Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Jun 23;19(6):e1010445.
doi: 10.1371/journal.pgen.1010445. eCollection 2023 Jun.

Genetic regulators of sputum mucin concentration and their associations with COPD phenotypes

Eric Van Buren  1   2 , Giorgia Radicioni  3 , Sarah Lester  4 , Wanda K O'Neal  3 , Hong Dang  3 , Silva Kasela  5   6 , Suresh Garudadri  7 , Jeffrey L Curtis  8   9 , MeiLan K Han  8 , Jerry A Krishnan  10 , Emily S Wan  11   12 , Edwin K Silverman  11 , Annette Hastie  13 , Victor E Ortega  14 , Tuuli Lappalainen  5   6 , Martijn C Nawijn  15   16 , Maarten van den Berge  16   17 , Stephanie A Christenson  7 , Yun Li  1   4 , Michael H Cho  11 , Mehmet Kesimer  3 , Samir N P Kelada  3   4
Affiliations

Genetic regulators of sputum mucin concentration and their associations with COPD phenotypes

Eric Van Buren et al. PLoS Genet. .

Abstract

Hyper-secretion and/or hyper-concentration of mucus is a defining feature of multiple obstructive lung diseases, including chronic obstructive pulmonary disease (COPD). Mucus itself is composed of a mixture of water, ions, salt and proteins, of which the gel-forming mucins, MUC5AC and MUC5B, are the most abundant. Recent studies have linked the concentrations of these proteins in sputum to COPD phenotypes, including chronic bronchitis (CB) and acute exacerbations (AE). We sought to determine whether common genetic variants influence sputum mucin concentrations and whether these variants are also associated with COPD phenotypes, specifically CB and AE. We performed a GWAS to identify quantitative trait loci for sputum mucin protein concentration (pQTL) in the Sub-Populations and InteRmediate Outcome Measures in COPD Study (SPIROMICS, n = 708 for total mucin, n = 215 for MUC5AC, MUC5B). Subsequently, we tested for associations of mucin pQTL with CB and AE using regression modeling (n = 822-1300). Replication analysis was conducted using data from COPDGene (n = 5740) and by examining results from the UK Biobank. We identified one genome-wide significant pQTL for MUC5AC (rs75401036) and two for MUC5B (rs140324259, rs10001928). The strongest association for MUC5B, with rs140324259 on chromosome 11, explained 14% of variation in sputum MUC5B. Despite being associated with lower MUC5B, the C allele of rs140324259 conferred increased risk of CB (odds ratio (OR) = 1.42; 95% confidence interval (CI): 1.10-1.80) as well as AE ascertained over three years of follow up (OR = 1.41; 95% CI: 1.02-1.94). Associations between rs140324259 and CB or AE did not replicate in COPDGene. However, in the UK Biobank, rs140324259 was associated with phenotypes that define CB, namely chronic mucus production and cough, again with the C allele conferring increased risk. We conclude that sputum MUC5AC and MUC5B concentrations are associated with common genetic variants, and the top locus for MUC5B may influence COPD phenotypes, in particular CB.

PubMed Disclaimer

Conflict of interest statement

I have read the journal’s policy and the authors of this manuscript have the following competing interests: EKS received grant support from GlaxoSmithKline and Bayer. ESW received honoraria from Pri-Med. JAK reports a grant from U.S. National Institutes of Health (NIH) paid to the institution during the conduct of the study. He also reports personal fees from GlaxoSmithKline consulting on antibodies for acute COVID-19; personal fees from AstraZeneca consulting on antibodies for severe asthma, paid to the institution; personal fees from CereVu Medical consultant for medical device for dyspnea, paid to the institution; and personal fees from BData consultant for severe asthma registry outside the submitted work. JLC reports grants from NIH/NHLBI and the COPD Foundation for the current work and paid to his institution; grants from NIH/NHLBI, the COPD Foundation, NIH/NIAID, and the Departments of Veterans Affairs and of Defense, outside the current work and paid to his institution; and consulting fees from CSL Behring, LLC, AstraZenca, and Novartis Corp., outside the current work and paid to his institution. MCN has received grant support from GlaxoSmithKline. MHC has received grant support from GlaxoSmithKline and Bayer, consulting fees from AstraZeneca, and speaking fees from Illumina. MK received consulting fees from Arrowhead pharmaceuticals and has a patent pending for mucin measurements in chronic bronchitis. MKH reports personal fees from GlaxoSmithKline, AstraZeneca, Boehringer Ingelheim, Cipla, Chiesi, Novartis, Pulmonx, Teva, Verona, Merck, Mylan, Sanofi, DevPro, Aerogen, Polarian, Regeneron, Amgen, UpToDate, Altesa Biopharma, Medscape, NACE, MDBriefcase, Integrity and Medwiz. She has received either in kind research support or funds paid to the institution from the NIH, Novartis, Sunovion, Nuvaira, Sanofi, Astrazeneca, Boehringer Ingelheim, Gala Therapeutics, Biodesix, the COPD Foundation and the American Lung Association. She has participated in Data Safety Monitoring Boards for Novartis and Medtronic with funds paid to the institution. She has received stock options from Meissa Vaccines and Altesa Biopharma. MVDB reports research grants paid to their institution by GlaxoSmithKline, Novartis, AstraZeneca, Roche and Genentech. SAC received consulting fees from Sanofi/Regeneron, GlaxoSmithKline, AstraZeneca, Glenmark Pharmaceuticals, and Amgen; honoraria from Sanofi/Regeneron, MJH Holdings LLC: Physicians? Education Resource, Sunovion, UpToDate, and Wolters Kluwer Health; travel support from AstraZeneca and GlaxoSmithKline; and sits on the data safety board or advisory boards of Sanofi/Regeneron, and AstraZeneca, and GlaxoSmithKline. TL has stock options from Variant Bio. VEO is on the Data Safety Monitoring Board or Advisory Board for Sanofi and Regeneron. ATH, EVB, GR, HD, SG, SL, SK, SNPK, WKO, and YL have no competing interests to declare.

