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Record W4411124100 · doi:10.1101/2025.06.07.658415

Neurodevelopmental Impact of Bipolar Disorder Genetic Risk on Cortical Thickness and Network Topology in Adolescents

2025· preprint· en· W4411124100 on OpenAlexaff
Xiaobo Liu, Lang Liu, Jiadong Yan, Jinzhi He, Bin Wan, Ruiyang Ge, Jinming Xiao, Guoyuan Yang

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British ColumbiaMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsBipolar disorderTopology (electrical circuits)PsychologyComputer scienceNeuroscienceCognitionEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Bipolar disorder (BD) is a highly heritable psychiatric condition characterized by recurrent mood episodes that commonly manifest during adolescence. Although polygenic risk scores (PRS) effectively quantify genetic susceptibility to BD, the neurobiological correlates of this genetic risk during adolescent brain development remain unclear. Using normative modeling and longitudinal neuroimaging data from the Adolescent Brain Cognitive Development (ABCD) cohort (N = 4519), we examined cortical thickness (CT) deviations and structural covariance network (SCN) alterations in adolescents stratified into high and low BD genetic risk groups based on PRS. Adolescents with high PRS for bipolar disorder exhibited greater cortical thickening in the inferior frontal gyrus and primary visual cortex, whereas those with low PRS demonstrated greater thickening in the posterior cingulate cortex and middle precentral gyrus. These patterns suggest PRS-related variations in cortical maturation, potentially reflecting distinct neurodevelopmental trajectories associated with genetic susceptibility to bipolar disorder. Furthermore, high PRS individuals displayed altered SCN topology, characterized by decreased local clustering and enhanced global network efficiency. Longitudinal data show that these abnormal regions exhibit atypical developmental trajectories, accompanied by a global reorganization of network topology. Additionally, high genetic risk was associated with lifestyle factors, especially correlated with increased positive expectancies toward substance use. Eventually, we found three potential BD risk genes during adolescence, including PLEKHA2, ZSCAN31 and ANK3, encoding the function of the postsynaptic membrane and synaptic membrane. These findings elucidate early neurodevelopmental deviations linked to genetic risk for BD, highlighting potential biomarkers for early identification and targeted interventions.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.009
GPT teacher head0.247
Teacher spread0.238 · 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 designObservational
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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