Multimodal Magnetic Resonance Imaging Assessment of White Matter Aging Trajectories Over the Lifespan of Healthy Individuals
Postmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and...
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| Published in | Biological psychiatry (1969) Vol. 72; no. 12; pp. 1026 - 1034 |
|---|---|
| Main Authors | , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
Elsevier Inc
15.12.2012
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0006-3223 1873-2402 1873-2402 |
| DOI | 10.1016/j.biopsych.2012.07.010 |
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| Abstract | Postmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and degeneration/repair trajectories of white matter (WM) microstructure biomarkers.
Healthy subjects (n = 171) 14–93 years of age were examined with transverse relaxation rate (R2) and four diffusion tensor imaging measures (fractional anisotropy [FA] and radial, axial, and mean diffusivity [RD, AxD, MD, respectively]) of frontal lobe, genu, and splenium of the corpus callosum WM (FWM, GWM, and SWM, respectively).
Only R2 reflected known levels of myelin content with high values in late-myelinating FWM and GWM regions and low ones in early-myelinating SWM. In FWM and GWM, all metrics except FA had significant quadratic components that peaked at different ages (R2 < RD < MD < AxD), with FWM peaking later than GWM. Factor analysis revealed that, although they defined different factors, R2 and RD were the metrics most closely associated with each other and differed from AxD, which entered into a third factor.
The R2 and RD trajectories were most dynamic in late-myelinating regions and reflect age-related differences in myelination, whereas AxD reflects axonal size and extra-axonal space. The FA and MD had limited specificity. The data suggest that the healthy adult brain undergoes continual change driven by development and repair processes devoted to creating and maintaining synchronous function among neural networks on which optimal cognition and behavior depend. |
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| AbstractList | Postmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and degeneration/repair trajectories of white matter (WM) microstructure biomarkers.
Healthy subjects (n = 171) 14-93 years of age were examined with transverse relaxation rate (R(2)) and four diffusion tensor imaging measures (fractional anisotropy [FA] and radial, axial, and mean diffusivity [RD, AxD, MD, respectively]) of frontal lobe, genu, and splenium of the corpus callosum WM (FWM, GWM, and SWM, respectively).
Only R(2) reflected known levels of myelin content with high values in late-myelinating FWM and GWM regions and low ones in early-myelinating SWM. In FWM and GWM, all metrics except FA had significant quadratic components that peaked at different ages (R(2) < RD < MD < AxD), with FWM peaking later than GWM. Factor analysis revealed that, although they defined different factors, R(2) and RD were the metrics most closely associated with each other and differed from AxD, which entered into a third factor.
The R(2) and RD trajectories were most dynamic in late-myelinating regions and reflect age-related differences in myelination, whereas AxD reflects axonal size and extra-axonal space. The FA and MD had limited specificity. The data suggest that the healthy adult brain undergoes continual change driven by development and repair processes devoted to creating and maintaining synchronous function among neural networks on which optimal cognition and behavior depend. Postmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and degeneration/repair trajectories of white matter (WM) microstructure biomarkers. Healthy subjects (n = 171) 14–93 years of age were examined with transverse relaxation rate (R2) and four diffusion tensor imaging measures (fractional anisotropy [FA] and radial, axial, and mean diffusivity [RD, AxD, MD, respectively]) of frontal lobe, genu, and splenium of the corpus callosum WM (FWM, GWM, and SWM, respectively). Only R2 reflected known levels of myelin content with high values in late-myelinating FWM and GWM regions and low ones in early-myelinating SWM. In FWM and GWM, all metrics except FA had significant quadratic components that peaked at different ages (R2 < RD < MD < AxD), with FWM peaking later than GWM. Factor analysis revealed that, although they defined different factors, R2 and RD were the metrics most closely associated with each other and differed from AxD, which entered into a third factor. The R2 and RD trajectories were most dynamic in late-myelinating regions and reflect age-related differences in myelination, whereas AxD reflects axonal size and extra-axonal space. The FA and MD had limited specificity. The data suggest that the healthy adult brain undergoes continual change driven