Healthy Dietary Intake Diminishes the Effect of Vascular Pathology on Cognitive Performance in Older Adults
Bibliographic record
Abstract
Abstract Background Cognitive reserve (CR) in the context of Alzheimer’s’ disease has been widely studied, yet less is known about how CR protects against vascular brain pathologies. Here, we explored whether dietary factors might attenuate the association between magnetic resonance imaging (MRI)‐derived vascular biomarkers and cognition. Method Seventy‐one older adults (ages 60‐85) were scanned using a 3‐Tesla MRI Siemens Magnetom Prisma at the University of Kentucky. Data from a 3D T1‐weighted sequence, a 3D fluid‐attenuated inversion recovery sequence, and a 126‐direction diffusion MRI sequence were acquired. The vascular biomarkers used [White Matter Hyperintensity Volume (WMHV), Free Water (FW), and Peak Width of Skeletonized Mean Diffusivity (PSMD)] were developed and validated through the MarkVCID consortium ( https://markvcid.partners.org ). WMHV was computed using a 4‐tissue segmentation model, mean FW in all white matter was calculated using a two‐compartment model, and PSMD was calculated as the difference between the 95th and 5th percentiles in white matter MD values. Grey matter volume (GMV; non‐vascular biomarker) and intracranial volume (ICV) were estimated using FreeSurfer. The “Newly Developed Antioxidant Nutrient Questionnaire” was used to quantify dietary‐intake for the preceding month. Nutrients were grouped into nutrition factors based on previous literature and factor analysis (Factor 1= representing fruits and vegetables; Factor 2= representing nuts, healthy oils, and fish; Factor 3= representing green tea). All participants completed the Montreal Cognitive Assessment (MoCA). Multivariate linear regression models tested whether dietary factors, vascular biomarkers, and/or their interaction (i.e. moderation) were associated with MoCA scores. All models controlled for age, sex, ICV, and education. Result There were no significant main effects of WMHV, FW, PSMD, or GMV on MoCA scores. However, Factor 2 (but not other factors) positively moderated all 3 vascular biomarkers [WMHV (β=0.309, p=0.009); FW (β=0.324, p=0.007); PSMD (β=0.354, p=0.008)] such that a negative association between vascular markers and MoCA scores was only present in those with low but not high Factor 2 intake (Figure 1). Factor 2 did not moderate the association between non‐vascular biomarkers (i.e. GMV) and MoCA scores. Conclusion Our results suggest that consuming more nuts, healthy oils, and fish may help protect against vascular contributions to cognitive impairment.
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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 | 0.002 |
| 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 | 0.000 | 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".