<i>CYP2C19</i> variant mitigates Alzheimer disease pathophysiology in vivo and postmortem
Bibliographic record
Abstract
Objective To verify whether CYP polymorphisms are associated with amyloid-β (Aβ) pathology across the spectrum of clinical Alzheimer disease using in vivo and postmortem data from 2 independent cohorts. Methods A candidate-gene approach tested the association between 5 genes (28 single nucleotide polymorphisms) and Aβ load measured in vivo by the global [18F]florbetapir PET standardized uptake value ratio (SUVR) in 338 Alzheimer9s Disease Neuroimaging Initiative participants. Significant results were then tested using plasma Aβ and CSF Aβ and Aβ/phosphorylated tau (Aβ/p-tau) ratio in the same cohort. The significant association was also generalized to postmortem Aβ load measurement in the Rush Religious Orders Study/Memory and Aging Project cohorts. In addition, global cognition was used as a phenotype in the analysis in both cohorts. Results Analysis of Aβ PET identified a variant in the CYP2C19 gene (rs4388808; p = 0.0006), in which carriers of the minor allele (MA) had a lower global SUVR. A voxel-wise analysis revealed that the variant is associated with a lower Aβ load in the frontal, inferior temporal, and posterior cingulate cortices. MA carriers also had higher CSF Aβ (p = 0.003) and Aβ/p-tau ratio (p = 0.02) but had no association with Aβ plasma levels. In postmortem brains, MA carriers had a lower Aβ load (p = 0.03). Global cognition was higher in MA carriers, which was found to be mediated by Aβ. Conclusions Together, these findings point to an association between CYP2C19 polymorphism and Aβ pathology, suggesting a protective effect of the MA of rs4388808. Despite the several possibilities in which CYP2C19 affects brain Aβ, the biological mechanism by which this genetic variation may act as a protective factor merits further investigation.
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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 | 0.001 |
| 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".