples. Instead of constructing a similarity graph for each modality, we learn a joint graph for multiple modalities to capture the correlations among modalities. Finally, the representations in the latent space are projected into the target space to perform AD diagnosis. An alternating optimization algorithm with proved convergence is developed to solve the optimization objective. Extensive experimental results show the effectiveness of the proposed method.
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Affiliation(s)
- Zhi Chen
- Knowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Yongguo Liu
- Knowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Yun Zhang
- Knowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Qiaoqin Li
- Knowledge and Data Engineering Laboratory of Chinese Medicine, School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
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31
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Srivishagan S, Kumaralingam L, Thanikasalam K, Pinidiyaarachchi UAJ, Ratnarajah N. Discriminative patterns of white matter changes in Alzheimer's. Psychiatry Res Neuroimaging 2023; 328:111576. [PMID: 36495726 DOI: 10.1016/j.pscychresns.2022.111576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 11/12/2022] [Accepted: 11/22/2022] [Indexed: 12/02/2022]
Abstract
Changes in structural connectivity of the Alzheimer's brain have not been widely studied utilizing cutting-edge methodologies. This study develops an efficient structural connectome-based convolutional neural network (CNN) to classify the AD and uses explanations of CNNs' choices in classification to pinpoint the discriminative changes in white matter connectivity in AD. A CNN architecture has been developed to classify normal control (NC) and AD subjects from the weighted structural connectome. Then, the CNN classification decision is visually analyzed using gradient-based localization techniques to identify the discriminative changes in white matter connectivity in Alzheimer's. The cortical regions involved in the identified discriminative structural connectivity changes in AD are highly covered in the temporal/subcortical regions. A specific pattern is identified in the discriminative changes in structural connectivity of AD, where the white matter changes are revealed within the temporal/subcortical regions and from the temporal/subcortical regions to the frontal and parietal regions in both left and right hemispheres. The proposed approach has the potential to comprehensively analyze the discriminative structural connectivity differences in AD, change the way of detecting biomarkers, and help clinicians better understand the structural changes in AD and provide them with more confidence in automated diagnostic systems.
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Affiliation(s)
- Subaramya Srivishagan
- Department of Physical Science, Faculty of Applied Science, University of Vavuniya, Vavuniya, Sri Lanka; PGIS, University of Peradeniya, Peradeniya, Sri Lanka
| | - Logiraj Kumaralingam
- Department of Computer Science, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - Kokul Thanikasalam
- Department of Computer Science, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - U A J Pinidiyaarachchi
- Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka
| | - Nagulan Ratnarajah
- Department of Physical Science, Faculty of Applied Science, University of Vavuniya, Vavuniya, Sri Lanka.
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32
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Liu Y, Liu D, Liu M, Li K, Shi Q, Wang C, Pan Z, Zhou L. The microstructural abnormalities of cingulum was related to patients with mild cognitive impairment: a diffusion kurtosis imaging study. Neurol Sci 2023; 44:171-180. [PMID: 36169754 PMCID: PMC9816220 DOI: 10.1007/s10072-022-06408-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 09/13/2022] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Our study aimed to investigate the correlations between microstructural changes of cingulum and patients with mild cognitive impairment (MCI) by diffusion kurtosis imaging (DKI) technique. METHOD A total of 104 patients with cerebral small vessel diseases (cSVD) were retrospectively enrolled in this study. According to Montreal Cognitive Assessment Scale (MoCA) scores, these patients were divided into MCI group (n = 59) and non-MCI group (n = 45). The general clinical data was collected and analyzed. The regions of interests (ROIs) were selected for investigation in cingulum. The values of DKI parameters were measured in each ROI and compared between the two groups, the correlations between DKI parameters and MoCA scores were examined. RESULTS Compared to non-MCI group, MCI patients had more severe white matter hyperintensities (WMHs) (P = 0.038) and lower MoCA scores (P < 0.01). MCI patients showed significantly decreased fractional anisotropy (FA), axial kurtosis (AK), mean kurtosis (MK), radial kurtosis (RK), and kurtosis fractional anisotropy (KFA) in the left cingulum in the cingulated cortex (CgC) region (all P < 0.0125). In the left CgC region, FA, AK, MK, RK, and KFA were positively correlated with MoCA scores (r = 0.348, 0.409, 0.310, 0.441, 0.422, all P < 0.001). Meanwhile, FA, AK, MK, RK, and KFA were also positively correlated with MoCA scores (r = 0.338, 0.352, 0.289, 0.380, 0.370, all P < 0.001) in the right CgC region. CONCLUSION DKI technique could be used to explore the microstructural changes of cingulum in MCI patients and DKI-derived parameters might be feasible to evaluate MCI patients.
