Accelerated Changes in White Matter Microstructure during Aging: A Longitudinal Diffusion Tensor Imaging Study

It is well established that human brain white matter structure changes with aging, but the timescale and spatial distribution of this change remain uncertain. Cross-sectional diffusion tensor imaging (DTI) studies indicate that, after a period of relative stability during adulthood, there is an accelerated decline in anisotropy and increase in diffusivity values during senescence; and, spatially, results have been discussed within the context of several anatomical frameworks. However, inferring trajectories of change from cross-sectional data can be challenging; and, as yet, there have been no longitudinal reports of the timescale and spatial distribution of age-related white matter change in healthy adults across the adult lifespan. In a longitudinal DTI study of 203 adults between 20 and 84 years of age, we used tract-based spatial statistics to characterize the pattern of annual change in fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity and examined whether there was an acceleration of change with age. We found extensive and overlapping significant annual decreases in fractional anisotropy, and increases in axial diffusivity, radial diffusivity, and mean diffusivity. Spatially, results were consistent with inferior-to-superior gradients of lesser-to-greater vulnerability. Annual change increased with age, particularly within superior regions, with age-related decline estimated to begin in the fifth decade. Charting white matter microstructural changes in healthy aging provides essential context to clinical studies, and future studies should compare age trajectories between healthy participants and at-risk populations and also explore the relationship between DTI rates of change and cognitive decline.

[1]  T. Salthouse Selectivity of attrition in longitudinal studies of cognitive functioning. , 2014, The journals of gerontology. Series B, Psychological sciences and social sciences.

[2]  John O. Willis,et al.  Wechsler Abbreviated Scale of Intelligence , 2014 .

[3]  Paolo Fusar-Poli,et al.  Tracking cerebral white matter changes across the lifespan: insights from diffusion tensor imaging studies , 2013, Journal of Neural Transmission.

[4]  G. Bartzokis,et al.  Multimodal Magnetic Resonance Imaging Assessment of White Matter Aging Trajectories Over the Lifespan of Healthy Individuals , 2012, Biological Psychiatry.

[5]  Bruce Fischl,et al.  Within-subject template estimation for unbiased longitudinal image analysis , 2012, NeuroImage.

[6]  L. Nyberg,et al.  Memory aging and brain maintenance , 2012, Trends in Cognitive Sciences.

[7]  C. Lebel,et al.  Diffusion tensor imaging of white matter tract evolution over the lifespan , 2012, NeuroImage.

[8]  D. Glahn,et al.  Fractional anisotropy of water diffusion in cerebral white matter across the lifespan , 2012, Neurobiology of Aging.

[9]  H. Hampel,et al.  Longitudinal changes of fractional anisotropy in Alzheimer’s disease patients treated with galantamine: a 12-month randomized, placebo-controlled, double-blinded study , 2012, European Archives of Psychiatry and Clinical Neuroscience.

[10]  David H. Salat,et al.  The Declining Infrastructure of the Aging Brain , 2011, Brain Connect..

[11]  L. Westlye,et al.  Associations between regional cortical thickness and attentional networks as measured by the attention network test. , 2011, Cerebral cortex.

[12]  John D. Van Horn,et al.  Quantitative in vivo evidence for broad regional gradients in the timing of white matter maturation during adolescence , 2011, NeuroImage.

[13]  Torsten Rohlfing,et al.  Fiber tracking functionally distinct components of the internal capsule , 2010, Neuropsychologia.

[14]  A. Dale,et al.  Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. , 2010, Cerebral cortex.

[15]  Anders M. Dale,et al.  Differentiating maturational and aging-related changes of the cerebral cortex by use of thickness and signal intensity , 2010, NeuroImage.

[16]  Thomas R. Barrick,et al.  White matter structural decline in normal ageing: A prospective longitudinal study using tract-based spatial statistics , 2010, NeuroImage.

[17]  Anders M. Dale,et al.  When does brain aging accelerate? Dangers of quadratic fits in cross-sectional studies , 2010, NeuroImage.

[18]  A. Pfefferbaum,et al.  Quantitative fiber tracking of lateral and interhemispheric white matter systems in normal aging: Relations to timed performance , 2010, Neurobiology of Aging.

[19]  Hauke R. Heekeren,et al.  Age-related differences in white matter microstructure: Region-specific patterns of diffusivity , 2010, NeuroImage.

[20]  J. H. Howard,et al.  Age‐related differences in multiple measures of white matter integrity: A diffusion tensor imaging study of healthy aging , 2009, Human brain mapping.

[21]  Bram Stieltjes,et al.  Longitudinal changes in fiber tract integrity in healthy aging and mild cognitive impairment: a DTI follow-up study. , 2010, Journal of Alzheimer's disease : JAD.

[22]  Roberto Cabeza,et al.  Assessing the effects of age on long white matter tracts using diffusion tensor tractography , 2009, NeuroImage.

[23]  Wiro J Niessen,et al.  White matter microstructural integrity and cognitive function in a general elderly population. , 2009, Archives of general psychiatry.

[24]  Stephen M. Smith,et al.  Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference , 2009, NeuroImage.

[25]  J. Mcardle Latent variable modeling of differences and changes with longitudinal data. , 2009, Annual review of psychology.

[26]  Jung-Lung Hsu,et al.  Gender differences and age-related white matter changes of the human brain: A diffusion tensor imaging study , 2008, NeuroImage.

[27]  M. Jenkinson Non-linear registration aka Spatial normalisation , 2007 .

[28]  N. Raz,et al.  Differential Aging of the Brain: Patterns, Cognitive Correlates and Modifiers , 2022 .

[29]  Daniel Rueckert,et al.  Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data , 2006, NeuroImage.

[30]  Peter Rodgers,et al.  Constructing Area-Proportional Venn and Euler Diagrams with Three Circles , 2005 .

[31]  K Warner Schaie,et al.  What Can We Learn From Longitudinal Studies of Adult Development? , 2005, Research in human development.

[32]  Schaie Kw,et al.  What Can We Learn From Longitudinal Studies of Adult Development , 2005 .

[33]  C. Brayne,et al.  A systematic literature review of attrition between waves in longitudinal studies in the elderly shows a consistent pattern of dropout between differing studies. , 2005, Journal of clinical epidemiology.

[34]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[35]  D. Head,et al.  Differential vulnerability of anterior white matter in nondemented aging with minimal acceleration in dementia of the Alzheimer type: evidence from diffusion tensor imaging. , 2004, Cerebral cortex.

[36]  G. Bartzokis Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease , 2004, Neurobiology of Aging.

[37]  V. Wedeen,et al.  Reduction of eddy‐current‐induced distortion in diffusion MRI using a twice‐refocused spin echo , 2003, Magnetic resonance in medicine.

[38]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[39]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[40]  Edith V. Sullivan,et al.  Equivalent disruption of regional white matter microstructure in ageing healthy men and women , 2001, Neuroreport.

[41]  A M Dale,et al.  Measuring the thickness of the human cerebral cortex from magnetic resonance images. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[42]  P. Greenwood,et al.  The frontal aging hypothesis evaluated , 2000, Journal of the International Neuropsychological Society.

[43]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[44]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[45]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[46]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.