Elsevier

NeuroImage

Volume 49, Issue 3, 1 February 2010, Pages 2104-2112
NeuroImage

Age-related differences in white matter microstructure: Region-specific patterns of diffusivity

https://doi.org/10.1016/j.neuroimage.2009.09.041Get rights and content

Abstract

We collected MRI diffusion tensor imaging data from 80 younger (20–32 years) and 63 older (60–71 years) healthy adults. Tract-based spatial statistics (TBSS) analysis revealed that white matter integrity, as indicated by decreased fractional anisotropy (FA), was disrupted in numerous structures in older compared to younger adults. These regions displayed five distinct region-specific patterns of age-related differences in other diffusivity properties: (1) increases in both radial and mean diffusivity; (2) increases in radial diffusivity; (3) no differences in parameters other than FA; (4) a decrease in axial and an increase in radial diffusivity; and (5) a decrease in axial and mean diffusivity. These patterns suggest different biological underpinnings of age-related decline in FA, such as demyelination, Wallerian degeneration, gliosis, and severe fiber loss, and may represent stages in a cascade of age-related degeneration in white matter microstructure. This first simultaneous description of age-related differences in FA, mean, axial, and radial diffusivity requires histological and functional validation as well as analyses of intermediate age groups and longitudinal samples.

Introduction

The human brain displays significant structural and functional changes across adulthood (Raz and Rodrigue, 2006). The volume of white matter (WM), as measured by in vivo magnetic resonance imaging (MRI), continues to increase until the fourth decade of life and is associated with ongoing myelination (Bartzokis, 2004, Courchesne et al., 2000, Ge et al., 2002, Giedd, 1999). The subsequent decrease in WM volume accelerates in late adulthood (Courchesne et al., 2000, Raz et al., 2005) and coincides with a smaller number and shorter length of myelinated fibers, myelin pallor, and axonal loss as shown in post-mortem histological studies (Aboitiz et al., 1996, Marner et al., 2003, Meier-Ruge et al., 1992, Tang and Nyengaard, 1997).

Due to limitations of histological studies (restricted possibility of sample selection, necessity of tissue fixation, and resulting artifacts), none of these previous studies addressed regional specificity of the aforementioned microstructural alterations in aging. In contrast, in vivo structural MRI studies allow identifying regional differences in WM volume loss. They do, however, not provide much insight into the mechanisms responsible for these aging-related WM changes. In this study, we therefore employed diffusion tensor imaging (DTI), which combines some of the benefits of both histological and volumetric approaches in studying WM.

By quantifying the magnitude and directionality of diffusion of water within a tissue, DTI allows inferences about WM microstructure in vivo (Pierpaoli and Basser, 1996, Pierpaoli et al., 1996). Investigating DTI-derived parameters may help to elucidate the mechanisms underlying age-related WM changes because different parameters reflect distinct aspects of WM microstructure. The eigenvalues of the diffusion tensor are obtained through diffusion tensor diagonalization (Basser and Pierpaoli, 1996, Basser and Pierpaoli, 1998, Pierpaoli and Basser, 1996). The first eigenvalue is referred to as axial diffusivity (AD, diffusion parallel to the axon fibers; Basser, 1995, Song et al., 2002), whereas the average of the second and third eigenvalues is termed radial diffusivity (RD, diffusivity perpendicular to the axonal fibers; Basser, 1995, Song et al., 2002). Lowered AD reflects axon injury both in ischemic (Song et al., 2003, Song et al., 2005) and chemically induced (Sun et al., 2006) WM lesions. Increases in RD have been linked to incomplete myelination in shiverer mice (Song et al., 2002), drug-induced demyelination (Song et al., 2005), and loss of myelin following axon injury (Song et al., 2003, Song et al., 2005). Fractional anisotropy (FA), a measure of the directional dependence of diffusion (Basser, 1995), reflects fiber density and coherence within a voxel (Beaulieu, 2002). FA values range between 0 (isotropic diffusion) and 1 (perfectly anisotropic diffusion). Lowered FA has been observed in various conditions in which loss of fiber integrity occurs (Beaulieu, 2002), such as multiple sclerosis (Rovaris et al., 2005) and Alzheimer's disease (Medina et al., 2006). Mean diffusivity (MD) is a mean of all three eigenvalues of the diffusion tensor and reflects the magnitude of water diffusion within a voxel, which depends on the density of physical obstructions such as membranes and the distribution of water molecules between different cellular compartments (Beaulieu, 2002, Sen and Basser, 2005). Increased MD was observed in conditions of reduced membrane density (Sen and Basser, 2005) such as tissue degeneration after injury (Beaulieu, 2002, Beaulieu et al., 1996, Concha et al., 2006). Thus, comparing the values of FA, MD, RD, and AD between younger and older adults allows inferring potential age-related microstructural mechanisms underlying the observed differences in diffusivity properties.

WM diffusivity changes in late adulthood—FA decreases and MD increases (Minati et al., 2007)—likely reflect microstructural alterations such as an increase in brain water content, demyelination, disruption of axon structure, and overall rarefaction of fibers (Minati et al., 2007). To obtain a comprehensive picture of differences in different elements of WM microstructure, however, it is necessary to consider conjointly all measures derived from the diffusion tensor (Assaf and Pasternak, 2008). This has not been done systematically in previous research; few studies have reported eigenvalues for selected WM structures (Abe et al., 2002, Bhagat and Beaulieu, 2004, Hsu et al., 2008, Ota et al., 2006, Stadlbauer et al., 2008, Sullivan et al., 2006b), and only one tractography-based study reported the values of MD, RD, and AD for all main cerebral WM tracts in adults between 20 and 81 years of age (Sullivan et al., in press). The diffusivities were, however, not analyzed conjointly and studying a mean value for the whole tract does not use the localized information of diffusivity properties obtained for each voxel given that the age effect on diffusivity properties may not be uniform along a WM tract.