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Affiliation(s)
- Yueyang Liu
- Department of Neurology, Civil Aviation General Hospital, Beijing, China
| | - Dongtao Liu
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, No. 5, Jingyuan Road, Beijing, China
| | - Mingyong Liu
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, No. 5, Jingyuan Road, Beijing, China
| | - Kun Li
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Qinglei Shi
- MR Scientific Marketing, Diagnosis Imaging, Siemens Healthineers China, Beijing, China
| | - Chenlong Wang
- Department of Neurology, Civil Aviation General Hospital, Beijing, China
| | - Zhenyu Pan
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Lichun Zhou
- Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, No. 5, Jingyuan Road, Beijing, China
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33
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Lissaman R, Lancaster TM, Parker GD, Graham KS, Lawrence AD, Hodgetts CJ. Tract-specific differences in white matter microstructure between young adult APOE ε4 carriers and non-carriers: A replication and extension study. NEUROIMAGE. REPORTS 2022; 2:None. [PMID: 36507069 PMCID: PMC9726682 DOI: 10.1016/j.ynirp.2022.100126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 08/05/2022] [Accepted: 08/18/2022] [Indexed: 12/15/2022]
Abstract
The parahippocampal cingulum bundle (PHCB) interconnects regions known to be vulnerable to early Alzheimer's disease (AD) pathology, including posteromedial cortex and medial temporal lobe. While AD-related pathology has been robustly associated with alterations in PHCB microstructure, specifically lower fractional anisotropy (FA) and higher mean diffusivity (MD), emerging evidence indicates that the reverse pattern is evident in younger adults at increased risk of AD. In one such study, Hodgetts et al. (2019) reported that healthy young adult carriers of the apolipoprotein-E (APOE) ε4 allele - the strongest common genetic risk factor for AD - showed higher FA and lower MD in the PHCB but not the inferior longitudinal fasciculus (ILF). These results are consistent with proposals claiming that heightened neural activity and intrinsic connectivity play a significant role in increasing posteromedial cortex vulnerability to amyloid-β and tau spread beyond the medial temporal lobe. Given the implications for understanding AD risk, here we sought to replicate Hodgetts et al.'s finding in a larger sample (N = 128; 40 APOE ε4 carriers, 88 APOE ε4 non-carriers) of young adults (age range = 19-33). Extending this work, we also conducted an exploratory analysis using a more advanced measure of white matter microstructure: hindrance modulated orientational anisotropy (HMOA). Contrary to the original study, we did not observe higher FA or lower MD in the PHCB of APOE ε4 carriers relative to non-carriers. Bayes factors (BFs) further revealed moderate-to-strong evidence in support of these null findings. In addition, we observed no APOE ε4-related differences in PHCB HMOA. Our findings indicate that young adult APOE ε4 carriers and non-carriers do not differ in PHCB microstructure, casting some doubt on the notion that early-life variation in PHCB tract microstructure might enhance vulnerability to amyloid-β accumulation and/or tau spread.
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Affiliation(s)
- Rikki Lissaman
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
- Douglas Research Centre, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Thomas M. Lancaster
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
- School of Psychology, University of Bath, Bath, England, United Kingdom
| | - Greg D. Parker
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
| | - Kim S. Graham
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Andrew D. Lawrence
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
| | - Carl J. Hodgetts
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
- Department of Psychology, Royal Holloway, University of London, Egham, England, United Kingdom
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34
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Alruwais NM, Rusted JM, Tabet N, Dowell NG. Evidence of emerging BBB changes in mid-age apolipoprotein E epsilon-4 carriers. Brain Behav 2022; 12:e2806. [PMID: 36408825 PMCID: PMC9759141 DOI: 10.1002/brb3.2806] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/23/2022] [Accepted: 10/08/2022] [Indexed: 11/22/2022] Open
Abstract
INTRODUCTION Studies have recognized that the loss of the blood-brain barrier (BBB) integrity is a major structural biomarker where neurodegenerative disease potentially begins. Using a combination of high-quality neuroimaging techniques, we investigated potential subtle differences in BBB permeability in mid-age healthy people, comparing carriers of the apolipoprotein E epsilon-4 (APOEε4) genotype, the biggest risk factor for late onset, non-familial AD (LOAD) with APOEε3 carriers, the population norm. METHODS Forty-one cognitively healthy mid-age participants (42-59) were genotyped and pseudo-randomly selected to participate in the study by a third party. Blind to genotype, all participants had a structural brain scan acquisition including gadolinium-based dynamic contrast-enhanced magnetic resonance imaging acquired using a T1-weighted 3D vibe sequence. A B1 map and T1 map were acquired as part of the multi-parametric mapping acquisition. RESULTS Non-significant, but subtle differences in blood-brain barrier permeability were identified between healthy mid-age APOEε4 and APOEε3 carriers, matched on age, education, and gender. DISCUSSION This study demonstrated a tendency toward BBB permeability in APOEε4 participants emerging from mid-age, with quantitative differences observable on a number of the measures. While the differences did not reach a statistical significance, the results from this study hint at early changes in ε4 carrier BBB that may help identify at-risk populations and facilitate the development of early interventions to change the trajectory of decline.
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Affiliation(s)
- Nourah M Alruwais
- Health science department, College of Applied Studies and Community Services, King Saud University, Riyadh, Saudi Arabia.,School of Psychology, University of Sussex, Brighton, UK
| | | | - Naji Tabet
- Brighton and Sussex Medical School (BSMS), Brighton, UK
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Xu J, Guan X, Wen J, Zhang M, Xu X. Polygenic hazard score modified the relationship between hippocampal subfield atrophy and episodic memory in older adults. Front Aging Neurosci 2022; 14:943702. [PMID: 36389062 PMCID: PMC9659745 DOI: 10.3389/fnagi.2022.943702] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 09/30/2022] [Indexed: 12/30/2023] Open
Abstract
BACKGROUND Understanding genetic influences on Alzheimer's disease (AD) may improve early identification. Polygenic hazard score (PHS) is associated with the age of AD onset and cognitive decline. It interacts with other risk factors, but the nature of such combined effects remains poorly understood. MATERIALS AND METHODS We examined the effect of genetic risk and hippocampal atrophy pattern on episodic memory in a sample of older adults ranging from cognitively normal to those diagnosed with AD using structural MRI. Participants included 51 memory unimpaired normal control (NC), 69 mild cognitive impairment (MCI), and 43 AD adults enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Hierarchical linear regression analyses examined the main and interaction effects of hippocampal subfield volumes and PHS, indicating genetic risk for AD, on a validated episodic memory composite score. Diagnosis-stratified models further assessed the role of PHS. RESULTS Polygenic hazard score moderated the relationship between right fimbria/hippocampus volume ratio and episodic memory, such that patients with high PHS and lower volume ratio had lower episodic memory composite scores [ΔF = 6.730, p = 0.011, ΔR 2 = 0.059]. This effect was also found among individuals with MCI [ΔF = 4.519, p = 0.038, ΔR 2 = 0.050]. In contrast, no interaction effects were present for those NC or AD individuals. A follow-up mediation analysis also indicated that the right fimbria/hippocampus volume ratio might mediate the link between PHS and episodic memory performance in the MCI group, whereas no mediation effects were present for those NC or AD individuals. CONCLUSION These findings suggest that the interaction between AD genetic risk and hippocampal subfield volume ratio increases memory impairment among older adults. Also, the results highlighted a potential pathway in which genetic risk affects memory by degrading hippocampal subfield volume ratio in cognitive decline subjects.
