High consistency of regional cortical thinning in aging across multiple samples - PubMed (original) (raw)

. 2009 Sep;19(9):2001-12.

doi: 10.1093/cercor/bhn232. Epub 2009 Jan 15.

Lars T Westlye, Inge Amlien, Thomas Espeseth, Ivar Reinvang, Naftali Raz, Ingrid Agartz, David H Salat, Doug N Greve, Bruce Fischl, Anders M Dale, Kristine B Walhovd

Affiliations

High consistency of regional cortical thinning in aging across multiple samples

Anders M Fjell et al. Cereb Cortex. 2009 Sep.

Abstract

Cross-sectional magnetic resonance imaging (MRI) studies of cortical thickness and volume have shown age effects on large areas, but there are substantial discrepancies across studies regarding the localization and magnitude of effects. These discrepancies hinder understanding of effects of aging on brain morphometry, and limit the potential usefulness of MR in research on healthy and pathological age-related brain changes. The present study was undertaken to overcome this problem by assessing the consistency of age effects on cortical thickness across 6 different samples with a total of 883 participants. A surface-based segmentation procedure (FreeSurfer) was used to calculate cortical thickness continuously across the brain surface. The results showed consistent age effects across samples in the superior, middle, and inferior frontal gyri, superior and middle temporal gyri, precuneus, inferior and superior parietal cortices, fusiform and lingual gyri, and the temporo-parietal junction. The strongest effects were seen in the superior and inferior frontal gyri, as well as superior parts of the temporal lobe. The inferior temporal lobe and anterior cingulate cortices were relatively less affected by age. The results are discussed in relation to leading theories of cognitive aging.

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Figures

Figure 1.

Figure 1.

Example scans from each sample. Scans representative of image quality of 1 young and 1 elderly participant from each of the samples are shown (because sample 4 and 5 are from the same scanner, only examples from sample 4 are shown. All scans are converted from their native format to Freesurfer format. Samples 1, 2, and 4 are taken from Siemens scanners, and 2–4 acquisitions were averaged from each participant to yield high contrast and signal to noise ratio. Sample 2 and 6 are from GE scanners (Signa), with 1 acquisition. The cortex–CSF boundary (red) and the gray–white boundary (yellow) are indicated by the thin line. Anatomical differences between the scans from each sample are incidental.

Figure 2.

Figure 2.

Mean cortical thickness in 3 age groups. Mean thickness in each hemisphere for the age groups <40 years, 40–60 years, and >60 years are color coded and projected onto an inflated template brain for better visualization of effects buried in sulci. Note that the participants from all the samples are pooled together in each of the age groups, with no corrections for scanner or sample.

Figure 3.

Figure 3.

Age effects on cortical thickness in each sample. The figure shows the effect of age on cortical thickness across the entire brain surface when effects of sex were regressed out. The results are color coded and projected onto a semi-inflated template brain for better visualization of effects buried in sulci. Each row represents the results from 1 sample. On the left side of the figure, the effects are thresholded at FDR < 0.05 (corrected for multiple comparisons). On the right side, the results are color coded by use of a wider P value scale.

Figure 4.

Figure 4.

Consistency across samples. The number of samples in which a statistical effect was reached is color coded and projected onto a semi-inflated template brain. The first row depicts the results when a threshold of FDR < 0.05 was used. As can be seen, age-related thinning of the cerebral cortex is seen in all or 5 of the samples across most of the brain surface. In the second and third row, higher P value thresholds were used.

Figure 5.

Figure 5.

Age effects in the total sample. The figure shows the effects of age on cortical thickness when all samples were included in the same analysis (n = 883), with main effect of sample regressed out. In the second row, a higher P value threshold was employed. Even with a P value threshold of 10−25, large effects were seen in several areas.

Figure 6.

Figure 6.

Sample × age interaction effects. The figure shows which areas of the cerebral cortex that were affected differently by age across samples. The color-coded areas represent significant age × sample interaction effects. Note that the areas which display age × sample interactions are the ones where the strongest age effects were found.

Figure 7.

Figure 7.

Scatter plots of mean thickness in selected cortical areas. Manual ROIs were drawn on the inflated template brain surface. The areas in which age and sample interacted were used to guide the manual drawing of ROIs. Mean thickness in different cortical areas were calculated, and plotted against age. The ROIs are shown in the upper row. The scatter plots are shown in the middle row. The participants from each sample are coded in different colors. The last row depicts the Pearson correlation coefficients between age and mean thickness in each of the ROIs. The coefficients are given above each bar if P ≤ 0.05 (uncorrected), and not given if not significant (P > 0.05).

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