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AOP: 237

Title

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

Substance interaction with lung resident cell membrane components leading to atherosclerosis

Short name
A name that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
Interaction with lung cells leading to atherosclerosis

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

Authors

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

Claudia Torero Gutierrez1, Sarah Søs Poulsen1, Jorid Birkelund Sørli1,  Håkan Wallin2, Sabina Halappanavar3, Carole L. Yauk4, Ulla Vogel1,*

1The National Research Centre for the Working Environment, Denmark

2Statens Arbeidsmiljøinstitutt, Norway

3Health Canada, Canada

4University of Ottawa, Canada

*Corresponding author: Ulla Vogel (ubv@nfa.dk)

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
Ulla Vogel   (email point of contact)

Contributors

Users with write access to the AOP page.  Entries in this field are controlled by the Point of Contact. More help
  • Sarah Søs Poulsen
  • Ulla Vogel
  • Claudia Torero Gutierrez
  • Jorid Birkelund Sørli

Coaches

This field is used to identify coaches who supported the development of the AOP.Each coach selected must be a registered author. More help
  • Sabina Halappanavar

Status

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
Handbook Version OECD status OECD project
v2.5 Under Development 1.55
This AOP was last modified on December 19, 2023 09:56

Revision dates for related pages

Page Revision Date/Time
Transcription of genes encoding acute phase proteins, Increased December 18, 2023 07:14
Systemic acute phase response December 18, 2023 07:41
Atherosclerosis December 18, 2023 07:50
Substance interaction with the lung resident cell membrane components May 17, 2023 15:10
Increased, secretion of proinflammatory mediators May 17, 2023 15:18
Interaction with the lung cell membrane leads to Increased proinflammatory mediators August 29, 2023 09:00
Interaction with the lung cell membrane leads to Increased transcription of genes encoding acute phase proteins December 19, 2023 05:17
Increased proinflammatory mediators leads to Increased transcription of genes encoding acute phase proteins December 19, 2023 05:16
Interaction with the lung cell membrane leads to Systemic acute phase response December 19, 2023 05:19
Increased proinflammatory mediators leads to Systemic acute phase response December 19, 2023 05:20
Increased transcription of genes encoding acute phase proteins leads to Systemic acute phase response December 19, 2023 05:17
Interaction with the lung cell membrane leads to Atherosclerosis December 18, 2023 10:40
Systemic acute phase response leads to Atherosclerosis December 18, 2023 09:14
Lipopolysaccharride May 29, 2018 07:05
Graphene oxide nanoparticles February 15, 2017 04:41
Carbon nanotubes August 09, 2017 08:03
Insoluble nano-sized particles May 29, 2018 07:09
Virus May 29, 2018 07:10

Abstract

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

AOP 237 the key events between the interaction of substances with the membrane components of the pulmonary cells leading to atherosclerosis in humans. Atherosclerosis is defined as the thickening of the wall of an artery due to plaque deposition, and this condition can lead to severe events as myocardial infarction and stroke. This AOP presents the induction of acute phase response as a pathway for atherosclerosis progression. The interaction between a substance and the lung resident cell membrane components is the molecular initiating event (MIE; Event 1495) for this AOP; this interaction leads to an increased secretion of proinflammatory mediators [Key event (KE)1; Event 1496]. The release of proinflammatory factors triggers an increase in transcription of genes encoding acute phase proteins (KE2; Event 1438), leading to systemic acute phase response (KE3; Event 1439) once the acute phase proteins are translated and released into the systemic circulation. A continuous acute phase response leads to atherosclerosis, the adverse outcome (AO) of this AOP (Event 1443).

AOP 237 mainly focus on particles or particulate matter as stressors, however other compounds or inflammatory conditions that induce acute phase response, can be consider stressors and lead to atherosclerosis. In addition, most of the evidence is based on animal studies (mice) as a model for the human system, however the adverse outcome of the present AOP, atherosclerosis, is only applicable to humans. The AOP presents the biological plausibility, evidence and quantitative understanding for the relationship between KEs. In addition, evidence that KE2, KE3 and KE4 occur after the MIE is presented as non-adjacent relationships. This AOP presents a mechanism of substance-induced acute phase response leading to atherosclerosis, and it can be used for regulatory purposes and health-based risk assessments of inhalable materials.

