Background The anti-inflammatory pneumoprotein club cell secretory protein-16 (CC-16) is associated with the clinical expression of chronic obstructive pulmonary disease (COPD). We aimed to determine if there is a causal effect of serum CC-16 level on the risk of having COPD and/or its 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=3850 and ECLIPSE, n=1702). We then used the CC-16-associated single-nucleotide polymorphisms (SNPs) as instrumental variables in MR analysis to identify a causal effect of serum CC-16 on ‘COPD risk’ (ie, case status in the International COPD Genetics Consortium/UK-Biobank dataset; n=35 735 COPD cases, n=222 076 controls) and ‘COPD progression’ (ie, annual change in forced expiratory volume in 1 s in LHS and ECLIPSE). We also determined the associations between SNPs associated with CC-16 and gene expression using n=1111 lung tissue samples from the Lung Expression Quantitative Trait Locus Study.
Results We identified seven SNPs independently associated (p<5×10–8) with serum CC-16 levels; six of these were novel. MR analysis suggested a protective causal effect of increased serum CC-16 on COPD risk (MR estimate (SE) −0.11 (0.04), p=0.008) and progression (LHS only, MR estimate (SE) 7.40 (3.28), p=0.02). Five of the SNPs were also associated with gene expression in lung tissue (at false discovery rate <0.1) of several genes, including the CC-16-encoding gene SCGB1A1.
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 the risk of having COPD and its progression, the biological basis of which warrants further investigation.
- COPD ÀÜ mechanisms
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SM and XL contributed equally.
Contributors SM and XL devised the study, analysed the data, wrote and revised the draft manuscripts and contributed equally to this work. AIHC, CXY and MC contributed to the data analysis pipeline and interpretation of results and revised the draft manuscripts. TB, IR, NNH, YB, C-AB and DDS contributed to data collection and revised the draft manuscripts. MO contributed to study design, the data analysis pipeline and the interpretation of results and revised the draft manuscript. All authors approved the final manuscript. MO serves as senior author with full access to the data and responsibility for data integrity.
Funding There were no direct financial sponsors for the submitted work. SM and AIHC are supported by the MITACS Accelerate program. MHC is supported by R01 R01 HL135142, R01 HL137927, R01 HL089856, R01 HL147148 and R01HL133135.
Disclaimer The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The funding body has no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.
Competing interests SM reports personal fees from Novartis, Boehringer Ingelheim and Menarini, and non-financial support from Draeger Australia, outside the submitted work. MHC has received grant support from GSK and Bayer and consulting fees from Genentech. DDS reports grants from Merck, personal fees from Sanofi-Aventis, Regeneron and Novartis, and grants and personal fees from Boehringer Ingelheim and AstraZeneca, outside the submitted work. MO is currently employed by Novartis Pharmaceuticals. YB holds a Canada Research Chair in Genomics of Heart and Lung Diseases. DDS holds the De Lazzari Family Chair at HLI and a Tier 1 Canada Research Chair in COPD. MO is a Fellow of the Parker B Francis Foundation and a Scholar of the Michael Smith Foundation for Health Research (MSFHR).
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available on reasonable request. Summary statistics from ICGC/UK Biobank GWAS meta-analysis are available through the Database of Genotypes and Phenotypes (dbGaP) repository (accession no. phs000179.v5.p2) and from the UK Biobank. Summary GWAS data from Lung Health Study (accession no. phs000335.v3.p2) and ECLIPSE (accession no. phs001252.v1.p1) are available through dbGaP. Lung eQTL Study data are available through dbGap (accession no. phs001745.v1.p1) and by direct application to the Lung eQTL Consortium.
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