Abstract
Background and Purpose
Several cardiovascular risk factors are associated with cognitive disorders in older persons. Little is known about the association of the burden of coronary atherosclerosis with brain structure and function.
Methods
Cross-sectional analysis of data from the AGES Reykjavik Study cohort of men and women born 1907-35. Coronary artery calcification (CAC), a marker of atherosclerotic burden was measured with computed tomography. Memory, speed of processing, and executive function composites were calculated from a cognitive test battery. Dementia was assessed in a multi-step procedure and diagnosed according to international guidelines. Quantitative data on total intracranial and tissue volumes [total, Gray (GMV), White (WMV), and White Matter Lesions (WMLV)], cerebral infarcts and cerebral microbleeds (CMB) were obtained with brain MRI. The association of CAC with dementia (n=165 cases) and cognitive function in non-demented subjects (n=4085), and separately with MRI outcomes, was examined in multivariate models adjusting for demographic and vascular risk factors. Analyses tested whether brain structure mediated the associations of CAC to cognitive function.
Results
Subjects with higher CAC were more likely to have dementia and lower cognitive scores, more likely to have lower WMV, GMV and total brain tissue, and more cerebral infarcts, CMB and WMLV. The relations of cognitive performance and dementia to CAC were significantly attenuated when the models were adjusted for brain lesions and volumes.
Conclusions
In a population-based sample increasing atherosclerotic load, assessed by CAC, is associated with poorer cognitive performance and dementia, and these relations are mediated by evidence of brain pathology.
Keywords: Atherosclerosis, Coronary Artery Disease, Calcinosis/radiography, Dementia, Cognitive function
Introduction
Cardiovascular risk factors such as hypertension or diabetes are associated with cognitive impairment,1,2 brain lesions and atrophy,3 as well as dementia.4,5 Although there is an increasing body of literature showing associations of cardiovascular risk factors to brain function and structure, there are fewer studies of the burden of atherosclerosis diffuse chronic arterial disease to cognition, and whether these associations are mediated by pathologic changes in brain structure.6,7
Atherosclerotic burden can be indirectly estimated by coronary artery calcium (CAC),8 carotid intima-media thickness (CIMT) and ankle-brachial index (ABI). Some studies have shown an association between CIMT or ABI with cognitive decline9 and separately dementia,10 however CAC is a more sensitive 11,12 and more reliable13,14 measure of atherosclerosis that captures the cumulative exposure to the individual.
The AGES-Reykjavik Study, a large population-based study, with a reliable measure of CAC, a comprehensive cognitive assessment, and a brain MRI with a fully automated procedure for estimating the brain volumes, provides the opportunity to study the relation of CAC to brain function and structure We hypothesize that an increasing load of CAC is strongly related to diminished cognitive performance and to dementia, as well as to lower brain volumes and greater burden of brain lesions. Furthermore we hypothesize that the brain volumes and lesions mediate the relation of CAC with cognitive performance and dementia.
Materials and methods
The Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik) was initiated in 2002 to examine environmental factors, genetic susceptibility and gene/environment interaction in relation to disease and disability in the elderly.15 Subjects (n=5764, aged 66 to 98 years old) recruited for the AGES-Reykjavik cohort came from the population-based Reykjavik Study cohort composed of men and women, born 1907-1935 and living in Reykjavik at the time the study was initiated in 1967 by the Icelandic Heart Association (IHA).16 As described previously, all eligible AGES-Reykjavik subjects participated in a comprehensive clinical evaluation, including cognitive testing, brain MRI and a computed tomography (CT) cardiac scan.15 All participants signed an informed consent. The study was approved (VSN00-063) by the National Bioethics Committee in Iceland as well as the Institutional Review Board of the Intramural Research Program of the National Institute on Aging.
Coronary artery calcifications
The heart was imaged with a Siemens Somatom Sensation 4 multi-detector CT (Siemens Medical Solutions, Malvern, PA) with prospective electrocardiographic triggering.15 CT scans were analyzed with a calcium scoring software, previously described as a part of the Multi-Ethnic Study of Atherosclerosis (MESA) study.17 CAC, quantified according to the Agatston method,18 was the sum of all four coronary artery scores. Based on the re-analysis of 200 scans, the intra-reader agreement was r=0.99 and the inter-observer Spearman correlation of measure made by the five readers compared to an expert reader from the MESA study was r=0.94.