AOP Development Strategy

Context

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

Cardiovascular disease (CVD) is the leading cause of death worldwide, being responsible for 32% of all deaths in 2019 (WHO; http://www.who.int). The term CVD covers all diseases of the cardiovascular system, including atherosclerosis, which is manifested as increased plaque deposition or build-up in the arteries. Although, atherosclerosis is not a cause of death, it can lead to fatal conditions as stroke and myocardial infarction. Atherosclerosis is normally an asymptotic disease and is initiated by a biological, chemical or physical insult to the artery walls. This leads to the expression of cell adhesion molecules on the endothelial lining of the arteries, which facilitates the activation, recruitment, and migration of monocytes through the endothelial monolayer (Cybulsky et al., 2001; Hansson & Libby, 2006). Inside the intima layer, the monocytes differentiate into macrophages and internalize fatty deposits (mainly oxidized low-density lipoprotein). This results in them transforming into foam cells, which is a major component of the atherosclerotic fatty streaks. The fatty streaks reduce the elasticity of the artery walls and the foam cells promote a pro-inflammatory environment by secretion of cytokines and reactive oxidative species. In addition, foam cells also induce the recruitment of smooth muscle cells to the intima. Added together, these changes lead to the formation of plaques on the artery walls. A fibrous cap of collagen and vascular smooth muscle cells protects the necrotic core and stabilizes the plaque (Libby, 2012; Virmani et al., 2005). However, blood clots can be formed if the plaque ruptures. These may travel with the bloodstream and obstruct the blood flow of smaller vessels, e.g. the coronary arteries, which ultimately can lead to myocardial infarction.

Inhalation of particulate matter, chemicals and pathogens have been related to increased pulmonary inflammation. Whereas a normal immune reaction is crucial for effective elimination of threats to the body, chronic and unresolved inflammation has been linked to both adverse pulmonary and adverse systemic effects in humans. In concordance with this, various retrospective and prospective epidemiological studies have linked pulmonary exposure to respirable air particulates with increased the risk of developing CVD (Clancy, Goodman, Sinclair, & Dockery, 2002; Dockery et al., 1993; Pope et al., 2004; Pope et al., 1995). Inhalation of particles has been proposed to affect the cardiovascular system in several different ways, including through disruption of vasomotor function and through acceleration of plaque progression in atherosclerosis (Cao et al., 2014; Moller et al., 2016).

Acute phase response is characterized by the change in plasma concentration of acute phase proteins (APP), along with other physiological changes during inflammatory conditions (Gabay & Kushner, 1999; Mantovani & Garlanda, 2023). Serum amyloid A (SAA) and C-reactive protein (CRP) are the major acute phase proteins in humans and are considered risk factors for CVDs (Table 1 presents acute phase response characteristics in humans and mice). In particular, SAA restricts the transport of cholesterol to the liver, allowing the accumulation of cholesterol in arteries and the formation of foam cells.

Table 1. Selected differences in APR between humans and mice.

Characteristic

Humans

Mice

Number of identified genes involved in acute phase response

61

62

Major acute phase proteins

CRP, SAA

Haptoglobin, SAA, serum amyloid P

Moderate and minor acute phase proteins

Haptoglobin, fibrinogen, α1 acid glycoprotein

CRP, fibrinogen

SAA isoforms

Saa1, Saa2 and Saa4

Saa1, Saa2, Saa3 and Saa4

References: (Cray, 2012; Gabay & Kushner, 1999; NCBI, 2023; Tannock et al., 2018).

Atherosclerosis is a disease influenced by multiple factors including high levels of lipoproteins in blood, elevated blood pressure, smoking, obesity, type 2 diabetes, diet, and physical activity (Herrington, Lacey, Sherliker, Armitage, & Lewington, 2016; Libby et al., 2019; Raitakari, Pahkala, & Magnussen, 2022). Inflammation is also involved in atherosclerosis, providing pathways via which risk factors might cause the development and advancement of atherosclerotic plaques (Libby, 2021a, 2021b). Therefore, although inflammation and acute phase response are not the only causes of atherosclerosis, the early key events (KE1, KE2 and KE3) can be used to evaluate the particle-induced risk of developing atherosclerosis.

