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Faulkner ME, Gong Z, Guo A, Laporte JP, Bae J, Bouhrara M. Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review. J Neurochem 2024. [PMID: 38973579 DOI: 10.1111/jnc.16170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/12/2024] [Accepted: 06/19/2024] [Indexed: 07/09/2024]
Abstract
Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.
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Affiliation(s)
- Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Alex Guo
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Jonghyun Bae
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
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Kohli JS, Linke AC, Martindale IA, Wilkinson M, Kinnear MK, Lincoln AJ, Hau J, Shryock I, Omaleki V, Alemu K, Pedrahita S, Fishman I, Müller R, Carper RA. Associations between atypical intracortical myelin content and neuropsychological functions in middle to older aged adults with ASD. Brain Behav 2024; 14:e3594. [PMID: 38849980 PMCID: PMC11161394 DOI: 10.1002/brb3.3594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 05/06/2024] [Accepted: 05/23/2024] [Indexed: 06/09/2024] Open
Abstract
INTRODUCTION In vivo myeloarchitectonic mapping based on Magnetic Resonance Imaging (MRI) provides a unique view of gray matter myelin content and offers information complementary to other morphological indices commonly employed in studies of autism spectrum disorder (ASD). The current study sought to determine if intracortical myelin content (MC) and its age-related trajectories differ between middle aged to older adults with ASD and age-matched typical comparison participants. METHODS Data from 30 individuals with ASD and 36 age-matched typical comparison participants aged 40-70 years were analyzed. Given substantial heterogeneity in both etiology and outcomes in ASD, we utilized both group-level and subject-level analysis approaches to test for signs of atypical intracortical MC as estimated by T1w/T2w ratio. RESULTS Group-level analyses showed no significant differences in average T1w/T2w ratio or its associations with age between groups, but revealed significant positive main effects of age bilaterally, with T1w/T2w ratio increasing with age across much of the cortex. In subject-level analyses, participants were classified into subgroups based on presence or absence of clusters of aberrant T1w/T2w ratio, and lower neuropsychological function was observed in the ASD subgroup with atypically high T1w/T2w ratio in spatially heterogeneous cortical regions. These differences were observed across several neuropsychological domains, including overall intellectual functioning, processing speed, and aspects of executive function. CONCLUSIONS The group-level and subject-level approaches employed here demonstrate the value of examining inter-individual variability and provide important preliminary insights into relationships between brain structure and cognition in the second half of the lifespan in ASD, suggesting shared factors contributing to atypical intracortical myelin content and poorer cognitive outcomes for a subset of middle aged to older autistic adults. These atypicalities likely reflect diverse histories of neurodevelopmental deficits, and possible compensatory changes, compounded by processes of aging, and may serve as useful markers of vulnerability to further cognitive decline in older adults with ASD.
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Affiliation(s)
- Jiwandeep S. Kohli
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
- San Diego Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Annika C. Linke
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ian A. Martindale
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Molly Wilkinson
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
- San Diego Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Mikaela K. Kinnear
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Alan J. Lincoln
- California School of Professional PsychologyAlliant International UniversitySan DiegoCaliforniaUSA
| | - Janice Hau
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ian Shryock
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Vinton Omaleki
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Kalekirstos Alemu
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Stephanie Pedrahita
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Inna Fishman
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ralph‐Axel Müller
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ruth A. Carper
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
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Parker KJ, Kabir IE, Doyley MM, Faiyaz A, Uddin MN, Flores G, Schifitto G. Brain elastography in aging relates to fluid/solid trendlines. Phys Med Biol 2024; 69:115037. [PMID: 38670141 DOI: 10.1088/1361-6560/ad4446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 04/26/2024] [Indexed: 04/28/2024]
Abstract
The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury. We address these issues by examining trendlines in aging from our elastography data, also utilizing data from an earlier landmark study of brain composition, and from a biophysics model that captures the multiscale biphasic (fluid/solid) structure of the brain. Taken together, these imply that long term changes in extracellular water in the glymphatic system of the brain along with a decline in the extracellular matrix have a profound effect on the measured viscoelastic properties. Specifically, the trendlines indicate that water tends to replace solid fraction as a function of age, then grey matter stiffness decreases inversely as water fraction squared, whereas white matter stiffness declines inversely as water fraction to the 2/3 power, a behavior consistent with the cylindrical shape of the axons. These unique behaviors point to elastography of the brain as an important macroscopic measure of underlying microscopic structural change, with direct implications for clinical studies of aging, disease, and injury.
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Affiliation(s)
- Kevin J Parker
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
| | - Irteza Enan Kabir
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
| | - Marvin M Doyley
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
| | - Abrar Faiyaz
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
| | - Md Nasir Uddin
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
- Department of Neurology, University of Rochester Medical Center, 601 Elmwood Ave, Box 673, Rochester, NY 14642, United States of America
| | - Gilmer Flores
- Department of Biomedical Engineering, University of Rochester, 204 Goergen Hall, Box 270168, Rochester, NY 14627, United States of America
| | - Giovanni Schifitto
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
- Department of Imaging Sciences, University of Rochester Medical Center, 601 Elmwood Ave, Box 648, Rochester, NY 14642, United States of America
- Department of Neurology, University of Rochester Medical Center, 601 Elmwood Ave, Box 673, Rochester, NY 14642, United States of America
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Schäper J, Bieri O. Myelin water imaging at 0.55 T using a multigradient-echo sequence. Magn Reson Med 2024; 91:1043-1056. [PMID: 38010053 DOI: 10.1002/mrm.29949] [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: 09/07/2023] [Revised: 10/19/2023] [Accepted: 11/12/2023] [Indexed: 11/29/2023]
Abstract
PURPOSE To investigate the prospects of a multigradient-echo (mGRE) acquisition for in vivo myelin water imaging at 0.55 T. METHODS Scans were performed on the brain of four healthy volunteers at 0.55 and 3 T, using a 3D mGRE sequence. The myelin water fraction (MWF) was calculated for both field strengths using a nonnegative least squares (NNLS) algorithm, implemented in the qMRLab suite. The quality of these maps as well as single-voxel fits were compared visually for 0.55 and 3 T. RESULTS The obtained MWF values at 0.55 T are consistent with previously reported ones at higher field strengths. The MWF maps are a considerable improvement over the ones at 3 T. Example fits show that 0.55 T data is better described by an exponential model than 3 T data, making the assumed multi-exponential model of the NNLS algorithm more accurate. CONCLUSION This first assessment shows that mGRE myelin water imaging at 0.55 T is feasible and has the potential to yield better results than at higher fields.
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Affiliation(s)
- Jessica Schäper
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Oliver Bieri
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
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Gangadin SS, Mandl RCW, de Witte LD, van Haren NEM, Schutte MJL, Begemann MJH, Kahn RS, Sommer IEC. Lower fractional anisotropy without evidence for neuro-inflammation in patients with early-phase schizophrenia spectrum disorders. Schizophr Res 2024; 264:557-566. [PMID: 36577563 DOI: 10.1016/j.schres.2022.12.009] [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: 06/09/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 12/28/2022]
Abstract
Various lines of research suggest immune dysregulation as a potential therapeutic target for negative and cognitive symptoms in schizophrenia spectrum disorders (SSD). Immune dysregulation would lead to higher extracellular free-water (EFW) in cerebral white matter (WM), which may partially underlie the frequently reported lower fractional anisotropy (FA) in SSD. We aim to investigate differences in EFW concentrations - a presumed proxy for neuro-inflammation - between early-phase SSD patients (n = 55) and healthy controls (HC; n = 37), and to explore immunological and cognitive correlates. To increase specificity for EFW, we study several complementary magnetic resonance imaging contrasts that are sensitive to EFW. FA, mean diffusivity (MD), magnetization transfer ratio (MTR), myelin water fraction (MWF) and quantitative T1 and T2 were calculated from diffusion-weighted imaging (DWI), magnetization transfer imaging (MTI) and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT). For each measure, WM skeletons were constructed with tract-based spatial statistics. Multivariate SSD-HC comparisons with WM skeletons and their average values (i.e. global WM) were not statistically significant. In voxel-wise analyses, FA was significantly lower in SSD in the genu of the corpus callosum and in the left superior longitudinal fasciculus (p < 0.04). Global WM measures did not correlate with immunological markers (i.e. IL1-RA, IL-6, IL-8, IL-10 and CRP) or cognition in HC and SSD after corrections for multiple comparisons. We confirmed lower FA in early-phase SSD patients. However, nonFA measures did not provide additional evidence for immune dysregulation or for higher EFW as the primary mechanism underlying the reported lower FA values in SSD.