Assessment of cognition and dementia
A battery of six different cognitive tests was administered to all participants. From these tests, three cognitive domain composite scores were calculated: the memory composite score included the immediate and delayed recall of a modified version of the California Verbal Learning Test;19 the speed of processing composite included the Figure Comparison Test,20 the Digit Symbol Substitution Test (DSST)21 and the Stroop Test part 1 and 2;22 and the executive function composite included a short version of the Cambridge Neuropsychological Test Automated Battery Spatial Working Memory (CANTAB) test,23 the Digits Backward test21 and the Stroop test part 3.22 Sex specific composite measures were computed by converting raw scores on each test to standardized Z-scores separately by sex, and averaging the Z-scores across the tests in each composite.24 Inter-rater reliability for all tests was excellent (Spearman correlations range from 0.96 to 0.99).
Dementia case ascertainment was a three-step process described previously.15 Briefly, all subjects were screened on cognitive function with the MMSE25 and DSST.21 Screen positives were administered a diagnostic battery of neuropsychological tests, and among them, screen positives were examined by a neurologist and a proxy interview was administered. A consensus diagnosis, according to international guideline, was made by a panel that included a geriatrician, neurologist, neuropsychologist, and neuroradiologist.
Brain MRI measures
All participants without contraindications were eligible for a brain MRI performed on a study dedicated 1.5 T Signa Twinspeed system (General Electric (GE) Medical Systems, Waukesha, Wisconsin, USA). The image protocol, described previously, 25 included an axial T1-weighted 3D, T2* weighted gradient echo type echo planar (T2*), a proton density/T2 weighted fast spin echo (T2) and a fluid attenuated inversion recovery (FLAIR) sequences.
The intracranial volume and the brain parenchyma compartments were segmented automatically with an AGES-Reykjavik Study modified algorithm based on the Montreal Neurological Institute pipeline.26 The volumes of gray matter (GMV), white matter (WMV), white matter lesions (WMLV) and cerebrospinal fluid (CSFV) were estimated for each subject, and divided by total intracranial volume, giving a percent tissue volume. Total brain tissue volume was defined as the sum of GMV, WMV and WMHV. Cerebral infarcts (CI) were identified by trained radiographers as defects in the brain parenchyma with associated hyperintensity on T2 and FLAIR images with a maximal diameter of at least 4 mm. For infarcts in the cerebellum and brain stem or infarcts with cortical involvement, no size criterion was required. Cerebral microbleeds (CMB) were defined as focal areas of signal void within the brain parenchyma that met the following criteria: visible on T2* images and smaller or invisible on T2 images, not abutting a parenchymal defect, and not showing any other structure in the signal-void area.25 The average inter-rater reliability (weighted kappa) was 0.7 for both CI and CMB (presence/absence) and intra-rater reliability was 0.9 and 1.0 respectively in 5% of all scans re-read without knowledge of the prior reading.
Potential confounders
Analyses were adjusted for demographic, health, and vascular risk factors associated with both CAC and cognitive function or dementia.1-5 Presence of depressive symptoms was defined as a score of 6 or higher on the Geriatric Depression Scale (GDS).27 Education level (college or university versus lower education) and smoking history (never, ever) were assessed by questionnaire. Diabetes was defined as a history of diabetes, use of glucose modifying medication, or a fasting blood glucose of >7 mmol/L. Hypertension (HBP) was defined as measured systolic blood pressure ≥ 140 mmHg, or diastolic blood pressure ≥ 90 mmHg, or self-reported doctor's diagnosis of HBP, or using antihypertensive medications. Prevalent coronary heart disease was defined as self reported history of coronary artery disease or coronary artery bypass surgery or angioplasty or angina pectoris on the Rose Angina Questionnaire,28 or evidence on ECG of possible or probable myocardial infarction.
