Schizophrenia Following Early Adolescence Prodrome: A Neurodevelopmental Subtype With Autism-like Sensorimotor and Social Cognition Deficits
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: While age at onset in schizophrenia (SCZ) is usually defined by age at onset of psychosis, the illness actually occurs earlier, with a prodrome often starting in childhood or adolescence. We postulated that SCZ with early-adolescence prodromes (SCZ-eaP) presents with social cognition deficits and sensorimotor impairments more similar to autism spectrum disorders (ASD) than SCZ with late-adolescence prodromes (SCZ-laP). STUDY DESIGN: The movie for the assessment of social cognition and neurological soft signs (NSS) were compared between four groups, ASD, SCZ-eaP (<15 years), SCZ-laP (>15 years), and controls (N = 119), while accounting for age, sex, intelligence quotient, education level, and medication effect. Mediation analyses tested the effect of NSS on social cognition, across groups, and local gyrification indices were used to test whether NSS reflected deviations in early neurodevelopmental trajectories. STUDY RESULTS: For social cognition and NSS, subjects with ASD were not different from SCZ-eaP, while they differed from SCZ-laP. Age at onset of prodrome correlated with NSS (r = -0.34, P = .018), and social cognition (r = 0.28, P = .048). Neurological soft signs mediated social cognition impairment across diagnoses (β = -1.24, P < 1e-6), and was explained by hypergyrification in the right fusiform gyrus, right frontal pole gyrus, and left postcentral gyrus. CONCLUSIONS: Earlier age of prodrome in SCZ is associated with impaired social cognition, mediated by neurodevelopmentally-related sensorimotor impairments along the ASD-SCZ spectrum. It suggests age of prodrome, rather than the age at psychosis onset, should be considered to define more homogeneous subgroups in SCZ.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".