For the development of AOP 237, the MIE and KE1 from AOP 173 have been used (AOP 173: Substance interaction with the pulmonary resident cell membrane components leading to pulmonary fibrosis). The information presented in AOP 173 has not been modified for AOP 237.

The development of the present AOP was supported by the EU project NanoPASS (Grant number: 101092741) and the Focused Research Effort on Chemicals in the Working Environment (FFIKA) form the Danish Government.

Strategy

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

Events:

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 1495 Substance interaction with the lung resident cell membrane components Interaction with the lung cell membrane
KE 1496 Increased, secretion of proinflammatory mediators Increased proinflammatory mediators
KE 1438 Transcription of genes encoding acute phase proteins, Increased Increased transcription of genes encoding acute phase proteins
KE 1439 Systemic acute phase response Systemic acute phase response
AO 1443 Atherosclerosis Atherosclerosis

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
Adult High

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 High NCBI
mouse Mus musculus High NCBI

Sex Applicability

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

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

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

This AOP is applicable to adult humans of both sexes. Although atherosclerosis is a condition that begins during childhood and progresses through life, its clinical manifestation is mostly observed in older individuals (Raitakari et al., 2022).

The AOP is applicable to all stressors that can be inhaled and, therefore, interact with the pulmonary cells and induce pulmonary inflammation.

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

For the development of AOP 237, the molecular initiating event (MIE) and key event (KE) 1 from AOP 173 have been reused (AOP 173: Substance interaction with the pulmonary resident cell membrane components leading to pulmonary fibrosis). The information presented in AOP 173 has not been modified for AOP 237.

Support for essentiality of KEs

Defining question

High

Moderate

Low

What is the impact on downstream KEs and/or the AO if an upstream KE is modified or prevented?

Direct evidence from specifically designed experimental studies illustrating prevention or impact on downstream KEs and/or the AO if upstream KEs are blocked or modified

Indirect evidence that modification of one or more upstream KEs is associated with a corresponding (increase or decrease) in the magnitude or frequency of downstream KEs

No or contradictory experimental evidence of the essentiality of any of the KEs.

MIE: Substance interaction with the lung resident cell membrane components (Event 1495)

Moderate.

Stressors have a dose-response relationship with transcription of genes encoding acute phase proteins (KE2) and systemic acute phase response (KE3) (Bengtson et al., 2017; Di Ianni et al., 2020; Monse et al., 2018; Poulsen et al., 2017; Saber et al., 2013).

Knockout of toll-like receptor 4 (Tlr4) prevents the lipopolysaccharide-induced increase of cytokine/chemokines mRNA levels in lung and liver tissues (KE1) and prevents lipopolysaccharide-induced systemic acute phase response (KE3) in mice (Danielsen et al., 2021).

Knockout of toll-like receptor 2 (Tlr2) prevents the multiwalled carbon nanotubes-induced increase of Saa1 mRNA levels in liver tissue (KE2) and serum amyloid A (SAA)1 levels in plasma (KE3) in mice (Danielsen et al., 2021).

KE1: Increased, secretion of proinflammatory mediators (Event 1496)

High.

Interleukin (IL) 6 gene disruption (IL-6-/-) reduces the liver mRNA levels (KE2) and serum levels (KE3) of the acute phase proteins haptoglobin, α1-acid glycoprotein and SAA in mice (Kopf et al., 1994).

Blockage of IL-6 receptors reduced SAA1 mRNA, while blockage of IL-1β and tumor necrosis factor α receptors partially reduces the expression of SAA1 mRNA (KE2), in hepatic cell lines (Hagihara et al., 2004).

Administration of monoclonal antibodies for IL-1β reduces blood levels of C-reactive protein (CRP) (KE2 and KE3), and decreased the incidence rates of recurrent cardiovascular events (AO), in patients with a history of myocardial infarction (Ridker et al., 2017)

KE2: Transcription of genes encoding acute phase proteins, Increased (Event 1438)

High.

