TY - JOUR
T1 - Multimodal magnetic resonance imaging assessment of white matter aging trajectories over the lifespan of healthy individuals
AU - Bartzokis, George
AU - Lu, Po H.
AU - Heydari, Panthea
AU - Couvrette, Alexander
AU - Lee, Grace J.
AU - Kalashyan, Greta
AU - Freeman, Frank
AU - Grinstead, John W.
AU - Villablanca, Pablo
AU - Finn, J. Paul
AU - Mintz, Jim
AU - Alger, Jeffry R.
AU - Altshuler, Lori L.
N1 - Funding Information:
This work was supported in part by National Institutes of Health Grants MH0266029 , AG027342 , and K23-AG028727 ; Risk Control Strategies Inc. Alzheimer's Foundation; and the Department of Veterans Affairs. These funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, and approval of the manuscript. George Bartzokis, Po H. Lu, and Jim Mintz had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
PY - 2012/12/15
Y1 - 2012/12/15
N2 - Background: 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. Methods: 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). Results: 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 (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. Conclusions: 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.
AB - Background: 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. Methods: 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). Results: 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 (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. Conclusions: 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.
KW - Aging
KW - Alzheimer
KW - axial diffusivity
KW - cognition
KW - degeneration
KW - development
KW - diffusion tensor imaging (DTI)
KW - fractional anisotropy
KW - magnetic resonance imaging (MRI)
KW - myelin
KW - oligodendrocytes
KW - radial diffusivity
KW - relaxation rate (R )
KW - white matter (WM)
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U2 - 10.1016/j.biopsych.2012.07.010
DO - 10.1016/j.biopsych.2012.07.010
M3 - Article
C2 - 23017471
SN - 0006-3223
VL - 72
SP - 1026
EP - 1034
JO - Biological Psychiatry
JF - Biological Psychiatry
IS - 12
ER -