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Record W2994738115 · doi:10.1101/2019.12.20.885384

The protective effect of club cell secretory protein (CC-16) on COPD risk and progression: a Mendelian randomisation study

2019· preprint· en· W2994738115 on OpenAlexafffund
Stephen Milne, Xuan Li, Ana I. Hernández Cordero, Chen Yang, Michael H. Cho, Terri H. Beaty, Ingo Ruczinski, Nadia N. Hansel, Yohan Bossé, Corry‐Anke Brandsma, Don D. Sin, Ma’en Obeidat

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité LavalSt. Paul's HospitalUniversity of British Columbia
FundersMitacsNational Institutes of HealthMichael Smith Health Research BC
KeywordsCOPDSingle-nucleotide polymorphismMedicineInternal medicineLung cancerOncologyBioinformaticsGenotypeGeneBiologyGenetics

Abstract

fetched live from OpenAlex

ABSTRACT Background There are currently no robust biomarkers of chronic obstructive pulmonary disease (COPD) risk or progression. Club cell secretory protein-16 (CC-16) is associated with the clinical expression of COPD. We aimed to determine if there is a causal effect of serum CC-16 level on COPD risk and/or progression using Mendelian randomisation (MR) analysis. Methods We performed a genome-wide association meta-analysis for serum CC-16 in two COPD cohorts (Lung Health Study [LHS], n=3,850 and ECLIPSE, n=1,702). We then used the CC-16-associated single-nucleotide polymorphisms (SNPs) in MR analysis to estimate the causal effect of serum CC-16 on COPD risk (International COPD Genetics Consortium/UK-Biobank dataset; n=35,735 cases, n=222,076 controls) and progression (change in forced expiratory volume in 1 s [FEV 1 ] in LHS and ECLIPSE). We also determined the associations between SNPs associated with CC-16 and gene expression using n=1,111 lung tissue samples from the Lung eQTL Study. Results We identified 7 SNPs independently associated (p<5×10 −8 ) with serum CC-16 levels; 6 of these were novel. MR analysis suggested a protective causal effect of increased serum CC-16 on COPD risk (p=0.008) and progression (LHS only, p=0.02). Five of the SNPs were also associated with gene expression in lung tissue, including that of the CC-16-encoding gene SCGB1A1 (false discovery rate<0.1). Conclusion We have identified several novel genetic variants associated with serum CC-16 level in COPD cohorts. These genetic associations suggest a potential causal effect of serum CC-16 on COPD risk and progression. Further investigation of CC-16 as a biomarker or therapeutic target in COPD is warranted. KEY MESSAGES What is the key question? Can genetics help uncover a causal effect of serum CC-16 level on COPD risk and/or progression? What is the bottom line? There is a protective effect of genetically-increased serum CC-16 on both COPD risk and progression (as measured by change in FEV 1 over time), which may be due to increased expression of the CC-16-encoding gene SCGB1A1 in the lung. Why read on? This is the first study to demonstrate a possible causal effect of serum CC-16 in people with COPD, and highlights the potential for CC-16 as a biomarker or therapeutic target.

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)0.024
metaresearch head score (Gemma)0.037
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 score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.037
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.006
GPT teacher head0.231
Teacher spread0.225 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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