Gene transcription is necessary for the synthesis of proteins (KE3) (Alberts, 2017).

Suppression of SAA3 and double knockout of SAA1/SAA2 reduces atherosclerotic plaque area (AO), in ApoE-/- mice (Thompson et al., 2018).

KE3: Systemic acute phase response (Event 1439)

High.

Elevated levels of SAA induce plaque progression (AO) (Christophersen et al., 2021; Dong et al., 2011; Thompson et al., 2018).

CRP and SAA levels are predictive of risk of cardiovascular disease (Pai et al., 2004; Ridker, Hennekens, Buring, & Rifai, 2000).

AO: Atherosclerosis (Event 1443)

N/A.

This is the AO and it is essential for the AOP.

Uncertainties or Inconsistencies

  • Physicochemical characteristics of nanomaterials such as size, surface area, surface functionalization, shape, composition, among others, affect the magnitude and duration of acute phase response in mice (Bengtson et al., 2017; Gutierrez et al., 2023; Poulsen et al., 2017). In animal models, both inflammatory and acute phase response are predicted by the total surface area of the retained, insoluble particles (Cosnier et al., 2021; Gutierrez et al., 2023).
  • C-reactive protein (CRP) and serum amyloid A (SAA) are risk factors for cardiovascular disease (Ridker et al., 2000). However, Mendelian randomization studies have shown that CRP genotypes are not associated with risk of coronary heart disease and that genetically elevated levels of CRP are not associated with coronary heart disease risk (Collaboration et al., 2011; Elliott et al., 2009).
  • In mice studies, it is possible to measure both Saa gene expression and SAA protein levels, however the dynamic range for Saa gene expression is larger. In humans, measuring gene expression of acute phase proteins is not very common, as a tissue sample is needed, while measuring acute phase protein in blood is more common.
  • It is suggested that acute phase proteins are mainly produced in the liver (Gabay & Kushner, 1999), however in mice the liver has little upregulation of Saa genes after exposure to ultrafine carbon particles or diesel exhaust particle. On the other hand, the lung shows a marked expression of Saa3 mRNA (Saber et al., 2009; Saber et al., 2013).
  • A level of inconsistency between the results from human studies exists. It has been observed that in most controlled human studies, an increase in CRP and/or SAA was observed after exposure to particulate matter (Baumann et al., 2018; Haase et al., 2022; Monse et al., 2018; Monse et al., 2021; Walker et al., 2022; Wyatt, Devlin, Rappold, Case, & Diaz-Sanchez, 2020). However, in other  studies the exposure did not induce acute phase response (Andersen, Saber, Clausen, et al., 2018; Andersen, Saber, Pedersen, et al., 2018), maybe due to low levels of exposure (Andersen et al., 2019) or limited statistical power.

Evidence Assessment

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

Biological plausibility of each KER

Please also refer to AOP173: Substance interaction with the pulmonary resident cell membrane components leading to pulmonary fibrosis, which shares MIE and KE1 with the present AOP.

Support for Biological Plasuibility of KERs

Defining question

High

Moderate

Low

Is there a mechanistic (i.e., structural or functional) relationship between KEup and KEdown consistent with established biological knowledge?

Extensive understanding based on extensive previous documentation and broad acceptance -Established mechanistic basis

The KER is plausible based on analogy to accepted biological relationships but scientific understanding is not completely established.

There is empirical support for a statistical association between KEs (See 3.), but the structural or functional relationship between them is not understood.

MIE => KE1: Interaction with the lung cell membrane leads to Increased proinflammatory mediators (Relationship 1702)

Biological Plausibility of the MIE => KE1 is High.

Rationale: There is extensive evidence showing that interaction of stressors with the respiratory system induces the release of proinflammatory markers (Behzadi et al., 2017; Denholm & Phan, 1990; Dostert et al., 2008; Mossman & Churg, 1998).

KE1 => KE2: Increased proinflammatory mediators leads to Increased transcription of genes encoding acute phase proteins (Relationship 2053)

Biological Plausibility of the KE1 => KE2 is High.