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Affiliation(s)
| | | | | | | | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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36
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Ma J, Liu F, Wang Y, Ma L, Niu Y, Wang J, Ye Z, Zhang J. Frequency-dependent white-matter functional network changes associated with cognitive deficits in subcortical vascular cognitive impairment. Neuroimage Clin 2022; 36:103245. [PMID: 36451351 PMCID: PMC9668649 DOI: 10.1016/j.nicl.2022.103245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/07/2022] [Accepted: 10/21/2022] [Indexed: 11/11/2022]
Abstract
Vascular cognitive impairment (VCI) refers to all forms of cognitive decline associated with cerebrovascular diseases, in which white matter (WM) is highly vulnerable. Although previous studies have shown that blood oxygen level-dependent (BOLD) signals inside WM can effectively reflect neural activities, whether WM BOLD signal alterations are present and their roles underlying cognitive impairment in VCI remain largely unknown. In this study, 36 subcortical VCI (SVCI) patients and 36 healthy controls were enrolled to evaluate WM dysfunction. Specifically, fourteen distinct WM networks were identified from resting-state functional MRI using K-means clustering analysis. Subsequently, between-network functional connectivity (FC) and within-network BOLD signal amplitude of WM networks were calculated in three frequency bands (band A: 0.01-0.15 Hz, band B: 0.08-0.15 Hz, and band C: 0.01-0.08 Hz). Patients with SVCI manifested decreased FC mainly in bilateral parietal WM regions, forceps major, superior and inferior longitudinal fasciculi. These connections extensively linked with distinct WM networks and with gray-matter networks such as frontoparietal control, dorsal and ventral attention networks, which exhibited frequency-specific alterations in SVCI. Additionally, extensive amplitude reductions were found in SVCI, showing frequency-dependent properties in parietal, anterior corona radiate, pre/post central, superior and inferior longitudinal fasciculus networks. Furthermore, these decreased FC and amplitudes showed significant positive correlations with cognitive performances in SVCI, and high diagnostic performances for SVCI especially combining all bands. Our study indicated that VCI-related cognitive deficits were characterized by frequency-dependent WM functional abnormalities, which offered novel applicable neuromarkers for VCI.
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Affiliation(s)
- Juanwei Ma
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China; National Clinical Research Center for Cancer, Tianjin, China; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China; Tianjin's Clinical Research Center for Cancer, Tianjin, China; Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yang Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yali Niu
- Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jing Wang
- Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China; National Clinical Research Center for Cancer, Tianjin, China; Key Laboratory of Cancer Prevention and Therapy, Tianjin, China; Tianjin's Clinical Research Center for Cancer, Tianjin, China.
| | - Jing Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.
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Xiao D, Wang K, Theriault L, Charbel E. White matter integrity and key structures affected in Alzheimer's disease characterized by diffusion tensor imaging. Eur J Neurosci 2022; 56:5319-5331. [PMID: 36048971 DOI: 10.1111/ejn.15815] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 08/13/2022] [Accepted: 08/22/2022] [Indexed: 12/14/2022]
Abstract
White matter (WM) degeneration is suggested to predict the early signs of Alzheimer's disease (AD). The exact structural regions of brain circuitry involved are not known. This study aims to examine the associations between WM tract integrity, represented by the diffusion tensor imaging (DTI) measures, and AD diagnosis and to denote the key substrates in predicting AD. It included DTI measures of mean diffusivity (MD), fractional anisotropy, radial diffusivity and axial diffusivity of 18 main WM tracts in 84 non-Hispanic white participants from the Alzheimer's Disease Neuroimaging Initiative dataset. The multivariable general linear model was used to examine the association of AD diagnosis with each DTI measure adjusting for age, gender and education. The corpus callosum, fornix, cingulum hippocampus, uncinate fasciculus, sagittal striatum, left posterior thalamic radiation and fornix-stria terminalis showed significant increases in MD, radial and axial diffusivity, whereas the splenium of corpus callosum and the fornix showed significant decreases in fractional anisotropy among AD patients. Variable cluster analysis identified that hippocampus volume, mini-mental state examination (MMSE), cingulate gyrus/hippocampus, inferior fronto-occipital fasciculus and uncinate fasciculus are highly correlated in one cluster with MD measures. In conclusion, there were significant differences in DTI measures between the brain WM of AD patients and controls. Age is the risk factor associated with AD, not gender or education. Right cingulum gyrus and right uncinate fasciculus are particularly affected, correlating well with a cognitive test MMSE and MD measures for dementia in AD patients and could be a region of focus for AD staging.
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Affiliation(s)
- Danqing Xiao
- Department of STEM, School of Arts and Sciences, Regis College, Weston, Massachusetts, USA.,Neuroimaging Center, McLean Hospital, Belmont, Massachusetts, USA
| | - Kesheng Wang
- Department of Family and Community Health, School of Nursing, Health Sciences Center, West Virginia University, Morgantown, West Virginia, USA
| | - Luke Theriault
- Department of STEM, School of Arts and Sciences, Regis College, Weston, Massachusetts, USA.,School of Medicine, St. George's University, Saint George's, Grenada
| | - Elhelou Charbel
- Department of STEM, School of Arts and Sciences, Regis College, Weston, Massachusetts, USA
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Anctil-Robitaille B, Théberge A, Jodoin PM, Descoteaux M, Desrosiers C, Lombaert H. Manifold-aware synthesis of high-resolution diffusion from structural imaging. FRONTIERS IN NEUROIMAGING 2022; 1:930496. [PMID: 37555146 PMCID: PMC10406190 DOI: 10.3389/fnimg.2022.930496] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 08/16/2022] [Indexed: 08/10/2023]
Abstract
The physical and clinical constraints surrounding diffusion-weighted imaging (DWI) often limit the spatial resolution of the produced images to voxels up to eight times larger than those of T1w images. The detailed information contained in accessible high-resolution T1w images could help in the synthesis of diffusion images with a greater level of detail. However, the non-Euclidean nature of diffusion imaging hinders current deep generative models from synthesizing physically plausible images. In this work, we propose the first Riemannian network architecture for the direct generation of diffusion tensors (DT) and diffusion orientation distribution functions (dODFs) from high-resolution T1w images. Our integration of the log-Euclidean Metric into a learning objective guarantees, unlike standard Euclidean networks, the mathematically-valid synthesis of diffusion. Furthermore, our approach improves the fractional anisotropy mean squared error (FA MSE) between the synthesized diffusion and the ground-truth by more than 23% and the cosine similarity between principal directions by almost 5% when compared to our baselines. We validate our generated diffusion by comparing the resulting tractograms to our expected real data. We observe similar fiber bundles with streamlines having <3% difference in length, <1% difference in volume, and a visually close shape. While our method is able to generate diffusion images from structural inputs in a high-resolution space within 15 s, we acknowledge and discuss the limits of diffusion inference solely relying on T1w images. Our results nonetheless suggest a relationship between the high-level geometry of the brain and its overall white matter architecture that remains to be explored.
