Abstract 4144467: Associations between High-density Lipoprotein Cholesterol Efflux and Brain Health
Bibliographic record
Abstract
Previous studies have linked plasma levels of high-density lipoprotein cholesterol (HDL-C) with impaired cognitive function. However, few studies have investigated the associations between plasma HDL functionality and brain structure and function. Thus, our study aimed to elucidate the associations between plasma HDL measures and brain structure/function in a multiethnic cohort of middle-aged adults. Accordingly, we conducted a cross-sectional study in 1,826 adults (mean age 51.0±9.7 years, 58% female, 47% Black adults) without preexisting cardiovascular disease or stroke who participated in the Dallas Heart Study to determine associations between HDL measures and brain structure/function. Whole brain white matter hyperintensities (WMH) and grey matter volume (GMV) was measured using a 3-T MRI scanner and normalized to total cranial volume (TCV), and the Montreal Cognitive Assessment (MoCA) was used to measure cognition. HDL cholesterol efflux capacity (HDL-CEC) was assessed using fluorescence-labeled cholesterol efflux from J774 macrophages and was expressed in arbitrary units. HDL particle measures were assessed using NMR spectroscopy. Adjusted multivariable linear regression models were performed with standardized beta estimates reported. Higher HDL-CEC and small HDL particles (HDL-P) were positively associated with GMV/TCV after adjustment for relevant risk factors (β=0.078 [95% CI: 0.029, 0.126], Figure , and β=0.063 [95% CI: 0.014, 0.111], respectively, all p<0.05). Conversely, there were no associations between HDL measures and WMH or MoCA after adjustment (all p>0.05). Associations of HDL-CEC and small HDL-P with GMV were not modified by race/ethnicity or ApoE-ε4 status. In conclusion, higher HDL function and small HDL-P were associated with higher GMV after adjustment for traditional risk factors and were not modified by race/ethnicity or ApoE-ε4 carrier status. As such, these findings suggest that better HDL functionality is linked with larger brain GM volume in middle-aged adults. Since GMV loss has been linked to the development of mild cognitive impairment (MCI) and conversion of MCI to Alzheimer's disease, our study may have implications for prevention of age-related decline in cognitive function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".