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Relationship: 1314


The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Chronic, Mucus hypersecretion leads to Decreased lung function

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
EGFR Activation Leading to Decreased Lung Function adjacent High Moderate Cataia Ives (send email) Under development: Not open for comment. Do not cite Under Development

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Mixed High

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
Adult High

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

Increased mucin production and mucus hypersecretion following acute exposure are thought to contribute to innate airway defenses and are most likely limited by anti-inflammatory mechanisms aimed at resolving the exposure-related stress (Rose and Voynow 2006; Ramos et al., 2014). However, under chronic exposure conditions, airway remodeling will persist, leading to airway narrowing, and the elevated number of goblet cells results in higher basal mucus levels (Rogers, 2007). Eventually, increased mucin production and mucus hypersecretion may lead to airway obstruction and a progressive decline in lung function over time (Kim and Criner, 2015; Aoshiba and Nagai, 2004; Vestbo et al, 1996). In the general population, the prevalence of chronic mucus hypersecretion is estimated to be between 3.5% to 12.7% (de Oca et al., 2012), and chronic mucus hypersecretion is linked to an excess decline of the forced expiratory volume in 1 s (FEV1) as well as increased hospitalization and mortality rates (Vestbo et al., 1989; Ekberg-Aronsson et al., 2005).

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

Clinical studies showed that MUC5AC expression in bronchial epithelium was inversely correlated with FEV1 (% predicted) and with FEV1/FVC ratio (Caramori et al., 2009; Innes et al., 2006), and epidemiological evidence indicates a link between mucus hypersecretion and decreased lung function (Allinson et al., 2015; Pistelli et al., 2003; Vestbo et al., 1996). As a cause-effect relationship between goblet cell hyperplasia/metaplasia, increased mucin production, mucus hypersecretion and airway obstruction cannot be conclusively proven, but the link between chronic mucus hypersecretion and lung function is clinically accepted, we believe that biological plausibility is high.

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

Mucus hypersecretion is a physiological response to inhalation exposures such as pollutants or infectious agents. As such, it is typically of short duration and does not pose a major problem to normal lung function. However, in the presence of chronic inflammation and goblet cell hyperplasia, increased mucus production may turn into mucus hypersecretion and ultimately decrease airflow. Because this may be accompanied by impaired mucociliary clearance and ineffective cough (Ramos et al., 2014), and owing to the lack of direct evidence, it is currently unclear whether chronic mucus hypersecretion alone is sufficient to elicit a decrease in lung function.

The prevalence of chronic mucus hypersecretion generally increases with age (Fletcher et al., 1976; Viegi et al., 2007). This may explain why Sunyer et al. (1998) did not observe decreased lung function in a randomly selected population of 20-45 year-old men and women that experienced occupational exposures to o dusts, gases, and fumes, even though those exposures were associated with a higher incidence of chronic phlegm in men exposed to mineral dust (relative risk, 1.94 [1.29–2.91]) and gases and fumes (relative risk, 1.53 [0.99–2.36]).

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help

Following exposure to smoke from 3R4F research cigarettes for 1 h twice daily for 6 months (SCIREQ, InExpose model), ferrets developed goblet cell hyperplasia/metaplasia and chronic mucus hypersecretion (histology, PAS staining, Muc5b and Muc5ac staining). Mucus expression measured by PAS-positive goblet cell area, normalized by the size of the airway lumen to account for cell variation due to airway diameter, was 60% higher in smoke-exposed than in air-exposed animals (0.042% ± 0.025% smoke vs. 0.025% ± 0.013% air control). Inspiratory capacity, a sensitive marker of airway obstruction, was significantly reduced in smoke-exposed ferrets (79.5 ± 9.4 mL vs. 85.9 ± 5.9 mL air control) (Raju et al., 2016).

In a Dutch population-based cohort study, COPD subjects with chronic bronchitis (defined as having a productive cough for ⩾3 months a year during the past 2 years) had a 38.2 mL per year greater decline in FEV1 than COPD subjects without chronic bronchitis (95% CI −61.7 to−14.6 mL) adjusted for age, sex and pack-years of cigarette smoking (Lahousse et al., 2017).