Rationale: Acute phase proteins are induced by pro-inflammatory cytokines. These cytokines are produced at sites of inflammation mainly by monocytes and macrophages (Gabay & Kushner, 1999; Mantovani & Garlanda, 2023; Uhlar & Whitehead, 1999; Venteclef, Jakobsson, Steffensen, & Treuter, 2011).

KE2 => KE3: Increased transcription of genes encoding acute phase proteins leads to Systemic acute phase response (Relationship 1589)

Biological Plausibility of the KE2 => KE3 is High.

Rationale: After gene expression of acute phase proteins in tissues mRNA is translated and folded into proteins (Alberts, 2017). These proteins are then release to the systemic circulation (Van Eeden, Leipsic, Paul Man, & Sin, 2012).

KE3 => AO:  Systemic acute phase response leads to Atherosclerosis (Relationship 2860)

Biological Plausibility of the KE3 => KE2 is High.

Rationale: During acute phase response, serum amyloid A (SAA), one of the major acute phase proteins, replaces apolipoprotein A-1 from high density lipoprotein (HDL). This replacement obstructs the reverse transport of cholesterol to the liver, allowing the accumulation of cholesterol in cells (Lindhorst, Young, Bagshaw, Hyland, & Kisilevsky, 1997; McGillicuddy et al., 2009; Meek, Urieli-Shoval, & Benditt, 1994).

Non-adjacent

MIE => KE2: Interaction with the lung cell membrane leads to Increased transcription of genes encoding acute phase proteins (Relationship 2958)

Biological Plausibility of the MIE => KE2 is High.

Rationale: After cells sense pathogens, tissue damage or dysmetabolism, production of acute phase proteins is triggered by cellular pattern-recognition molecules, through a cytokine cascade (Mantovani & Garlanda, 2023).

There is extensive evidence that nanomaterials induce the expression of acute phase response genes in mice (Bengtson et al., 2017; Di Ianni et al., 2020; Erdely, Liston, et al., 2011; Gutierrez et al., 2023; Hadrup et al., 2019; Halappanavar et al., 2015; Poulsen, Saber, Mortensen, et al., 2015; Saber et al., 2013).

Non-adjacent

MIE => KE3: Interaction with the lung cell membrane leads to Systemic acute phase response (Relationship 2959)

Biological Plausibility of the MIE => KE3 is High.

Rationale: Pulmonary inflammation occurs when stressors interact with the airways (Moldoveanu et al., 2009) and acute phase response is induced during inflammatory conditions (Gabay & Kushner, 1999).

There is plenty of evidence showing that inhalation or instillation of stressors induces systemic acute phase response in humans and mice mice (Baumann et al., 2016; Bendtsen et al., 2019; Bengtson et al., 2017; Bourdon et al., 2012; Erdely, Liston, et al., 2011; Kim, Chen, Boyce, & Christiani, 2005; Monse et al., 2018; Monse et al., 2021; Poulsen et al., 2017; Poulsen, Saber, Williams, et al., 2015; Westberg et al., 2016).

Non-adjacent

KE1 => KE3: Increased proinflammatory mediators leads to Systemic APR (Relantionship 3052)

Biological Plausibility of the KE1 => KE3 is High.

Rationale: Pro-inflammatory cytokines induce the release of acute phase proteins. These proteins are released from inflammatory sites to the systemic circulation (Gabay & Kushner, 1999; Mantovani & Garlanda, 2023).

Non-adjacent

MIE => AO: Interaction with the lung cell membrane leads to Atherosclerosis (Relantionship 2960)

Biological Plausibility of the MIE => AO is Moderate.

Rationale: There is evidence that the interaction of the lungs with stressor induces atherosclerotic plaque progression; however, the mechanistic relationship has not been clarified (Christophersen et al., 2021; Erdely, Hulderman, et al., 2011; M. R. Miller et al., 2013; M. R. Miller & Newby, 2020; Van Eeden et al., 2012).

Empirical support for each KER

Please also refer to AOP173: Substance interaction with the pulmonary resident cell membrane components leading to pulmonary fibrosis, which shares MIE and KE1 with the present AOP.

