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Relationship: 2960


A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Interaction with the lung cell membrane leads to Atherosclerosis

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). 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

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Substance interaction with lung resident cell membrane components leading to atherosclerosis non-adjacent High Moderate Ulla Vogel (send email) Under development: Not open for comment. Do not cite Under Development

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) 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.  More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Male High
Female High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
Adults High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

This KER presents the association between the interaction of stressors with the lungs and atherosclerosis as the outcome. The evidence of the KER presented is based on mouse models of human atherosclerosis.

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field 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.   More help

The biological plausibility is moderate. Exposure to different stressors have been shown to induce the progression of atherosclerotic in mouse models of human atherosclerosis (see below). In humans, it has been hypothesized that air pollution, an example of stressor that interacts with the lungs, and cardiovascular diseases are linked by three pathways: i) translocation of inflammatory mediators from the lungs to the systemic circulation, ii) activation of alveolar receptors that results in the alteration of autonomic response and changes in cardiovascular function, and iii) translocation of particles (stressors) from the lungs to the systemic circulation 1,2.

Uncertainties and Inconsistencies
Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

ApoE-/- mice seem to have a moderate plaque progression when feed a normal diet, instead of high-fat diet, and exposed to the stressor for a short period 6.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help
  • Following the ban of coal in Dublin, a decrease of 70% of black smoke (35 μg/m3) was observed along with a 10.3% decrease (p<0.0001) in cardiovascular deaths 10.
  • A prospective study following postmenopausal women from USA for 6 years observed that an increase of 10 μg of PM2.5 (particulate matter with a diameter of less than 2.5 μm) was associated with 24% increased risk of cardiovascular event and a 76% increased risk of death from a cardiovascular disease 11.
  • Beelen et al. analyzed data from 22 European cohort studies on long-term exposure to air pollution and associations with cardiovascular diseases mortality. It was obtained that a PM2.5 increase of 5 μg/m3 was associated with 21% increased risk of death from cerebrovascular disease, while an increase of 10 μg/m3 of PM10 (particulate matter with a diameter of less than 10 μm) was associated with an 22% increased risk of death from cerebrovascular disease 12.
  • Results from 11 cohort studies on long-term exposure to air pollution and incidence of acute coronary events showed a 13% increased risk of coronary events associated to 5 μg/m3 increase of PM2.5, and a 12% increased risk of coronary events associated to 10 μg/m3 increase of PM10 13.
  • A cohort study of population living in Denmark between 2005 and 2017, and aged more than 50 years old, showed that a 5 μg/m3 increase of PM2.5 was associated to a 22% increased risk of stroke, while an increase of 1.85 μg/m3 increase of PM2.5 was associated to a 5.3% increased risk of myocardial infarction 14,15.
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?). More help
Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Mouse models of human atherosclerosis has been shown to present atherosclerotic lesion progression after exposure to concentrated ambient particles, welding fumes and diesel exhaust particles 3,5,7.

In humans, epidemiological studies have shown that air pollution, as a stressor that interacts with the lungs, is a risk factor for cardiovascular diseases 14.


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

1            Miller, M. R. & Newby, D. E. Air pollution and cardiovascular disease: car sick. Cardiovasc Res 116, 279-294, doi:10.1093/cvr/cvz228 (2020).

2            Van Eeden, S., Leipsic, J., Paul Man, S. F. & Sin, D. D. The relationship between lung inflammation and cardiovascular disease. Am J Respir Crit Care Med 186, 11-16, doi:10.1164/rccm.201203-0455PP (2012).

3            Chen, L. C. & Nadziejko, C. Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice. V. CAPs exacerbate aortic plaque development in hyperlipidemic mice. Inhal Toxicol 17, 217-224, doi:10.1080/08958370590912815 (2005).

4            Li, Z. et al. Cardiovascular effects of pulmonary exposure to single-wall carbon nanotubes. Environ Health Perspect 115, 377-382, doi:10.1289/ehp.9688 (2007).

5            Erdely, A. et al. Inhalation exposure of gas-metal arc stainless steel welding fume increased atherosclerotic lesions in apolipoprotein E knockout mice. Toxicol Lett 204, 12-16, doi:10.1016/j.toxlet.2011.03.030 (2011).

6            Mikkelsen, L. et al. Modest effect on plaque progression and vasodilatory function in atherosclerosis-prone mice exposed to nanosized TiO(2). Part Fibre Toxicol 8, 32, doi:10.1186/1743-8977-8-32 (2011).

7            Miller, M. R. et al. Diesel exhaust particulate increases the size and complexity of lesions in atherosclerotic mice. Part Fibre Toxicol 10, 61, doi:10.1186/1743-8977-10-61 (2013).

8            Christophersen, D. V. et al. Accelerated atherosclerosis caused by serum amyloid A response in lungs of ApoE(-/-) mice. FASEB J 35, e21307, doi:10.1096/fj.202002017R (2021).

9            Dockery, D. W. et al. An association between air pollution and mortality in six U.S. cities. N Engl J Med 329, 1753-1759, doi:10.1056/NEJM199312093292401 (1993).

10          Clancy, L., Goodman, P., Sinclair, H. & Dockery, D. W. Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study. Lancet 360, 1210-1214, doi:10.1016/S0140-6736(02)11281-5 (2002).

11          Miller, K. A. et al. Long-term exposure to air pollution and incidence of cardiovascular events in women. N Engl J Med 356, 447-458, doi:10.1056/NEJMoa054409 (2007).

12          Beelen, R. et al. Long-term exposure to air pollution and cardiovascular mortality: an analysis of 22 European cohorts. Epidemiology 25, 368-378, doi:10.1097/EDE.0000000000000076 (2014).

13          Cesaroni, G. et al. Long term exposure to ambient air pollution and incidence of acute coronary events: prospective cohort study and meta-analysis in 11 European cohorts from the ESCAPE Project. BMJ 348, f7412, doi:10.1136/bmj.f7412 (2014).

14          Poulsen, A. H. et al. 'Source-specific' air pollution and risk of stroke in Denmark. Int J Epidemiol 52, 727-737, doi:10.1093/ije/dyad030 (2023).

15          Poulsen, A. H. et al. Source-Specific Air Pollution Including Ultrafine Particles and Risk of Myocardial Infarction: A Nationwide Cohort Study from Denmark. Environ Health Perspect 131, 57010, doi:10.1289/EHP10556 (2023).

16          Vaduganathan, M., Mensah, G. A., Turco, J. V., Fuster, V. & Roth, G. A. The Global Burden of Cardiovascular Diseases and Risk: A Compass for Future Health. J Am Coll Cardiol 80, 2361-2371, doi:10.1016/j.jacc.2022.11.005 (2022).