Accelerated longitudinal gray/white matter contrast decline in aging in lightly myelinated cortical regions

Abstract

Highly myelinated cortical regions seem to develop early and are more robust to age-related decline. By use of different magnetic resonance imaging (MRI) measures such as contrast between T1- and T2-weighted MRI scans (T1w/T2w) it is now possible to assess correlates of myelin content in vivo. Further, previous studies indicate that gray/white matter contrast (GWC) become blurred as individuals' age, apparently reflecting age-related changes in myelin structure. Here we address whether longitudinal changes in GWC are dependent on initial myelin content within tissue as defined by baseline T1w/T2w contrast, and hypothesize that lightly myelinated regions undergo more decline longitudinally. A sample of 207 healthy adult participants (range: 20-84 years) was scanned twice (interscan interval: 3.6 years). Results showed widespread longitudinal reductions of GWC throughout the cortical surface, especially in the frontal cortices, mainly driven by intensity decay in the white matter. Annual rate of GWC blurring showed acceleration with age in temporal and medial prefrontal regions. Moreover, the anatomical distribution of increased rate of GWC decline with advancing age was strongly related to baseline levels of intracortical myelin. This study provides a first evidence of accelerated regional GWC blurring with advancing age, relates GWC patterns to cortical myeloarchitectonics and supports the hypothesis of increased age-related vulnerability of lightly myelinated areas. Hum Brain Mapp 37:3669-3684, 2016. © 2016 Wiley Periodicals, Inc.

Modeling white matter tract integrity in aging with diffusional kurtosis imaging

“…These are intriguing preliminary findings that warrant replication. It is also important to note that the observation of preferential degeneration of late-myelinating regions may be specific to intracortical or juxtacortical myelin (Phillips et al, 2016; Vidal-Piñeiro et al, 2016), rather than to the large fiber bundles on which this paper is focused.…”

Development of the Cerebral Cortex across Adolescence: A Multisample Study of Inter-Related Longitudinal Changes in Cortical Volume, Surface Area, and Thickness

“…First, spaghetti plots and longitudinal curve fitting were performed using the Multimodal Imaging Laboratory data portal (Bartsch et al, 2014; Vidal-Pineiro et al, 2016), which uses functions freely available through the statistical environment R (http://www.r-project.org/, RRID:SCR_001905). Cortical volume, surface area, and thickness measures from each time point, adjusted for the effect of sex, were introduced as predicted variables in generalized additive mixed model (GAMM) analyses where the predictor was age, with k parameters specifying the stiffness of the model curves set to five (except for temporal lobe volume where four was used so the models would converge).…”

Joint contributions of cortical morphometry and white matter microstructure in healthy brain aging: A partial least squares correlation analysis

“…Specificity in this coupled aging include proposed leadlag relationships such that cortical thinning via cell body damage leads to axonal alteration and decreased WM health (e.g., Wallerian degeneration), or that decreased axonal health propagates from the axon to produce alterations in the cell body (e.g., transneuronal atrophy) (Kochunov et al, 2011;Storsve et al, 2016). Univariate correlational analyses revealed associations between aging trajectories of cortical morphometry and indices of WM health (such as fractional anisotropy (FA), which is sensitive to the directionality of water flow, or mean diffusivity (MD), which measures the overall rate of diffusion) (Kochunov et al, 2011;Storsve et al, 2016) and the underlying intracortical myelin (He, Chen, & Evans, 2007;Vidal-Pineiro et al, 2016). Univariate correlational analyses revealed associations between aging trajectories of cortical morphometry and indices of WM health (such as fractional anisotropy (FA), which is sensitive to the directionality of water flow, or mean diffusivity (MD), which measures the overall rate of diffusion) (Kochunov et al, 2011;Storsve et al, 2016) and the underlying intracortical myelin (He, Chen, & Evans, 2007;Vidal-Pineiro et al, 2016).…”

“…Given this GM-WM dependency, studies have begun to incorporate the idea of coupled age-differences (Brickman, Habeck, Zarahn, Flynn, & Stern, 2007) and coupled decline (Brickman et al, 2007;Raz et al, 2005). Univariate correlational analyses revealed associations between aging trajectories of cortical morphometry and indices of WM health (such as fractional anisotropy (FA), which is sensitive to the directionality of water flow, or mean diffusivity (MD), which measures the overall rate of diffusion) (Kochunov et al, 2011;Storsve et al, 2016) and the underlying intracortical myelin (He, Chen, & Evans, 2007;Vidal-Pineiro et al, 2016). Additionally, multivariate frameworks can be utilized to make accurate predictions of age when accounting for age-related patterns of covariance among multiple tissue types (Groves et al, 2012).…”