Empirical Support

Defining question

High

Moderate

Low

Does KEup occur at lower doses and earlier time points than KE down and at the same dose of prototypical stressor, is the incidence of KEup > than that for KEdown?

Are there inconsistencies in empirical support across taxa, species and prototypical stressor that don’t align with expected pattern for hypothesised

AOP?

Multiple studies showing dependent change in both events following exposure to a wide range of specific prototypical stressors. (Extensive evidence for temporal, dose- response and incidence concordance) and no or few critical data gaps or conflicting data

Demonstrated dependent change in both events following exposure to a small number of specific prototypical stressors and some evidence inconsistent with expected pattern that can be explained by factors such as experimental design, technical considerations, differences among laboratories, etc.

 

Limited or no studies reporting dependent change in both events following exposure to a specific prototypical stressor (i.e., endpoints never measured in the same study or not at all); and/or significant inconsistencies in empirical support across taxa and species that don’t align with expected pattern for hypothesised AOP

MIE => KE1: Interaction with the lung cell membrane leads to Increased proinflammatory mediators (Relationship 1702)

Empirical Support of the MIE => KE1 is Moderate. 

Rationale: There are limited in vitro studies which show a temporal and dose-dependent relationship between these two events (Chan et al., 2018; Denholm & Phan, 1990; Roy, Singh, Das, Tripathi, & Dwivedi, 2014).

KE1 => KE2: Increased proinflammatory mediators leads to Increased transcription of genes encoding acute phase proteins (Relationship 2053)

Empirical Support of the KE1 => KE2 is High.

Rationale: There are several studies showing a dose concordance and temporal concordance between KEs (Bendtsen et al., 2019; Di Ianni et al., 2020; Kyjovska et al., 2015; Saber et al., 2012; Saber et al., 2013; Wallin et al., 2017).

KE2 => KE3: Increased transcription of genes encoding acute phase proteins leads to Systemic acute phase response (Relationship 1589)

Empirical Support of the KE2 => KE3 is High.

Rationale: There are studies showing a dose concordance and temporal concordance between KE (Bengtson et al., 2017; Gutierrez et al., 2023; Poulsen et al., 2017). However, there are inconsistencies between gene expression and translation of acute phase proteins.

KE3 => AO:  Systemic acute phase response leads to Atherosclerosis (Relationship 2860)

Empirical Support of the KE3 => AO is Moderate.

Rationale: There is a limited number of animal studies showing the relationship between the KEs, in addition of epidemiological studies showing association between the KEs (Christophersen et al., 2021; Dong et al., 2011; Pai et al., 2004; Rivera et al., 2013; Thompson et al., 2015; Thompson et al., 2018).

Non-adjacent

MIE => KE2: Interaction with the lung cell membrane leads to Increased transcription of genes encoding acute phase proteins (Relationship 2958)

Empirical Support of the MIE => KE2 is Moderate.

Rationale: There are several studies showing a dose concordance and temporal concordance in animal studies. However, in the case of nanomaterials it has been shown that physicochemical characteristics affect the magnitude and duration of the expression of acute phase proteins in mice (Bengtson et al., 2017; Bourdon et al., 2012; Gutierrez et al., 2023; Kyjovska et al., 2015; Poulsen et al., 2017; Saber et al., 2013; Wallin et al., 2017).

Non-adjacent

MIE => KE3: Interaction with the lung cell membrane leads to Systemic acute phase response (Relationship 2959)

Empirical Support of the MIE => KE3 is Moderate.

Rationale: There are plenty of studies showing a dose concordance and temporal concordance in animal and controlled human studies (Brand et al., 2014; Erdely, Liston, et al., 2011; Kim et al., 2005; Monse et al., 2018; Monse et al., 2021; Poulsen et al., 2017; Walker et al., 2022; Wyatt et al., 2020). However, it has been observed that systemic acute phase response is not always observed after exposure.

Non-adjacent

KE1 => KE3: Increased proinflammatory mediators leads to Systemic APR (Relantionship 3052)

Empirical Support of the KE1 => KE3 is Moderate.

Rationale: There are several studies showing a dose concordance and temporal concordance. However, there are inconsistencies between changes in blood levels of pro-inflammatory mediators and systemic APR (Baumann et al., 2016; Kim et al., 2005; Monse et al., 2018; Monse et al., 2021; Poulsen et al., 2017).