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Affiliation(s)
- Benoit Anctil-Robitaille
- The Shape Lab, Department of Computer and Software Engineering, ETS Montreal, Montreal, QC, Canada
| | - Antoine Théberge
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, Sherbrooke University, Sherbrooke, QC, Canada
| | - Pierre-Marc Jodoin
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, Sherbrooke University, Sherbrooke, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Department of Computer Science, Sherbrooke University, Sherbrooke, QC, Canada
| | - Christian Desrosiers
- The Shape Lab, Department of Computer and Software Engineering, ETS Montreal, Montreal, QC, Canada
| | - Hervé Lombaert
- The Shape Lab, Department of Computer and Software Engineering, ETS Montreal, Montreal, QC, Canada
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Forrest SL, Wagner S, Kim A, Kovacs GG. Association of glial tau pathology and LATE-NC in the ageing brain. Neurobiol Aging 2022; 119:77-88. [DOI: 10.1016/j.neurobiolaging.2022.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/20/2022] [Accepted: 07/27/2022] [Indexed: 11/25/2022]
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Medaglia JD, Erickson BA, Pustina D, Kelkar AS, DeMarco AT, Dickens JV, Turkeltaub PE. Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia. J Neurosci 2022; 42:4913-4926. [PMID: 35545436 PMCID: PMC9188386 DOI: 10.1523/jneurosci.1163-21.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 11/21/2022] Open
Abstract
Aphasia is a prevalent cognitive syndrome caused by stroke. The rarity of premorbid imaging and heterogeneity of lesion obscures the links between the local effects of the lesion, global anatomic network organization, and aphasia symptoms. We applied a simulated attack approach in humans to examine the effects of 39 stroke lesions (16 females) on anatomic network topology by simulating their effects in a control sample of 36 healthy (15 females) brain networks. We focused on measures of global network organization thought to support overall brain function and resilience in the whole brain and within the left hemisphere. After removing lesion volume from the network topology measures and behavioral scores [the Western Aphasia Battery Aphasia Quotient (WAB-AQ), four behavioral factor scores obtained from a neuropsychological battery, and a factor sum], we compared the behavioral variance accounted for by simulated poststroke connectomes to that observed in the randomly permuted data. Global measures of anatomic network topology in the whole brain and left hemisphere accounted for 10% variance or more of the WAB-AQ and the lexical factor score beyond lesion volume and null permutations. Streamline networks provided more reliable point estimates than FA networks. Edge weights and network efficiency were weighted most highly in predicting the WAB-AQ for FA networks. Overall, our results suggest that global network measures provide modest statistical value beyond lesion volume when predicting overall aphasia severity, but less value in predicting specific behaviors. Variability in estimates could be induced by premorbid ability, deafferentation and diaschisis, and neuroplasticity following stroke.SIGNIFICANCE STATEMENT Poststroke, the remaining neuroanatomy maintains cognition and supports recovery. However, studies often use small, cross-sectional samples that cannot fully model the interactions between lesions and other variables that affect networks in stroke. Alternate methods are required to account for these effects. "Simulated attack" models are computational approaches that apply virtual damage to the brain and measure their putative consequences. Using a simulated attack model, we estimated how simulated damage to anatomic networks could account for language performance. Overall, our results reveal that global network measures can provide modest statistical value predicting overall aphasia severity, but less value in predicting specific behaviors. These findings suggest that more theoretically precise network models could be necessary to robustly predict individual outcomes in aphasia.