We also adjusted the analyses for mid-life systolic blood pressure and total cholesterol measured at the Reykjavik Study examination that occurred 25 years (SD=4.2) earlier, as these two variables were strongly associated with CAC and cognition.
Analytical sample
Out of the 5764 examined subjects, 453 did not have a CAC measure because of technical or medical reasons or refusal, leaving 5311 subjects with a measure of CAC. The three cognitive domains could be computed for 5215, of whom 4490 had a brain MRI from which the brain volumes could be assessed. Complete data for this analysis were therefore available for 4250 subjects, including 165 with a diagnosis of dementia. Compared to the 4250 subjects with complete data, subjects with incomplete data (n=1514) were significantly older (76.3 (SD=5.4) vs. 79.5 (6.7)), had a higher rate of depressive symptoms, and were more likely to have diabetes and a history of smoking. At mid-life they had higher systolic and diastolic blood pressure. The coronary artery calcium score, CI, and CMB, did not differ between the 2 groups after adjusting for age and sex.
Statistical analyses
Because CAC load differed significantly between men and women, quartiles of distribution of CAC were calculated separately by sex and then pooled (thresholds for men 60, 584 and 1498 and for women 12, 136 and 521). This ensures women are ranked and compared to other women, and similarly men are compared to other men. WMLV was highly skewed so the measure was log-transformed; for clarity, we report the means of WMLV as anti-logs.
General characteristics and cardiovascular risk factors of the sample were examined among demented and non demented subjects, for each cognitive domain and across the quartiles of CAC. Logistic regression was used to evaluate the association with dichotomized variables, and analysis of covariance with continuous variables.
Analysis of covariance was used to calculate the adjusted means (and 95% confidence intervals) of the three cognitive domains for each quartile of CAC, and logistic regression was used to calculate the OR (95% confidence intervals) associated with each quartile of CAC. The overall difference among the quartiles, as well as the linear trend across quartiles was tested. The first quartile was also compared to the three others. All primary analyses were adjusted for age and sex (by virtue of using sex-specific quartile cut points); we added education and presence of depressive symptoms (Model 1), and then further adjusted the model for vascular risk factors (Model 2).
The association of the different brain abnormalities to CAC was studied with logistic regression for CI and CMB and analysis of covariance for brain volumes, adjusted for age, education and cardiovascular risk factors. To examine whether brain changes mediate the association of CAC to cognition, we entered into Model 2, the structural findings in the brain.
Finally, to better understand the relation between cognition and CAC, we adjusted the models for age and for each brain characteristic (CI, CMB, and volumes) taken separately without any other adjustment.
All analyses were carried out using the statistical software package SAS Version 9.1 (SAS Institute Inc., Cary, N.C., USA).
Results
The median Agatston score of CAC was 278 among the 4250 subjects; median score was higher among men than women (584 vs. 136). Increasing CAC quartile was associated with older age, presence of depressive symptoms, higher mid-life systolic and diastolic blood pressure, and more HBP treatment (Table 1). At late-life, subjects in the higher quartiles of CAC were more likely to have HBP and diabetes and more likely to be a smoker or ex-smoker.
Table 1. Cohort characteristics across the sex-specific quartiles of coronary artery calcium: the AGES-Reykjavik Study.
