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Record W2920846185 · doi:10.1186/s12890-019-0811-0

Limited overlap in significant hits between genome-wide association studies on two airflow obstruction definitions in the same population

2019· article· en· W2920846185 on OpenAlexafffund
Diana A. van der Plaat, Judith M. Vonk, Lies Lahousse, Kim de Jong, Alen Faiz, Ivana Nedeljković, Najaf Amin, Cleo C. van Diemen, Guy Brusselle, Yohan Bossé, Corry‐Anke Brandsma, Ke Hao, Peter D. Paré, Cornelia M. van Duijn, Dirkje S. Postma, H. Marike Boezen

Bibliographic record

VenueBMC Pulmonary Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of British ColumbiaSt. Paul's HospitalUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersFonds de Recherche du Québec - SantéVlaamse regeringFonds Wetenschappelijk OnderzoekUniversité Laval
KeywordsMedicineVital capacityCOPDGenome-wide association studyRotterdam StudyCohortInternal medicineSingle-nucleotide polymorphismPopulationConfidence intervalCohort studyCardiologyLungGenotypeGeneticsLung functionDiffusing capacity

Abstract

fetched live from OpenAlex

Airflow obstruction is a hallmark of chronic obstructive pulmonary disease (COPD), and is defined as either the ratio between forced expiratory volume in one second and forced vital capacity (FEV 1 /FVC) < 70% or < lower limit of normal (LLN). This study aimed to assess the overlap between genome-wide association studies (GWAS) on airflow obstruction using these two definitions in the same population stratified by smoking. GWASes were performed in the LifeLines Cohort Study for both airflow obstruction definitions in never-smokers (NS = 5071) and ever-smokers (ES = 4855). The FEV 1 /FVC < 70% models were adjusted for sex, age, and height; FEV 1 /FVC < LLN models were not adjusted. Ever-smokers models were additionally adjusted for pack-years and current-smoking. The overlap in significantly associated SNPs between the two definitions and never/ever-smokers was assessed using several p -value thresholds. To quantify the agreement, the Pearson correlation coefficient was calculated between the p -values and ORs. Replication was performed in the Vlagtwedde-Vlaardingen study (NS = 432, ES = 823). The overlapping SNPs with p < 10 − 4 were validated in the Vlagtwedde-Vlaardingen and Rotterdam Study cohorts (NS = 1966, ES = 3134) and analysed for expression quantitative trait loci (eQTL) in lung tissue ( n = 1087). In the LifeLines cohort, 96% and 93% of the never- and ever-smokers were classified concordantly based on the two definitions. 26 and 29% of the investigated SNPs were overlapping at p < 0.05 in never- and ever-smokers, respectively. At p < 10 − 4 the overlap was 4% and 6% respectively, which could be change findings as shown by simulation studies. The effect estimates of the SNPs of the two definitions correlated strongly, but the p-values showed more variation and correlated only moderately. Similar observations were made in the Vlagtwedde-Vlaardingen study. Two overlapping SNPs in never-smokers ( NFYC and FABP7) had the same direction of effect in the validation cohorts and the NFYC SNP was an eQTL for NFYC-AS1 . NFYC is a transcription factor that binds to several known COPD genes, and FABP7 may be involved in abnormal pulmonary development. The definition of airflow obstruction and the population under study may be important determinants of which SNPs are associated with airflow obstruction. The genes FABP7 and NFYC(-AS1) could play a role in airflow obstruction in never-smokers specifically.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.074
GPT teacher head0.333
Teacher spread0.259 · 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 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

Citations5
Published2019
Admission routes2
Has abstractyes

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