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Affiliation(s)
- John D Medaglia
- Department of Psychology, Drexel University, Philadelphia, Pennsylvania 19104
- Department of Neurology, Drexel University, Philadelphia, Pennsylvania 19104
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Brian A Erickson
- Department of Psychology, Drexel University, Philadelphia, Pennsylvania 19104
| | - Dorian Pustina
- Cure Huntingdon's Disease Initiative (CHDI) Foundation, Princeton, New Jersey 08540
| | - Apoorva S Kelkar
- Department of Psychology, Drexel University, Philadelphia, Pennsylvania 19104
| | - Andrew T DeMarco
- Department of Neurology, Georgetown University, Washington, DC 20007
| | - J Vivian Dickens
- Department of Neurology, Georgetown University, Washington, DC 20007
| | - Peter E Turkeltaub
- Department of Neurology, Georgetown University, Washington, DC 20007
- MedStar National Rehabilitation Hospital, Washington, DC 20007
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Leng F, Zhan Z, Sun Y, Liu F, Edison P, Sun Y, Wang Z. Cerebrospinal Fluid sTREM2 Has Paradoxical Association with Brain Structural Damage Rate in Early- and Late-Stage Alzheimer’s Disease. J Alzheimers Dis 2022; 88:117-126. [PMID: 35491791 DOI: 10.3233/jad-220102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Recently it has been proposed that microglial response has a stage-dependent effect on the progression of Alzheimer’s disease (AD). Cerebrospinal fluid (CSF) sTREM2 has emerged as a promising microglial activation marker. Objective: To test the stage-dependent role of microglia by studying the association between baseline sTREM2 and dynamic brain structural changes in AD and mild cognitive impairment (MCI) patients. Methods: 22 amyloid-β-positive (A+) and tau-positive (T+) AD and 24 A+T+MCI patients were identified from the Alzheimer’s Disease Neuroimaging Initiative. The patients had baseline CSF amyloid-β, phosphorylated-tau, and sTREM2, and were followed up for at least one year by T1-weighted and diffusion tensor imaging scans. Gray matter volumes and white matter microstructural integrity were evaluated. Linear mixed models were applied to analyze how baseline sTREM2 may influence the rate of brain structural changes while adjusting for the effects of age, APOE4 status, and the CSF core markers. Results: In A+T+AD patients, baseline CSF sTREM2 was associated with faster mean diffusivity increase in the bilateral posterior corona radiata and right superior longitudinal fasciculus. In A+T+MCI patients, baseline CSF sTREM2 was associated slower gray matter volumetric loss in parahippocampal gyrus, left fusiform cortex, left middle temporal gyrus, and left lateral occipital cortex. Baseline CSF sTREM2 also had a protective effect against mean diffusivity increase in right inferior fronto-occipital fasciculus, left superior longitudinal fasciculus, left forceps minor, and left uncinate fasciculus. Conclusion: Microglial activation at early stage might have a protective effect against neurodegeneration, while at late stage it might facilitate AD. Future efforts on modulating microglial activation could be promising, given a carefully selected time window for intervention.
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Affiliation(s)
- Fangda Leng
- Department of Neurology, Peking University First Hospital, Peking University, Beijing, China
| | - Zhenying Zhan
- Department of Neurology, Pujiang Branch, The First Affiliated Hospital of Zhejiang University, Zhejiang, China
| | - Yunchuang Sun
- Department of Neurology, Peking University First Hospital, Peking University, Beijing, China
| | - Fang Liu
- Department of Neurology, Tsinghua University First Hospital, Tsinghua University, Beijing, China
| | - Paul Edison
- Department of Brain Sciences, Imperial College London, London, UK
| | - Yongan Sun
- Department of Neurology, Peking University First Hospital, Peking University, Beijing, China
| | - Zhaoxia Wang
- Department of Neurology, Peking University First Hospital, Peking University, Beijing, China
- Beijing Key Laboratory of Neurovascular Disease Discovery, Beijing, China
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Kilgore CB, Strain JF, Nelson B, Cooley SA, Rosenow A, Glans M, Cade WT, Reeds DN, Paul RH, Ances BM. Cardiorespiratory Fitness Is Associated With Better White Matter Integrity in Persons Living With HIV. J Acquir Immune Defic Syndr 2022; 89:558-565. [PMID: 34966145 PMCID: PMC9058177 DOI: 10.1097/qai.0000000000002907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 11/29/2021] [Indexed: 11/26/2022]
Abstract
BACKGROUND Despite improved survival rates, neurocognitive impairment persists in persons living with HIV (PLWH). An active lifestyle is linked to improved cognition among PLWH, yet the neural substrates remain unclear. Diffusion tensor imaging and diffusion basis spectrum imaging measure HIV-related changes in brain white matter integrity. We used these measures of structural brain integrity to assess white matter changes, physical fitness, and cognition in a cross-sectional study of PLWH. METHODS Forty-four virologically well-controlled PLWH were recruited (average age of 56 years, a median recent CD4+ count of 682 cells/mm3). Diffusion tensor imaging -derived fractional anisotropy (FA) and diffusion basis spectrum imaging-derived axonal density were calculated. Cardiorespiratory fitness [maximal volume of oxygen consumption (VO2 max)] was measured by performing indirect calorimetry during exercise to volitional exhaustion. Cardiovascular risk was assessed by the Framingham risk score. Neuropsychological performance (NP) testing evaluated learning, memory, psychomotor/processing speed, and executive function. Partial correlations assessed the relationships among cardiorespiratory fitness, neuroimaging, NP, and HIV clinical metrics (CD4+ count and time since diagnosis). RESULTS Higher VO2 max was associated with higher FA and higher axonal density in multiple white matter tracts, including the corticospinal tract and superior longitudinal fasciculus. Better NP in the motor/psychomotor domain was positively associated with FA and axonal density in diverse tracts including those associated with motor and visuospatial processing. However, higher VO2 max was not associated with NP or HIV clinical metrics. CONCLUSIONS An active lifestyle promoting cardiorespiratory fitness may lead to better white matter integrity and decreased susceptibility to cognitive decline in virologically well-controlled PLWH.