| Coronary Artery Calcium Sex-specific Quartiles | ||||||
|---|---|---|---|---|---|---|
| General characteristics | 1st | 2nd | 3rd | 4th | p*† | p linear tend* |
| N=1058 | N=1067 | N=1062 | N=1063 | |||
| Late life variables | ||||||
| Age, M (SD) | 74.5 (4.9) | 75.8 (5.2) | 77.1 (5.5) | 78.0 (5.3) | <.0001 | <.0001 |
| Men, % (N) | 25.0 (444) | 25.0 (444) | 25.0 (444) | 25.0 (444) | ||
| Higher education, % (N) | 24.9 (284) | 26.8 (304) | 23.9 (272) | 24.3 (276) | 0.53 | 0.49 |
| Hypertension, % (N) | 21.9 (746) | 24.7 (841) | 25.9 (883) | 27.5 (938) | <.0001 | <.0001 |
| Diabetes, % (N) | 16.5 (77) | 23.8 (111) | 25.1 (117) | 34.7 (162) | <.0001 | <.0001 |
| Ever Smoker, % (N) | 21.5 (521) | 24.8 (601) | 26.2 (635) | 27.5 (668) | <.0001 | <.0001 |
| BMI, kg/m2, M (SD) | 26.1 (4.1) | 25.9 (4.3) | 25.9 (4.3) | 26.0 (4.3) | 0.07 | 0.02 |
| Presence of depressive symptoms, % (N) | 24.4 (72) | 23.4 (69) | 22.7 (67) | 29.5 (87) | 0.0005 | <.0001 |
| Prevalent coronary heart disease, % (N) | 7.6 (67) | 14.6 (128) | 27.1 (238) | 50.7 (446) | <.0001 | <.0001 |
| Dementia | 10.3 (17) | 21.8 (36) | 29.1 (48) | 38.8 (64) | <.0001 | <.0001 |
| Midlife variables | ||||||
| Systolic Pressure, mmHg, M (SD) | 127.8 (14.7) | 130.0 (15.4) | 133.0 (17.4) | 136.0 (18.0) | <.0001 | <.0001 |
| Diastolic Pressure, mmHg, M (SD) | 81.4 (8.8) | 82.2 (9.0) | 83.7 (9.9) | 85.1 (10.0) | <.0001 | <.0001 |
| Cholesterol, mg/100mL, M (SD) | 6.03 (0.98) | 6.27 (1.10) | 6.41 (1.11) | 6.67 (1.13) | <.0001 | <.0001 |
M (SD): Mean (Standard Deviation); BMI: Body Mass Index;
Adjusted for age;
Overall difference between the four quartiles of combined sex specific quartiles.
Lower scores on each cognitive domain were strongly associated with older age, lower educational level, presence of depressive symptoms, and more cardiovascular risk factors and disease. Low scores were also associated with CI, CMB, lower brain volumes, and higher WMLV. Compared to non demented individuals those with dementia were more often male, had lower BMI, reported more depressive symptoms, and had a lower educational level.
In age-adjusted analyses, lower scores on each cognition domain were strongly related to higher CAC (table 2). Adjustment for age, education, and presence of depressive symptoms (Model 1) reduced the group differences in speed of processing and executive function, but the linear trend of decreasing cognitive score and increasing CAC remained significant (p=0.001 and 0.01 respectively). The relation between memory and CAC, however, was attenuated and no longer significant. Additional adjustment for cardiovascular risk factors (Model 2) did not substantially modify these results.
Table 2. Association of sex-specific quartiles of coronary artery calcium with cognitive domains and dementia: the AGES-Reykjavik Study.
| Coronary Artery Calcium Sex-specific Quartiles | p* | p linear trend | ||||
|---|---|---|---|---|---|---|
| 1st | 2nd | 3rd | 4th | |||
