Association of Arterial Stiffness Index and Brain Structure in the UK Biobank: A 10-Year Retrospective Analysis.
Bibliographic record
Abstract
Arterial stiffening and changes in brain structure both occur with normal aging and can be exacerbated via acquired health conditions. While cross-sectional associations exist, the longitudinal relationship between arterial stiffness and brain structure remains unclear. In this study, we investigated 1) associations between baseline arterial stiffness index (ASI) and brain structure (global and regional grey matter volumes (GMV), white matter hyperintensities (WMH)) 10-years post-baseline (10.4±0.8 years) and 2) associations between the 10-year change in ASI from baseline and brain structure 10-years post-baseline in 650 healthy middle- to older-aged adults (53.4±7.5 years) from the UK Biobank. We observed significant associations between baseline ASI and GMV (p<0.001) and WMH (p=0.0036) 10-years post-baseline. No significant associations between 10-year change in ASI and brain structure (global GMV p=0.24; WMH volume p=0.87) were observed. There were significant associations of baseline ASI in 2 of 60 regional brain volumes analyzed (right posterior superior temporal gyrus p=0.001; left superior lateral occipital cortex p<0.001). Strong associations with baseline ASI, but not changes in ASI over 10-years, suggest arterial stiffness at the entry point of older adulthood is more impactful on brain structure 10-years later compared to age-related stiffening. Based on these associations, we suggest clinical monitoring and potential intervention for reducing arterial stiffness should occur in midlife to reduce vascular contributions to structural changes in the brain, supporting a healthy trajectory of brain aging. Our findings also support use of ASI as a surrogate for gold standard measures in showing overall relationships between arterial stiffness and brain structure.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".