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T8. INSULIN ASSOCIATED VENTRAL TEGMENTAL AREA EXPRESSION-BASED POLYGENIC SCORE PREDICTS ADULT PSYCHIATRIC-CARDIOMETABOLIC COMORBIDITY AFTER PRENATAL ADVERSITY

2025· article· en· W4414824323 on OpenAlexaffabout
Ameyalli Gómez‐Ilescas, Guillaume Elgbeili, Nicholas O’Toole, Irina Pokhvisneva, Patrícia Pelufo Silveira

Bibliographic record

VenueEuropean Neuropsychopharmacology · 2025
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsDouglas Mental Health University InstituteMcGill University
Fundersnot available
KeywordsVentral tegmental areaImpulsivityBrain stimulation rewardDopaminergicPolygenic risk scoreGestational diabetesCREB1Candidate geneOffspringObesity

Abstract

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Background Psychiatric patients exhibit elevated prevalence of obesity and cardiometabolic disorders, traits that also demonstrate substantial heritability and a potential genetic overlap in the brain. Emerging evidence indicates that prenatal adversity may sensitize midbrain reward circuits, promoting dysfunctional signaling linked to childhood impulsivity and persistent overeating, which may contribute to an increased risk of adult metabolic and psychiatric disorders. Notably, not everyone exposed to early life adversity will develop behavioral alterations or adult diseases, therefore simply using a history of adversity exposure is not enough to identify individuals at risk. Brain insulin signaling has been suggested as a mediator of the effects of prenatal adversity on neurodevelopment and behavior, with long-term consequences on physical and mental health. Since the ventral tegmental area/substantia nigra (VTA) integrates dopaminergic and metabolic signals, where insulin receptors (IR) are found on dopaminergic neurons, we propose that IR-function associated genetic variants (SNPs) in the VTA could moderate the effect on prenatal adversity on the risk for childhood impulsivity and adult metabolic-psychiatric disorders. Methods Available rodent brain mass spectrometry data was used to identify a network of proteins binding to the IR in brain cells nuclei. Characterization of the network was performed by gene ontology terms (GO), nested cluster analysis and drug-gene interactions (DGIdb). SNPs associated to the genes from the protein network were mapped and weighted by their expression in the VTA/SN (GTEx), and then used to calculate an expression-based polygenic score (mssIR-ePRS) in two different human cohorts. We used low birth weight (LBW) as an indicator of prenatal adversity to investigate how IR-function associated genetic background influences early-life adversity associated outcomes. In the Canadian MAVAN birth cohort, infant reflective-impulsivity was assessed at 48 months using the Information Sampling Task (IST), while mental and cardiometabolic comorbidities were evaluated in adulthood within the UK Biobank cohort. Results We observed an enrichment of GO terms related to DNA binding, suggesting that this network captures the IR’s ability to act as a transcription factor. Nested cluster analysis identified four clusters of protein complexes, with some of the nodes being drug targets of diabetes and hypercholesterolemia related treatments. mssIR-ePRS moderated the association between LBW and reflective-impulsivity in MAVAN (βˆ= 0.17, p = .043, N=288). In which LBW was associated with high impulsivity only in participants with high mssIR-ePRS (βˆ= 0.22, p = 0.05), suggesting that mssIR-ePRS captures individual susceptibility to prenatal adversity. In adults from UK Biobank, LBW was associated with higher risk of having mental and cardio-metabolic co-morbidities especially in those with high mssIR-ePRS scores (βˆ= -0.25, p < 0.001, N=225,839). Discussion These results provide a developmental explanation to the comorbidity of psychiatric and cardiometabolic disorders, confirming that brain insulin function plays a key role in defining long-term risk for childhood behavioral alterations and adult chronic diseases. Our biologically informed polygenic score method is able to identify gene-environment interactions and may be useful in informing vulnerability.

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 score0.008
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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