Aop: 425


A descriptive phrase which references both the Molecular Initiating Event and Adverse Outcome.It should take the form “MIE leading to AO”. For example, “Aromatase inhibition leading to reproductive dysfunction” where Aromatase inhibition is the MIE and reproductive dysfunction the AO. In cases where the MIE is unknown or undefined, the earliest known KE in the chain (i.e., furthest upstream) should be used in lieu of the MIE and it should be made clear that the stated event is a KE and not the MIE. More help

Oxidative Stress Leading to Decreased Lung Function via Decreased FOXJ1

Short name
A name that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
ox stress-mediated FOXJ1/cilia/CBF/MCC impairment

Graphical Representation

A graphical representation of the AOP.This graphic should list all KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs. More help
Click to download graphical representation template Explore AOP in a Third Party Tool


The names and affiliations of the individual(s)/organisation(s) that created/developed the AOP. More help

Karsta Luettich, Philip Morris Products S.A., Philip Morris International R&D, Neuchatel, Switzerland

Hasmik Yepiskoposyan, Philip Morris Products S.A., Philip Morris International R&D, Neuchatel, Switzerland

Monita Sharma, PETA Science Consortium International e.V., Stuttgart, Germany

Frazer Lowe, Broughton Nicotine Services, Earby, Lancashire, United Kingdom

Damien Breheny, British American Tobacco (Investments) Ltd., Group Research and Development, Southampton, United Kingdom

Point of Contact

The user responsible for managing the AOP entry in the AOP-KB and controlling write access to the page by defining the contributors as described in the next section.   More help
Karsta Luettich   (email point of contact)


Users with write access to the AOP page.  Entries in this field are controlled by the Point of Contact. More help
  • Karsta Luettich
  • Hasmik Yepiskoposyan
  • Monita Sharma
  • Damien Breheny
  • Frazer Lowe


Provides users with information concerning how actively the AOP page is being developed, what type of use or input the authors feel comfortable with given the current level of development, and whether it is part of the OECD AOP Development Workplan and has been reviewed and/or endorsed. OECD Status - Tracks the level of review/endorsement the AOP has been subjected to. OECD Project Number - Project number is designated and updated by the OECD. SAAOP Status - Status managed and updated by SAAOP curators. More help
Author status OECD status OECD project SAAOP status
Open for comment. Do not cite
This AOP was last modified on January 24, 2022 15:12

Revision dates for related pages

Page Revision Date/Time
Oxidative Stress March 21, 2023 15:16
FOXJ1 Protein, Decreased September 10, 2021 04:56
Motile Cilia Number/Length, Decreased September 10, 2021 03:24
Cilia Beat Frequency, Decreased September 10, 2021 01:38
Mucociliary Clearance, Decreased September 10, 2021 07:19
Decrease, Lung function September 08, 2021 04:54
Oxidative Stress leads to FOXJ1 Protein, Decreased September 28, 2021 07:28
FOXJ1 Protein, Decreased leads to Motile Cilia Number/Length, Decreased August 02, 2021 10:08
Motile Cilia Number/Length, Decreased leads to CBF, Decreased September 28, 2021 07:41
CBF, Decreased leads to MCC, Decreased March 24, 2023 08:17
MCC, Decreased leads to Decreased lung function March 24, 2023 08:27
Cigarette smoke September 28, 2021 09:07


A concise and informative summation of the AOP under development that can stand-alone from the AOP page. The aim is to capture the highlights of the AOP and its potential scientific and regulatory relevance. More help

This AOP evaluates one of the major processes known to be involved in regulating efficient mucociliary clearance (MCC). MCC is a key aspect of the innate immune defense against airborne pathogens and inhaled chemicals and is governed by the concerted action of its functional components, the cilia and the airway surface liquid (ASL), which is composed of mucus and periciliary layers (Bustamante-Marin and Ostrowski, 2017). In response to various irritants and pathogens mucus is secreted by goblet cells, and cilia sweep mucus upward by coordinated beating motions thus clearing the airways from these substances. The ciliated airway epithelial cells are typically covered by hundreds of motile cilia. Cilia formation is initiated and coordinated by a distinct gene expression program, led by the transcription factor forkhead box J1 (FOXJ1) (Brody et al., 2000; Zhou and Roy, 2015). FOXJ1 appears to be the major factor in multiciliogenesis, whereby its activity is necessary and also sufficient for programming cells to assemble functional motile cilia (Vij et al., 2012). A decrease in the levels or absence of FOXJ1 protein in cells of the respiratory tract therefore inhibits ciliogenesis, preventing physiological mucus clearance and decreasing MCC. MCC dysfunction is linked to airway diseases such as chronic obstructive pulmonary disease (COPD) or asthma, both of which are characterized by decreased lung function and bear a significant risk of increased morbidity and mortality.

