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Association of a Schizophrenia-Risk Nonsynonymous Variant With Putamen Volume in Adolescents

2019· article· en· W2908578463 on OpenAlexafffundabout
Qiang Luo, Qiang Chen, Wenjia Wang, Sylvane Desrivières, Erin Burke Quinlan, Tianye Jia, Christine Macare, Guillaume Robert, Jing Cui, Mickaël Guedj, Lena Palaniyappan, Ferath Kherif, Tobias Banaschewski, Arun L.W. Bokde, Christian Büchel, Herta Flor, Vincent Frouin, Hugh Garavan, Penny Gowland, Andreas Heinz, Bernd Ittermann, Jean‐Luc Martinot, Éric Artiges, Marie‐Laure Paillère Martinot, Frauke Nees, Dimitri Papadopoulos Orfanos, Luise Poustka, Juliane H. Fröhner, Michael N. Smolka, Henrik Walter, Robert Whelan, Joseph H. Callicott, Venkata S. Mattay, Zdenka Pausová, Jean‐François Dartigues, Christophe Tzourio, Fabrice Crivello, Karen F. Berman, Fēi Li, Tomáš Paus, Daniel R. Weinberger, Robin Murray, Günter Schumann, Jianfeng Feng

Bibliographic record

VenueJAMA Psychiatry · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of TorontoHospital for Sick ChildrenHolland Bloorview Kids Rehabilitation HospitalSickKids FoundationWestern University
FundersMedical Research CouncilMedizinische Universität WienInstitute of Psychiatry, Psychology and Neuroscience, King’s College LondonVetenskapsrådetUniversité Paris DescartesUniversität WienSvenska Forskningsrådet FormasUniversité Paris-SaclayFondation pour la Recherche MédicaleInstitut National de la Santé et de la Recherche MédicaleAgence Nationale de la RechercheUniversité Paris-SudUniversity of TorontoFondation de FranceRotman Research Institute, BaycrestTrinity College DublinDeutsche ForschungsgemeinschaftMission Interministérielle de Lutte Contre les Drogues et les Conduites AddictivesScience Foundation IrelandKing's College LondonTechnische Universität DresdenNational Institute for Health and Care ResearchNational Institutes of HealthNIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
KeywordsPutamenGenome-wide association studyCohortPopulationNeuroimagingSchizophrenia (object-oriented programming)MedicinePsychopathologyPsychologyPsychiatryInternal medicineGeneticsSingle-nucleotide polymorphismBiologyGenotype

Abstract

fetched live from OpenAlex

Importance: Deviation from normal adolescent brain development precedes manifestations of many major psychiatric symptoms. Such altered developmental trajectories in adolescents may be linked to genetic risk for psychopathology. Objective: To identify genetic variants associated with adolescent brain structure and explore psychopathologic relevance of such associations. Design, Setting, and Participants: Voxelwise genome-wide association study in a cohort of healthy adolescents aged 14 years and validation of the findings using 4 independent samples across the life span with allele-specific expression analysis of top hits. Group comparison of the identified gene-brain association among patients with schizophrenia, unaffected siblings, and healthy control individuals. This was a population-based, multicenter study combined with a clinical sample that included participants from the IMAGEN cohort, Saguenay Youth Study, Three-City Study, and Lieber Institute for Brain Development sample cohorts and UK biobank who were assessed for both brain imaging and genetic sequencing. Clinical samples included patients with schizophrenia and unaffected siblings of patients from the Lieber Institute for Brain Development study. Data were analyzed between October 2015 and April 2018. Main Outcomes and Measures: Gray matter volume was assessed by neuroimaging and genetic variants were genotyped by Illumina BeadChip. Results: The discovery sample included 1721 adolescents (873 girls [50.7%]), with a mean (SD) age of 14.44 (0.41) years. The replication samples consisted of 8690 healthy adults (4497 women [51.8%]) from 4 independent studies across the life span. A nonsynonymous genetic variant (minor T allele of rs13107325 in SLC39A8, a gene implicated in schizophrenia) was associated with greater gray matter volume of the putamen (variance explained of 4.21% in the left hemisphere; 8.66; 95% CI, 6.59-10.81; P = 5.35 × 10-18; and 4.44% in the right hemisphere; t = 8.90; 95% CI, 6.75-11.19; P = 6.80 × 10-19) and also with a lower gene expression of SLC39A8 specifically in the putamen (t127 = -3.87; P = 1.70 × 10-4). The identified association was validated in samples across the life span but was significantly weakened in both patients with schizophrenia (z = -3.05; P = .002; n = 157) and unaffected siblings (z = -2.08; P = .04; n = 149). Conclusions and Relevance: Our results show that a missense mutation in gene SLC39A8 is associated with larger gray matter volume in the putamen and that this association is significantly weakened in schizophrenia. These results may suggest a role for aberrant ion transport in the etiology of psychosis and provide a target for preemptive developmental interventions aimed at restoring the functional effect of this mutation.

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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.003
GPT teacher head0.207
Teacher spread0.204 · 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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Citations68
Published2019
Admission routes3
Has abstractyes

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Same venueJAMA PsychiatrySame topicGenetic Associations and EpidemiologyFrench-language works237,207