Accelerating cortical thinning: unique to dementia or universal in aging? - PubMed (original) (raw)

Accelerating cortical thinning: unique to dementia or universal in aging?

Anders M Fjell et al. Cereb Cortex. 2014 Apr.

Abstract

Does accelerated cortical atrophy in aging, especially in areas vulnerable to early Alzheimer's disease (AD), unequivocally signify neurodegenerative disease or can it be part of normal aging? We addressed this in 3 ways. First, age trajectories of cortical thickness were delineated cross-sectionally (n = 1100) and longitudinally (n = 207). Second, effects of undetected AD on the age trajectories were simulated by mixing the sample with a sample of patients with very mild to moderate AD. Third, atrophy in AD-vulnerable regions was examined in older adults with very low probability of incipient AD based on 2-year neuropsychological stability, CSF Aβ(1-42) levels, and apolipoprotein ε4 negativity. Steady decline was seen in most regions, but accelerated cortical thinning in entorhinal cortex was observed across groups. Very low-risk older adults had longitudinal entorhinal atrophy rates similar to other healthy older adults, and this atrophy was predictive of memory change. While steady decline in cortical thickness is the norm in aging, acceleration in AD-prone regions does not uniquely signify neurodegenerative illness but can be part of healthy aging. The relationship between the entorhinal changes and changes in memory performance suggests that non-AD mechanisms in AD-prone areas may still be causative for cognitive reductions.

Keywords: Alzheimer's disease; aging; atrophy; cortical thickness; magnetic resonance imaging.

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Figures

Figure 1.

Figure 1.

Age correlations. Correlations between age and cortical thickness at each vertex in each of the 5 subsamples, as well as in the total sample. The correlations in the total sample are corrected for both offset and slope differences between the subsamples. As can be seen, strong negative correlations are found in all subsamples, being especially strong in medial and lateral frontal cortex. The maps are smoothed with a Gaussian kernel of full-with at half-maximum (FWHM) of 30 mm.

Figure 2.

Figure 2.

Nonlinear lifespan trajectories. The figure show the individual cross-sectional data points and the estimated trajectories for cortical thickness in the 9 cortical regions of interest (ROI) that deviated the most from linearity. Values represent standardized mean thickness across hemispheres, corrected for the influence of sample (_Z_-scores), and the ROIs are displayed on a semi-inflated template brain surface.

Figure 3.

Figure 3.

Linear lifespan trajectories. The figure shows the individual data points and the cross-sectionally estimated trajectories for cortical thickness in 9 representative cortical regions of interest (ROI) where a linear fit was the most appropriate. Values represent mean thickness across hemispheres, corrected for the influence of sample (_Z_-scores), and the ROIs are displayed on a semi-inflated template brain surface.

Figure 4.

Figure 4.

Estimated change per decade from cross-sectional data. Based on cross-sectional data, percentage annual percentage change in cortical thickness was calculated per year, smoothed across time, and displayed per decade. The estimates are adjusted for effects of sample differences and sex. Only right hemisphere is shown. Right panel: Estimated annual change in the right entorhinal cortex, based on cross-sectional data, plotted as a function of age. Note that even for the participants >60 years, these estimates are substantially lower than those obtained from the longitudinal data.

Figure 5.

Figure 5.

Cortical thinning: longitudinal and cross-sectional comparisons. Left panel: Annualized percentage change in cortical thickness was calculated from the longitudinal data and displayed as a color-coded map on semi-inflated brain models. Middle panel: For comparison, annualized percentage change in thickness was also calculated from the cross-sectional data from the same participants. Right panel: Annualized percentage change in cortical thickness calculated from the cross-sectional data of all participants in the age range 60–90 years (corresponding to the age range of the longitudinal sample).

Figure 6.

Figure 6.

Nonlinear lifespan trajectories with Alzheimer patients included. Age trajectories for the OASIS subsample (n = 309), with an addition of patients (n = 96) with mild AD in an attempt to mimic the effect of undetected dementing disorder. The healthy controls are illustrated with green dots and the AD patients with pink dots. With the exception of the entorhinal cortex, inclusion of AD patients had relatively minor impacts on the estimated lifespan trajectory for each cortical area. _x_-Axis values represent the mean thickness across hemispheres, corrected for the influence of sample (_Z_-scores), and the _y_-axis represent age in year. ROIs are displayed on a semi-inflated template brain surface.

Figure 7.

Figure 7.

The rate of change in participants with low risk of Alzheimer's disease. From the ADNI sample, subgroups of participants with very low risk of Alzheimer's disease (AD) were selected based on 2-year clinical and neuropsychological stability (n = 18), levels of CSF Aβ1-42 (n = 28) or a combination of CSF Aβ1-42 levels and no APOE ɛ4 alleles (n = 22). The annual rate of change in the entorhinal cortex did not differ statistically between any of the subgroups and the full ADNI sample. Thus, it is very unlikely that thinning in this area in healthy older adults is solely caused by undetected AD processes.

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