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Vieites V, Ralph Y, Reeb-Sutherland B, Dick AS, Mattfeld AT, Pruden SM. Neurite density of the hippocampus is associated with trace eyeblink conditioning latency in 4- to 6-year-olds. Eur J Neurosci 2024; 59:358-369. [PMID: 38092417 PMCID: PMC10872972 DOI: 10.1111/ejn.16217] [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: 02/04/2022] [Revised: 11/16/2023] [Accepted: 11/19/2023] [Indexed: 02/06/2024]
Abstract
Limited options exist to evaluate the development of hippocampal function in young children. Research has established that trace eyeblink conditioning (EBC) relies on a functional hippocampus. Hence, we set out to investigate whether trace EBC is linked to hippocampal structure, potentially serving as a valuable indicator of hippocampal development. Our study explored potential associations between individual differences in hippocampal volume and neurite density with trace EBC performance in young children. We used onset latency of conditioned responses (CR) and percentage of conditioned responses (% CR) as measures of hippocampal-dependent associative learning. Using a sample of typically developing children aged 4 to 6 years (N = 30; 14 girls; M = 5.70 years), participants underwent T1- and diffusion-weighted MRI scans and completed a 15-min trace eyeblink conditioning task conducted outside the MRI. % CR and CR onset latency were calculated based on all trials involving tone-puff presentations and tone-alone trials. Findings revealed a connection between greater left hippocampal neurite density and delayed CR onset latency. Children with higher neurite density in the left hippocampus tended to blink closer to the onset of the unconditioned stimulus, indicating that structural variations in the hippocampus were associated with more precise timing of conditioned responses. No other relationships were observed between hippocampal volume, cerebellum volume or neurite density, hippocampal white matter connectivity and any EBC measures. Preliminary results suggest that trace EBC may serve as a straightforward yet innovative approach for studying hippocampal development in young children and populations with atypical development.
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Affiliation(s)
- Vanessa Vieites
- Department of Psychology, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA
| | - Yvonne Ralph
- Department of Psychology, University of Texas at Tyler, Tyler, Texas, USA
| | | | - Anthony Steven Dick
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Aaron T Mattfeld
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Shannon M Pruden
- Department of Psychology, Florida International University, Miami, Florida, USA
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Zhong S, Lou J, Ma K, Shu Z, Chen L, Li C, Ye Q, Zhou L, Shen Y, Ye X, Zhang J. Disentangling in-vivo microstructural changes of white and gray matter in mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis. Brain Imaging Behav 2023; 17:764-777. [PMID: 37752311 DOI: 10.1007/s11682-023-00805-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/14/2023] [Indexed: 09/28/2023]
Abstract
The microstructural characteristics of white and gray matter in mild cognitive impairment (MCI) and the early-stage of Alzheimer's disease (AD) remain unclear. This study aimed to systematically identify the microstructural damages of MCI/AD in studies using neurite orientation dispersion and density imaging (NODDI), and explore their correlations with cognitive performance. Multiple databases were searched for eligible studies. The 10 eligible NODDI studies were finally included. Patients with MCI/AD showed overall significant reductions in neurite density index (NDI) of specific white matter structures in bilateral hemispheres (left hemisphere: -0.40 [-0.53, -0.27], P < 0.001; right: -0.33 [-0.47, -0.19], P < 0.001), involving the bilateral superior longitudinal fasciculus (SLF), uncinate fasciculus (UF), the left posterior thalamic radiation (PTR), and the left cingulum. White matter regions exhibited significant increased orientation dispersion index (ODI) (left: 0.25 [0.02, 0.48], P < 0.05; right: 0.27 [0.07, 0.46], P < 0.05), including the left cingulum, the right UF, and the bilateral parahippocampal cingulum (PHC), and PTR. Additionally, the ODI of gray matter showed significant reduction in bilateral hippocampi (left: -0.97 [-1.42, -0.51], P < 0.001; right: -0.90 [-1.35, -0.45], P < 0.001). The cognitive performance in MCI/AD was significantly associated with NDI (r = 0.50, P < 0.001). Our findings highlight the microstructural changes in MCI/AD were characterized by decreased fiber orientation dispersion in the hippocampus, and decreased neurite density and increased fiber orientation dispersion in specific white matter tracts, including the cingulum, UF, and PTR. Moreover, the decreased NDI may indicate the declined cognitive level of MCI/AD patients.
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Affiliation(s)
- Shuchang Zhong
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jingjing Lou
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Ke Ma
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Zhenyu Shu
- Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Lin Chen
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Chao Li
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Qing Ye
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Liang Zhou
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Ye Shen
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Xiangming Ye
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jie Zhang
- Center for Rehabilitation Medicine, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China.