Non-adjacent

MIE => AO: Interaction with the lung cell membrane leads to Atherosclerosis (Relantionship 2960)

Empirical Support of the MIE => AO is Moderate.

Rationale: There are several studies showing the relationship between the key events (Christophersen et al., 2021; Li et al., 2007; Mikkelsen et al., 2011; M. R. Miller et al., 2013).

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

Modulating factor

Influence on outcome

KER involved

High body mass index

Increased risk of atherosclerosis.

KER4

Smoking

Increased risk of atherosclerosis.

KER4

Intake of non-steroidal anti-inflammatory drugs

Decreased risk of atherosclerosis.

KER4

Chronic inflammatory diseases

Increased risk of atherosclerosis.

KER4

Infectious diseases

Increased risk of atherosclerosis.

KER4

Quantitative Understanding

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

The table below presents the quantitative understanding of every KER.

It is important to clarify that when assessing stressors in mice studies, it is possible to measure the gene expression of acute phase proteins (KE2) in different tissues, whereas in humans this is not likely as a tissue sample would be required. On the other hand, in humans it is much more common and easier to measure systemic acute phase response (KE3) through a blood sample. In mice, it has been shown that Saa3 mRNA in lung tissue and blood levels of serum amyloid A (SAA)3 are correlated (Gutierrez et al., 2023). In addition, SAA levels in mice and humans seem to be in level in magnitude after exposure to zinc oxide nanoparticles (Gutierrez et al., 2023). This suggest that systemic acute phase response in humans can be estimated from mice studies.

Saa3 mRNA in lung tissue is also correlated to pulmonary inflammation measured as neutrophil numbers in broncheoalveolar lavage fluid (i.e. indirect marker of the release of pro-inflammatory factors because the release of inflammatory mediators) in mice after pulmonary exposure to nanomaterials. Both of these endpoints can be estimated by calculating the dosed surface area (specific surface area multiplied by dose level) (Gutierrez et al., 2023).

Finally, the relative risk of people developing a cardiovascular disease can be calculated from blood levels of acute phase proteins in epidemiological studies.

KER

Quantitative understanding

MIE => KE1: Interaction with the lung cell membrane leads to Increased proinflammatory mediators (Relationship 1702)

The quantitative understanding of MIE => KE1 is Low.

Rationale: The quantitative prediction of the release of proinflammatory factors can be made from the interaction of the stressors with the pulmonary system.

In the case of some stressors (nanomaterials) it is possible to make a prediction using the dosed surface area of the materials and neutrophil numbers in broncheoalveolar lavage (BALF) as an indirect marker of the release of pro-inflammatory factors (Gutierrez et al., 2023; Oberdorster, Ferin, Gelein, Soderholm, & Finkelstein, 1992; Oberdorster, Ferin, & Lehnert, 1994; Schmid & Stoeger, 2016; Stoeger et al., 2006).

KE1 => KE2: Increased proinflammatory mediators leads to Increased transcription of genes encoding acute phase proteins (Relationship 2053)

The quantitative understanding is of KE1 => KE2 is Moderate.

Rationale: In mice, the gene expression of Saa after exposure to metal oxide nanomaterials can be estimated using an indirect marker of the release of pro-inflammatory factors (neutrophil numbers in BALF)  (Gutierrez et al., 2023).

KE2 => KE3: Increased transcription of genes encoding acute phase proteins leads to Systemic acute phase response (Relationship 1589)

The quantitative understanding of KE2 => KE3 is Moderate.

Rationale: In mice, the systemic levels of SAA after exposure to metal oxide nanomaterials can be estimated from the gene expression in lung tissue (Gutierrez et al., 2023).

KE3 => AO:  Systemic acute phase response leads to Atherosclerosis (Relationship 2860)

The quantitative understanding is of KE3 => AO is High.

Rationale: The risk of developing a cardiovascular disease at population level can be calculated from blood levels of acute phase proteins (KER 2860).