Investigating the direct relationship between age effects on different diffusivity parameters could provide more insight into the mechanisms of WM aging. Zhang et al. (in press) identified WM regions with simultaneous age-related variations in FA and MD, as well as regions showing FA differences without a significant MD difference and vice versa. In a separate analysis, they showed that age-related increases in RD were of greater magnitude than the corresponding increases in AD (Zhang et al., in press). Still, the direct relationship between these four DTI measures remains to be evaluated. Due to the lack of simultaneous analysis of FA, RD, and AD, Zhang's conclusion that increased RD mostly explains the FA reductions is not justified. By analyzing RD and AD separately from FA and MD it is also impossible to distinguish between diffusivity patterns characteristic of Wallerian degeneration (FA and AD decrease, RD increase and no net difference in MD, Pierpaoli et al., 2001) and patterns characteristic of other mechanisms (FA decrease and no difference in other diffusivities).

Zhang et al. (in press) applied voxel-based morphometry (VBM) analysis, an approach originally designed for assessing changes in grey matter density. This approach includes smoothing of the diffusivity maps, a step that is generally not recommended for DTI data (Jones et al., 2005). In addition, this approach does not allow precise tract-related localization of the observations. Tract-based spatial statistics (TBSS; Smith et al., 2006) is an alternative approach for analyzing differences in WM. TBSS brings together the strengths of whole-brain VBM methods and localized region-of-interest (ROI) analyses. TBSS circumvents the problem of cross-subject alignment and contamination due to differences in brain morphology by sampling the center-of-tract voxel value in individual space. It, therefore, enables reliable detection of localized differences in diffusivity parameters in all major WM tracts without the necessity of smoothing (Smith et al., 2006). The applicability of TBSS to aging studies has been demonstrated in two recent studies. In a study comparing 8 younger and 22 older participants, Damoiseaux et al. (2009) reported age-related FA decreases in the frontal, parietal, and temporal lobes, corpus callosum, and the internal capsule. In a large sample of adults above the age of 60 (n = 832), Vernooij et al. (2008) examined the relationships between DTI parameters and macrostructural differences, such as overall brain atrophy and lesion volumes.

In this study, we investigated differences in WM diffusivity properties between healthy adults in their third and seventh decade of life. Specifically, we addressed the following questions: What is the voxelwise pattern of simultaneous differences in FA, MD, AD, and RD in the whole WM from early to late adulthood? Are the patterns of age-related differences in diffusivity parameters not only region- but also tract-specific? What is the neurobiological meaning of these patterns and are they meaningful in view of extant histological knowledge?

We analyzed FA, MD, RD, and AD in all major WM tracts of the cerebrum using TBSS. Next, we investigated, on the voxel level, the spatial distribution of age-related differences in AD, RD, and MD within those regions showing age-related FA decreases. This approach allows for a more specific interpretation of age-related decreases in FA as opposed to considering FA and MD or AD and RD alone. We hypothesized that WM tracts and their subregions would differ with respect to age-related differences in diffusivity properties. For instance, we predicted that in the regions most susceptible to aging, such as the frontal lobes, irreversible loss of myelinated fibers would result in a decrease in FA and a general increase in diffusivity. In other regions, axonal injury may result in a decrease in AD and demyelination may cause an increase in RD. In some regions, age effects may be represented mainly by glial infiltration resulting in lowered FA and MD. Taken together, the analysis of region-specific patterns in diffusivity properties may reveal spatial specificity of differential age-related differences in WM microstructure.

Section snippets

Participants

The participants were 80 younger adults (35 women) between 20 and 32 years of age (M = 25.7 ± 3.2) and 63 older adults (29 women) between 60 and 71 years of age (M = 64.8 ± 2.9), all of whom had at least 8 years of education, were right-handed, and had no history of psychiatric or neurological disease. For 58 of 63 older adults, we had information about their vascular risk factors: 25 (43%) reported arterial hypertension (defined as blood pressure constantly above 140/90 mm Hg), 11 of the 25

Age-related differences in FA

For both younger and older adults, FA values differed among brain regions. For more details on regional specificity of FA values on the TBSS skeleton, see Supplementary Materials.

We performed voxelwise comparison of age-related differences in FA values between younger and older adults. FA was lower in older than in younger adults (p < 0.01) in numerous WM regions, which included: the anterior, superior and posterior corona radiata, WM of the superior, inferior, middle, frontal and straight gyri,

Discussion

The aim of this study was to investigate the whole-brain pattern of age-related differences in all diffusivity parameters and to explore their regional specificity. For the analysis of FA, MD, RD, and AD values, we used TBSS, which accounts for morphological differences that can be observed between healthy adults in the third and seventh decade of life. In addition to the previously reported anteroposterior gradient of age-related FA decrease in the corpus callosum (Head et al., 2004, Salat et

Acknowledgments

This research was supported by the Innovation Fund of the Max Planck Society (M.FE.A.BILD0005) and the German Federal Ministry for Research to the Berlin NeuroImaging Center (01GO0501), the Swedish Research Council (521-2007-2892 to L.B.), and Swedish Brain Power (to L.B.). A.Z.B. received a predoctoral fellowship from the International Max Planck Research School, The Life Course: Evolutionary and Ontogenetic Dynamics (LIFE).

The authors thank Nils Bodammer for valuable comments, and Peter

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