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Callow DD, Kommula Y, Stark CEL, Smith JC. Acute cycling exercise and hippocampal subfield function and microstructure in healthy older adults. Hippocampus 2023; 33:1123-1138. [PMID: 37526119 PMCID: PMC10543457 DOI: 10.1002/hipo.23571] [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: 06/07/2023] [Revised: 07/04/2023] [Accepted: 07/10/2023] [Indexed: 08/02/2023]
Abstract
Aging is associated with deterioration in dentate gyrus (DG) and CA3, both crucial hippocampal subfields for age susceptible memory processes such as mnemonic discrimination (MD). Meanwhile, a single aerobic exercise session alters DG/CA3 function and neural activity in both rats and younger adults and can elicit short-term microstructural alterations in the hippocampus of older adults. However, our understanding of the effects of acute exercise on hippocampal subfield integrity via function and microstructure in older adults is limited. Thus, a within subject-design was employed to determine if 20-min of moderate to vigorous aerobic exercise alters bilateral hippocampal subfield function and microstructure using high-resolution functional magnetic resonance imaging (fMRI) during an MD task (n = 35) and high angular resolution multi-shell diffusion imaging (n = 31), in healthy older adults, compared to seated rest. Following the exercise condition, participants exhibited poorer MD performance, particularly when their perception of effort was higher. Exercise was also related to lower MD-related activity within the DG/CA3 but not CA1 subfield. Finally, after controlling for whole brain gray matter diffusion, exercise was associated with lower neurite density index (NDI) within the DG/CA3. However, exercise-related differences in DG/CA3 activity and NDI were not associated with differences in MD performance. Our results suggest moderate to vigorous aerobic exercise may temporarily inhibit MD performance, and suppress DG/CA3 MD-related activity and NDI, potentially through neuroinflammatory/glial processes. However, additional studies are needed to confirm whether these short-term changes in behavior and hippocampal subfield neurophysiology are beneficial and how they might relate to long-term exercise habits.
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Affiliation(s)
- Daniel D. Callow
- Department of Kinesiology, University of Maryland, College Park, MD, USA
- Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA
| | - Yash Kommula
- Department of Kinesiology, University of Maryland, College Park, MD, USA
- Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA
| | - Craig E. L. Stark
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - J. Carson Smith
- Department of Kinesiology, University of Maryland, College Park, MD, USA
- Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA
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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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Walker KA, Duggan MR, Gong Z, Dark HE, Laporte JP, Faulkner ME, An Y, Lewis A, Moghekar AR, Resnick SM, Bouhrara M. MRI and fluid biomarkers reveal determinants of myelin and axonal loss with aging. Ann Clin Transl Neurol 2023; 10:397-407. [PMID: 36762407 PMCID: PMC10014005 DOI: 10.1002/acn3.51730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/15/2022] [Accepted: 12/31/2022] [Indexed: 02/11/2023] Open
Abstract
OBJECTIVE White matter damage is a feature of Alzheimer's disease, yet little is known about how facets of the Alzheimer's disease process relate to key features of white matter structure. We examined the association of Alzheimer's disease (Aß42/40 ratio; pTau181), neuronal injury (NfL), and reactive astrogliosis (GFAP) biomarkers with MRI measures of myelin content and axonal density. METHODS Among cognitively normal participants in the BLSA and GESTALT studies who received MRI measures of myelin content (defined by myelin water fraction [MWF]) and axonal density (defined by neurite density index [NDI]), we quantified plasma levels of Aβ42 , Aβ40 , pTau181, NfL, and GFAP. Linear regression models adjusted for demographic variables were used to relate these plasma biomarker levels to the MRI measures. RESULTS In total, 119 participants received MWF imaging (age: 56 [SD 21]), of which 43 received NDI imaging (age: 50 [SD 18]). We found no relationship between plasma biomarkers and total brain myelin content. However, secondary analysis found higher GFAP was associated with lower MWF in the temporal lobes (ß = -0.13; P = 0.049). Further, higher levels of NfL (ß = -0.22; P = 0.009) and GFAP (ß = -0.29; P = 0.002) were associated with lower total brain axonal density. Secondary analyses found lower Aβ42/40 ratio and higher pTau181 were also associated with lower axonal density, but only in select brain regions. These results remained similar after additionally adjusting for cardiovascular risk factors. INTERPRETATION Plasma biomarkers of neuronal injury and astrogliosis are associated with reduced axonal density and region-specific myelin content. Axonal loss and demyelination may co-occur with neurodegeneration and astrogliosis ahead of clinically meaningful cognitive decline.
