Ceramide Accumulation Is Associated with Declining Verbal Memory in Coronary Artery Disease Patients: An Observational Study
Bibliographic record
Abstract
BACKGROUND: Biomarkers in cognitively vulnerable populations, like those with coronary artery disease (CAD), may inform earlier intervention in vascular neurodegeneration. Circulating ceramide C18:0 (CerC18:0) is associated with changes in verbal memory in early neurodegeneration and CAD progression. OBJECTIVE: To investigate whether plasma CerC18:0 accumulation is associated with longitudinal declines in verbal memory performance in CAD. METHODS: In addition to total CerC18:0, we assessed its relative abundance to its precursors as ratios: CerC18:0 to monohexosylceramide C18:0 (MHxCer18:0), CerC18:0 to sphingomyelin C18:0 (SM18:0), and CerC18:0 to sphingosine-1-phosphate (S1P). Verbal memory was assessed using the California Verbal Learning Test 2nd Ed. Using mixed models in 60 CAD participants, we evaluated associations between baseline CerC18:0 ratios and changes in verbal memory performance, adjusting for age, body mass index, and education. Given that cognitive decline is more rapid following onset of deficits, these associations were compared between those with possible mild vascular neurocognitive disorder (MVND). RESULTS: Increased baseline CerC18:0 concentrations correlated with worse verbal memory performance over time (b[SE] = - 0.91[0.30], p = 0.003). Increased baseline CerC18:0/SM18:0 (b[SE] = - 1.11[`], p = 0.03) were associated with worse verbal memory performance over time. These associations were not mediated by whether or not patients had possible MVND at baseline. CONCLUSION: These findings support aberrant CerC18:0 metabolism as an early neurobiological change in vascular neurodegeneration. Future studies should measure enzymes responsible for conversion of sphingolipid precursors into CerC18:0 to assess enzymatic activity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".