In a  cross-sectional multicenter study in Belgium and Luxembourg, COPD patients with chronic bronchitis (defined as cough and sputum production for at least 3 months in each of two consecutive years, in the absence of other causes of chronic cough) had both lower FEV1% predicted and FEV1/VC% (Corhay et al., 2013). 

In the PLATINO study of 5,314 subjects (759 with and 4,554 without COPD), subjects with chronic bronchitis (defined as phlegm on most days, at least 3 months per year for >2 yrs) had worse lung function (pre-bronchodilator FEV1: 67.6 ± 2.10% predicted vs 81.0 ± 0.93; post-bronchodilator FEV1: 73.0 ± 2.10% predicted vs 84.0 ± 0.85; pre-bronchodilator FVC: 90.5 ± 2.18% predicted vs 99.6 ± 0.90; post-bronchodilator FVC: 96.0 ± 2.32% predicted vs 104.0±0.82) (de Oca et al., 2012).  

In the COPDgene study, COPD patients with chronic bronchitis had significantly lower FEV1% predicted and FVC% predicted than those without (63.20 ± 25.03 vs 79.91 ± 26.07 and 83.18 ± 17.44 vs 89.74 ± 18.12). They also experienced a greater annual decline in FEV1 than COPD patients without chronic bronchitis (-44.60 ± 61.58 mL vs -39.20 ± 49.42), although this was not significant (Kim et al., 2016).

In a Chinese study, COPD patients with chronic bronchitis (defined as the presence of cough and sputum production for at least 3 months in each of two consecutive years, in the absence of other causes of chronic cough) had lower FEV1% predicted and FVC% predicted than those without (42.1±18.0 vs 52.6±19.7 and 64.7±21.2 vs 75.1±24.2) (Liang et al., 2017).

This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help

In a 12-year follow-up study of 1,757 males and 2,191 females, men and women with chronic phlegm, a clinical surrogate of chronic mucus hypersecretion, showed a decline in FEV1 of 4.5±2.0 mL/year and 1.7±1.5 mL/year, respectively (Sherman et al., 1992).

In a 5-year follow-up study of 5,354 women and 4,081 men, chronic airway mucus hypersecretion was significantly associated with an excess decline in FEV1 decline of 22.8 mL/year and 12.6 mL/year among male and female COPD patients, respectively compared with men without airway mucus hypersecretion after adjusting for age, height, weight, and smoking (Vestbo et al., 1996).

An analysis of the National Survey of Health and Development (NSHD) data indicated that chronic mucus hypersecretion was associated with smoking status, and that the longer it was present, the faster was the decline in FEV1 (Allinson et al., 2015).

Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help

Allinson et al. (2015) reported that smoking cessation at any age reversed or avoided the escalating prevalence of smoking-related chronic mucus hypersecretion, similar to Kim et al. (2016) who found that quitting smoking increased the odds of "resolving" chronic bronchitis.

Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help


List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Allinson, J.P., Hardy, R., Donaldson, G.C., Shaheen, S.O., Kuh, D., and Wedzicha, J.A. (2016). The presence of chronic mucus hypersecretion across adult life in relation to chronic obstructive pulmonary disease development. Am. J. Respir. Crit. Care Med. 193, 662-672.

Aoshiba, K., and Nagai, A. (2004). Differences in airway remodeling between asthma and chronic obstructive pulmonary disease. Clin. Rev.  Allergy Immunol. 27, 35-43.

Caramori, G., Casolari, P., Di Gregorio, C., Saetta, M., Baraldo, S., Boschetto, P., Ito, K., Fabbri, L.M., Barnes, P.J., and Adcock, I.M. (2009). MUC5AC expression is increased in bronchial submucosal glands of stable COPD patients. Histopathology 55, 321-331.

Corhay, J.-L., Vincken, W., Schlesser, M., Bossuyt, P., and Imschoot, J. (2013). Chronic bronchitis in COPD patients is associated with increased risk of exacerbations: a cross‐sectional multicentre study. Int. J. Clin. Pract. 67, 1294-1301.

de Oca, M.M., Halbert, R.J., Lopez, M.V., Perez-Padilla, R., Tálamo, C., Moreno, D., et al. (2012). The chronic bronchitis phenotype in subjects with and without COPD: the PLATINO study. Eur. Respir. J. 40, 28-36. 

