Brain cholesterol metabolism in Alzheimer's disease: Insights from ADNI and the UK BioBank
Bibliographic record
Abstract
BACKGROUND: Brain cholesterol metabolism plays a critical role in maintaining neuronal health and cognitive function. The CYP46A1 gene encodes cholesterol 24-hydroxylase, which converts brain cholesterol to 24S-hydroxycholesterol (24S-HOC), a metabolite that can pass the blood brain barrier. In Alzheimer's disease (AD) and vascular dementia, minor allele variants of CYP46A1, including rs3742376-C>T, rs4900442-C>T, rs7157609-G>A, and rs754203-A>G, have been associated with increased peripheral blood 24S-HOC concentrations, indicative of impaired brain cholesterol metabolism. However, it is unclear how brain cholesterol metabolism is associated with AD-specific markers, cognitive function and dementia risk. METHOD: Using the Alzheimer's Disease Neuroimaging Initiative (ADNI), and UK Biobank (UKB) datasets, we conducted a candidate gene study with the four CYP46A1 variants previously associated with increased 24S-HOC production (Table 1). In ADNI, linear regressions were used to investigate the association between the CYP46A1 variants and AD biofluid markers (amyloid-beta, phospho-tau, neurofilament light [NfL], and glial fibrillary acid protein). Linear mixed models were used to investigate the association between CYP46A1 variants and cognition (language, memory, executive function, and attention). All analyses were stratified by cognitively normal (CN), mild cognitive impairment, and AD, and adjusted for age, sex, MMSE, and apolipoprotein (APOE) ε4 allele status. In UKB, Cox proportional hazards models were used to investigate the association between CYP46A1 variants and dementia risk in participants dementia-free at baseline (age≥55). All analyses were performed using additive genetic models. Covariates included age, sex, APOEε4 allele status, hypertension, dyslipidemia, smoking history, obesity, and diabetes. RESULT: In ADNI (N = 702), CYP46A1 minor allele variants were significantly associated with lower amyloid-beta, higher p-tau, and higher NfL (Table 2). In CN individuals, these variants were also associated with poorer cognition in language, memory, and executive function (Table 3). In UKB (N = 26,620), the minor C allele of rs4900442 was associated with increased 15-year dementia risk [HR(95% CI): 1.17 (1.02-1.34), p = .03] compared to non-carriers. CONCLUSION: These findings implicate brain cholesterol metabolism in cognitive decline and dementia risk, with specific effects on AD pathophysiology. Brain cholesterol metabolism is implicated as a potential pathway for targeted preventative and therapeutic intervention strategies.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".