Common and Disorders-Specific Cortical Thickness Alterations in Internalizing, Externalizing and Thought Disorders over a 2-year Period in the Preadolescents of the ABCD Study
Bibliographic record
Abstract
Abstract Overlap of brain changes across mental disorders has reinforced transdiagnostic models. However, the developmental basis for this overlap is unclear as are neural differences among internalizing, externalizing and thought disorders. These issues are critical to inform the theoretical framework for hierarchical transdiagnostic psychiatric taxonomy. We examined cortical thickness (CT) difference between healthy controls (n=4041) and patients with externalizing (n=1182), internalizing (n=1959) and thought (n=347) disorders in preadolescents (9-10 years) from the Adolescent Brain and Cognitive Development Study using linear mixed models. Genome-wide association analysis and cell type specificity analysis were performed on regional CT across 4,716 unrelated European youth. We found that youth with externalizing or internalizing disorders, but not thought disorders, exhibited significantly thicker cortex than controls. Externalizing and internalizing disorders shared thicker CT in left pars opercularis and caudal middle frontal gyrus related to lower cognitive performance. Somatosensory and primary auditory cortex were uniquely affected in externalizing disorders; primary motor cortex and higher-order visual association areas were uniquely affected in internalizing disorders. Only group of externalizing disorders demonstrated significant CT increase than controls at 2-year follow-up and decelerated cortical thinning from 10 to 12 years old. At genetic level, genes associated with CT in common and disorders-specific regions were also implicated in related diagnostic families. Microglia were the cell-type associated with CT for both externalizing/internalizing while dopaminergic/glutamatergic/GABAergic cells related only to externalizing-specific regions. These results showed that distinct anatomical trajectories relevant to internalizing/externalizing phenotypes may result from unique genetic and cell-type changes, but these occur in the background of significantly shared morphological variance.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".