Assessment of Neurobiological Mechanisms of Cortical Thinning During Childhood and Adolescence and Their Implications for Psychiatric Disorders
Bibliographic record
Abstract
Importance: Many psychiatric disorders can be conceptualized as disorders of brain maturation during childhood and adolescence. Discovering the neurobiological underpinnings of brain maturation may elucidate molecular pathways of vulnerability and resilience to such disorders. Objective: To investigate the underlying neurobiological mechanisms of age-associated cortical thinning during maturation and their implications for psychiatric disorders. Design, Setting, and Participants: This multicohort analysis used data from 3 community-based studies. The Saguenay Youth Study provided data from 1024 adolescents who were recruited at a single site in Quebec, Canada. The IMAGEN cohort provided data from 1823 participants who were recruited in 8 European cities. The Brazil High Risk Cohort Study for the Development of Childhood Psychiatric Disorders provided data from 815 participants who were recruited in 2 Brazilian cities. Cortical thickness was estimated from the results of magnetic resonance imaging (MRI) scans, and age-associated cortical thinning was estimated in 34 cortical regions. Gene expression from the Allen Human Brain Atlas was aligned with the same regions. Similarities in the interregional profiles of gene expression and the profiles of age-associated cortical thinning were measured. The involvement of dendrites, dendritic spines, and myelin was tested using 3 gene panels. Enrichment for genes associated with psychiatric disorders was tested among the genes associated with thinning and their coexpression networks. Data analysis was conducted between March and October 2019. Main Outcomes and Measures: MRI-derived estimates of age-associated cortical thinning and gene expression in 34 cortical regions. Results: A total of 3596 individuals aged 9 to 21 years were included in this study. Of those, 1803 participants (50.1%) were female, and the mean (SD) age was 15.2 (2.6) years. Interregional profiles of age-associated cortical thinning were associated with interregional gradients in the expression of genes associated with dendrites, dendritic spines, and myelin; the variance in thinning explained by the gene panels across different points ranged from 0.45% to 10.55% for the dendrite panel, 0.00% to 9.98% for the spine panel, and 0.19% to 26.39% for the myelin panel. These genes and their coexpression networks were enriched for genes associated with several psychiatric disorders. Conclusions and Relevance: In this study, genetic similarity between interregional variation in cortical thinning during maturation and multiple psychiatric disorders suggests overlapping molecular underpinnings. This finding adds to the understanding of the neurodevelopmental mechanisms of psychiatric disorders.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".