Inter-Regional Variations in Gene Expression and Age-Related Cortical Thinning in the Adolescent Brain
Bibliographic record
Abstract
Age-related decreases in cortical thickness observed during adolescence may be related to fluctuations in sex and stress hormones. We examine this possibility by relating inter-regional variations in age-related cortical thinning (data from the Saguenay Youth Study) to inter-regional variations in expression levels of relevant genes (data from the Allen Human Brain Atlas); we focus on genes coding for glucocorticoid receptor (NR3C1), androgen receptor (AR), progesterone receptor (PGR), and estrogen receptors (ESR1 and ESR2). Across 34 cortical regions (Desikan-Killiany parcellation), age-related cortical thinning varied as a function of mRNA expression levels of NR3C1 in males (R2 = 0.46) and females (R2 = 0.30) and AR in males only (R2 = 0.25). Cortical thinning did not vary as a function of expression levels of PGR, ESR1, or ESR2 in either sex; this might be due to the observed low consistency of expression profiles of these 3 genes across donors. Inter-regional levels of the NR3C1 and AR expression interacted with each other vis-à-vis cortical thinning: age-related cortical thinning varied as a function of NR3C1 mRNA expression in brain regions with low (males: R2 = 0.64; females: R2 = 0.58) but not high (males: R2 = 0.0045; females: R2 = 0.15) levels of AR mRNA expression. These results suggest that glucocorticoid and androgen receptors contribute to cortical maturation during adolescence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".