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Affiliation(s)
- Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Michael R Duggan
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Heather E Dark
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Alexandria Lewis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, 21224
| | - Abhay R Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, 21224
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, 21224
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Öztekin I, Garic D, Bayat M, Hernandez ML, Finlayson MA, Graziano PA, Dick AS. Structural and diffusion-weighted brain imaging predictors of attention-deficit/hyperactivity disorder and its symptomology in very young (4- to 7-year-old) children. Eur J Neurosci 2022; 56:6239-6257. [PMID: 36215144 PMCID: PMC10165616 DOI: 10.1111/ejn.15842] [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: 09/17/2021] [Revised: 09/15/2022] [Accepted: 09/21/2022] [Indexed: 12/29/2022]
Abstract
The current study aimed to identify the key neurobiology of attention-deficit/hyperactivity disorder (ADHD), as it relates to ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. To do so, we adapted a predictive modelling approach to identify the key structural and diffusion-weighted brain imaging measures and their relative standing with respect to teacher ratings of executive function (EF) (measured by the Metacognition Index of the Behavior Rating Inventory of Executive Function [BRIEF]) and negativity and emotion regulation (ER) (measured by the Emotion Regulation Checklist [ERC]), in a critical young age range (ages 4 to 7, mean age 5.52 years, 82.2% Hispanic/Latino), where initial contact with educators and clinicians typically take place. Teacher ratings of EF and ER were predictive of both ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. Among the neural measures evaluated, the current study identified the critical importance of the largely understudied diffusion-weighted imaging measures for the underlying neurobiology of ADHD and its associated symptomology. Specifically, our analyses implicated the inferior frontal gyrus as a critical predictor of ADHD diagnostic category and its associated symptomology, above and beyond teacher ratings of EF and ER. Collectively, the current set of findings have implications for theories of ADHD, the relative utility of neurobiological measures with respect to teacher ratings of EF and ER, and the developmental trajectory of its underlying neurobiology.
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Affiliation(s)
- Ilke Öztekin
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA.,Exponent, Inc., Philadelphia, Pennsylvania, USA
| | - Dea Garic
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mohammadreza Bayat
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA
| | - Melissa L Hernandez
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA
| | - Mark A Finlayson
- School of Computing and Information Sciences, Florida International University, Miami, Florida, USA
| | - Paulo A Graziano
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA
| | - Anthony Steven Dick
- Center for Children and Families and Department of Psychology, Florida International University, Miami, Florida, USA
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7
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Nakaya M, Sato N, Matsuda H, Maikusa N, Shigemoto Y, Sone D, Yamao T, Ogawa M, Kimura Y, Chiba E, Ohnishi M, Kato K, Okita K, Tsukamoto T, Yokoi Y, Sakata M, Abe O. Free water derived by multi-shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12356. [PMID: 36304723 PMCID: PMC9594557 DOI: 10.1002/trc2.12356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 08/03/2022] [Accepted: 08/20/2022] [Indexed: 11/23/2022]
Abstract
Introduction Free-water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET). Methods Seventy-one participants underwent multi-shell diffusion MRI, 18F-THK5351 PET, 11C-Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD-spectrum group (AD-S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores. Results In AD-S group, there was a significant positive correlation between FW and 18F-THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between 18F-THK5351 and cognitive function in the same regions. Discussion FW imaging could be a biomarker for tau in AD alongside clinical correlations.
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Affiliation(s)
- Moto Nakaya
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
- Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
| | - Noriko Sato
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Hiroshi Matsuda
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
- Drug Discovery and Cyclotron Research CenterSouthern TOHOKU Research Institute for NeuroscienceKoriyamaJapan
| | - Norihide Maikusa
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Yoko Shigemoto
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Daichi Sone
- Department of PsychiatryThe Jikei University School of MedicineTokyoJapan
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tensho Yamao
- Department of Radiological SciencesSchool of Health SciencesFukushima Medical UniversityFukushimaJapan
| | - Masayo Ogawa
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Yukio Kimura
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Emiko Chiba
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Masahiro Ohnishi
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Koichi Kato
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Kyoji Okita
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tadashi Tsukamoto
- Department of NeurologyNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Yuma Yokoi
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Masuhiro Sakata
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Osamu Abe
- Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