| Adjusted means (95% Confidence Limits) | ||||||
| Memory† | ||||||
| Adjusted for age | 0.04 (−0.02; 0.10) | 0.02 (−0.04; 0.08) | −0.005 (−0.06; 0.05) | −0.07 (−0.13; −0.01) | 0.07 | 0.01 |
| Model 1 | 0.03 (−0.03; 0.08) | 0.01 (−0.04; 0.07) | 0.000 (−0.06; 0.06) | −0.05 (−0.11; 0.005) | 0.24 | 0.06 |
| Model 2 | 0.02 (−0.05; 0.09) | 0.01 (−0.06; 0.08) | 0.001 (−0.07; 0.07) | −0.04 (−0.11; 0.03) | 0.56 | 0.20 |
| Speed of processing† | ||||||
| Adjusted for age | 0.08 (0.02; 0.14) | 0.04 (−0.01; 0.10) | −0.01 (−0.07; 0.04)‡ | −0.09 (−0.15; −0.04)¶ | 0.0002 | <.0001 |
| Model 1 | 0.06 (0.01; 0.12) | 0.03 (−0.02; 0.09) | −0.01 (−0.06; 0.04) | −0.08 (−0.13; −0.03)‖ | 0.002 | 0.0001 |
| Model 2 | 0.04 (−0.02; 0.11) | 0.02 (−0.05; 0.08) | −0.03 (−0.09; 0.04) | −0.09 (−0.15; −0.002)§ | 0.01 | 0.001 |
| Executive function† | ||||||
| Adjusted for age | 0.07 (0.02; 0.14) | 0.03 (−0.03; 0.09) | −0.03 (−0.08; 0.03)‡ | −0.08 (−0.14; −0.02)§ | 0.002 | 0.0001 |
| Model 1 | 0.07 (0.01; 0.12) | 0.02 (−0.03; 0.08) | −0.03 (−0.08; 0.03)‡ | −0.06 (−0.12; −0.006)§ | 0.01 | 0.0009 |
| Model 2 | 0.08 (0.01; 0.15) | 0.04 (−0.02; 0.11) | 0.00 (−0.07; 0.07) | −0.02 (−0.09; 0.05)‡ | 0.09 | 0.01 |
| Odds Ratios (95% Confidence Intervals) | ||||||
| Dementia | ||||||
| Adjusted for age | 1 (ref) | 1.75 (0.97; 3.16) | 1.95 (1.10; 3.46)‡ | 2.43 (1.39; 4.22)§ | 0.02 | 0.002 |
| Model 1 | 1 (ref) | 1.85 (1.02; 3.35)‡ | 2.03 (1.14; 3.61)‡ | 2.47 (1.42; 4.32)§ | 0.02 | 0.002 |
| Model 2 | 1 (ref) | 1.76 (0.97; 3.21) | 1.95 (1.09; 3.50)‡ | 2.34 (1.31; 4.19)§ | 0.04 | 0.005 |
Overall difference between the four quartiles;
Demented subjects (N=165) excluded;
Comparison to the first sex-specific quartile:
p<0.05
p<0.01
p<0.001
p<0.0001.
Model 1: Adjusted for age, education level and presence of depressive symptoms;
Model 2: model 1 + ever smoker, prevalent coronary heart disease, current hypertension and diabetes and mid-life systolic pressure and total cholesterol.
The percentage of dementia, adjusted for age, significantly increased with quartiles of CAC (Q1 10.3%, Q2 21.8%, Q3 29.1%, Q4 38.8%). Similar to the results with cognitive function, the association of CAC and dementia was markedly reduced in Model 1 but the linear trend for dementia and higher CAC remained significant. The relation was only slightly attenuated by further adjustment for vascular risk factors in Model 2.
With increasing CAC quartile, GMV, WMV and total brain tissue volume decreased, and WMLV increased, as did the likelihood of CMB and CI (Table 3). Linear trends for a dose-response relation of CAC to brain volumes, CMB, and CI were all significant. The relation between the brain changes and CAC remained strongly significant after adjustment for age, education level, and vascular risk factors.
Table 3. Association of sex-specific quartiles of coronary artery calcium with MRI detected brain characteristics and pathology: the AGES-Reykjavik Study.
