Associations of MAP2K3 Gene Variants With Superior Memory in SuperAgers
Bibliographic record
Abstract
Introduction: SuperAgers are adults age 80+ with episodic memory performance that is at least as good as that of average middle-aged adults. Understanding the biological determinants of SuperAging may have relevance to preventing age-related cognitive decline and dementia. This study aimed to identify associations between genetic variations and the SuperAging phenotype using Whole Exome Sequencing (WES). Methods: Sequence Kernel Association Combined (SKAT-C) test was conducted at the gene level including both rare and common variants in 56 SuperAgers and 22 cognitively-average controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Results: The SuperAging phenotype was associated with variants in the Mitogen-Activated Protein Kinase Kinase 3 (MAP2K3) gene. Three single nucleotide polymorphisms (SNPs) contributed to the significance (rs2363221 [intron 1], rs2230435 [exon 5], rs736103 [intron 7]). Conclusions: MAP2K3 resides in a biological pathway linked to memory. It is in a signaling cascade associated with beta-amyloid mediated apoptosis and has enriched expression in microglia. This preliminary work suggests MAP2K3 may represent a novel therapeutic target for age-related memory decline and perhaps Alzheimer’s disease.
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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 | 0.001 |
| 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) | 0.004 | 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".