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Affiliation(s)
- Shiral S Gangadin
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - René C W Mandl
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Lot D de Witte
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
| | - Neeltje E M van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center-Sophia Children's Hospital, Rotterdam, the Netherlands.
| | - Maya J L Schutte
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - Marieke J H Begemann
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - René S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
| | - Iris E C Sommer
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
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Motegi H, Kufukihara K, Kitagawa S, Sekiguchi K, Hata J, Fujiwara H, Jinzaki M, Okano H, Nakamura M, Iguchi Y, Nakahara J. Non-lesional white matter changes depicted by q-space diffusional MRI correlate with clinical disabilities in multiple sclerosis. J Neurol Sci 2024; 456:122851. [PMID: 38181653 DOI: 10.1016/j.jns.2023.122851] [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: 07/12/2023] [Revised: 11/20/2023] [Accepted: 12/17/2023] [Indexed: 01/07/2024]
Abstract
BACKGROUND We previously developed an optimized q-space diffusional MRI technique (normalized leptokurtic diffusion [NLD] map) to delineate the demyelinated lesions of multiple sclerosis (MS) patients. Herein, we evaluated the utility of NLD maps to discern the white matter abnormalities in normal-appearing white matter (NAWM) and the abnormalities' possible associations with physical and cognitive disabilities in MS. METHODS We conducted a retrospective observational study of MS patients treated at our hospital (Jan. 2012 to Dec. 2022). Clinical and MRI data were collected; Processing Speed Test (PST) data were obtained when possible. For a quantitative analysis of the NLD maps, we calculated the NLD index as GVROI/GVREF, where GV is a mean grayscale value in the regions of interest (ROIs) and the reference area (REF; cerebrospinal fluid). RESULTS One hundred-one individuals with MS were included. The lower corpus callosum and non-lesional WM NLD index were associated with worse Expanded Disability Status Scale (EDSS) and PST scores. The NLD indexes in the corpus callosum (p < 0.0001) and non-lesional white matter (p < 0.0001) were significantly reduced in progressive MS compared to relapsing-remitting MS. We categorized MS severity as moderate/severe (EDSS score ≥ 4 points) and mild (EDSS score < 4 points). The NLD indexes in the corpus callosum (p < 0.0001) and non-lesional white matter (p < 0.0001) were significantly lower in the moderate/severe MS group compared to the mild MS group. CONCLUSION The NLD map revealed abnormalities in the non-lesional white matter, providing valuable insights for evaluating manifestations in MS patients.
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Affiliation(s)
- Haruhiko Motegi
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan; Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan.
| | - Kenji Kufukihara
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan; Department of Neurology, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
| | - Satoshi Kitagawa
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan.
| | - Koji Sekiguchi
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan.
| | - Junichi Hata
- Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan; Department of Physiology, Keio University School of Medicine, Tokyo, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Japan.
| | - Hirokazu Fujiwara
- Center of Preventive Medicine, Keio University School of Medicine, Tokyo, Japan.
| | - Masahiro Jinzaki
- Department of Radiology, Keio University School of Medicine, Tokyo, Japan.
| | - Hideyuki Okano
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Japan.
| | - Masaya Nakamura
- Department of Orthopedic Surgery, Keio University School of Medicine, Tokyo, Japan.
| | - Yasuyuki Iguchi
- Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan.
| | - Jin Nakahara
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan.
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Bosticardo S, Schiavi S, Schaedelin S, Battocchio M, Barakovic M, Lu PJ, Weigel M, Melie-Garcia L, Granziera C, Daducci A. Evaluation of tractography-based myelin-weighted connectivity across the lifespan. Front Neurosci 2024; 17:1228952. [PMID: 38239829 PMCID: PMC10794573 DOI: 10.3389/fnins.2023.1228952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 12/04/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction Recent studies showed that the myelin of the brain changes in the life span, and demyelination contributes to the loss of brain plasticity during normal aging. Diffusion-weighted magnetic resonance imaging (dMRI) allows studying brain connectivity in vivo by mapping axons in white matter with tractography algorithms. However, dMRI does not provide insight into myelin; thus, combining tractography with myelin-sensitive maps is necessary to investigate myelin-weighted brain connectivity. Tractometry is designated for this purpose, but it suffers from some serious limitations. Our study assessed the effectiveness of the recently proposed Myelin Streamlines Decomposition (MySD) method in estimating myelin-weighted connectomes and its capacity to detect changes in myelin network architecture during the process of normal aging. This approach opens up new possibilities compared to traditional Tractometry. Methods In a group of 85 healthy controls aged between 18 and 68 years, we estimated myelin-weighted connectomes using Tractometry and MySD, and compared their modulation with age by means of three well-known global network metrics. Results Following the literature, our results show that myelin development continues until brain maturation (40 years old), after which degeneration begins. In particular, mean connectivity strength and efficiency show an increasing trend up to 40 years, after which the process reverses. Both Tractometry and MySD are sensitive to these changes, but MySD turned out to be more accurate. Conclusion After regressing the known predictors, MySD results in lower residual error, indicating that MySD provides more accurate estimates of myelin-weighted connectivity than Tractometry.
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Affiliation(s)
- Sara Bosticardo
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Simona Schiavi
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
- ASG Superconductors S.p.A., Genoa, Italy
| | - Sabine Schaedelin
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
| | - Matteo Battocchio
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Département d’Informatique, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Lester Melie-Garcia
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINK), Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Alessandro Daducci
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
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Khodanovich M, Svetlik M, Naumova A, Kamaeva D, Usova A, Kudabaeva M, Anan’ina T, Wasserlauf I, Pashkevich V, Moshkina M, Obukhovskaya V, Kataeva N, Levina A, Tumentceva Y, Yarnykh V. Age-Related Decline in Brain Myelination: Quantitative Macromolecular Proton Fraction Mapping, T2-FLAIR Hyperintensity Volume, and Anti-Myelin Antibodies Seven Years Apart. Biomedicines 2023; 12:61. [PMID: 38255168 PMCID: PMC10812983 DOI: 10.3390/biomedicines12010061] [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: 11/07/2023] [Revised: 12/09/2023] [Accepted: 12/21/2023] [Indexed: 01/24/2024] Open
Abstract
Age-related myelination decrease is considered one of the likely mechanisms of cognitive decline. The present preliminary study is based on the longitudinal assessment of global and regional myelination of the normal adult human brain using fast macromolecular fraction (MPF) mapping. Additional markers were age-related changes in white matter (WM) hyperintensities on FLAIR-MRI and the levels of anti-myelin autoantibodies in serum. Eleven healthy subjects (33-60 years in the first study) were scanned twice, seven years apart. An age-related decrease in MPF was found in global WM, grey matter (GM), and mixed WM-GM, as well as in 48 out of 82 examined WM and GM regions. The greatest decrease in MPF was observed for the frontal WM (2-5%), genu of the corpus callosum (CC) (4.0%), and caudate nucleus (5.9%). The age-related decrease in MPF significantly correlated with an increase in the level of antibodies against myelin basic protein (MBP) in serum (r = 0.69 and r = 0.63 for global WM and mixed WM-GM, correspondingly). The volume of FLAIR hyperintensities increased with age but did not correlate with MPF changes and the levels of anti-myelin antibodies. MPF mapping showed high sensitivity to age-related changes in brain myelination, providing the feasibility of this method in clinics.
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Affiliation(s)
- Marina Khodanovich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Mikhail Svetlik
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Anna Naumova
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Radiology, University of Washington, 850 Republican Street, Seattle, WA 98109, USA
| | - Daria Kamaeva
- Laboratory of Molecular Genetics and Biochemistry, Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk 634014, Russia;
| | - Anna Usova
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 12/1 Savinykh St., Tomsk 634009, Russia;
| | - Marina Kudabaeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Tatyana Anan’ina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Irina Wasserlauf
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Valentina Pashkevich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Marina Moshkina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Victoria Obukhovskaya
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Fundamental Psychology and Behavioral Medicine, Siberian State Medical University, 2 Moskovskiy Trakt, Tomsk 634050, Russia
| | - Nadezhda Kataeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Neurology and Neurosurgery, Siberian State Medical University, 2 Moskovskiy Trakt, Tomsk 634050, Russia
| | - Anastasia Levina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Medica Diagnostic and Treatment Center, 86 Sovetskaya st., Tomsk 634510, Russia
| | - Yana Tumentceva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Vasily Yarnykh
- Department of Radiology, University of Washington, 850 Republican Street, Seattle, WA 98109, USA
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9
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Brenner EK, Bangen KJ, Clark AL, Delano-Wood L, Evangelista ND, Edwards L, Sorg SF, Jak AJ, Bondi MW, Deoni SCL, Lamar M. Sex moderates the association between age and myelin water fraction in the cingulum and fornix among older adults without dementia. Front Aging Neurosci 2023; 15:1267061. [PMID: 38161592 PMCID: PMC10757372 DOI: 10.3389/fnagi.2023.1267061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 11/27/2023] [Indexed: 01/03/2024] Open
Abstract
Background Decreasing white matter integrity in limbic pathways including the fornix and cingulum have been reported in Alzheimer's disease (AD), although underlying mechanisms and potential sex differences remain understudied. We therefore sought to explore sex as a moderator of the effect of age on myelin water fraction (MWF), a measure of myelin content, in older adults without dementia (N = 52). Methods Participants underwent neuropsychological evaluation and 3 T MRI at two research sites. Multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) quantified MWF in 3 a priori regions including the fornix, hippocampal cingulum (CgH), and cingulate cingulum (CgC). The California Verbal Learning Test-Second Edition assessed learning and delayed recall. Multiple linear regressions assessed for (1) interactions between age and sex on regional MWF and (2) associations of regional MWF and memory. Results (1) There was a significant age by sex interaction on MWF of the fornix (p = 0.002) and CgC (p = 0.005), but not the CgH (p = 0.192); as age increased, MWF decreased in women but not men. (2) Fornix MWF was associated with both learning and recall (ps < 0.01), but MWF of the two cingulum regions were not (p > 0.05). Results were unchanged when adjusting for hippocampal volume. Conclusion The current work adds to the literature by illuminating sex differences in age-related myelin decline using a measure sensitive to myelin and may help facilitate detection of AD risk for women.