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Preziosa P, Pagani E, Bonacchi R, Cacciaguerra L, Falini A, Rocca MA, Filippi M. In vivo detection of damage in multiple sclerosis cortex and cortical lesions using NODDI. J Neurol Neurosurg Psychiatry 2022; 93:628-636. [PMID: 34799405 DOI: 10.1136/jnnp-2021-327803] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/28/2021] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To characterise in vivo the microstructural abnormalities of multiple sclerosis (MS) normal-appearing (NA) cortex and cortical lesions (CLs) and their relations with clinical phenotypes and disability using neurite orientation dispersion and density imaging (NODDI). METHODS One hundred and seventy-two patients with MS (101 relapsing-remitting multiple sclerosis (RRMS), 71 progressive multiple sclerosis (PMS)) and 62 healthy controls (HCs) underwent a brain 3T MRI. Brain cortex and CLs were segmented from three-dimensional T1-weighted and double inversion recovery sequences. Using NODDI on diffusion-weighted sequence, intracellular volume fraction (ICV_f) and Orientation Dispersion Index (ODI) were assessed in NA cortex and CLs with default or optimised parallel diffusivity for the cortex (D//=1.7 or 1.2 µm2/ms, respectively). RESULTS The NA cortex of patients with MS had significantly lower ICV_f versus HCs' cortex with both D// values (false discovery rate (FDR)-p <0.001). CLs showed significantly decreased ICV_f and ODI versus NA cortex of both HCs and patients with MS with both D// values (FDR-p ≤0.008). Patients with PMS versus RRMS had significantly decreased NA cortex ICV_f and ODI (FDR-p=0.050 and FDR-p=0.032) with only D//=1.7 µm2/ms. No CL microstructural differences were found between MS clinical phenotypes. MS NA cortex ICV_f and ODI were significantly correlated with disease duration, clinical disability, lesion burden and global and regional brain atrophy (r from -0.51 to 0.71, FDR-p from <0.001 to 0.045). CONCLUSIONS A significant neurite loss occurs in MS NA cortex. CLs show a further neurite density reduction and a reduced ODI suggesting a simplification of neurite complexity. NODDI is relevant to investigate in vivo the heterogeneous pathology affecting the MS cortex.
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Affiliation(s)
- Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Raffaello Bonacchi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy
| | - Andrea Falini
- Vita-Salute San Raffaele University, Milano, Italy.,Department of Neuroradiology, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milano, Italy .,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milano, Italy
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9
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Hare MM, Dick AS, Graziano PA. Adverse childhood experiences predict neurite density differences in young children with and without attention deficit hyperactivity disorder. Dev Psychobiol 2022; 64:e22234. [PMID: 35050509 PMCID: PMC8827844 DOI: 10.1002/dev.22234] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 11/09/2021] [Accepted: 11/28/2021] [Indexed: 01/03/2023]
Abstract
Adverse childhood experiences (ACEs) put millions of children at risk for later health problems. As childhood represents a critical developmental period, it is important to understand how ACEs impact brain development in young children. In addition, children with attention-deficit/hyperactivity disorder (ADHD) are more likely than typically developing (TD) peers to experience ACEs. Therefore, the current study examined the impact of ACEs on early brain development, using a cumulative risk approach, in a large sample of children with and without ADHD. We examined 198 young children (Mage = 5.45, 82.3% Hispanic/Latino; 52.5% ADHD) across measures of brain volume, cortical thickness, neurite density index (NDI), and orientation dispersion index (ODI). For the NDI measure, there was a significant interaction between group and cumulative risk (ß = .18, p = .048), such that for children with ADHD, but not TD children, greater cumulate risk was associated with increased NDI in corpus callosum. No other interactions were detected. Additionally, when examining across groups, greater cumulative risk was associated with reduced ODI and volume in the cerebellum, although these findings did not survive a correction for multiple comparisons. Our results highlight the role early cumulative ACEs play in brain development across TD and children with ADHD.
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Affiliation(s)
- Megan M. Hare
- Center for Children and Families, Department of Psychology, Florida International University, Miami, FL 33199, USA
| | - Anthony Steven Dick
- Center for Children and Families, Department of Psychology, Florida International University, Miami, FL 33199, USA
| | - Paulo A. Graziano
- Center for Children and Families, Department of Psychology, Florida International University, Miami, FL 33199, USA
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Kamagata K, Andica C, Kato A, Saito Y, Uchida W, Hatano T, Lukies M, Ogawa T, Takeshige-Amano H, Akashi T, Hagiwara A, Fujita S, Aoki S. Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases. Int J Mol Sci 2021; 22:ijms22105216. [PMID: 34069159 PMCID: PMC8155849 DOI: 10.3390/ijms22105216] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/10/2021] [Accepted: 05/10/2021] [Indexed: 12/27/2022] Open
Abstract
There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.
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Affiliation(s)
- Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
- Correspondence:
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Ayumi Kato
- Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago 683-8504, Japan;
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Matthew Lukies
- Department of Diagnostic and Interventional Radiology, Alfred Health, Melbourne, VIC 3004, Australia;
| | - Takashi Ogawa
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Haruka Takeshige-Amano
- Department of Neurology, Juntendo University School of Medicine, Tokyo 113-8421, Japan; (T.H.); (T.O.); (H.T.-A.)
| | - Toshiaki Akashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Shohei Fujita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan; (C.A.); (Y.S.); (W.U.); (T.A.); (A.H.); (S.F.); (S.A.)
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