by development and repair processes devoted to creating and maintaining synchronous function among neural networks on which optimal cognition and behavior depend. BackgroundPostmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and degeneration/repair trajectories of white matter (WM) microstructure biomarkers. MethodsHealthy subjects ( n = 171) 14–93 years of age were examined with transverse relaxation rate (R 2) and four diffusion tensor imaging measures (fractional anisotropy [FA] and radial, axial, and mean diffusivity [RD, AxD, MD, respectively]) of frontal lobe, genu, and splenium of the corpus callosum WM (FWM, GWM, and SWM, respectively). ResultsOnly R 2 reflected known levels of myelin content with high values in late-myelinating FWM and GWM regions and low ones in early-myelinating SWM. In FWM and GWM, all metrics except FA had significant quadratic components that peaked at different ages (R 2 < RD < MD < AxD), with FWM peaking later than GWM. Factor analysis revealed that, although they defined different factors, R 2 and RD were the metrics most closely associated with each other and differed from AxD, which entered into a third factor. ConclusionsThe R 2 and RD trajectories were most dynamic in late-myelinating regions and reflect age-related differences in myelination, whereas AxD reflects axonal size and extra-axonal space. The FA and MD had limited specificity. The data suggest that the healthy adult brain undergoes continual change driven by development and repair processes devoted to creating and maintaining synchronous function among neural networks on which optimal cognition and behavior depend. Postmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and degeneration/repair trajectories of white matter (WM) microstructure biomarkers.BACKGROUNDPostmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in middle age. We examined whether known regional differences in axon size and age at myelination influence the timing and rates of development and degeneration/repair trajectories of white matter (WM) microstructure biomarkers.Healthy subjects (n = 171) 14-93 years of age were examined with transverse relaxation rate (R(2)) and four diffusion tensor imaging measures (fractional anisotropy [FA] and radial, axial, and mean diffusivity [RD, AxD, MD, respectively]) of frontal lobe, genu, and splenium of the corpus callosum WM (FWM, GWM, and SWM, respectively).METHODSHealthy subjects (n = 171) 14-93 years of age were examined with transverse relaxation rate (R(2)) and four diffusion tensor imaging measures (fractional anisotropy [FA] and radial, axial, and mean diffusivity [RD, AxD, MD, respectively]) of frontal lobe, genu, and splenium of the corpus callosum WM (FWM, GWM, and SWM, respectively).Only R(2) reflected known levels of myelin content with high values in late-myelinating FWM and GWM regions and low ones in early-myelinating SWM. In FWM and GWM, all metrics except FA had significant quadratic components that peaked at different ages (R(2) < RD < MD < AxD), with FWM peaking later than GWM. Factor analysis revealed that, although they defined different factors, R(2) and RD were the metrics most closely associated with each other and differed from AxD, which entered into a third factor.RESULTSOnly R(2) reflected known levels of myelin content with high values in late-myelinating FWM and GWM regions and low ones in early-myelinating SWM. In FWM and GWM, all metrics except FA had significant quadratic components that peaked at different ages (R(2) < RD < MD < AxD), with FWM peaking later than GWM. Factor analysis revealed that, although they defined different factors, R(2) and RD were the metrics most closely associated with each other and differed from AxD, which entered into a third factor.The R(2) and RD trajectories were most dynamic in late-myelinating regions and reflect age-related differences in myelination, whereas AxD reflects axonal size and extra-axonal space. The FA and MD had limited specificity. The data suggest that the healthy adult brain undergoes continual change driven by development and repair processes devoted to creating and maintaining synchronous function among neural networks on which optimal cognition and behavior depend.CONCLUSIONSThe R(2) and RD trajectories were most dynamic in late-myelinating regions and reflect age-related differences in myelination, whereas AxD reflects axonal size and extra-axonal space. The FA and MD had limited specificity. The data suggest that the healthy adult brain undergoes continual change driven by development and repair processes devoted to creating and maintaining synchronous function among neural networks on which optimal cognition and behavior depend. |
| Author | Couvrette, Alexander Bartzokis, George Mintz, Jim Lu, Po H. Lee, Grace J. Finn, J. Paul Altshuler, Lori L. Heydari, Panthea Freeman, Frank Villablanca, Pablo Kalashyan, Greta Grinstead, John W. Alger, Jeffry R. |