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Affiliation(s)
- Collin B Kilgore
- Department of Neurology, Washington University in St. Louis, St. Louis, MO
| | - Jeremy F Strain
- Department of Neurology, Washington University in St. Louis, St. Louis, MO
| | - Brittany Nelson
- Department of Neurology, Washington University in St. Louis, St. Louis, MO
| | - Sarah A Cooley
- Department of Neurology, Washington University in St. Louis, St. Louis, MO
| | - Alexander Rosenow
- Department of Neurology, Washington University in St. Louis, St. Louis, MO
| | - Michelle Glans
- Department of Neurology, Washington University in St. Louis, St. Louis, MO
| | | | - Dominic N Reeds
- Department of Medicine, Washington University in St. Louis, St. Louis, MO
| | - Robert H Paul
- Department of Psychology, University of Missouri-St. Louis, St. Louis, MO
| | - Beau M Ances
- Department of Neurology, Washington University in St. Louis, St. Louis, MO
- Department of Radiology, Washington University in St. Louis, St. Louis, MO; and
- Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO
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Nabizadeh F, Pourhamzeh M, Khani S, Rezaei A, Ranjbaran F, Deravi N. Plasma phosphorylated-tau181 levels reflect white matter microstructural changes across Alzheimer's disease progression. Metab Brain Dis 2022; 37:761-771. [PMID: 35015198 DOI: 10.1007/s11011-022-00908-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 01/06/2022] [Indexed: 01/25/2023]
Abstract
Alzheimer's Disease (AD) is characterized by cognitive impairments that hinder daily activities and lead to personal and behavioral problems. Plasma hyperphosphorylated tau protein at threonine 181 (p-tau181) has recently emerged as a new sensitive tool for the diagnosis of AD patients. We herein investigated the association of plasma P-tau181 and white matter (WM) microstructural changes in AD. We obtained data from a large prospective cohort of elderly individuals participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI), which included baseline measurements of plasma P-tau181 and imaging findings. A subset of 41 patients with AD, 119 patients with mild cognitive impairments (MCI), and 43 healthy controls (HC) was included in the study, all of whom had baseline blood P-tau181 levels and had also undergone Diffusion Tensor Imaging. The analysis revealed that the plasma level of P-tau181 has a positive correlation with changes in Mean Diffusivity (MD), Radial Diffusivity (RD), and Axial Diffusivity (AxD), but a negative with Fractional Anisotropy (FA) parameters in WM regions of all participants. There is also a significant association between WM microstructural changes in different regions and P-tau181 plasma measurements within each MCI, HC, and AD group. In conclusion, our findings clarified that plasma P-tau181 levels are associated with changes in WM integrity in AD. P-tau181 could improve the accuracy of diagnostic procedures and support the application of blood-based biomarkers to diagnose WM neurodegeneration. Longitudinal clinical studies are also needed to demonstrate the efficacy of the P-tau181 biomarker and predict its role in structural changes.
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Affiliation(s)
- Fardin Nabizadeh
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
- Neuroscience Research Group (NRG), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
| | - Mahsa Pourhamzeh
- Division of Neuroscience, Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran.
| | - Saghar Khani
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Ayda Rezaei
- Neuroscience Research Group (NRG), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Fatemeh Ranjbaran
- School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Niloofar Deravi
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Plasma neurofilament light levels correlate with white matter damage prior to Alzheimer's disease: results from ADNI. Aging Clin Exp Res 2022; 34:2363-2372. [PMID: 35226303 DOI: 10.1007/s40520-022-02095-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 02/10/2022] [Indexed: 11/01/2022]
Abstract
BACKGROUND The blood biomarker neurofilament light (NFL) is one of the most widely used for monitoring Alzheimer's disease (AD). According to recent research, a higher NFL plasma level has a substantial predictive value for cognitive deterioration in AD patients. Diffusion tensor imaging (DTI) is an MRI-based approach for detecting neurodegeneration, white matter (WM) disruption, and synaptic damage. There have been few studies on the relationship between plasma NFL and WM microstructure integrity. AIMS The goal of the current study is to assess the associations between plasma levels of NFL, CSF total tau, phosphorylated tau181 (P-tau181), and amyloid-β (Aβ) with WM microstructural alterations. METHODS We herein have investigated the cross-sectional association between plasma levels of NFL and WM microstructural alterations as evaluated by DTI in 92 patients with mild cognitive impairment (MCI) provided by Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. We analyzed the potential association between plasma NFL levels and radial diffusivity (RD), axial diffusivity (AxD), mean diffusivity (MD), and fractional anisotropy (FA) in each region of the Montreal Neurological Institute and Hospital (MNI) atlas, using simple linear regression models stratified by age, sex, and APOE ε4 genotype. RESULTS Our findings demonstrated a significant association between plasma NFL levels and disrupted WM microstructure across the brain. In distinct areas, plasma NFL has a negative association with FA in the fornix, fronto-occipital fasciculus, corpus callosum, uncinate fasciculus, internal capsule, and corona radiata and a positive association with RD, AxD, and MD values in sagittal stratum, corpus callosum, fronto-occipital fasciculus, corona radiata, internal capsule, thalamic radiation, hippocampal cingulum, fornix, and cingulum. Lower FA and higher RD, AxD, and MD values are related to demyelination and degeneration in WM. CONCLUSION Our findings revealed that the level of NFL in the blood is linked to WM alterations in MCI patients. Plasma NFL has the potential to be a biomarker for microstructural alterations. However, further longitudinal studies are necessary to validate the predictive role of plasma NFL in cognitive decline.
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Mauschitz MM, Lohner V, Koch A, Stöcker T, Reuter M, Holz FG, Finger RP, Breteler MMB. Retinal layer assessments as potential biomarkers for brain atrophy in the Rhineland Study. Sci Rep 2022; 12:2757. [PMID: 35177781 PMCID: PMC8854401 DOI: 10.1038/s41598-022-06821-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 01/20/2022] [Indexed: 01/09/2023] Open
Abstract
Retinal assessments have been discussed as biomarkers for brain atrophy. However, available studies did not investigate all retinal layers due to older technology, reported inconsistent results, or were based on small sample sizes. We included 2872 eligible participants of the Rhineland Study with data on spectral domain-optical coherence tomography (SD-OCT) and brain magnetic resonance imaging (MRI). We used multiple linear regression to examine relationships between retinal measurements and volumetric brain measures as well as fractional anisotropy (FA) as measure of microstructural integrity of white matter (WM) for different brain regions. Mean (SD) age was 53.8 ± 13.2 years (range 30-94) and 57% were women. Volumes of the inner retina were associated with total brain and grey matter (GM) volume, and even stronger with WM volume and FA. In contrast, the outer retina was mainly associated with GM volume, while both, inner and outer retina, were associated with hippocampus volume. While we extend previously reported associations between the inner retina and brain measures, we found additional associations of the outer retina with parts of the brain. This indicates that easily accessible retinal SD-OCT assessments may serve as biomarkers for clinical monitoring of neurodegenerative diseases and merit further research.
