Neurostructural and cognitive signatures of novel polygenic risk scores for molecular brain aging
Bibliographic record
Abstract
Abstract The world population is shifting sharply toward an older-age demographic. To navigate the escalating burden of physical and cognitive decline common to aging, and heightened risk of neurodegenerative and neuropsychiatric disease, we require advances in treatment and prevention interventions. These advances are predicated on attaining a deeper understanding of the molecular processes underlying brain aging. Here, we employed novel GWAS and cis-eQTL-based polygenic risk scores ( GWAS AGE-PRS and cis-eQTL AGE-PRS) indexing genetic risk for accelerated molecular brain aging, and examined their associations with cortical thickness and performance in age-sensitive cognitive domains in 31 384 participants (16 392 women, age 64.1±7.65) from the UK Biobank. While GWAS AGE-PRS was nominally associated with lower cortical thickness in frontotemporal regions, cis-eQTL AGE-PRS displayed robust associations with greater cortical thickness in age-sensitive frontal, temporal, and parietal regions, including the left and right precentral (pFDR<0.0001, pFDR=0.05), left insula (pFDR=0.05), as well as the right supramarginal (pFDR=0.05) and precuneus (pFDR=0.05) regions. Similar pFDR trending associations occurred bilaterally in the caudal middle frontal (pFDR=0.052, pFDR=0.078) and right insula (pFDR=0.071). These structural findings co-occurred alongside increased executive function performance on the Trail Making Test B (pFDR=0.035), suggesting a potential neurostructural and cognitive reserve phenotype. This resilience profile may reflect previously uncharacterized pathways of brain reserve in age-related pathology, informing future translational research identifying novel treatment and prevention targets.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".