AOP Development Strategy


Used to provide background information for AOP reviewers and users that is considered helpful in understanding the biology underlying the AOP and the motivation for its development.The background should NOT provide an overview of the AOP, its KEs or KERs, which are captured in more detail below. More help

With a surface area of ~100 m2 and ventilated by 10,000 to 20,000 liters of air per day (National Research Council, 1988; Frohlich et al., 2016), the lungs are a major barrier that protect the body from a host of external factors that enter the respiratory system and may cause lung pathologies. Mucociliary clearance (MCC) is a key aspect of the innate immune defense against airborne pathogens and inhaled particles and is governed by the concerted action of its functional components, the cilia and the airway surface liquid (ASL), which comprises mucus and the periciliary layer (Bustamante-Marin and Ostrowski, 2017). In healthy subjects, ≥10 mL airway secretions are continuously produced and transported daily by the mucociliary escalator. Disturbances in any of the processes regulating ASL volume, mucus production, mucus viscoelastic properties, or ciliary function can cause MCC dysfunction and are linked to airway diseases such as chronic obstructive pulmonary disease (COPD) or asthma, both of which bear a significant risk of increased morbidity and mortality. The mechanism by which exposure to inhaled toxicants might lead to mucus hypersecretion and thereby impact pulmonary function has already been mapped in AOP148 on decreased lung function. However, whether an exposure-related decline in lung function is solely related to excessive production of mucus is debatable, particularly in light of the close relationship between mucus, ciliary function, and efficient MCC. To date, no single event has been attributed to MCC impairment, and it is likely that events described in this AOP as well as in AOPs 148, 411 and 424 have to culminate to lead to decreased lung function.


Provides a description of the approaches to the identification, screening and quality assessment of the data relevant to identification of the key events and key event relationships included in the AOP or AOP network.This information is important as a basis to support the objective/envisaged application of the AOP by the regulatory community and to facilitate the reuse of its components.  Suggested content includes a rationale for and description of the scope and focus of the data search and identification strategy/ies including the nature of preliminary scoping and/or expert input, the overall literature screening strategy and more focused literature surveys to identify additional information (including e.g., key search terms, databases and time period searched, any tools used). More help

Summary of the AOP

This section is for information that describes the overall AOP. The information described in section 1 is entered on the upper portion of an AOP page within the AOP-Wiki. This is where some background information may be provided, the structure of the AOP is described, and the KEs and KERs are listed. More help


Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a prototypical stressor and the biological system) of an AOP. More help
Key Events (KE)
A measurable event within a specific biological level of organisation. More help
Adverse Outcomes (AO)
An AO is a specialized KE that represents the end (an adverse outcome of regulatory significance) of an AOP. More help
Type Event ID Title Short name
MIE 1392 Oxidative Stress Oxidative Stress
KE 1911 FOXJ1 Protein, Decreased FOXJ1 Protein, Decreased
KE 1912 Motile Cilia Number/Length, Decreased Motile Cilia Number/Length, Decreased
KE 1908 Cilia Beat Frequency, Decreased CBF, Decreased
KE 1909 Mucociliary Clearance, Decreased MCC, Decreased
AO 1250 Decrease, Lung function Decreased lung function

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarizes all of the KERs of the AOP and is populated in the AOP-Wiki as KERs are added to the AOP.Each table entry acts as a link to the individual KER description page. More help

Network View

This network graphic is automatically generated based on the information provided in the MIE(s), KEs, AO(s), KERs and Weight of Evidence (WoE) summary tables. The width of the edges representing the KERs is determined by its WoE confidence level, with thicker lines representing higher degrees of confidence. This network view also shows which KEs are shared with other AOPs. More help

Prototypical Stressors

A structured data field that can be used to identify one or more “prototypical” stressors that act through this AOP. Prototypical stressors are stressors for which responses at multiple key events have been well documented. More help

Life Stage Applicability

The life stage for which the AOP is known to be applicable. More help
Life stage Evidence
All life stages

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected.In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available. More help
Term Scientific Term Evidence Link
human Homo sapiens NCBI

Sex Applicability

The sex for which the AOP is known to be applicable. More help
Sex Evidence

Overall Assessment of the AOP

Addressess the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and Weight of Evidence (WoE) for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). More help

The experimental evidence to support the biological plausibility of the KERs from MIE to AO is moderate to strong overall for the AOP presented here, while there is a moderate concordance of dose-response relationships. In terms of essentiality, we have rated all of the KEs as either moderate or high.

AOPs such as this one can play a central role in risk assessment strategies for a wide variety of regulatory purposes by providing mechanistic support to an integrated approach to testing and assessment (IATA; (Clippinger et al., 2018)). IATAs are flexible frameworks that can be adapted to best address the regulatory question or purpose at hand. More specifically, this AOP can be applied to the risk assessment of inhaled toxicants, by enabling the development of testing strategies through the assembly of existing information and the generation of new data where they are currently lacking. Targeted approaches to fill data gaps can be developed using new approach methodologies (NAMs) informed by this AOP.

