Divergent Influences of Cardiovascular Disease Risk Factor Domains on Cognition and Gray and White Matter Morphology

Abstract

Objective: Hypertension, diabetes, dyslipidemia, and obesity are associated with preclinical alterations in cognition and brain structure; however, this often comes from studies of comprehensive risk scores or single isolated factors. We examined associations of empirically derived cardiovascular disease risk factor domains with cognition and brain structure.

Methods: A total of 124 adults (age, 59.8 [13.1] years; 41% African American; 50% women) underwent neuropsychological and cardiovascular assessments and structural magnetic resonance imaging. Principal component analysis of nine cardiovascular disease risk factors resulted in a four-component solution representing 1, cholesterol; 2, glucose dysregulation; 3, metabolic dysregulation; and 4, blood pressure. Separate linear regression models for learning, memory, executive functioning, and attention/information processing were performed, with all components entered at once, adjusting for age, sex, and education. MRI analyses included whole-brain cortical thickness and tract-based fractional anisotropy adjusted for age and sex.

Results: Higher blood pressure was associated with poorer learning (B = -0.19; p = .019), memory (B = -0.22; p = .005), and executive functioning performance (B = -0.14; p = .031), and lower cortical thickness within the right lateral occipital lobe. Elevated glucose dysregulation was associated with poorer attention/information processing performance (B = -0.21; p = .006) and lower fractional anisotropy in the right inferior and bilateral superior longitudinal fasciculi. Cholesterol was associated with higher cortical thickness within left caudal middle frontal cortex. Metabolic dysfunction was positively associated with right superior parietal lobe, left inferior parietal lobe, and left precuneus cortical thickness.

Conclusions: Cardiovascular domains were associated with distinct cognitive, gray, and white matter alterations and distinct age groups. Future longitudinal studies may assist in identifying vulnerability profiles that may be most important for individuals with multiple cardiovascular disease risk factors.

Figure 1

Cortical thickness associations between (A) BP and right lateral occipital; (B) Chol and left caudal medial frontal; (C) MetabDys and left inferior parietal; (D) MetabDys and left precuneus; (E) MetabDys and right superior parietal NOTE: Whole brain cortical thickness results derived from FreeSurfer. Maps were smoothed with a 15mm full width half maximum Gaussian kernel and correction for multiple comparisons was performed using the Monte Carlo Null-z simulation (p<0.05). All analyses have been adjusted for age and sex. Red indicates negative associations with cortical thickness and yellow indicates positive associations with cortical thickness.

Figure 2

TBSS results in red overlayed on the mean white matter tract skeleton (in green) derived from FSL using non-parametric permutation testing and cluster-based thresholding correction (p<0.001, cluster size>100 voxels). Significant cluster voxels associated with GluDys and fractional anisotropy adjusted for age and sex are depicted by the arrows pointing to the right inferior longitudinal fasciculus (ILF) and the right and left superior longitudinal fasciculus (SLF).