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Record W2026386906 · doi:10.1007/s00439-009-0643-8

Analyses of associations with asthma in four asthma population samples from Canada and Australia

2009· article· en· W2026386906 on OpenAlexafffundabout
Denise Daley, Mathieu Lemire, Loubna Akhabir, Moira Chan‐Yeung, Jian‐Qing He, Treena McDonald, Andrew J. Sandford, Dorota Stefanowicz, Ben Tripp, David Zamar, Yohan Bossé, Vincent Ferretti, Alexandre Montpetit, Marie-Catherine Tessier, Allan B. Becker, Anita L. Kozyrskyj, John Beilby, Pamela A. McCaskie, Bill Musk, Nicole M. Warrington, Catherine Laprise, Lyle J. Palmer, Peter D. Paré, Thomas J. Hudson

Bibliographic record

VenueHuman Genetics · 2009
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversité du Québec à ChicoutimiManitoba HealthUniversity of ManitobaUniversité de MontréalUniversité LavalOntario Institute for Cancer ResearchInstitut universitaire de cardiologie et de pneumologie de QuébecMcGill University and Génome Québec Innovation CentreUniversity of British Columbia
FundersNational Health and Medical Research CouncilCanadian Institutes of Health ResearchMedical Research CouncilHealthwayBritish Columbia Lung AssociationBurroughs Wellcome Fund
KeywordsAtopySingle-nucleotide polymorphismCandidate geneBiologyAsthmaGeneticsGenetic associationGenotypingSNPAllelePopulationImmunologyGeneGenotypeMedicine

Abstract

fetched live from OpenAlex

Asthma, atopy, and related phenotypes are heterogeneous complex traits, with both genetic and environmental risk factors. Extensive research has been conducted and over hundred genes have been associated with asthma and atopy phenotypes, but many of these findings have failed to replicate in subsequent studies. To separate true associations from false positives, candidate genes need to be examined in large well-characterized samples, using standardized designs (genotyping, phenotyping and analysis). In an attempt to replicate previous associations we amalgamated the power and resources of four studies and genotyped 5,565 individuals to conduct a genetic association study of 93 previously associated candidate genes for asthma and related phenotypes using the same set of 861 single-nucleotide polymorphisms (SNPs), a common genotyping platform, and relatively harmonized phenotypes. We tested for association between SNPs and the dichotomous outcomes of asthma, atopy, atopic asthma, and airway hyperresponsiveness using a general allelic likelihood ratio test. No SNP in any gene reached significance levels that survived correction for all tested SNPs, phenotypes, and genes. Even after relaxing the usual stringent multiple testing corrections by performing a gene-based analysis (one gene at a time as if no other genes were typed) and by stratifying SNPs based on their prior evidence of association, no genes gave strong evidence of replication. There was weak evidence to implicate the following: IL13, IFNGR2, EDN1, and VDR in asthma; IL18, TBXA2R, IFNGR2, and VDR in atopy; TLR9, TBXA2R, VDR, NOD2, and STAT6 in airway hyperresponsiveness; TLR10, IFNGR2, STAT6, VDR, and NPSR1 in atopic asthma. Additionally we found an excess of SNPs with small effect sizes (OR < 1.4). The low rate of replication may be due to small effect size, differences in phenotypic definition, differential environmental effects, and/or genetic heterogeneity. To aid in future replication studies of asthma genes a comprehensive database was compiled and is available to the scientific community at http://genapha.icapture.ubc.ca/.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.025
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0010.001
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 head0.067
GPT teacher head0.334
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".

Quick stats

Citations110
Published2009
Admission routes3
Has abstractyes

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