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Record W4409322696 · doi:10.1101/2025.04.08.25325481

A Novel Diathesis-Stress Model of Comorbid Early Onset Psychiatric Disorders

2025· preprint· en· W4409322696 on OpenAlexaff
Charlotte Bowers Caswell, Niki Hosseini‐Kamkar, Sylvia M L Cox, Nicole Palacio Prada, Maisha Iqbal, Maja Nikolic, Tobias Banaschewski, Gareth J. Barker, Arun L.W. Bokde, Rüdiger Brühl, Sylvane Desrivières, Herta Flor, Hugh Garavan, Penny Gowland, Antoine Grigis, Andreas Heinz, Jean-Luc Martinot, Marie‐Laure Paillère Martinot, Éric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Luise Poustka, Michael N. Smolka, Sarah Hohmann, Nilakshi Vaidya, Henrik Walter, Robert Whelan, Günter Schumann, Tomáš Paus, Marco Leyton

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineMental Health Research CanadaMcGill University
FundersHORIZON EUROPE Framework ProgrammeUK Research and Innovation
KeywordsPsychologyPsychiatryVentral striatumAnterior cingulate cortexPutamenClinical psychologyPopulationCohortMedicineInternal medicineStriatumNeuroscienceDopamineCognition

Abstract

fetched live from OpenAlex

ABSTRACT Importance Psychiatric comorbidity is the norm. Identifying transdiagnostic risk factors will inform our understanding of developmental pathways and early intervention targets. Objective We recently reported that many psychiatric outcomes are predicted by a three-factor model composed of adolescent externalizing (EXT) behaviors, early life adversity, and dopamine autoreceptor availability. Here, we investigated whether this model could be reproduced in a large population-based sample using functional magnetic resonance imaging (fMRI) instead of positron emission tomography. Design Data were collected by the IMAGEN consortium beginning in 2010 when cohort members were 14 years old, with follow-up testing at ages 16 and 19. These longitudinal data were used to predict psychiatric disorders by 19 years of age. Setting Participants were recruited from secondary schools across Europe. Participants Adolescents (n = 1338) with fMRI, behavioural, diagnostic, and early life trauma data. Main Outcomes and Measures Binary regression models tested whether a combination of EXT behaviors, childhood trauma, and mesocorticolimbic reward anticipation responses at age 14 or 19 predicted the presence of a disorder by age 19. Results A total of 1338 participants had the required data (52.4% female). In all models, EXT and adversity scores were significant predictors ( p < 0.001). Reward anticipation responses in the ventral striatum, caudate, putamen, and anterior cingulate cortex (ACC) at age 14 ( p ≤ 0.05) and in the ventral striatum at age 19 ( p ≤ 0.029) were predictors in their respective models. The three- factor models overall were highly significant ( p < 1.0 x 10 -21 ), yielding greater predictive strength than each factor alone. They had an accuracy of nearly 75%, accounting for ≥ 11% (Nagelkerke R 2 ) of the variance in psychiatric disorders. The relationship between trauma and diagnoses was partially mediated by higher EXT (indirect path B = 0.0535, 95% CI = 0.0301- 0.0835), and moderated by fMRI responses in the ACC ( p = 0.0038) and putamen ( p = 0.0135) at age 14. Conclusions and Relevance The results extend our previous findings, increasing confidence in a novel diathesis-stress model of commonly comorbid early onset psychiatric disorders. The results have implications for diagnostic classification schemes and pleiotropic views of psychiatric disorder etiology. Key Points Question What factors contribute to a diathesis-stress model of commonly comorbid psychiatric disorders? Findings A combination of childhood adversity, adolescent externalizing behavior, and lower mesocorticolimbic reward cue reactivity predicted psychopathology by age 19 in a large population-based cohort. Liability was modified by interactions between trauma and mesocorticolimbic responses, with trauma effects larger in those with smaller striatal and anterior cingulate cortex responses. Meaning The study identifies a transdiagnostic diathesis-stress model of early onset 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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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.

Opus teacher head0.028
GPT teacher head0.288
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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