Plasma NfL and cognitive functioning in older adults: The moderating role of HDL cholesterol
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Plasma neurofilament light chain (NfL) is a marker of neuroaxonal injury associated with cognitive decline. High-density lipoprotein (HDL) cholesterol has neuroprotective properties, but its interaction with neurodegeneration remains unclear. This study examined whether HDL moderates the association between NfL and cognitive performance. METHODS: Baseline data from 417 participants in the Aging Adult Brain Connectome study were analyzed. Plasma NfL and HDL were measured via Simoa and enzymatic assays; cognition was assessed using Montreal Cognitive Assessment (MoCA) and Preclinical Alzheimer Cognitive Composite (PACC). Generalized linear models were used to evaluate NfL and HDL interactions, adjusting for demographics. Sensitivity analyses included apolipoprotein E ε4, body mass index, total cholesterol, LDL, and triglycerides. RESULTS: = 0.004), indicating HDL moderates the negative association between NfL and cognition. DISCUSSION: These findings suggest that HDL modifies the cognitive impact of neurodegeneration, highlighting the importance of metabolic-neurological interactions. Highlights: High-density lipoprotein (HDL) cholesterol moderates the negative association between plasma neurofilament light chain (NfL) and cognition.Higher HDL levels intensify the negative effect of NfL on cognitive performance.Findings challenge the assumption of HDL's uniformly protective role.Results support the integrated use of metabolic and neurodegenerative biomarkers.
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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) | 0.000 | 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) | 0.001 | 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".