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Affiliation(s)
- Einat K. Brenner
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Katherine J. Bangen
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- VA San Diego Healthcare System, San Diego, CA, United States
| | - Alexandra L. Clark
- Department of Psychology, The University of Texas at Austin, Austin, TX, United States
| | - Lisa Delano-Wood
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- VA San Diego Healthcare System, San Diego, CA, United States
| | - Nicole D. Evangelista
- Department of Clinical and Health Psychology, Center for Cognitive Aging and Memory, College of Public Health and Health Professions, McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - Lauren Edwards
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, CA, United States
| | - Scott F. Sorg
- Home Base, A Red Sox Foundation and Massachusetts General Hospital Program, Boston, MA, United States
| | - Amy J. Jak
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- VA San Diego Healthcare System, San Diego, CA, United States
| | - Mark W. Bondi
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- VA San Diego Healthcare System, San Diego, CA, United States
| | | | - Melissa Lamar
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States
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10
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Swain A, Soni ND, Wilson N, Juul H, Benyard B, Haris M, Kumar D, Nanga RPR, Detre J, Lee VM, Reddy R. Early-stage mapping of macromolecular content in APP NL-F mouse model of Alzheimer's disease using nuclear Overhauser effect MRI. Front Aging Neurosci 2023; 15:1266859. [PMID: 37876875 PMCID: PMC10590923 DOI: 10.3389/fnagi.2023.1266859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 09/15/2023] [Indexed: 10/26/2023] Open
Abstract
Non-invasive methods of detecting early-stage Alzheimer's disease (AD) can provide valuable insight into disease pathology, improving the diagnosis and treatment of AD. Nuclear Overhauser enhancement (NOE) MRI is a technique that provides image contrast sensitive to lipid and protein content in the brain. These macromolecules have been shown to be altered in Alzheimer's pathology, with early disruptions in cell membrane integrity and signaling pathways leading to the buildup of amyloid-beta plaques and neurofibrillary tangles. We used template-based analyzes of NOE MRI data and the characteristic Z-spectrum, with parameters optimized for increase specificity to NOE, to detect changes in lipids and proteins in an AD mouse model that recapitulates features of human AD. We find changes in NOE contrast in the hippocampus, hypothalamus, entorhinal cortex, and fimbria, with these changes likely attributed to disruptions in the phospholipid bilayer of cell membranes in both gray and white matter regions. This study suggests that NOE MRI may be a useful tool for monitoring early-stage changes in lipid-mediated metabolism in AD and other disorders with high spatial resolution.
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Affiliation(s)
- Anshuman Swain
- School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Narayan D. Soni
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Neil Wilson
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Halvor Juul
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Blake Benyard
- School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Mohammad Haris
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Dushyant Kumar
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Ravi Prakash Reddy Nanga
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - John Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Center for Functional Neuroimaging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Virginia M. Lee
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Alzheimer’s Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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11
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Chou SM, Yen YH, Yuan F, Zhang SC, Chong CM. Neuronal Senescence in the Aged Brain. Aging Dis 2023; 14:1618-1632. [PMID: 37196117 PMCID: PMC10529744 DOI: 10.14336/ad.2023.0214] [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: 12/23/2022] [Accepted: 02/14/2023] [Indexed: 05/19/2023] Open
Abstract
Cellular senescence is a highly complicated cellular state that occurs throughout the lifespan of an organism. It has been well-defined in mitotic cells by various senescent features. Neurons are long-lived post-mitotic cells with special structures and functions. With age, neurons display morphological and functional changes, accompanying alterations in proteostasis, redox balance, and Ca2+ dynamics; however, it is ambiguous whether these neuronal changes belong to the features of neuronal senescence. In this review, we strive to identify and classify changes that are relatively specific to neurons in the aging brain and define them as features of neuronal senescence through comparisons with common senescent features. We also associate them with the functional decline of multiple cellular homeostasis systems, proposing the possibility that these systems are the main drivers of neuronal senescence. We hope this summary will serve as a steppingstone for further inputs on a comprehensive but relatively specific list of phenotypes for neuronal senescence and in particular their underlying molecular events during aging. This will in turn shine light on the association between neuronal senescence and neurodegeneration and lead to the development of strategies to perturb the processes.
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Affiliation(s)
- Shu-Min Chou
- Program in Neuroscience & Behavioral Disorders, Duke-NUS Medical School, 169857 Singapore, Singapore.
| | - Yu-Hsin Yen
- Program in Neuroscience & Behavioral Disorders, Duke-NUS Medical School, 169857 Singapore, Singapore.
| | - Fang Yuan
- Program in Neuroscience & Behavioral Disorders, Duke-NUS Medical School, 169857 Singapore, Singapore.
| | - Su-Chun Zhang
- Program in Neuroscience & Behavioral Disorders, Duke-NUS Medical School, 169857 Singapore, Singapore.
- Department of Neuroscience, Department of Neurology, Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA.
| | - Cheong-Meng Chong
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, China.
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12
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Lopez-Lee C, Kodama L, Fan L, Wong MY, Foxe NR, Jiaz L, Yu F, Ye P, Zhu J, Norman K, Torres ER, Kim RD, Mousa GA, Dubal D, Liddelow S, Luo W, Gan L. Sex Chromosomes and Gonads Shape the Sex-Biased Transcriptomic Landscape in Tlr7-Mediated Demyelination During Aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.19.558439. [PMID: 37781600 PMCID: PMC10541118 DOI: 10.1101/2023.09.19.558439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Demyelination occurs in aging and associated diseases, including Alzheimer's disease. Several of these diseases exhibit sex differences in prevalence and severity. Biological sex primarily stems from sex chromosomes and gonads releasing sex hormones. To dissect mechanisms underlying sex differences in demyelination of aging brains, we constructed a transcriptomic atlas of cell type-specific responses to illustrate how sex chromosomes, gonads, and their interaction shape responses to demyelination. We found that sex-biased oligodendrocyte and microglial responses are driven by interaction of sex chromosomes and gonads prior to myelin loss. Post demyelination, sex chromosomes mainly guide microglial responses, while gonadal composition influences oligodendrocyte signaling. Significantly, ablation of the X-linked gene Toll-like receptor 7 (Tlr7), which exhibited sex-biased expression during demyelination, abolished the sex-biased responses and protected against demyelination.
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Affiliation(s)
- Chloe Lopez-Lee
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY
| | - Lay Kodama
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
- Neuroscience Graduate Program, University of California San Francisco, San Francisco, CA
| | - Li Fan
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Man Ying Wong
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Nessa R. Foxe
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Laraib Jiaz
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Fangmin Yu
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Pearly Ye
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Jingjie Zhu
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Kendra Norman
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Eileen Ruth Torres
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Rachel D. Kim
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY
| | - Gergey Alzaem Mousa
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Dena Dubal
- Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA
| | - Shane Liddelow
- Neuroscience Institute, NYU Grossman School of Medicine, New York, NY
- Department of Neuroscience & Physiology, NYU Grossman School of Medicine, New York, NY
- Department of Ophthalmology, NYU Grossman School of Medicine, New York, NY
- Parekh Center for Interdisciplinary Neurology, NYU Grossman School of Medicine, New York, NY
| | - Wenjie Luo
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
| | - Li Gan
- Helen and Robert Appel Institute for Alzheimer’s Disease Research, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY
- Neuroscience Graduate Program, Weill Cornell Medicine, New York, NY
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13
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Endt S, Engel M, Naldi E, Assereto R, Molendowska M, Mueller L, Mayrink Verdun C, Pirkl CM, Palombo M, Jones DK, Menzel MI. In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods. APPLIED MAGNETIC RESONANCE 2023; 54:1571-1588. [PMID: 38037641 PMCID: PMC10682074 DOI: 10.1007/s00723-023-01584-1] [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: 06/15/2023] [Revised: 07/18/2023] [Accepted: 07/25/2023] [Indexed: 12/02/2023]
Abstract
Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.