| Coronary Artery Calcium Sex-specific Quartiles | p* | p linear tend | ||||
|---|---|---|---|---|---|---|
| Brain characteristics | 1st | 2nd | 3rd | 4th | ||
| Odds Ratios (95% Confidence Intervals) | ||||||
| Cerebral infarcts | ||||||
| Adjusted for age | 1 (ref) | 1.09 (0.89; 1.07) | 1.21 (0.99; 1.47) | 1.83 (1.51; 2.22) | <.0001 | <.0001 |
| Adjusted model | 1 (ref) | 0.99 (0.80; 1.21) | 1.00 (0.82; 1.23) | 1.36 (1.10; 1.23) | 0.002 | 0.004 |
| Cerebral microbleeds | ||||||
| Adjusted for age | 1 (ref) | 1.28 (0.81; 2.02) | 1.00 (0.62; 1.62) | 1.94 (1.23; 2.98) | 0.0002 | 0.004 |
| Adjusted model | 1 (ref) | 1.25 (0.79; 1.98) | 0.97 (0.59; 1.58) | 1.80 (1.14; 2.86) | 0.01 | 0.02 |
| Adjusted means (95% Confidence Limits) | ||||||
| White matter volume† | ||||||
| Adjusted for age | 25.9 (25.8; 26.0) | 25.8 (25.7; 25.9) | 25.7 (25.5; 25.8) | 25.4 (25.3; 25.5) | <.0001 | <.0001 |
| Adjusted model | 26.0 (25.8; 26.1) | 25.9 (25.8; 26.0) | 25.8 (25.6; 25.9) | 25.6 (25.4; 25.7) | <.0001 | <.0001 |
| Gray Matter volume† | ||||||
| Adjusted for age | 46.1 (45.9; 46.2) | 45.4 (45.2; 45.6) | 45.0 (44.8; 45.2) | 44.2 (44.0; 44.4) | <.0001 | <.0001 |
| Adjusted model | 45.4 (42.2; 45.6) | 45.2 (45.0; 45.4) | 45.2 (45.0; 45.4) | 44.7 (44.4; 44.9) | <.0001 | <.0001 |
| Total brain tissue volume† | ||||||
| Adjusted for age | 72.7 (72.5; 72.9) | 72.4 (72.2; 72.6) | 72.1 (71.9; 72.3) | 71.5 (71.3; 71.7) | <.0001 | <.0001 |
| Adjusted model | 72.4 (72.1; 72.7) | 72.3 (72.0; 72.5) | 72.1 (71.8; 72.3) | 71.7 (71.4; 71.9) | <.0001 | <.0001 |
| WML volume† | ||||||
| Adjusted for age | 1.03 (0.96; 1.11) | 1.24 (1.17; 1.32) | 1.32 (1.24; 1.40) | 1.68 (1.60; 1.76) | <.0001 | <.0001 |
| Adjusted model | 1.05 (0.95; 1.14) | 1.17 (1.07; 1.26) | 1.15 (1.06; 1.24) | 1.45 (1.35; 1.55) | <.0001 | <.0001 |
Overall difference between the four quartiles;
Relative to intracranial volume;
WML: white matter lesion;
Adjusted model: adjusted for age, education level, ever smoker, prevalent coronary heart disease, current hypertension and diabetes, mid-life systolic pressure and total cholesterol.
When the brain volumes and brain lesions were entered into the models, the relation of CAC to speed of processing and executive function was strongly attenuated and the overall difference between the CAC quartiles as well as the linear relation was no longer significant (Table 3 and Table 4). Similarly, the relation of CAC and dementia was dramatically weakened when MRI brain volumes and brain lesions were added into the model (Table 3 and Table 4).
Table 4. Association of sex-specific quartiles of coronary artery calcium with cognition and dementia adjusted for brain characteristics and lesions: AGES-Reykjavik Study.
| Coronary Artery Sex-specific Calcium Quartiles | p* | p linear trend | |||||
|---|---|---|---|---|---|---|---|
| 1st | 2nd | 3rd | 4th | ||||
| Adjusted means (95% Confidence Limits)† | |||||||
| Cognitive domains‡ | |||||||
| Memory | −0.01 (−0.08;0.06) | −0.003 (−0.07; 0.07) | −0.009 (−0.08; 0.06) | −0.01 (−0.08; 0.06) | 0.99 | 0.97 | |
| Speed of processing | 0.007 (−0.06; 0.07) | −0.005 (−0.07; 0.06) | −0.04 (−0.10; 0.02) | −0.05 (−0.11; 0.02) | 0.43 | 0.10 | |
| Executive function | 0.05 (−0.02; 0.12) | 0.03 (−0.04; 0.10) | −0.01 (0.08; 0.06) | 0.005 (−0.07; 0.08) | 0.52 | 0.23 | |
| Odds Ratios (95% Confidence Intervals)† | |||||||
| Dementia | 1 (ref) | 1.55 (0.84; 2.85) | 1.72 (0.95; 3.11) | 1.56 (0.86; 2.83) | 0.20 | 0.24 | |
Overall difference between the four quartiles;
Adjustment for age, education level, presence of depressive symptoms, ever smoker, prevalent coronary heart disease, current hypertension and diabetes, mid-life systolic pressure and total cholesterol, cerebral infarct, cerebral microbleeds, white matter volume, white matter lesion volume and total brain tissue volume.
