Blood pressure variability, central autonomic network dysfunction and cerebral small vessel disease in APOE4 carriers
Bibliographic record
Abstract
Abstract Background Increased blood pressure variability (BPV) is a risk factor for cerebral small vessel disease (CSVD) and neurodegeneration, independent of age and average blood pressure, particularly in apolipoprotein E4 ( APOE4 ) carriers. However, it remains uncertain whether BPV elevation is a cause or a consequence of vascular brain injury, or to what degree injury to the central autonomic network (CAN) may contribute to BPV-associated risk in APOE4 carriers. Methods Independently living older adults (n=70) with no history of stroke or dementia were recruited from the community and underwent 5 minutes of resting beat-to-beat blood pressure monitoring, genetic testing, and brain MRI. Resting BPV, APOE genotype, CSVD burden on brain MRI, and resting state CAN connectivity by fMRI were analyzed. Causal mediation and moderation analysis evaluated BPV and CAN effects on CSVD in APOE4 carriers (n=37) and non-carriers (n=33). Results Higher BPV was associated with the presence and extent of CSVD in APOE4 carriers, but not non-carriers, independent of CAN connectivity ( B = 18.92, P = .02), and CAN connectivity did not mediate the relationship between BPV and CSVD. In APOE4 carriers, CAN connectivity moderated the relationship between BPV and CSVD, whereby BPV effects on CSVD were greater in those with lower CAN connectivity ( B = 36.43, P = .02). Conclusions Older APOE4 carriers with higher beat-to-beat BPV exhibit more extensive CSVD, independent of average blood pressure, and the strength of CAN connectivity does not mediate these effects. Findings suggest increased BPV is more likely a cause, not a consequence, of CSVD. BPV is more strongly associated with CSVD in APOE4 carriers with lower rsCAN connectivity, suggesting CAN dysfunction and BPV elevation may have synergistic effects on CSVD. Further studies are warranted to understand the interplay between BPV and CAN function in APOE4 carriers.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".