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Affiliation(s)
- Sebastian Endt
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Maria Engel
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Emanuele Naldi
- Technische Universität Braunschweig, Braunschweig, Germany
| | | | - Malwina Molendowska
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Medical Radiation Physics, Lund University, Lund, Sweden
| | - Lars Mueller
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), University of Leeds, Leeds, United Kingdom
| | - Claudio Mayrink Verdun
- Technical University of Munich, Munich, Germany
- Munich Center for Machine Learning, Munich, Germany
| | | | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Marion I. Menzel
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- GE HealthCare, Munich, Germany
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14
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Nguyen JN, Chauhan A. Bystanders or not? Microglia and lymphocytes in aging and stroke. Neural Regen Res 2023; 18:1397-1403. [PMID: 36571333 PMCID: PMC10075112 DOI: 10.4103/1673-5374.360345] [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: 11/06/2022] Open
Abstract
As the average age of the world population increases, more people will face debilitating aging-associated conditions, including dementia and stroke. Not only does the incidence of these conditions increase with age, but the recovery afterward is often worse in older patients. Researchers and health professionals must unveil and understand the factors behind age-associated diseases to develop a therapy for older patients. Aging causes profound changes in the immune system including the activation of microglia in the brain. Activated microglia promote T lymphocyte transmigration leading to an increase in neuroinflammation, white matter damage, and cognitive impairment in both older humans and rodents. The presence of T and B lymphocytes is observed in the aged brain and correlates with worse stroke outcomes. Preclinical strategies in stroke target either microglia or the lymphocytes or the communications between them to promote functional recovery in aged subjects. In this review, we examine the role of the microglia and T and B lymphocytes in aging and how they contribute to cognitive impairment. Additionally, we provide an important update on the contribution of these cells and their interactions in preclinical aged stroke.
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Affiliation(s)
- Justin N Nguyen
- University of Texas McGovern Medical School at Houston, Houston, TX, USA
| | - Anjali Chauhan
- Department of Neurology, University of Texas McGovern Medical School at Houston, Houston, TX, USA
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15
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Maitre M, Jeltsch-David H, Okechukwu NG, Klein C, Patte-Mensah C, Mensah-Nyagan AG. Myelin in Alzheimer's disease: culprit or bystander? Acta Neuropathol Commun 2023; 11:56. [PMID: 37004127 PMCID: PMC10067200 DOI: 10.1186/s40478-023-01554-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/20/2023] [Indexed: 04/03/2023] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder with neuronal and synaptic losses due to the accumulation of toxic amyloid β (Αβ) peptide oligomers, plaques, and tangles containing tau (tubulin-associated unit) protein. While familial AD is caused by specific mutations, the sporadic disease is more common and appears to result from a complex chronic brain neuroinflammation with mitochondriopathies, inducing free radicals' accumulation. In aged brain, mutations in DNA and several unfolded proteins participate in a chronic amyloidosis response with a toxic effect on myelin sheath and axons, leading to cognitive deficits and dementia. Αβ peptides are the most frequent form of toxic amyloid oligomers. Accumulations of misfolded proteins during several years alters different metabolic mechanisms, induce chronic inflammatory and immune responses with toxic consequences on neuronal cells. Myelin composition and architecture may appear to be an early target for the toxic activity of Aβ peptides and others hydrophobic misfolded proteins. In this work, we describe the possible role of early myelin alterations in the genesis of neuronal alterations and the onset of symptomatology. We propose that some pathophysiological and clinical forms of the disease may arise from structural and metabolic disorders in the processes of myelination/demyelination of brain regions where the accumulation of non-functional toxic proteins is important. In these forms, the primacy of the deleterious role of amyloid peptides would be a matter of questioning and the initiating role of neuropathology would be primarily the fact of dysmyelination.
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Affiliation(s)
- Michel Maitre
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France.
| | - Hélène Jeltsch-David
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
- Biotechnologie et signalisation cellulaire, UMR 7242 CNRS, Université de Strasbourg, 300 Boulevard Sébastien Brant CS 10413, Illkirch cedex, 67412, France
| | - Nwife Getrude Okechukwu
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
| | - Christian Klein
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
| | - Christine Patte-Mensah
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
| | - Ayikoe-Guy Mensah-Nyagan
- Biopathologie de la Myéline, Neuroprotection et Stratégies Thérapeutiques, Fédération de Médecine Translationnelle de Strasbourg (FMTS), INSERM U1119, Université de Strasbourg, Bâtiment CRBS de la Faculté de Médecine, 1 rue Eugène Boeckel, Strasbourg, 67000, France
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16
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Murray CJ, Vecchiarelli HA, Tremblay MÈ. Enhancing axonal myelination in seniors: A review exploring the potential impact cannabis has on myelination in the aged brain. Front Aging Neurosci 2023; 15:1119552. [PMID: 37032821 PMCID: PMC10073480 DOI: 10.3389/fnagi.2023.1119552] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 02/22/2023] [Indexed: 04/11/2023] Open
Abstract
Consumption of cannabis is on the rise as public opinion trends toward acceptance and its consequent legalization. Specifically, the senior population is one of the demographics increasing their use of cannabis the fastest, but research aimed at understanding cannabis' impact on the aged brain is still scarce. Aging is characterized by many brain changes that slowly alter cognitive ability. One process that is greatly impacted during aging is axonal myelination. The slow degradation and loss of myelin (i.e., demyelination) in the brain with age has been shown to associate with cognitive decline and, furthermore, is a common characteristic of numerous neurological diseases experienced in aging. It is currently not known what causes this age-dependent degradation, but it is likely due to numerous confounding factors (i.e., heightened inflammation, reduced blood flow, cellular senescence) that impact the many cells responsible for maintaining overall homeostasis and myelin integrity. Importantly, animal studies using non-human primates and rodents have also revealed demyelination with age, providing a reliable model for researchers to try and understand the cellular mechanisms at play. In rodents, cannabis was recently shown to modulate the myelination process. Furthermore, studies looking at the direct modulatory impact cannabis has on microglia, astrocytes and oligodendrocyte lineage cells hint at potential mechanisms to prevent some of the more damaging activities performed by these cells that contribute to demyelination in aging. However, research focusing on how cannabis impacts myelination in the aged brain is lacking. Therefore, this review will explore the evidence thus far accumulated to show how cannabis impacts myelination and will extrapolate what this knowledge may mean for the aged brain.
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Affiliation(s)
- Colin J. Murray
- Neuroscience Graduate Program, University of Victoria, Victoria, BC, Canada
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- *Correspondence: Colin J. Murray,
| | | | - Marie-Ève Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Départment de Médicine Moléculaire, Université Laval, Québec City, QC, Canada
- Axe Neurosciences, Center de Recherche du CHU de Québec, Université Laval, Québec City, QC, Canada
- Neurology and Neurosurgery Department, McGill University, Montréal, QC, Canada
- Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada
- Centre for Advanced Materials and Related Technology (CAMTEC), University of Victoria, Victoria, BC, Canada
- Institute for Aging and Lifelong Health, University of Victoria, Victoria, BC, Canada
- Marie-Ève Tremblay,
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17
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Sethi S, Friesen-Waldner LJ, Wade TP, Courchesne M, Nygard K, Sarr O, Sutherland B, Regnault TRH, McKenzie CA. Feasibility of MRI Quantification of Myelin Water Fraction in the Fetal Guinea Pig Brain. J Magn Reson Imaging 2022; 57:1856-1864. [PMID: 36239714 DOI: 10.1002/jmri.28482] [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: 07/25/2022] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Fetal myelination assessment is important for understanding neurodevelopment and neurodegeneration. Myelin water imaging (MWI) quantifies myelin water fraction (MWF), a validated marker for myelin content, and has been used to assess brain myelin in children and neonates. PURPOSE To demonstrate that MWI can quantify MWF in fetal guinea pigs (GPs). STUDY TYPE Animal model. ANIMAL MODEL Nine pregnant, Dunkin-Hartley GPs with 31 fetuses (mean ± standard deviation = 60 ± 1.5 days gestation). FIELD STRENGTH/SEQUENCE 3D spoiled gradient echo and balanced steady-state free precession sequences at 3.0 T. ASSESSMENT MWF maps were reconstructed for maternal and fetal GP brains using the multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) approach. Myelin basic protein (MBP) stain provided histological validation of the MWF. Regions of interest were placed in the maternal corpus callosum (CC), maternal fornix (FOR), fetal CC, and fetal FOR in MWF maps and MBP stains. STATISTICAL TESTS Linear regression between MWF and MBP stain intensity (SI) of all four regions (coefficient of determination, R2 ). A paired t-test compared the MWF of maternal and mean fetal CC, MBP SI of maternal and mean fetal CC, MWF of maternal and mean fetal FOR, MBP SI of maternal and mean fetal FOR. A paired t-test with a linear mixed model compared the MWF of fetal CC and fetal FOR, and MBP SI of fetal CC and fetal FOR. A P value < 0.0083 was considered statistically significant. RESULTS The mean MWF of the analyzed regions are as follows (mean ± standard deviation): 0.338 + 0.016 (maternal CC), 0.340 ± 0.017 (maternal FOR), 0.214 ± 0.016 (fetal CC), and 0.305 ± 0.025 (fetal FOR). MWF correlated with MBP SI in all regions (R2 = 0.81). Significant differences were found between MWF and MBP SI of maternal and fetal CC, and MWF and MBP SI of fetal CC and fetal FOR. DATA CONCLUSION This study demonstrated the feasibility of MWI in assessing fetal brain myelin content. EVIDENCE LEVEL 2 Technical Efficacy: Stage 1.