Demented subjects (N=165) excluded.
Finally, in models only adjusted for age and sex, taking into the model each brain characteristic separately (i.e.: CI, CMB, and MRI brain volumes) we found that the magnitude and significance of the associations of CAC to cognitive domain and dementia were dramatically reduced by the addition of brain volumes, and marginally reduced by the addition of CI or CMB (see supplementary table).
Discussion
We found that increasing calcification of the coronary arteries, a robust cumulative measure of atherosclerosis, was associated with decreased cognitive speed of processing, executive function, and increase risk of dementia in a large well described cohort of men and women, aged on average 76 years old, and that these relations were mediated by brain volume and lesions.
The strength of this study lies in the very large number of participants and the quality and reproducibility of assessment of the different outcomes. Cognitive function was assessed with a robust battery of tests that allowed us to develop more stable measures of 3 different cognitive domains: memory, speed of processing and executive function.24
This study has some limitations that should be taken into account when interpreting the results. Subjects not included in this analysis were older, more often diabetic, and had higher levels of systolic blood pressure at mid-life. Furthermore they had significantly lower cognitive performance and lower brain volumes. Therefore, the proportion of people with low cognitive performance, as well as lower brain volumes and higher CAC, may be underrepresented in this analysis. However, there is no reason to suggest a differential association of CAC to cognitive function between subjects included or not from the analysis.
The magnitude of the association of CAC to speed of processing and executive function did not diminish after adjustment for cardiovascular risk factors. This likely reflects the fact that CAC is a measure of lifetime exposure to these risk factors, which lead to atherosclerosis.
Before adjusting for brain structure, CAC was significantly associated with speed of processing and executive function, but not with memory. In addition, increasing CAC was associated with an increased risk for dementia These results are consistent with other published studies showing memory is not significantly associated with atherosclerosis burden.7,29 Speed of processing and executive function involve the subcortical network, which is particularly susceptible to ischemic damage.30 Compared to Alzheimer's disease, patients with cerebrovascular cognitive impairment have characteristically more impaired tests on speed and executive functions than on memory.31 CAC was associated with CI, CMB and brain tissue volumes, in a linear dose response relation. The increased risk for CI as CAC increases has been reported in other large population based cohorts.32,33 Other atherosclerosis markers such as carotid intima-media thickness or ankle brachial index have also been reported to be associated with brain lesion and atrophy,34,35 but these studies did have little or no measures of brain function.
Finally, the relations of increasing CAC to dementia and to decreasing scores on tests of speed of processing and executive function were most strongly mediated by brain volumes, and less so by CI or CMB. This analysis suggests atherosclerosis may lead to more diffuse, as opposed to focal damage in the brain. The dementia results are consistent with the findings from the Cardiovascular Health Study of 727 participants, suggesting that the association of dementia to CAC was not independent of brain atrophy and WMHV.7 The association of CAC to cognitive function was not assessed in that study.
Summary
Overall, this study shows that coronary atherosclerosis, measured with the CAC, is associated with pathologic changes in the brain that have functional consequences ranging in severity from mild to severe cognitive function. Additional research is needed to understand how atherosclerosis interacts with other factors, such as hemodynamic changes, to damage the brain. On a practical basis, these findings highlight the chances that individuals who present with high CAC may also have concomitant cerebral damage that should be investigated.
Supplementary Material
Acknowledgments
This study was supported by a grant from the National Institutes of Health (N01-AG-1-2100), National Institute on Aging Intramural Research Program, the Hjartavernd (the Icelandic Heart Association) and the Althingi (the Icelandic Parliament). We would like to thank the participants of the study and the IHA clinic staff for their invaluable contribution.
Footnotes
Conflicts of Interest: none
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