Abstract
Cerebral small vessel disease (SVD) may cause cognitive dysfunction. We tested the association between the combined presence of magnetic resonance imaging (MRI) features of SVD and cognitive ability in older age. Cognitive testing and brain MRI were performed in 680 older participants. MRI presence of lacunes, white matter hyperintensities, microbleeds, and perivascular spaces were summed in a score of 0–4 representing all SVD features combined. We also applied latent variable modeling to test whether the 4 MRI features form a unitary SVD construct. The SVD score showed significant associations with general cognitive ability. Latent variable modeling indicated that the 4 MRI markers formed a unitary construct, which showed consistent associations with cognitive ability compared with the SVD score. Total MRI load of SVD is associated with lower general cognitive ability in older age. The total SVD score performed consistently with the more complex latent variable model, suggesting validity and potential utility in future research for determining total SVD load.
Highlights
Cerebral small vessel disease (SVD) is a prevalent disease in older people
Greater total SVD load on magnetic resonance imaging (MRI) was associated with lower general cognitive ability (g) in a population of healthy older participants
The latent variable SVD measure showed consistent associations with g when compared with a simple-sum SVD score, but there was a small degree of variability in the magnitudes of the parameter estimates for speed and memory
Summary
Cerebral small vessel disease (SVD) is a prevalent disease in older people. The underlying pathogenesis is still debated, and classic vascular risk factors are only one contributing variable (Wardlaw et al, 2013). Huijts et al (2013) devised a score of overall SVD load by summing all 4 MRI features and found an association with poorer cognitive function (Huijts et al, 2013) in a small study in a mixed sample of patients with lacunar stroke and hypertension More validity to this total SVD score was recently added in a publication that showed associations with previously described well-known risk factors for individual SVD features, such as age, hypertension, and lacunar stroke (Staals et al, 2014). In a large community-dwelling sample of older people, we used latent variable modeling to test whether the 4 MRI features form a unitary SVD construct This would contribute to validating a simple and practical summed score for total SVD load. We explored whether total SVD score remained predictive independent of WMH, as WMH have been most regularly associated with cognitive functioning in published research (Valdés Hernández Mdel et al, 2013) and could solely drive the results
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