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Record W2265594191 · doi:10.1038/ncomms9559

Genome-wide association study identifies multiple susceptibility loci for glioma

2015· review· en· W2265594191 on OpenAlexafffund
Ben Kinnersley, Marianne Labussière, Amy Holroyd, Anna Luisa Di Stefano, Peter Broderick, Jayaram Vijayakrishnan, Karima Mokhtari, Jean‐Yves Delattre, Konstantinos Gousias, Johannes Schramm, Minouk J. Schoemaker, Sarah Fleming, Stefan Herms, Stefanie Heilmann‐Heimbach, Stefan Schreiber, Heinz‐Erich Wichmann, Markus M. Nöthen, Anthony J. Swerdlow, Mark Lathrop, Matthias Simon, Melissa L. Bondy, Marc Sanson, Richard S. Houlston

Bibliographic record

VenueNature Communications · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsMcGill Genome Centre
FundersNational Cancer InstituteMedical Research CouncilInstitut National Du CancerDeutsche KrebshilfeAlfried Krupp von Bohlen und Halbach-StiftungMünchner Zentrum für GesundheitswissenschaftenWellcome TrustAgence Nationale de la RechercheFondation ARC pour la Recherche sur le CancerNational Institute for Health and Care ResearchBundesministerium für Bildung und ForschungMinistère de l'Education Nationale, de l'Enseignement Superieur et de la RechercheDeutsche ForschungsgemeinschaftCancer Research UKHealth and Safety ExecutiveEuropean CommissionUniversity of Texas MD Anderson Cancer CenterSir John Fisher FoundationMcGill University
KeywordsGenome-wide association studyGliomaGenotypingGenetic association1000 Genomes ProjectBiologyImputation (statistics)GeneticsGenomeComputational biologyLinkage disequilibriumSingle-nucleotide polymorphismGenotypeGeneComputer scienceMissing data

Abstract

fetched live from OpenAlex

Previous genome-wide association studies (GWASs) have shown that common genetic variation contributes to the heritable risk of glioma. To identify new glioma susceptibility loci, we conducted a meta-analysis of four GWAS (totalling 4,147 cases and 7,435 controls), with imputation using 1000 Genomes and UK10K Project data as reference. After genotyping an additional 1,490 cases and 1,723 controls we identify new risk loci for glioblastoma (GBM) at 12q23.33 (rs3851634, near POLR3B, P=3.02 × 10(-9)) and non-GBM at 10q25.2 (rs11196067, near VTI1A, P=4.32 × 10(-8)), 11q23.2 (rs648044, near ZBTB16, P=6.26 × 10(-11)), 12q21.2 (rs12230172, P=7.53 × 10(-11)) and 15q24.2 (rs1801591, near ETFA, P=5.71 × 10(-9)). Our findings provide further insights into the genetic basis of the different glioma subtypes.

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.652
Threshold uncertainty score1.000

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 science0.0020.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.348
Teacher spread0.313 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations137
Published2015
Admission routes2
Has abstractyes

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