Figures

Fig 1
Fig 1. Distal and local pQTL for sputum MUC5AC and MUC5B concentration.
Results of association analysis using sputum mucin concentration data from 215 EA SPIROMICS participants are shown. Dashed red line denotes genome-wide significance threshold.
Fig 2
Fig 2. A genotype x smoking interaction locus (rs6043852) for sputum MUC5B concentration on Chromosome 20.
A. Locus zoom plot for the genotype x smoking locus (rs6043852). B. MUC5B concentration as a function of both rs6043852 genotype and current smoking status. The not current smoker category includes never smokers and former smokers. Numbers in parentheses on x-axis denote sample size per genotype. Note that while we plot carriers of the minor allele here as one group, the regression model for MUC5B used genotype dosages.
Fig 3
Fig 3. The chromosome 11 MUC5B pQTL.
A. Regional view of association test results. Four genes not shown due to small size. The lead variant, rs140324259, is approximately 100 kb upstream of MUC5B. B. Effect of rs140324259 genotype on sputum MUC5B concentration. Numbers in parentheses on x-axis denote sample size per genotype. Each C allele yields a 0.8 log (ln) unit decreased in MUC5B, equating to a 2.3 picomol/ml decrease in MUC5B concentration.
Fig 4
Fig 4. Mediation analysis reveals that rs140324259 exerts effects on exacerbations in the year prior to enrollment through direct and indirect paths with contrasting allele effects.
We leveraged the mediation analysis framework of Baron and Kenny [22] to examine whether rs140324259 exerts effects on exacerbations through MUC5B. Using complete data on 142 subjects, in (A) we tested for the total effect of rs140324259 on acute exacerbations of COPD (“c”). In (B), the mediation analysis framework is shown in which the effect of rs140324259 on acute exacerbations is modeled as the sum of direct (rs140324259 to exacerbations, c’) and indirect paths (rs140324259 to exacerbations via MUC5B (a, b)). Statistical evidence of the indirect path assessed by jointly testing that both rs140324259 → MUC5B (a) and MUC5B → exacerbations (b) are significant using an intersection union test (which is equivalent to testing that γ x β1 is not equal to 0). β1 (b) and β2 (c’) come from the same negative binomial regression model including both rs140324259 and MUC5B as predictors of exacerbations. Note that in this mediation analysis framework, the total effect (c) in part A is the sum of the direct (c’) and indirect paths (a→b) in part B, i.e., c = c’ + (a x b). Thus, because the sign of path a is negative while both b and c’ are positive, the total effect c (in panel A) is necessarily weaker in magnitude.
See this image and copyright information in PMC

References

    1. Diaz-Guzman E, Mannino DM. Epidemiology and prevalence of chronic obstructive pulmonary disease. Clin Chest Med. 2014;35: 7–16. doi: 10.1016/j.ccm.2013.10.002 - DOI - PubMed
    1. Ferkol T, Schraufnagel D. The global burden of respiratory disease. Ann Am Thorac Soc. 2014;11: 404–406. doi: 10.1513/AnnalsATS.201311-405PS - DOI - PubMed
    1. Dunican EM, Elicker BM, Henry T, Gierada DS, Schiebler ML, Anderson W, et al.. Mucus Plugs and Emphysema in the Pathophysiology of Airflow Obstruction and Hypoxemia in Smokers. Am J Respir Crit Care Med. 2021;203: 957–968. doi: 10.1164/rccm.202006-2248OC - DOI - PMC - PubMed
    1. Ramos FL, Krahnke JS, Kim V. Clinical issues of mucus accumulation in COPD. Int J Chron Obstruct Pulmon Dis. 2014;9: 139–50. doi: 10.2147/COPD.S38938 - DOI - PMC - PubMed
    1. Kim V, Han MK, Vance GB, Make BJ, Newell JD, Hokanson JE, et al.. The chronic bronchitic phenotype of COPD: An analysis of the COPDGene study. Chest. 2011;140: 626–633. doi: 10.1378/chest.10-2948 - DOI - PMC - PubMed

Publication types