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Affiliation(s)
- Simran Sethi
- Department of Medical Biophysics, Western University, London, Ontario, Canada
| | | | - Trevor P Wade
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Robarts Research Institute, Western University, London, Ontario, Canada
| | - Marc Courchesne
- Biotron Experimental Climate Change Research Centre, Western University, London, Ontario, Canada
| | - Karen Nygard
- Biotron Experimental Climate Change Research Centre, Western University, London, Ontario, Canada
| | - Ousseynou Sarr
- Department of Physiology & Pharmacology, Western University, London, Ontario, Canada
| | - Brian Sutherland
- Department of Physiology & Pharmacology, Western University, London, Ontario, Canada
| | - Timothy R H Regnault
- Department of Physiology & Pharmacology, Western University, London, Ontario, Canada.,Department of Obstetrics & Gynaecology, Western University, London, Ontario, Canada.,Division of Maternal, Fetal, and Newborn Health, Children's Health Research Institute, Lawson Health Research Institute, Western University, London, Ontario, Canada
| | - Charles A McKenzie
- Department of Medical Biophysics, Western University, London, Ontario, Canada.,Robarts Research Institute, Western University, London, Ontario, Canada.,Division of Maternal, Fetal, and Newborn Health, Children's Health Research Institute, Lawson Health Research Institute, Western University, London, Ontario, Canada
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18
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Ota Y, Shah G. Imaging of Normal Brain Aging. Neuroimaging Clin N Am 2022; 32:683-698. [PMID: 35843669 DOI: 10.1016/j.nic.2022.04.010] [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: 11/16/2022]
Abstract
Understanding normal brain aging physiology is essential to improving healthy human longevity, differentiation, and early detection of diseases, such as neurodegenerative diseases, which are an enormous social and economic burden. Functional decline, such as reduced physical activity and cognitive abilities, is typically associated with brain aging. The authors summarize the aging brain mechanism and effects of aging on the brain observed by brain structural MR imaging and advanced neuroimaging techniques, such as diffusion tensor imaging and functional MR imaging.
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Affiliation(s)
- Yoshiaki Ota
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 East Medical Center Drive, UH B2, Ann Arbor, MI 48109, USA
| | - Gaurang Shah
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 East Medical Center Drive, UH B2, Ann Arbor, MI 48109, USA.
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19
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Fischi-Gomez E, Girard G, Koch PJ, Yu T, Pizzolato M, Brügger J, Piredda GF, Hilbert T, Cadic-Melchior AG, Beanato E, Park CH, Morishita T, Wessel MJ, Schiavi S, Daducci A, Kober T, Canales-Rodríguez EJ, Hummel FC, Thiran JP. Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions. FRONTIERS IN RADIOLOGY 2022; 2:930666. [PMID: 37492668 PMCID: PMC10365099 DOI: 10.3389/fradi.2022.930666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/30/2022] [Indexed: 07/27/2023]
Abstract
Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acquired in a healthy population. This study focuses on multi-echo T2 relaxometry, a qMRI technique that probes the complex tissue microstructure by differentiating compartment-specific T2 relaxation times. However, estimation methods are still limited by their sensitivity to the underlying noise. Moreover, estimating the model's parameters is challenging because the resulting inverse problem is ill-posed, requiring advanced numerical regularization techniques. As a result, the estimates from distinct regularization strategies are different. In this work, we aimed to investigate the variability and reproducibility of different techniques for estimating the transverse relaxation time of the intra- and extra-cellular space (T2IE) in gray (GM) and white matter (WM) tissue in a clinical setting, using a multi-site, multi-session, and multi-run T2 relaxometry dataset. To this end, we evaluated three different techniques for estimating the T2 spectra (two regularized non-negative least squares methods and a machine learning approach). Two independent analyses were performed to study the effect of using raw and denoised data. For both the GM and WM regions, and the raw and denoised data, our results suggest that the principal source of variance is the inter-subject variability, showing a higher coefficient of variation (CoV) than those estimated for the inter-site, inter-session, and inter-run, respectively. For all reconstruction methods studied, the CoV ranged between 0.32 and 1.64%. Interestingly, the inter-session variability was close to the inter-scanner variability with no statistical differences, suggesting that T2IE is a robust parameter that could be employed in multi-site neuroimaging studies. Furthermore, the three tested methods showed consistent results and similar intra-class correlation (ICC), with values superior to 0.7 for most regions. Results from raw data were slightly more reproducible than those from denoised data. The regularized non-negative least squares method based on the L-curve technique produced the best results, with ICC values ranging from 0.72 to 0.92.
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Affiliation(s)
- Elda Fischi-Gomez
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Translational Machine Learning Lab, Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Gabriel Girard
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Philipp J. Koch
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University of Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany
| | - Thomas Yu
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Marco Pizzolato
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Julia Brügger
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Gian Franco Piredda
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Tom Hilbert
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Andéol G. Cadic-Melchior
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Elena Beanato
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Chang-Hyun Park
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Takuya Morishita
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Maximilian J. Wessel
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Simona Schiavi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Alessandro Daducci
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Tobias Kober
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Erick J. Canales-Rodríguez
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Friedhelm C. Hummel
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Clinical Neuroscience, University Hospital of Geneva (HUG), Geneva, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
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Update on myelin imaging in neurological syndromes. Curr Opin Neurol 2022; 35:467-474. [PMID: 35788545 DOI: 10.1097/wco.0000000000001078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
PURPOSE OF REVIEW Myelin water imaging (MWI) is generally regarded as the most rigorous approach for noninvasive, in-vivo measurement of myelin content, which has been histopathologically validated. As such, it has been increasingly applied to neurological diseases with white matter involvement, especially those affecting myelin. This review provides an overview of the most recent research applying MWI in neurological syndromes. RECENT FINDINGS Myelin water imaging has been applied in neurological syndromes including multiple sclerosis, Alzheimer's disease, Huntington's disease, traumatic brain injury, Parkinson's disease, cerebral small vessel disease, leukodystrophies and HIV. These syndromes generally showed alterations observable with MWI, with decreased myelin content tending to correlate with lower cognitive scores and worse clinical presentation. MWI has also been correlated with genetic variation in the APOE and PLP1 genes, demonstrating genetic factors related to myelin health. SUMMARY MWI can detect and quantify changes not observable with conventional imaging, thereby providing insight into the pathophysiology and disease mechanisms of a diverse range of neurological syndromes.
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21
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Silva NCBS, Dao E, Hsu CL, Tam RC, Stein R, Alkeridy W, Laule C, Vavasour IM, Liu-Ambrose T. Myelin Content and Gait Impairment in Older Adults with Cerebral Small Vessel Disease and Mild Cognitive Impairment. Neurobiol Aging 2022; 119:56-66. [DOI: 10.1016/j.neurobiolaging.2022.03.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 02/19/2022] [Accepted: 03/15/2022] [Indexed: 11/25/2022]
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22
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Cárdenas-Tueme M, Trujillo-Villarreal LÁ, Ramírez-Amaya V, Garza-Villarreal EA, Camacho-Morales A, Reséndez-Pérez D. Fornix volumetric increase and microglia morphology contribute to spatial and recognition-like memory decline in ageing male mice. Neuroimage 2022; 252:119039. [PMID: 35227858 DOI: 10.1016/j.neuroimage.2022.119039] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 02/07/2022] [Accepted: 02/24/2022] [Indexed: 10/19/2022] Open
Abstract
Ageing displays a low-grade pro-inflammatory profile in blood and the brain. Accumulation of pro-inflammatory cytokines, microglia activation and volumetric changes in the brain correlate with cognitive decline in ageing models. However, the interplay between them is not totally understood. Here, we aimed to globally identify an age-dependent pro-inflammatory profile and microglia morphological plasticity that favors major volume changes in the brain associated with cognitive decline. Cluster analysis of behavioral data obtained from 2-,12- and 20-month-old male C57BL/6 mice revealed age-dependent cognitive decline after the Y-maze, Barnes maze, object recognition (NORT) and object location tests (OLT). Global magnetic resonance imageing (MRI) analysis by deformation-based morphometry (DBM) in the brain identified a volume increase in the fornix and a decrease in the left medial entorhinal cortex (MEntC) during ageing. Notably, the fornix shows an increase in the accumulation of pro-inflammatory cytokines, whereas the left MEntC displays a decrease. Morphological assessment of microglia also confirms an active and dystrophic phenotype in the fornix and a surveillance phenotype in the left MEntC. Finally, biological modeling revealed that age-related volume increase in the fornix was associated with dystrophic microglia and cognitive impairment, as evidenced by failure on tasks examining memory of object location and novelty. Our results propose that the morphological plasticity of microglia might contribute to volumetric changes in brain regions associated with cognitive decline during physiological ageing.
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Affiliation(s)
- Marcela Cárdenas-Tueme
- Universidad Autonoma de Nuevo León, Facultad de Ciencias Biológicas, Departamento de Biología Celular y Genética, San Nicolás de los Garza, Nuevo León, México
| | - Luis Ángel Trujillo-Villarreal
- Universidad Autonoma de Nuevo León, Facultad de Medicina, Departamento de Bioquímica, Monterrey, Nuevo León, México; Universidad Autonoma de Nuevo León, Centro de Investigación y Desarrollo en Ciencias de la Salud, Unidad de Neurometabolismo, Monterrey, Nuevo León, México
| | - Victor Ramírez-Amaya
- Instituto de Investigación Médica Mercedes y Martín Ferreyra INIMEC-CONICET- UNC, Friuli 2434, Colinas de Vélez Sarsfield, Córdoba 5016, Argentina
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México Campus Juriquilla, Querétaro, México
| | - Alberto Camacho-Morales
- Universidad Autonoma de Nuevo León, Facultad de Medicina, Departamento de Bioquímica, Monterrey, Nuevo León, México; Universidad Autonoma de Nuevo León, Centro de Investigación y Desarrollo en Ciencias de la Salud, Unidad de Neurometabolismo, Monterrey, Nuevo León, México.
| | - Diana Reséndez-Pérez
- Universidad Autonoma de Nuevo León, Facultad de Ciencias Biológicas, Departamento de Biología Celular y Genética, San Nicolás de los Garza, Nuevo León, México.
