Carotid Arterial Stiffness Predicts White Matter Lesion Volume in Older Adults
Bibliographic record
Abstract
Markers of arterial wall stiffness are used commonly as indicators of cardiovascular risk. Stiff conduit vasculature transmits pulse waves with increased velocities, which may lead to end‐organ microvascular damage. However, the association of peripheral vascular stiffness to the brain's vulnerability for vascular impairment has not been established. In the brain, this microvascular damage could include breakdown of the blood‐brain barrier causing leakage of fluid through the cerebrovascular endothelial layer. Fluid‐attenuated inversion recovery (FLAIR) imaging allows the visualization of fluid‐abnormalities in subcortical tissue, which can be quantified as white matter lesions (WML). These WML have been linked to cognitive impairment, and labelled as risk factors for stroke, dementia, and cardiovascular mortality. This research tested the hypothesis that peripheral arterial stiffness predicts levels of WML volume. We examined normotensive controls (CTRL; n = 12; 6 males; age: 42–69 years) as well as normotensive ischemic heart disease patients (IHD; n = 17; 14 males; age: 40–75 years). Common carotid artery diameters were measured during systole and diastole (B‐mode ultrasound images with ECG‐gating), and time‐aligned corresponding blood pressure values were used for measures of arterial strain (strain), arterial stiffness index (β), carotid distensibility, carotid compliance, and arterial elastic modulus. All measures were taken in the supine posture. Magnetic resonance FLAIR imaging at T2 was used to assess periventricular WML volume (WMLv) using SPM software. The IHD and CTRL cohorts had similar WMLv (4.4 ± 3.2 vs. 3.2 ± 3.5 mL; p = 0.33). Also, all participants were normotensive. Therefore, the data were pooled (n = 29) to examine the association between WMLv and peripheral arterial stiffness. Following multiple linear regressions while adjusting for age and BMI, WMLv was correlated with arterial stiffness index (r 2 = 0.39, p = 0.001), strain (r 2 = 0.37, p = 0.002), carotid distensibility (r 2 = 0.36, p = 0.004), carotid compliance (r 2 = 0.26, p = 0.009), and absolute change in carotid diameter across one cardiac cycle (r 2 = 0.24, p = 0.01). Regardless of the age, BMI, and participant cohort, structural periventricular WMLv correlated with markers of arterial stiffness. These findings support the emerging hypothesis that systemic arterial stiffness affects damage in the microvasculature of the brain. Further, the resulting subcortical structural damage is apparent in older populations regardless of ageing and vascular pathology. Support or Funding Information Supported by the Canadian Institute of Health Research (201503MOP‐342412‐MOV‐CEEA). This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".