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Affiliation(s)
- Matthias M. Mauschitz
- grid.424247.30000 0004 0438 0426Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127 Bonn, Germany ,grid.15090.3d0000 0000 8786 803XDepartment of Ophthalmology, University Hospital Bonn, Bonn, Germany
| | - Valerie Lohner
- grid.424247.30000 0004 0438 0426Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127 Bonn, Germany
| | - Alexandra Koch
- grid.424247.30000 0004 0438 0426Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127 Bonn, Germany
| | - Tony Stöcker
- grid.424247.30000 0004 0438 0426MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ,grid.10388.320000 0001 2240 3300Department of Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Martin Reuter
- grid.424247.30000 0004 0438 0426Image Analysis, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Frank G. Holz
- grid.15090.3d0000 0000 8786 803XDepartment of Ophthalmology, University Hospital Bonn, Bonn, Germany
| | - Robert P. Finger
- grid.15090.3d0000 0000 8786 803XDepartment of Ophthalmology, University Hospital Bonn, Bonn, Germany
| | - Monique M. B. Breteler
- grid.424247.30000 0004 0438 0426Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1/99, 53127 Bonn, Germany ,grid.10388.320000 0001 2240 3300Institute for Medical Biometry, Informatics and Epidemiology, Faculty of Medicine, University of Bonn, Bonn, Germany
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Raghavan S, Przybelski SA, Reid RI, Lesnick TG, Ramanan VK, Botha H, Matchett BJ, Murray ME, Reichard RR, Knopman DS, Graff-Radford J, Jones DT, Lowe VJ, Mielke MM, Machulda MM, Petersen RC, Kantarci K, Whitwell JL, Josephs KA, Jack CR, Vemuri P. White matter damage due to vascular, tau, and TDP-43 pathologies and its relevance to cognition. Acta Neuropathol Commun 2022; 10:16. [PMID: 35123591 PMCID: PMC8817561 DOI: 10.1186/s40478-022-01319-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 01/19/2022] [Indexed: 12/27/2022] Open
Abstract
Multi-compartment modelling of white matter microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) can provide information on white matter health through neurite density index and free water measures. We hypothesized that cerebrovascular disease, Alzheimer's disease, and TDP-43 proteinopathy would be associated with distinct NODDI readouts of white matter damage which would be informative for identifying the substrate for cognitive impairment. We identified two independent cohorts with multi-shell diffusion MRI, amyloid and tau PET, and cognitive assessments: specifically, a population-based cohort of 347 elderly randomly sampled from the Olmsted county, Minnesota, population and a clinical research-based cohort of 61 amyloid positive Alzheimer's dementia participants. We observed an increase in free water and decrease in neurite density using NODDI measures in the genu of the corpus callosum associated with vascular risk factors, which we refer to as the vascular white matter component. Tau PET signal reflective of 3R/4R tau deposition was associated with worsening neurite density index in the temporal white matter where we measured parahippocampal cingulum and inferior temporal white matter bundles. Worsening temporal white matter neurite density was associated with (antemortem confirmed) FDG TDP-43 signature. Post-mortem neuropathologic data on a small subset of this sample lend support to our findings. In the community-dwelling cohort where vascular disease was more prevalent, the NODDI vascular white matter component explained variability in global cognition (partial R2 of free water and neurite density = 8.3%) and MMSE performance (8.2%) which was comparable to amyloid PET (7.4% for global cognition and 6.6% for memory). In the AD dementia cohort, tau deposition was the greatest contributor to cognitive performance (9.6%), but there was also a non-trivial contribution of the temporal white matter component (8.5%) to cognitive performance. The differences observed between the two cohorts were reflective of their distinct clinical composition. White matter microstructural damage assessed using advanced diffusion models may add significant value for distinguishing the underlying substrate (whether cerebrovascular disease versus neurodegenerative disease caused by tau deposition or TDP-43 pathology) for cognitive impairment in older adults.
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Affiliation(s)
| | - Scott A. Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905 USA
| | - Robert I. Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN 55905 USA
| | - Timothy G. Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905 USA
| | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905 USA
| | | | | | - R. Ross Reichard
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905 USA
| | | | | | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN 55905 USA
| | - Val J. Lowe
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | - Michelle M. Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905 USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905 USA
| | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905 USA
| | | | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | - Jennifer L. Whitwell
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | | | - Clifford R. Jack
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 USA
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Porat S, Sibilia F, Yoon J, Shi Y, Dahl MJ, Werkle-Bergner M, Düzel S, Bodammer N, Lindenberger U, Kühn S, Mather M. Age Differences in Diffusivity in the Locus Coeruleus and its Ascending Noradrenergic Tract. Neuroimage 2022; 251:119022. [PMID: 35192943 PMCID: PMC9183949 DOI: 10.1016/j.neuroimage.2022.119022] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 12/11/2022] Open
Abstract
The noradrenergic locus coeruleus (LC) is a small brainstem nucleus that promotes arousal and attention. Recent studies have examined the microstructural properties of the LC using diffusion-weighted magnetic resonance imaging and found unexpected age-related differences in fractional anisotropy - a measure of white matter integrity. Here, we used two datasets (Berlin Aging Study-II, N = 301, the Leipzig Study for Mind-Body-Emotion Interactions, N = 220), to replicate published findings and expand them by investigating diffusivity in the LC’s ascending noradrenergic bundle. In younger adults, LC fractional anisotropy was significantly lower, compared to older adults. However, in the LC’s ascending noradrenergic bundle, we observed significantly higher fractional anisotropy in younger adults, relative to older adults. These findings indicate that diffusivity in the LC versus the ascending noradrenergic bundle are both susceptible to structural changes in aging that have opposing effects on fractional anisotropy.