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Comparison of the Effects of Cuprizone on Demyelination in the Corpus Callosum and Hippocampal Progenitors in Young Adult and Aged Mice. Neurochem Res 2022; 47:1073-1082. [DOI: 10.1007/s11064-021-03506-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/22/2021] [Accepted: 12/07/2021] [Indexed: 01/08/2023]
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Rodgers G, Tanner C, Schulz G, Migga A, Kuo W, Bikis C, Scheel M, Kurtcuoglu V, Weitkamp T, Müller B. Virtual histology of an entire mouse brain from formalin fixation to paraffin embedding. Part 2: Volumetric strain fields and local contrast changes. J Neurosci Methods 2022; 365:109385. [PMID: 34637810 DOI: 10.1016/j.jneumeth.2021.109385] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 10/07/2021] [Indexed: 01/14/2023]
Abstract
BACKGROUND Fixation and embedding of post mortem brain tissue is a pre-requisite for both gold-standard conventional histology and X-ray virtual histology. This process alters the morphology and density of the brain microanatomy. NEW METHOD To quantify these changes, we employed synchrotron radiation-based hard X-ray tomography with 3 μm voxel length to visualize the same mouse brain after fixation in 4% formalin, immersion in ethanol solutions (50%, 70%, 80%, 90%, and 100%), xylene, and finally after embedding in a paraffin block. The volumetric data were non-rigidly registered to the initial formalin-fixed state to align the microanatomy within the entire mouse brain. RESULTS Volumetric strain fields were used to characterize local shrinkage, which was found to depend on the anatomical region and distance to external surface. X-ray contrast was altered and enhanced by preparation-induced inter-tissue density changes. The preparation step can be selected to highlight specific anatomical features. For example, fiber tract contrast is amplified in 100% ethanol. COMPARISON WITH EXISTING METHODS Our method provides volumetric strain fields, unlike approaches based on feature-to-feature or volume measurements. Volumetric strain fields are produced by non-rigid registration, which is less labor-intensive and observer-dependent than volume change measurements based on manual segmentations. X-ray microtomography provides spatial resolution at least an order of magnitude higher than magnetic resonance microscopy, allowing for analysis of morphology and density changes within the brain's microanatomy. CONCLUSION Our approach belongs to three-dimensional virtual histology with isotropic micrometer spatial resolution and therefore complements atlases based on a combination of magnetic resonance microscopy and optical micrographs of serial histological sections.
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Affiliation(s)
- Griffin Rodgers
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; Biomaterials Science Center, Department of Clinical Research, University Hospital Basel, 4031 Basel, Switzerland
| | - Christine Tanner
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; Biomaterials Science Center, Department of Clinical Research, University Hospital Basel, 4031 Basel, Switzerland.
| | - Georg Schulz
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; Biomaterials Science Center, Department of Clinical Research, University Hospital Basel, 4031 Basel, Switzerland
| | - Alexandra Migga
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; Biomaterials Science Center, Department of Clinical Research, University Hospital Basel, 4031 Basel, Switzerland
| | - Willy Kuo
- The Interface Group, Institute of Physiology, University of Zurich, 8057 Zurich, Switzerland; National Centre of Competence in Research, Kidney.CH, 8057 Zurich, Switzerland
| | - Christos Bikis
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; Biomaterials Science Center, Department of Clinical Research, University Hospital Basel, 4031 Basel, Switzerland; Integrierte Psychiatrie Winterthur - Zürcher Unterland, 8408 Winterthur, Switzerland
| | - Mario Scheel
- Synchrotron Soleil, 91192 Gif-sur-Yvette, France
| | - Vartan Kurtcuoglu
- The Interface Group, Institute of Physiology, University of Zurich, 8057 Zurich, Switzerland; National Centre of Competence in Research, Kidney.CH, 8057 Zurich, Switzerland
| | | | - Bert Müller
- Biomaterials Science Center, Department of Biomedical Engineering, University of Basel, 4123 Allschwil, Switzerland; Biomaterials Science Center, Department of Clinical Research, University Hospital Basel, 4031 Basel, Switzerland
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Omer N, Galun M, Stern N, Blumenfeld-Katzir T, Ben-Eliezer N. Data-driven algorithm for myelin water imaging: Probing subvoxel compartmentation based on identification of spatially global tissue features. Magn Reson Med 2021; 87:2521-2535. [PMID: 34958690 DOI: 10.1002/mrm.29125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 11/23/2021] [Accepted: 11/26/2021] [Indexed: 01/10/2023]
Abstract
PURPOSE Multicomponent analysis of MRI T2 relaxation time (mcT2 ) is commonly used for estimating myelin content by separating the signal at each voxel into its underlying distribution of T2 values. This voxel-based approach is challenging due to the large ambiguity in the multi-T2 space and the low SNR of MRI signals. Herein, we present a data-driven mcT2 analysis, which utilizes the statistical strength of identifying spatially global mcT2 motifs in white matter segments before deconvolving the local signal at each voxel. METHODS Deconvolution is done using a tailored optimization scheme, which incorporates the global mcT2 motifs without additional prior assumptions regarding the number of microscopic components. The end results of this process are voxel-wise myelin water fraction maps. RESULTS Validations are shown for computer-generated signals, uniquely designed subvoxel mcT2 phantoms, and in vivo human brain. Results demonstrated excellent fitting accuracy, both for the numerical and the physical mcT2 phantoms, exhibiting excellent agreement between calculated myelin water fraction and ground truth. Proof-of-concept in vivo validation is done by calculating myelin water fraction maps for white matter segments of the human brain. Interscan stability of myelin water fraction values was also estimated, showing good correlation between scans. CONCLUSION We conclude that studying global tissue motifs prior to performing voxel-wise mcT2 analysis stabilizes the optimization scheme and efficiently overcomes the ambiguity in the T2 space. This new approach can improve myelin water imaging and the investigation of microstructural compartmentation in general.
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Affiliation(s)
- Noam Omer
- The Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Meirav Galun
- Department of Computer Science and Applied Mathematics, Weitzman Institute of Science, Rehovot, Israel
| | - Neta Stern
- The Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | | | - Noam Ben-Eliezer
- The Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University Langone Medical Center, New York, New York, USA
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Blinkouskaya Y, Caçoilo A, Gollamudi T, Jalalian S, Weickenmeier J. Brain aging mechanisms with mechanical manifestations. Mech Ageing Dev 2021; 200:111575. [PMID: 34600936 PMCID: PMC8627478 DOI: 10.1016/j.mad.2021.111575] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 09/09/2021] [Accepted: 09/22/2021] [Indexed: 12/14/2022]
Abstract
Brain aging is a complex process that affects everything from the subcellular to the organ level, begins early in life, and accelerates with age. Morphologically, brain aging is primarily characterized by brain volume loss, cortical thinning, white matter degradation, loss of gyrification, and ventricular enlargement. Pathophysiologically, brain aging is associated with neuron cell shrinking, dendritic degeneration, demyelination, small vessel disease, metabolic slowing, microglial activation, and the formation of white matter lesions. In recent years, the mechanics community has demonstrated increasing interest in modeling the brain's (bio)mechanical behavior and uses constitutive modeling to predict shape changes of anatomically accurate finite element brain models in health and disease. Here, we pursue two objectives. First, we review existing imaging-based data on white and gray matter atrophy rates and organ-level aging patterns. This data is required to calibrate and validate constitutive brain models. Second, we review the most critical cell- and tissue-level aging mechanisms that drive white and gray matter changes. We focuse on aging mechanisms that ultimately manifest as organ-level shape changes based on the idea that the integration of imaging and mechanical modeling may help identify the tipping point when normal aging ends and pathological neurodegeneration begins.
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Affiliation(s)
- Yana Blinkouskaya
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Andreia Caçoilo
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Trisha Gollamudi
- Department of Biomedical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Shima Jalalian
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States
| | - Johannes Weickenmeier
- Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States.
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MacDonald ME, Pike GB. MRI of healthy brain aging: A review. NMR IN BIOMEDICINE 2021; 34:e4564. [PMID: 34096114 DOI: 10.1002/nbm.4564] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 06/12/2023]
Abstract
We present a review of the characterization of healthy brain aging using MRI with an emphasis on morphology, lesions, and quantitative MR parameters. A scope review found 6612 articles encompassing the keywords "Brain Aging" and "Magnetic Resonance"; papers involving functional MRI or not involving imaging of healthy human brain aging were discarded, leaving 2246 articles. We first consider some of the biogerontological mechanisms of aging, and the consequences of aging in terms of cognition and onset of disease. Morphological changes with aging are reviewed for the whole brain, cerebral cortex, white matter, subcortical gray matter, and other individual structures. In general, volume and cortical thickness decline with age, beginning in mid-life. Prevalent silent lesions such as white matter hyperintensities, microbleeds, and lacunar infarcts are also observed with increasing frequency. The literature regarding quantitative MR parameter changes includes T1 , T2 , T2 *, magnetic susceptibility, spectroscopy, magnetization transfer, diffusion, and blood flow. We summarize the findings on how each of these parameters varies with aging. Finally, we examine how the aforementioned techniques have been used for age prediction. While relatively large in scope, we present a comprehensive review that should provide the reader with sound understanding of what MRI has been able to tell us about how the healthy brain ages.
