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Record W2799368344 · doi:10.1002/gepi.22122

Genetic associations with childhood brain growth, defined in two longitudinal cohorts

2018· article· en· W2799368344 on OpenAlex
Eszter Székely, T.‐H. Schwantes‐An, Cristina M. Justice, Jeremy Sabourin, Philip R. Jansen, Ryan L. Muetzel, Wendy Sharp, Henning Tiemeier, Heejong Sung, Tonya White, Alexander F. Wilson, Philip Shaw

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGenetic Epidemiology · 2018
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsMcGill University
FundersNational Human Genome Research InstituteNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteNational Institutes of HealthNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsGenome-wide association studyNeuroanatomyBiologySingle-nucleotide polymorphismGenetic associationGeneticsCohortTemporal cortexSNPWhite matterBrain sizeNeuroscienceAttention deficit hyperactivity disorderPsychologyMedicinePsychiatryInternal medicineMagnetic resonance imagingGeneGenotype

Abstract

fetched live from OpenAlex

ABSTRACT Genome‐wide association studies (GWASs) are unraveling the genetics of adult brain neuroanatomy as measured by cross‐sectional anatomic magnetic resonance imaging (aMRI). However, the genetic mechanisms that shape childhood brain development are, as yet, largely unexplored. In this study we identify common genetic variants associated with childhood brain development as defined by longitudinal aMRI. Genome‐wide single nucleotide polymorphism (SNP) data were determined in two cohorts: one enriched for attention‐deficit/hyperactivity disorder (ADHD) ( LONG cohort: 458 participants; 119 with ADHD) and the other from a population‐based cohort ( Generation R : 257 participants). The growth of the brain's major regions (cerebral cortex, white matter, basal ganglia, and cerebellum) and one region of interest (the right lateral prefrontal cortex) were defined on all individuals from two aMRIs, and a GWAS and a pathway analysis were performed. In addition, association between polygenic risk for ADHD and brain growth was determined for the LONG cohort. For white matter growth, GWAS meta‐analysis identified a genome‐wide significant intergenic SNP (rs12386571, P = 9.09 × 10 −9 ), near AKR1B10 . This gene is part of the aldo‐keto reductase superfamily and shows neural expression. No enrichment of neural pathways was detected and polygenic risk for ADHD was not associated with the brain growth phenotypes in the LONG cohort that was enriched for the diagnosis of ADHD. The study illustrates the use of a novel brain growth phenotype defined in vivo for further study.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.041
GPT teacher head0.343
Teacher spread0.302 · 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