Domain of Applicability

Addressess the relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context. More help

All KE proposed in this AOP occur and are measurable in several species, including frogs, mice, rats, guinea pigs, ferrets, sheep, and humans. The majority of the supporting empirical evidence derives from studies in rodent and human systems, and experimental findings in animals appear to be highly translatable to humans.

Data regarding the applicability of KE to all life-stages from birth to adulthood are available for the MIE (Oxidative Stress), KE2 (FOXJ1 Protein, Decreased), KE3 (Motile Cilia Number/Length, Decreased), KE4 (Cilia Beat Frequency, Decreased), KE5 (Mucociliary Clearance, Decreased), and AO (Decreased Lung Function), and indicate that they apply to all life stages. It is also worth noting here that age-dependent decreases in CBF, MCC, and lung function have been demonstrated in several species (e.g., guinea pigs, mice, and humans) and reflect normal physiological aging processes (Bailey et al., 2014; Grubb et al., 2016; Ho et al., 2001; Joki and Saano, 1997; Paul et al., 2013; Sharma and Goodwin, 2006).

Gender-specific data relevant to the AOP are not as widely available as species-specific data, and to our knowledge, the role of gender has not been systematically evaluated for all KE described here. Considering the essentiality of FOXJ1 for the ciliogenesis program and the impact of ciliary beating on MCC, we consider this AOP applicable to both genders.

Essentiality of the Key Events

The essentiality of KEs can only be assessed relative to the impact of manipulation of a given KE (e.g., experimentally blocking or exacerbating the event) on the downstream sequence of KEs defined for the AOP. Consequently, evidence supporting essentiality is assembled on the AOP page, rather than on the independent KE pages that are meant to stand-alone as modular units without reference to other KEs in the sequence. The nature of experimental evidence that is relevant to assessing essentiality relates to the impact on downstream KEs and the AO if upstream KEs are prevented or modified. This includes: Direct evidence: directly measured experimental support that blocking or preventing a KE prevents or impacts downstream KEs in the pathway in the expected fashion. Indirect evidence: evidence that modulation or attenuation in the magnitude of impact on a specific KE (increased effect or decreased effect) is associated with corresponding changes (increases or decreases) in the magnitude or frequency of one or more downstream KEs. More help

The definition of essentiality implies that the modulation of upstream KEs impacts the downstream KEs in an expected fashion. If blocked or failing to occur, the KEs in the current AOP will not necessarily stop the progression to subsequent KEs. Due to the complex biology of motile cilia formation and function, ASL homeostasis, mucus properties and MCC, the KEs and AO may be triggered because of alternative pathways or biological redundancies. However, when exacerbated, the KEs promote the occurrence of downstream events eventually leading to the AO. The causal pathway starting from the exposure to oxidants and leading to decreased lung function involves parallel routes with KEs, each of which is sufficient to cause the downstream KE to occur. Different mechanisms, such as oxidant-induced decreases in ASL height via CFTR function decline (AOP424) or oxidant-induced decreases in cilia number and length as a result of decreased FOXJ1 levels, lead to decreased CBF and decreased MCC. Each of these pathways contributes to the AO, but their relative contributions are difficult to evaluate. Based on the evidence we judge the MIE (Oxidative Stress), KE2 (FOXJ1 Protein, Decreased), KE3 (Motile Cilia Number/Length, Decreased), KE4 (Cilia Beat Frequency, Decreased), and KE5 (Mucociliary Clearance, Decreased) highly essential.

Evidence Assessment

Addressess the biological plausibility, empirical support, and quantitative understanding from each KER in an AOP. More help

We judge the overall biological plausibility of this AOP as strong. The KER Decreased FOXJ1 protein leading to decreased motile cilia length/number is supported by multiple studies across different species with ample empirical evidence reflecting both dose-response and time concordance. Other KER, such as Oxidative stress leading to decreased FOXJ1 lack this expanse of empirical evidence, or the evidence does not fully support the causality between the KE (Reduced cilia number/length leading to decreased CBF, Decreased CBF leading to decreased MCC) even though the relationship is logical and plausible. 

Known Modulating Factors

Modulating factors (MFs) may alter the shape of the response-response function that describes the quantitative relationship between two KES, thus having an impact on the progression of the pathway or the severity of the AO.The evidence supporting the influence of various modulating factors is assembled within the individual KERs. More help

Quantitative Understanding

Optional field to provide quantitative weight of evidence descriptors.  More help

Overall, our quantitative understanding of the AOP network is moderate.