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Affiliation(s)
- M Ethan MacDonald
- Department of Electrical and Software Engineering, University of Calgary, Calgary, Alberta, Canada
- Departments of Radiology and Clinical Neuroscience, University of Calgary, Calgary, Alberta, Canada
- Healthy Brain Aging Laboratory, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - G Bruce Pike
- Departments of Radiology and Clinical Neuroscience, University of Calgary, Calgary, Alberta, Canada
- Healthy Brain Aging Laboratory, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
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van de Stadt SIW, Huffnagel IC, Turk BR, van der Knaap MS, Engelen M. Imaging in X-Linked Adrenoleukodystrophy. Neuropediatrics 2021; 52:252-260. [PMID: 34192790 DOI: 10.1055/s-0041-1730937] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Magnetic resonance imaging (MRI) is the gold standard for the detection of cerebral lesions in X-linked adrenoleukodystrophy (ALD). ALD is one of the most common peroxisomal disorders and is characterized by a defect in degradation of very long chain fatty acids (VLCFA), resulting in accumulation of VLCFA in plasma and tissues. The clinical spectrum of ALD is wide and includes adrenocortical insufficiency, a slowly progressive myelopathy in adulthood, and cerebral demyelination in a subset of male patients. Cerebral demyelination (cerebral ALD) can be treated with hematopoietic cell transplantation (HCT) but only in an early (pre- or early symptomatic) stage and therefore active MRI surveillance is recommended for male patients, both pediatric and adult. Although structural MRI of the brain can detect the presence and extent of cerebral lesions, it does not predict if and when cerebral demyelination will occur. There is a great need for imaging techniques that predict onset of cerebral ALD before lesions appear. Also, imaging markers for severity of myelopathy as surrogate outcome measure in clinical trials would facilitate drug development. New quantitative MRI techniques are promising in that respect. This review focuses on structural and quantitative imaging techniques-including magnetic resonance spectroscopy, diffusion tensor imaging, MR perfusion imaging, magnetization transfer (MT) imaging, neurite orientation dispersion and density imaging (NODDI), and myelin water fraction imaging-used in ALD and their role in clinical practice and research opportunities for the future.
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Affiliation(s)
- Stephanie I W van de Stadt
- Department of Pediatric Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Irene C Huffnagel
- Department of Pediatric Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Bela R Turk
- Departments of Neurology and Pediatrics, Moser Center for Leukodystrophies, Kennedy Krieger Institute, Johns Hopkins University, Baltimore, Maryland, United States
| | - Marjo S van der Knaap
- Department of Pediatric Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Marc Engelen
- Department of Pediatric Neurology, Amsterdam Leukodystrophy Center, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam Neuroscience, Amsterdam, The Netherlands
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29
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Buyanova IS, Arsalidou M. Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review. Front Hum Neurosci 2021; 15:662031. [PMID: 34295229 PMCID: PMC8290169 DOI: 10.3389/fnhum.2021.662031] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 06/02/2021] [Indexed: 12/22/2022] Open
Abstract
White matter makes up about fifty percent of the human brain. Maturation of white matter accompanies biological development and undergoes the most dramatic changes during childhood and adolescence. Despite the advances in neuroimaging techniques, controversy concerning spatial, and temporal patterns of myelination, as well as the degree to which the microstructural characteristics of white matter can vary in a healthy brain as a function of age, gender and cognitive abilities still exists. In a selective review we describe methods of assessing myelination and evaluate effects of age and gender in nine major fiber tracts, highlighting their role in higher-order cognitive functions. Our findings suggests that myelination indices vary by age, fiber tract, and hemisphere. Effects of gender were also identified, although some attribute differences to methodological factors or social and learning opportunities. Findings point to further directions of research that will improve our understanding of the complex myelination-behavior relation across development that may have implications for educational and clinical practice.
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Affiliation(s)
- Irina S. Buyanova
- Neuropsy Lab, HSE University, Moscow, Russia
- Center for Language and Brain, HSE University, Moscow, Russia
| | - Marie Arsalidou
- Neuropsy Lab, HSE University, Moscow, Russia
- Cognitive Centre, Sirius University of Science and Technology, Sochi, Russia
- Department of Psychology, York University, Toronto, ON, Canada
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30
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Khattar N, Triebswetter C, Kiely M, Ferrucci L, Resnick SM, Spencer RG, Bouhrara M. Investigation of the association between cerebral iron content and myelin content in normative aging using quantitative magnetic resonance neuroimaging. Neuroimage 2021; 239:118267. [PMID: 34139358 PMCID: PMC8370037 DOI: 10.1016/j.neuroimage.2021.118267] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 06/10/2021] [Accepted: 06/11/2021] [Indexed: 12/24/2022] Open
Abstract
Myelin loss and iron accumulation are cardinal features of aging and various neurodegenerative diseases. Oligodendrocytes incorporate iron as a metabolic substrate for myelin synthesis and maintenance. An emerging hypothesis in Alzheimer’s disease research suggests that myelin breakdown releases substantial stores of iron that may accumulate, leading to further myelin breakdown and neurodegeneration. We assessed associations between iron content and myelin content in critical brain regions using quantitative magnetic resonance imaging (MRI) on a cohort of cognitively unimpaired adults ranging in age from 21 to 94 years. We measured whole-brain myelin water fraction (MWF), a surrogate of myelin content, using multicomponent relaxometry, and whole-brain iron content using susceptibility weighted imaging in all individuals. MWF was negatively associated with iron content in most brain regions evaluated indicating that lower myelin content corresponds to higher iron content. Moreover, iron content was significantly higher with advanced age in most structures, with men exhibiting a trend towards higher iron content as compared to women. Finally, relationship between MWF and age, in all brain regions investigated, suggests that brain myelination continues until middle age, followed by degeneration at older ages. This work establishes a foundation for further investigations of the etiology and sequelae of myelin breakdown and iron accumulation in neurodegeneration and may lead to new imaging markers for disease progression and treatment.
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Affiliation(s)
- Nikkita Khattar
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Curtis Triebswetter
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Matthew Kiely
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States.
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Bouhrara M, Cortina LE, Khattar N, Rejimon AC, Ajamu S, Cezayirli DS, Spencer RG. Maturation and degeneration of the human brainstem across the adult lifespan. Aging (Albany NY) 2021; 13:14862-14891. [PMID: 34115614 PMCID: PMC8221341 DOI: 10.18632/aging.203183] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 05/20/2021] [Indexed: 04/12/2023]
Abstract
Brainstem tissue microstructural properties change across the adult lifespan. However, studies elucidating the biological processes that govern brainstem maturation and degeneration in-vivo are lacking. In the present work, conducted on a large cohort of 140 cognitively unimpaired subjects spanning a wide age range of 21 to 94 years, we implemented a multi-parameter approach to characterize the sex- and age differences. In addition, we examined regional correlations between myelin water fraction (MWF), a direct measure of myelin content, and diffusion tensor imaging indices, and transverse and longitudinal relaxation rates to evaluate whether these metrics provide information complementary to MWF. We observed region-dependent differences in myelin content and axonal density with age and found that both exhibit an inverted U-shape association with age in several brainstem substructures. We emphasize that the microstructural differences captured by our distinct MRI metrics, along with their weak associations with MWF, strongly indicate the potential of using these outcome measures in a multi-parametric approach. Furthermore, our results support the gain-predicts-loss hypothesis of tissue maturation and degeneration in the brainstem. Indeed, our results indicate that myelination follows a temporally symmetric time course across the adult life span, while axons appear to degenerate significantly more rapidly than they mature.
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Affiliation(s)
- Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Luis E. Cortina
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Nikkita Khattar
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Abinand C. Rejimon
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Samuel Ajamu
- Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Defne S. Cezayirli
- Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Richard G. Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
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Daugherty AM. Hypertension-related risk for dementia: A summary review with future directions. Semin Cell Dev Biol 2021; 116:82-89. [PMID: 33722505 DOI: 10.1016/j.semcdb.2021.03.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/01/2021] [Accepted: 03/06/2021] [Indexed: 02/07/2023]
Abstract
Chronic hypertension, or high blood pressure, is the most prevalent vascular risk factor that accelerates cognitive aging and increases risk for Alzheimer's disease and related dementia. Decades of observational and clinical trials have demonstrated that midlife hypertension is associated with greater gray matter atrophy, white matter damage commiserate with demyelination, and functional deficits as compared to normotension over the adult lifespan. Critically, hypertension is a modifiable dementia risk factor: successful blood pressure control with antihypertensive treatment improves outcomes as compared to uncontrolled hypertension, but does not completely negate the risk for dementia. This suggests that hypertension-related risk for neural and cognitive decline in aging cannot be due to elevations in blood pressure alone. This summary review describes three putative pathways for hypertension-related dementia risk: oxidative damage and metabolic dysfunction; systemic inflammation; and autonomic control of heart rate variability. The same processes contribute to pre-clinical hypertension, and therefore hypertension may be an early symptom of an aging nervous system that then exacerbates cumulative and progressive neurodegeneration. Current evidence is reviewed and future directions for research are outlined, including blood biomarkers and novel neuroimaging methods that may be sensitive to test the specific hypotheses.
