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Polygenic Risk of Psychosis and Ventral Striatal Activation During Reward Processing in Healthy Adolescents

2016· article· en· W2467590665 on OpenAlexaff
T. Lancaster, David E.J. Linden, Katherine E. Tansey, Tobias Banaschewski, Arun L.W. Bokde, Uli Bromberg, Christian Büchel, Anna Cattrell, Patricia Conrod, Herta Flor, Vincent Frouin, Jürgen Gallinat, Hugh Garavan, Penny Gowland, Andreas Heinz, Bernd Ittermann, Jean‐Luc Martinot, Marie‐Laure Paillère Martinot, Éric Artiges, Hervé Lemaître, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Michael N. Smolka, Nora C. Vetter, Sarah Jurk, Eva Mennigen, Henrik Walter, Robert Whelan, Günter Schumann

Bibliographic record

VenueJAMA Psychiatry · 2016
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of TorontoBaycrest HospitalUniversité de Montréal
FundersMedical Research CouncilAssistance publique-Hôpitaux de ParisForskningsrådet om Hälsa, Arbetsliv och VälfärdNational Institute for Health and Care ResearchFondation de FranceSvenska Forskningsrådet FormasFondation pour la Recherche MédicaleInstitut National de la Santé et de la Recherche MédicaleWellcome TrustAgence Nationale de la RechercheEuropean CommissionDeutsche ForschungsgemeinschaftKing's College LondonNational Institutes of HealthNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
KeywordsPsychosisVentral striatumPsychologyImpulsivityFunctional magnetic resonance imagingExperience sampling methodStriatumPsychiatryClinical psychologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

IMPORTANCE: Psychotic disorders are characterized by attenuated activity in the brain's valuation system in key reward processing areas, such as the ventral striatum (VS), as measured with functional magnetic resonance imaging. OBJECTIVE: To examine whether common risk variants for psychosis are associated with individual variation in the VS. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional study of a large cohort of adolescents from the IMAGEN study (a European multicenter study of reinforcement sensitivity in adolescents) was performed from March 1, 2008, through December 31, 2011. Data analysis was conducted from October 1, 2015, to January 9, 2016. Polygenic risk profile scores (RPSs) for psychosis were generated for 1841 healthy adolescents. Sample size and characteristics varied across regression analyses, depending on mutual information available (N = 1524-1836). MAIN OUTCOMES AND MEASURES: Reward-related brain function was assessed with blood oxygen level dependency (BOLD) in the VS using the monetary incentive delay (MID) task, distinguishing reward anticipation and receipt. Behavioral impulsivity, IQ, MID task performance, and VS BOLD were regressed against psychosis RPS at 4 progressive P thresholds (P < .01, P < .05, P < .10, and P < .50 for RPS models 1-4, respectively). RESULTS: In a sample of 1841 healthy adolescents (mean age, 14.5 years; 906 boys and 935 girls), we replicated an association between increasing psychosis RPS and reduced IQ (matrix reasoning: corrected P = .003 for RPS model 2, 0.4% variance explained), supporting the validity of the psychosis RPS models. We also found a nominally significant association between increased psychosis RPS and reduced MID task performance (uncorrected P = .03 for RPS model 4, 0.2% variance explained). Our main finding was a positive association between psychosis RPS and VS BOLD during reward anticipation at all 4 psychosis RPS models and for 2 P thresholds for reward receipt (RPS models 1 and 3), correcting for the familywise error rate (0.8%-1.9% variance explained). CONCLUSIONS AND RELEVANCE: These findings support an association between psychosis RPS and VS BOLD in adolescents. Genetic risk for psychosis may shape an individual's response to rewarding stimuli.

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)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.011
GPT teacher head0.290
Teacher spread0.279 · 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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Citations49
Published2016
Admission routes1
Has abstractyes

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