Ekberg-Aronsson, M., Pehrsson, K., Nilsson, J.-Å., Nilsson, P.M., and Löfdahl, C.-G. (2005). Mortality in GOLD stages of COPD and its dependence on symptoms of chronic bronchitis. Respir. Res. 6, 1-9.

Fletcher, C., Peto, R., Tinker, C., and Speizer, F.E. (1976). The natural history of chronic bronchitis and emphysema. An eight-year study of early chronic obstructive lung disease in working men in London. Oxford University Press, London. 

Innes, A.L., Woodruff, P.G., Ferrando, R.E., Donnelly, S., Dolganov, G.M., Lazarus, S.C., and Fahy, J.V. (2006). Epithelial mucin stores are increased in the large airways of smokers with airflow obstruction. Chest 130, 1102-1108.

Kim, V., and Criner, G.J. (2015). The chronic bronchitis phenotype in chronic obstructive pulmonary disease: features and implications. Curr. Opin. Pulm. Med. 21, 133-141.

Kim, V., Zhao, H., Boriek, A.M., Anzueto, A., Soler, X., Bhatt, S.P., et al. (2016). Persistent and newly developed chronic bronchitis are associated with worse outcomes in chronic obstructive pulmonary disease. Ann. Am. Thorac. Soc. 13, 1016-1025.

Lahousse, L., Seys, L.J., Joos, G.F., Franco, O.H., Stricker, B.H., and Brusselle, G.G. (2017). Epidemiology and impact of chronic bronchitis in chronic obstructive pulmonary disease. Eur. Respir. J. 50, 1602470.

Liang, Y., Chen, Y., Wu, R., Lu, M., Yao, W., Kang, J., et al. (2017). Chronic bronchitis is associated with severe exacerbation and prolonged recovery period in Chinese patients with COPD: a multicenter cross-sectional study. J. Thorac. Dis. 9, 5120-5130. 

Ma, R., Wang, Y., Cheng, G., Zhang, H., Wan, H., and Huang, S. (2005). MUC5AC expression up-regulation goblet cell hyperplasia in the airway of patients with chronic obstructive pulmonary disease. Chin. Med. Sci. J 20, 181-184.

Pistelli, R., Lange, P., and Miller, D.L. (2003). Determinants of prognosis of COPD in the elderly: mucus hypersecretion, infections, cardiovascular comorbidity. Eur. Resp. J. 21, 10s-14s.

Raju, S.V., Kim, H., Byzek, S.A., Tang, L.P., Trombley, J.E., Jackson, P., et al. (2016). A ferret model of COPD-related chronic bronchitis. JCI Insight 1, e87536.

Rogers, D.F. (2007). Physiology of airway mucus secretion and pathophysiology of hypersecretion. Respir. Care 52, 1134-1149.

Rose, M.C., and Voynow, J.A. (2006). Respiratory tract mucin genes and mucin glycoproteins in health and disease. Physiol. Rev. 86, 245-278.

Sherman, C.B., Xu, X., Speizer, F.E., Ferris, B.G., Jr., Weiss, S.T., and Dockery, D.W. (1992). Longitudinal lung function decline in subjects with respiratory symptoms. Am. Rev. Respir. Dis. 146, 855-859. 

Sunyer, J., Zock, J.P., Kromhout, H., Garcia-Esteban, R., Radon, K., Jarvis, D., et al. (2005). Lung function decline, chronic bronchitis, and occupational exposures in young adults. Am. J. Respir. Crit. Care Med. 172, 1139-1145.

Vestbo, J., and Rasmussen, F. (1989). Respiratory symptoms and FEV1 as predictors of hospitalization and medication in the following 12 years due to respiratory disease. Eur. Respir. J. 2, 710-715.

Vestbo, J., Prescott, E., and Lange, P. (1996). Association of chronic mucus hypersecretion with FEV1 decline and chronic obstructive pulmonary disease morbidity. Copenhagen City Heart Study Group. Am. J. Respir. Crit. Care Med. 153, 1530-1535.

Viegi, G., Pistelli, F., Sherrill, D.L., Maio, S., Baldacci, S., and Carrozzi, L. (2007). Definition, epidemiology and natural history of COPD. Eur. Respir. J. 30, 993-1013.