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Affiliation(s)
- Ana M Daugherty
- Department of Psychology, Department of Psychiatry and Behavioral Neurosciences, Institute of Gerontology, Wayne State University, 5057 Woodward Ave., Detroit, MI, USA.
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Chen D, Huang Y, Shi Z, Li J, Zhang Y, Wang K, Smith AD, Gong Y, Gao Y. Demyelinating processes in aging and stroke in the central nervous system and the prospect of treatment strategy. CNS Neurosci Ther 2020; 26:1219-1229. [PMID: 33210839 PMCID: PMC7702227 DOI: 10.1111/cns.13497] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 10/26/2020] [Accepted: 10/26/2020] [Indexed: 12/12/2022] Open
Abstract
Demyelination occurs in response to brain injury and is observed in many neurodegenerative diseases. Myelin is synthesized from oligodendrocytes in the central nervous system, and oligodendrocyte death‐induced demyelination is one of the mechanisms involved in white matter damage after stroke and neurodegeneration. Oligodendrocyte precursor cells (OPCs) exist in the brain of normal adults, and their differentiation into mature oligodendrocytes play a central role in remyelination. Although the differentiation and maturity of OPCs drive endogenous efforts for remyelination, the failure of axons to remyelinate is still the biggest obstacle to brain repair after injury or diseases. In recent years, studies have made attempts to promote remyelination after brain injury and disease, but its cellular or molecular mechanism is not yet fully understood. In this review, we discuss recent studies examining the demyelination process and potential therapeutic strategies for remyelination in aging and stroke. Based on our current understanding of the cellular and molecular mechanisms underlying remyelination, we hypothesize that myelin and oligodendrocytes are viable therapeutic targets to mitigate brain injury and to treat demyelinating‐related neurodegeneration diseases.
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Affiliation(s)
- Di Chen
- Department of Critical Care Medicine and Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Yichen Huang
- Department of Critical Care Medicine and Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Ziyu Shi
- Department of Critical Care Medicine and Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Jiaying Li
- Department of Critical Care Medicine and Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Yue Zhang
- Department of Critical Care Medicine and Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Ke Wang
- Department of Critical Care Medicine and Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Amanda D Smith
- Geriatric Research, Education and Clinical Center, Veterans Affairs Pittsburgh Health Care System, Pittsburgh, PA, USA
| | - Ye Gong
- Department of Critical Care Medicine and Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Yanqin Gao
- Department of Critical Care Medicine and Neurosurgery of Huashan Hospital, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
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Wolfe T, Hoffman K, Hogan MK, Salazar B, Tang X, Chaboub L, Quini CC, Lu ZL, Horner PJ. Quantification of Myelinated Nerve Fraction and Degeneration in Spinal Cord Neuropil by SHIFT MRI. J Magn Reson Imaging 2020; 53:1162-1174. [PMID: 33098256 DOI: 10.1002/jmri.27397] [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: 06/05/2020] [Revised: 09/29/2020] [Accepted: 09/30/2020] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Neurodegeneration is a complex cellular process linked to prompt changes in myelin integrity and gradual neuron loss. Current imaging techniques offer estimations of myelin volumes in lesions/remyelinated areas but are limited to detect subtle injury. PURPOSE To investigate whether measurements detected by a signal hierarchically isolated as a function of time-to-echo (SHIFT) MRI technique can determine changes in myelin integrity and fiber axolemma. STUDY TYPE Prospective animal model. ANIMAL MODEL Surgically demyelinated spinal cord (SC) injury model in rodents (n = 6). FIELD STRENGTH/SEQUENCE Gradient-echo spin-echo at 3T. ASSESSMENT Multicompartment T2 relaxations were computed by SHIFT MRI in 75-microns-resolution images of the SC injury penumbra region 2 weeks post-trauma. G-ratio and axolemma delamination were assessed by transmission electron microscopy (TEM) in intact and injured samples. SC myelinated nerve fraction was computed by SHIFT MRI prospectively and assessed histologically. STATISTICAL TESTS Relations between SHIFT-isolated T2 -components and TEM measurements were studied using linear regression and t-tests. Pearson's correlation and significance were computed to determine the SHIFT's sensitivity to detect myelinated fibers ratio in gray matter. Regularized least-squares-based ranking analysis was employed to determine SHIFT MRI's ability to discern intact and injured myelinated nerves. RESULTS Biexponential signals isolated by SHIFT MRI for intact vs. lesion penumbra exhibited changes in T2 , shifting from intermediate components (25 ± 2 msec) to long (43 ± 11 msec) in white matter, and similarly in gray matter regions-of-interest (31 ± 2 to 46 ± 16 msec). These changes correlated highly with TEM g-ratio and axon delamination measurements (P < 0.05). Changes in short T2 components were observed but not statistically significant (8.5 ± 0.5 to 7 ± 3 msec, P = 0.445, and 4.0 ± 0.9 to 7 ± 3 msec, P = 0.075, respectively). SHIFT MRI's ability to detect myelinated fibers within gray matter was confirmed (P < 0.001). DATA CONCLUSION Changes detected by SHIFT MRI are associated with abnormal intermembrane spaces formed upon mild injury, directly correlated with early neuro integrity loss. Level of Evidence 1 Technical Efficacy Stage 2.
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Affiliation(s)
- Tatiana Wolfe
- Center for Neuroregneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas, USA
| | - Kristopher Hoffman
- Center for Neuroregneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas, USA
| | - Matthew K Hogan
- Center for Neuroregneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas, USA
| | - Betsy Salazar
- Center for Neuroregneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas, USA
| | - Xiufeng Tang
- Center for Neuroregneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas, USA
| | - Lesley Chaboub
- Center for Neuroregneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas, USA
| | - Caio C Quini
- Department of Biological Physics, Universidade Estadual Paulista UNESP, Botucatu, Sao Paulo, Brazil
| | - Zhong-Lin Lu
- Division of Arts and Sciences, NYU Shanghai, Shanghai, China, NYU-ECNU Institute of Cognitive Neuroscience at NYU Shanghai, Shanghai, China, Center for Neural Science and Department of Psychology, New York University, New York, USA
| | - Philip J Horner
- Center for Neuroregneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston Methodist Hospital, Houston, Texas, USA
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Lynn JD, Anand C, Arshad M, Homayouni R, Rosenberg DR, Ofen N, Raz N, Stanley JA. Microstructure of Human Corpus Callosum across the Lifespan: Regional Variations in Axon Caliber, Density, and Myelin Content. Cereb Cortex 2020; 31:1032-1045. [PMID: 32995843 DOI: 10.1093/cercor/bhaa272] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 08/21/2020] [Accepted: 08/21/2020] [Indexed: 12/13/2022] Open
Abstract
The myeloarchitecture of the corpus callosum (CC) is characterized as a mosaic of distinct differences in fiber density of small- and large-diameter axons along the anterior-posterior axis; however, regional and age differences across the lifespan are not fully understood. Using multiecho T2 magnetic resonance imaging combined with multi-T2 fitting, the myelin water fraction (MWF) and geometric-mean of the intra-/extracellular water T2 (geomT2IEW) in 395 individuals (7-85 years; 41% males) were examined. The approach was validated where regional patterns along the CC closely resembled the histology; MWF matched mean axon diameter and geomT2IEW mirrored the density of large-caliber axons. Across the lifespan, MWF exhibited a quadratic association with age in all 10 CC regions with evidence of a positive linear MWF-age relationship among younger participants and minimal age differences in the remainder of the lifespan. Regarding geomT2IEW, a significant linear age × region interaction reflected positive linear age dependence mostly prominent in the regions with the highest density of small-caliber fibers-genu and splenium. In all, these two indicators characterize distinct attributes that are consistent with histology, which is a first. In addition, these results conform to rapid developmental progression of CC myelination leveling in middle age as well as age-related degradation of axon sheaths in older adults.
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Affiliation(s)
- Jonathan D Lynn
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
| | - Chaitali Anand
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
| | - Muzamil Arshad
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
| | - Roya Homayouni
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
- Department of Psychology, Wayne State University, Detroit MI 48201, USA
| | - David R Rosenberg
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
| | - Noa Ofen
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
- Department of Psychology, Wayne State University, Detroit MI 48201, USA
- Lifespan Cognitive Neuroscience, Merrill Palmer Skillman Institute, Wayne State University, Detroit MI 14195, USA
| | - Naftali Raz
- Institute of Gerontology, Wayne State University, Detroit MI 48202, USA
- Department of Psychology, Wayne State University, Detroit MI 48201, USA
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin 14195, Germany
| | - Jeffrey A Stanley
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit MI 48201, USA
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