Subclinical cerebrovascular disease inversely associates with learning ability: The NOMAS

Abstract

Objective: Memory has been examined in subjects with imaging markers of cerebrovascular disease, but learning has been less well studied. We examined the relationship among subclinical cerebrovascular disease, cerebral volumes, and verbal learning in an ethnically and racially diverse community sample.

Methods: A clinically stroke-free subset of Northern Manhattan Study participants underwent cognitive testing and brain MRI with quantification of white matter hyperintensity volume (WMHV) and total cerebral volume (TCV) using semiautomated segmentation. We used generalized linear regression and mixed models to examine the association between imaging findings and verbal learning.

Results: There were 1,272 participants (61% women, mean age 70 ± 9 years). Participants with greater WMHV and smaller TCV remembered fewer total words on a list-learning task (β = -0.83 per SD change in WMHV, 95% confidence interval [CI] = -1.22 to -0.45, p < 0.0001; and β = 0.48 per SD change in TCV, 95% CI = 0.05 to 0.90, p = 0.03, respectively). Subclinical brain infarction (SBI) was not associated with total words learned (β = -0.04, 95% CI = -1.08 to 1.00, p = 0.94). Those with greater WMHV had increased odds of a flatter learning slope. After excluding participants with SBI, the association between total words learned and WMHV remained significant. All measurements were adjusted for age, education, race/ethnicity, medical insurance status, and the presence of SBI.

Conclusions: White matter hyperintensities, a marker of cerebral small vessel disease, may have an impact on learning slope. This suggests that verbal learning performance can be incorporated into neuropsychological measures for vascular cognitive impairment and that cerebrovascular disease discovered on imaging affects the ability to learn new information.

Figure 1. Verbal learning plots based on quartiles of white matter hyperintensity and cerebral volume

Plots are derived from least squares (LS) means in a mixed model after adjusting for age, sex, education, insurance status, race/ethnicity, and presence of subclinical brain infarction. Patients are divided by (A) top quartile of white matter hyperintensity volume (quartile 4) vs the lowest 3 quartiles (quartiles 1–3), and (B) bottom quartile of total cerebral volume (quartile 1) vs the top 3 quartiles (quartiles 2–4). *p < 0.05, **p < 0.01.