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48
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Ni R. Magnetic Resonance Imaging in Tauopathy Animal Models. Front Aging Neurosci 2022; 13:791679. [PMID: 35145392 PMCID: PMC8821905 DOI: 10.3389/fnagi.2021.791679] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
The microtubule-associated protein tau plays an important role in tauopathic diseases such as Alzheimer's disease and primary tauopathies such as progressive supranuclear palsy and corticobasal degeneration. Tauopathy animal models, such as transgenic, knock-in mouse and rat models, recapitulating tauopathy have facilitated the understanding of disease mechanisms. Aberrant accumulation of hyperphosphorylated tau contributes to synaptic deficits, neuroinflammation, and neurodegeneration, leading to cognitive impairment in animal models. Recent advances in molecular imaging using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided valuable insights into the time course of disease pathophysiology in tauopathy animal models. High-field MRI has been applied for in vivo imaging in animal models of tauopathy, including diffusion tensor imaging for white matter integrity, arterial spin labeling for cerebral blood flow, resting-state functional MRI for functional connectivity, volumetric MRI for neurodegeneration, and MR spectroscopy. In addition, MR contrast agents for non-invasive imaging of tau have been developed recently. Many preclinical MRI indicators offer excellent translational value and provide a blueprint for clinical MRI in the brains of patients with tauopathies. In this review, we summarized the recent advances in using MRI to visualize the pathophysiology of tauopathy in small animals. We discussed the outstanding challenges in brain imaging using MRI in small animals and propose a future outlook for visualizing tau-related alterations in the brains of animal models.
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Affiliation(s)
- Ruiqing Ni
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
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49
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Lin CP, Frigerio I, Boon BDC, Zhou Z, Rozemuller AJM, Bouwman FH, Schoonheim MM, van de Berg WDJ, Jonkman LE. OUP accepted manuscript. Brain 2022; 145:2869-2881. [PMID: 35259207 PMCID: PMC9420016 DOI: 10.1093/brain/awac093] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 01/23/2022] [Accepted: 02/13/2022] [Indexed: 11/24/2022] Open
Abstract
Cognitive deficits in Alzheimer’s disease, specifically amnestic (memory dominant) deficits, are associated with cholinergic degeneration in the basal forebrain. The cholinergic nucleus within the basal forebrain, the nucleus basalis of Meynert, exhibits local atrophy and reduced cortical tract integrity on MRI, and reveals amyloid-β and phosphorylated-tau pathology at autopsy. To understand the pathophysiology of nucleus basalis of Meynert atrophy and its neocortical projections in Alzheimer’s disease, we used a combined post-mortem in situ MRI and histopathology approach. A total of 19 Alzheimer’s disease (10 amnestic and nine non-amnestic) and nine non-neurological control donors underwent 3 T T1-weighted MRI for anatomical delineation and volume assessment of the nucleus basalis of Meynert, and diffusion-weighted imaging for microstructural assessment of the nucleus and its projections. At subsequent brain autopsy, tissue dissection and immunohistochemistry were performed for amyloid-β, phosphorylated-tau and choline acetyltransferase. Compared to controls, we observed an MRI-derived volume reduction and altered microstructural integrity of the nucleus basalis of Meynert in Alzheimer’s disease donors. Furthermore, decreased cholinergic cell density was associated with reduced integrity of the nucleus and its tracts to the temporal lobe, specifically to the temporal pole of the superior temporal gyrus, and the parahippocampal gyrus. Exploratory post hoc subgroup analyses indicated that cholinergic cell density could be associated with cortical tract alterations in amnestic Alzheimer’s disease donors only. Our study illustrates that in Alzheimer’s disease, cholinergic degeneration in the nucleus basalis of Meynert may contribute to damaged cortical projections, specifically to the temporal lobe, leading to cognitive deterioration.
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Affiliation(s)
- Chen Pei Lin
- Correspondence to: Chen-Pei Lin De Boelelaan 1117 1081 HV, Amsterdam, The Netherlands E-mail:
| | - Irene Frigerio
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Baayla D C Boon
- Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Department of Pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer centrum Amsterdam, Amsterdam, The Netherlands
| | - Zihan Zhou
- Zhejiang University, College of Biomedical Engineering and Instrument Science, Zhejiang, China
| | - Annemieke J M Rozemuller
- Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Department of Pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Femke H Bouwman
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer centrum Amsterdam, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Wilma D J van de Berg
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
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50
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Zhou Y, Si X, Chen Y, Chao Y, Lin CP, Li S, Zhang X, Ming D, Li Q. Hippocampus- and Thalamus-Related Fiber-Specific White Matter Reductions in Mild Cognitive Impairment. Cereb Cortex 2021; 32:3159-3174. [PMID: 34891164 DOI: 10.1093/cercor/bhab407] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/04/2021] [Accepted: 10/20/2021] [Indexed: 11/13/2022] Open
Abstract
Early diagnosis of mild cognitive impairment (MCI) fascinates screening high-risk Alzheimer's disease (AD). White matter is found to degenerate earlier than gray matter and functional connectivity during MCI. Although studies reveal white matter degenerates in the limbic system for MCI, how other white matter degenerates during MCI remains unclear. In our method, regions of interest with a high level of resting-state functional connectivity with hippocampus were selected as seeds to track fibers based on diffusion tensor imaging (DTI). In this way, hippocampus-temporal and thalamus-related fibers were selected, and each fiber's DTI parameters were extracted. Then, statistical analysis, machine learning classification, and Pearson's correlations with behavior scores were performed between MCI and normal control (NC) groups. Results show that: 1) the mean diffusivity of hippocampus-temporal and thalamus-related fibers are significantly higher in MCI and could be used to classify 2 groups effectively. 2) Compared with normal fibers, the degenerated fibers detected by the DTI indexes, especially for hippocampus-temporal fibers, have shown significantly higher correlations with cognitive scores. 3) Compared with the hippocampus-temporal fibers, thalamus-related fibers have shown significantly higher correlations with depression scores within MCI. Our results provide novel biomarkers for the early diagnoses of AD.
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Affiliation(s)
- Yu Zhou
- School of Microelectronics, Tianjin University, Tianjin 300072, China
| | - Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China.,Institute of Applied Psychology, Tianjin University, Tianjin 300350, China
| | - Yuanyuan Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Yiping Chao
- Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan 33302, Taiwan.,Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience Hsinchu City, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Sicheng Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Xingjian Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Qiang Li
- School of Microelectronics, Tianjin University, Tianjin 300072, China
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