Subclinical atherosclerosis and subsequent cognitive function
Introduction
A relationship between vascular risk factors and the onset and progression of cognitive dysfunction is well established, in large part by the well-known Framingham Study [1] and others [2], [3], [4], [5]. The most common cause of vascular disease is atherosclerosis [6] and atherosclerotic risk has been traditionally assessed based on the sum of predisposing factors such as hypertension [7], diabetes [8], and increased abdominal fat [9]; however, computerized tomography (CT) and magnetic resonance imaging (MRI) provide direct measurement of atherosclerosis. Carotid atherosclerosis has been associated with the onset, severity, and progression of cognitive dysfunction [10], [11], [12], [13]; however, atherosclerosis begins in the abdominal aorta and only later involves the carotid arteries [14]. Therefore, other direct measures may provide a better index of subclinical atherosclerosis [15], such as coronary artery calcium (CAC) [16], abdominal aortic plaque [17], and abdominal aortic wall thickness (AWT) [18], which have been shown to independently predict future adverse cardiovascular events [19].
The extent to which subclinical atherosclerosis is related to cognition is not fully understood, particularly whether these processes exert a detectable effect on cognition in the absence of stroke or prior to the onset of dementing illnesses. The relationship between objective evidence of atherosclerosis and cognition has been studied in convenience samples and studies of the elderly, but has not been widely examined in a population-based sample of adults with a wide age range. Research on subclinical atherosclerosis has recently increased due to advances in imaging, and the majority of this work has utilized carotid measures of atherosclerosis [20], [21]. This is the first study to date to simultaneously examine three direct measures of atherosclerosis (CAC, abdominal aortic plaque, abdominal AWT) in relationship to global cognitive function in a large, ethnically diverse community-based sample. Using a large community-based sample, it was hypothesized that higher levels of atherosclerosis as measured by CAC, abdominal aortic plaque, and abdominal AWT would be moderately related to lower cognitive performance at a later point in life and that an increasing number of positive atherosclerotic indicators would have an incremental negative effect on MoCA scores.
Section snippets
Participants
This investigation was conducted as part of the Dallas Heart Study (DHS), a longitudinal, population-based, multi-ethnic cohort study of factors contributing to cardiovascular disease [22]. All participants provided written informed consent and the study protocol was approved by the Institutional Review Board at the University of Texas Southwestern Medical Center. The first phase of DHS (DHS-1) was initiated in 1999, and participants were drawn from those who returned for follow-up in DHS-2
Sample characteristics
Descriptive information is presented in Table 1. The mean MoCA score for the entire sample was 23.36 (4.03) points. Education was associated with MoCA performance (r = .43, p < .001), as was age (r = −.20, p ≤ .001). After controlling for education and age, there was no difference in MoCA scores by sex (M, SD male: 23.29, 3.95 and female: 23.42, 4.08).
Relationship to cognition
A partial Spearman's correlation controlling for age and education showed a weak but statistically significant correlation between MoCA Total
Discussion
Much of the evidence for an association between cognitive function and atherosclerosis comes from studies of select populations, such as the elderly and those with advanced atherosclerosis, and the majority of this work has utilized carotid measures [13], [36], [37], [38]. This is the first study to simultaneously examine three direct measures of atherosclerosis (coronary artery calcium, abdominal aortic wall thickness, and aortic plaque) in relation to global cognitive function in a
Conflict of interest
None.
Acknowledgment
This work was conducted in part with support from the Wallace, Barbara and Kelly King Charitable Foundation and the National Center for Advancing Translational Sciences of the National Institutes of Health under award Number UL1TR001105. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
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