Polymorphism in the MAGI2 Gene Modifies the Effect of Amyloid β on Neurodegeneration
Bibliographic record
Abstract
INTRODUCTION: A weak association between amyloid β (Aβ) deposition and neurodegeneration biomarkers, such as brain atrophy, has been repeatedly reported in a subset of patients with Alzheimer disease, suggesting individual differences in response to Aβ deposition. METHODS: Here, we performed a genome-wide interaction study to identify single-nucleotide polymorphism (SNP) that modify the effect of Aβ (measured by 18F-florbetapir positron emission tomography) on brain atrophy (measured by cortical thickness using magnetic resonance imaging). We used magnetic resonance imaging, positron emission tomography, cerebrospinal fluid, and genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database [discovery cohort, ADNI-GO/2 (n=723) and replication cohort, ADNI-1 (n=129)]. RESULTS: We identified a genome-wide suggestive interaction of rs3807779 SNP (β=-0.14, SE=0.029, P=9.08×10-7) in the discovery cohort. The greater dosage of rs3807779 SNP increased the detrimental effect of Aβ deposition on cortical thickness. In replication analyses, the congruent results were replicated to confirm our findings. Furthermore, rs3807779 SNP augmented the detrimental effect of Aβ deposition on cognitive function. Genetic profiling showed that rs3807779 has chromatin interactions with the promoter region of MAGI2 gene, suggesting its association with MAGI2 expression. CONCLUSIONS: These findings demonstrate that subjects carrying the rs3807779 SNP are more susceptible to Aβ-related neurodegeneration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".