| Author_xml | – sequence: 1 givenname: George surname: Bartzokis fullname: Bartzokis, George email: gbar@ucla.edu organization: Department of Psychiatry, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 2 givenname: Po H. surname: Lu fullname: Lu, Po H. organization: Department of Neurology, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 3 givenname: Panthea surname: Heydari fullname: Heydari, Panthea organization: Department of Psychiatry, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 4 givenname: Alexander surname: Couvrette fullname: Couvrette, Alexander organization: Department of Psychiatry, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 5 givenname: Grace J. surname: Lee fullname: Lee, Grace J. organization: Department of Neurology, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 6 givenname: Greta surname: Kalashyan fullname: Kalashyan, Greta organization: Department of Psychiatry, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 7 givenname: Frank surname: Freeman fullname: Freeman, Frank organization: Department of Psychiatry, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 8 givenname: John W. surname: Grinstead fullname: Grinstead, John W. organization: Siemens Healthcare, Portland, Oregon – sequence: 9 givenname: Pablo surname: Villablanca fullname: Villablanca, Pablo organization: Department of Radiology, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 10 givenname: J. Paul surname: Finn fullname: Finn, J. Paul organization: Department of Radiology, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 11 givenname: Jim surname: Mintz fullname: Mintz, Jim organization: University of Texas Health Science Center at San Antonio, Department of Epidemiology and Biostatistics, San Antonio, Texas – sequence: 12 givenname: Jeffry R. surname: Alger fullname: Alger, Jeffry R. organization: Department of Neurology, The David Geffen School of Medicine at UCLA, Los Angeles, California – sequence: 13 givenname: Lori L. surname: Altshuler fullname: Altshuler, Lori L. organization: Department of Psychiatry, The David Geffen School of Medicine at UCLA, Los Angeles, California |
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| Copyright | 2012 Society of Biological Psychiatry Society of Biological Psychiatry 2015 INIST-CNRS Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved. |
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| Keywords | myelin development cognition radial diffusivity oligodendrocytes Alzheimer degeneration magnetic resonance imaging (MRI) Aging fractional anisotropy diffusion tensor imaging (DTI) axial diffusivity relaxation rate (R2) white matter (WM) relaxation rate (R 2) Senescence Alzheimer disease Neuroglia Multimodal imaging Cognition Relaxation Oligodendrocyte Development Degenerative disease Degeneration Evaluation Nervous system diseases Healthy subject Myelin ) Nuclear magnetic resonance imaging White matter Cerebral disorder Diffusion tensor imaging Treatment Anisotropy Central nervous system disease Medical imagery relaxation rate (R |
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| Snippet | Postmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions, peaks in... BackgroundPostmortem and volumetric imaging data suggest that brain myelination is a dynamic lifelong process that, in vulnerable late-myelinating regions,... |
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| SubjectTerms | Adolescent Adult Adult and adolescent clinical studies Aged Aged, 80 and over Aging Aging - physiology Alzheimer Anisotropy axial diffusivity Axons - ultrastructure Biological and medical sciences Biomarkers Brain - anatomy & histology Brain - growth & development Cerebral Cortex - anatomy & histology Cerebral Cortex - growth & development cognition degeneration Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases development diffusion tensor imaging (DTI) Diffusion Tensor Imaging - methods Echo-Planar Imaging Female fractional anisotropy Humans Image Processing, Computer-Assisted magnetic resonance imaging (MRI) Male Medical sciences Middle Aged myelin Myelin Sheath - physiology Nerve Degeneration - pathology Nerve Fibers - ultrastructure Neurology oligodendrocytes Oligodendroglia - physiology Organic mental disorders. Neuropsychology Psychiatric/Mental Health Psychology. Psychoanalysis. Psychiatry Psychopathology. Psychiatry radial diffusivity Reference Values Regression Analysis relaxation rate (R2) Relaxation. Biofeedback. Hypnosis. Selfregulation. Meditation Sex Characteristics Treatments white matter (WM) Young Adult |
| Title | Multimodal Magnetic Resonance Imaging Assessment of White Matter Aging Trajectories Over the Lifespan of Healthy Individuals |
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