There is robust evidence that provides an insight into several KER presented here, and the dose response and temporal relationship between the two KE in question are well described and quantified for different stressors across different test systems (Decreased FOXJ1 protein leading to decreased motile cilia length/number; Decreased motile cilia length/number leading to decreased cilia beating frequency; Decreased cilia beat frequency leading to decreased MCC). In some instances, we are less confident in our quantitative understanding. For example, dose response data as well as data supportive of the KE causality are limited for the KER Decreased MCC leading to decreased lung function

Considerations for Potential Applications of the AOP (optional)

Addressess potential applications of an AOP to support regulatory decision-making.This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. More help

Given the individual and public health burden of the consequences of lung function impairment, gaining a greater understanding of the underlying mechanisms is extremely important in the risk assessment of respiratory toxicants. An integrated assessment of substances with the potential to be inhaled, either intentionally or unintentionally, could incorporate inhalation exposure and dosimetry modelling to inform an in vitro approach with appropriate exposure techniques and cell systems to assess KEs in this AOP (EPA’s Office of Chemical Safety and Pollution Prevention, 2019). Standardization and robustness testing of assays against explicit performance criteria using suitable reference materials can greatly increase the level of confidence in their use for KE assessment (Petersen et al., 2021). Much of the empirical evidence that supports the KERs in the qualitative AOP described here was obtained from in vitro studies using well-established methodologies for biological endpoint assessment. Being chemical agnostic, this AOP can be applied to a variety of substances that share the AO. For example, impaired MCC and decreased lung function have a long-known relationship with smoking, but little is known about the consequences of long-term use of alternative inhaled nicotine delivery products such as electronic cigarettes and heated tobacco products. This AOP can form the basis of an assessment strategy to evaluate the effects of exposure to aerosol from these products based on the KEs identified here.


List of the literature that was cited for this AOP. More help

Antunes, M.B., and Cohen, N.A. (2007). Mucociliary clearance–a critical upper airway host defense mechanism and methods of assessment. Curr. Opin. Allergy Clin. Immunol. 7, 5-10.

Bailey, K.L., Bonasera, S.J., Wilderdyke, M., Hanisch, B.W., Pavlik, J.A., DeVasure, J., et al. (2014). Aging causes a slowing in ciliary beat frequency, mediated by PKCε. Am. J. Physiol. Lung Cell. Mol. Physiol. 306, L584-L589.

Bustamante-Marin, X.M., and Ostrowski, L.E. (2017a). Cilia and Mucociliary Clearance. Cold Spring Harb. Persp. Biol. 9, a028241. EPA’s Office of Chemical Safety and Pollution Prevention (2019). "FIFRA Scientific Advisory Panel Meeting Minutes and Final Report No. 2019-01 Peer Review on Evaluation of a Proposed Approach to Refine the Inhalation Risk Assessment for Point of Contact Toxicity: A Case Study Using a New Approach Methodology (NAM) December 4 and 6, 2018 FIFRA Scientific Advisory Panel Meeting". U.S. Environmental Protection Agency).

Frohlich, E., Mercuri, A., Wu, S., and Salar-Behzadi, S. (2016). Measurements of Deposition, Lung Surface Area and Lung Fluid for Simulation of Inhaled Compounds. Front. Pharmacol. 7, 181.

Grubb, B.R., Livraghi-Butrico, A., Rogers, T.D., Yin, W., Button, B., and Ostrowski, L.E. (2016). Reduced mucociliary clearance in old mice is associated with a decrease in Muc5b mucin. Am. J. Physiol. Lung Cell. Mol. Physiol. 310, L860-L867.

Ho, J.C., Chan, K.N., Hu, W.H., Lam, W.K., Zheng, L., Tipoe, G.L., et al. (2001). The effect of aging on nasal mucociliary clearance, beat frequency, and ultrastructure of respiratory cilia. Am. J. Respir. Crit. Care Med. 163, 983-988.

Joki, S., and Saano, V. (1997). Influence of ageing on ciliary beat frequency and on ciliary response to leukotriene D4 in guinea-pig tracheal epithelium. Clin. Exp. Pharmacol. Physiol. 24, 166-169.

National Research Council (1988). Air Pollution, the Automobile, and Public Health. Washington, DC: The National Academies Press.

Paul, P., Johnson, P., Ramaswamy, P., Ramadoss, S., Geetha, B., and Subhashini, A. (2013). The effect of ageing on nasal mucociliary clearance in women: a pilot study. ISRN 2013, 598589.

Petersen, E.J., Sharma, M., Clippinger, A.J., Gordon, J., Katz, A., Laux, P., et al. (2021). Use of Cause-and-Effect Analysis to Optimize the Reliability of In Vitro Inhalation Toxicity Measurements Using an Air–Liquid Interface. Chem. Res. Toxicol. 34, 1370–1385.

Sharma, G., and Goodwin, J. (2006). Effect of aging on respiratory system physiology and immunology. Clin. Interv. Aging 1, 253-260.