White matter lesions and brain gray matter volume in cognitively normal elders

Abstract

Cerebral white matter lesions (WMLs) reflect small vessel disease, are common in elderly individuals, and are associated with cognitive impairment. We sought to determine the relationships between WMLs, age, gray matter (GM) volume, and cognition in the Cardiovascular Health Study (CHS). From the Cardiovascular Health Study we selected 740 cognitively normal controls with a 1.5 T magnetic resonance imaging (MRI) scan of the brain and a detailed diagnostic evaluation. WML severity was determined using a standardized visual rating system. GM volumes were analyzed using voxel-based morphometry implemented in the Statistical Parametric Mapping software. WMLs were inversely correlated with GM volume, with the greatest volume loss in the frontal cortex. Age-related atrophy was observed in the hippocampus and posterior cingulate cortex. Regression analyses revealed links among age, APOE*4 allele, hypertension, WMLs, GM volume, and digit symbol substitution test scores. Both advancing age and hypertension predict higher WML load, which is itself associated with GM atrophy. Longitudinal data are needed to confirm the temporal sequence of events leading to a decline in cognitive function.

Figure 1

Main Effect of white matter grade (WMG) (top row) and age (bottom row) on regional GM volumes. This volume-rendered figure shows the partial correlations rp-values from the multiple regression model evaluating the relationship between WMG and GM volume rendered onto the SPM2 single subject cortical surface independent of, or controlled for, for previously mentioned covariates including age. Red indicates the highest partial correlations, green the smallest.

Figure 2

Main Effect of WMG and age projected onto the Standard Single Subject MNI template. WMLs (top row) and age (middle row) effects are projected as partial correlations (rp-values) independent of, or controlled for, pertinent covariates such as WMG. The bottom row shows the regional effects of WMG (red), age (green), and their overlap (yellow) (maps created using MRIcron (http://www.cabiatl.com/mricro/mricron/index.html))

Figure 3

Regression-based model of relationships among gray matter volume, white matter grade (WMG), age, hypertension (HTN), APOE*4, and DSST. Gray matter volume was extracted using the VOI tool in SPM2 and represents the hippocampus and frontal cortex volumes, adjusted for total intracranial volume (see text for details). Path weights are the standardized regression coefficients derived from multiple linear regression equations; no interactions among the predictor variables were statistically significant (p < .05). The direction of the arrows is based on the relationship between pairs of variables.