Non-adjacent

MIE => KE2: Interaction with the lung cell membrane leads to Increased transcription of genes encoding acute phase proteins (Relationship 2958)

The quantitative understanding of MIE => KE2 is Moderate.

Rationale: In mice, the gene expression of Saa after exposure to metal oxide nanomaterials can be estimated from the dosed surface area (Gutierrez et al., 2023).

Non-adjacent

MIE => KE3: Interaction with the lung cell membrane leads to Systemic acute phase response (Relationship 2959)

The quantitative understanding of MIE => KE3 is Moderate.

Rationale: In mice, the blood levels of SAA after exposure to metal oxide nanomaterials can be estimated from the dosed surface area (Gutierrez et al., 2023).

Non-adjacent

KE1 => KE3: Increased proinflammatory mediators leads to Systemic APR (Relantionship 3052)

The quantitative understanding of KE1 => KE3 is Moderate.

Rationale: In mice, the blood levels of SAA after exposure to metal oxide nanomaterials and multiwalled carbon nanotubes can be estimated from neutrophil numbers in BALF (Gutierrez et al., 2023; Poulsen et al., 2017).

Non-adjacent

MIE => AO: Interaction with the lung cell membrane leads to Atherosclerosis (Relantionship 2960)

The quantitative understanding of MIE => AO is Moderate.

Rationale: Epidemiological studies have shown the risk ratios of having a cardiovascular event per increase or decrease of exposure to particulate matter (Beelen et al., 2014; Cesaroni et al., 2014; Clancy et al., 2002; K. A. Miller et al., 2007)

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

Particle-induced acute phase response can be regarded as a critical effect linking particle-exposure to cardiovascular disease. Dose-response relationships can be used to establish no-observed-adverse-effect levels (NOAEL) for regulatory purposes and occupational exposure limits for inhalable materials can be determined through health-based risk assessments. This approach was taken by the Danish National Research Centre for the Working Environment at request of the Danish Working Environment Authority and an occupational exposure limit for zinc oxide was proposed based on the induction of acute phase response as the critical effect (the report can be found in: Dokumentation for helbredsbaserede grænseværdier for kemiske stoffer i arbejdsmiljøet (nfa.dk)).

As mentioned previously, not all KE can easily be measured in humans, therefore animal studies can be used to measure early KEs and perform a risk assessment of different stressors. Additionally, physicochemical properties, such as specific surface area and dissolution, are important predictors of particle-induced acute phase response that can be used for hazard assessment (Gutierrez et al., 2023).

References

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

Alberts, B. (2017). Molecular biology of the cell (Sixth edition. ed.). Boca Raton, FL: CRC Press, an imprint of Garland Science.

Andersen, M. H. G., Frederiksen, M., Saber, A. T., Wils, R. S., Fonseca, A. S., Koponen, I. K., . . . Vogel, U. (2019). Health effects of exposure to diesel exhaust in diesel-powered trains. Part Fibre Toxicol, 16(1), 21. doi:10.1186/s12989-019-0306-4

Andersen, M. H. G., Saber, A. T., Clausen, P. A., Pedersen, J. E., Lohr, M., Kermanizadeh, A., . . . Vogel, U. (2018). Association between polycyclic aromatic hydrocarbon exposure and peripheral blood mononuclear cell DNA damage in human volunteers during fire extinction exercises. Mutagenesis, 33(1), 105-115. doi:10.1093/mutage/gex021

Andersen, M. H. G., Saber, A. T., Pedersen, J. E., Pedersen, P. B., Clausen, P. A., Lohr, M., . . . Moller, P. (2018). Assessment of polycyclic aromatic hydrocarbon exposure, lung function, systemic inflammation, and genotoxicity in peripheral blood mononuclear cells from firefighters before and after a work shift. Environ Mol Mutagen, 59(6), 539-548. doi:10.1002/em.22193

Baumann, R., Gube, M., Markert, A., Davatgarbenam, S., Kossack, V., Gerhards, B., . . . Brand, P. (2018). Systemic serum amyloid A as a biomarker for exposure to zinc and/or copper-containing metal fumes. J Expo Sci Environ Epidemiol, 28(1), 84-91. doi:10.1038/jes.2016.86

Baumann, R., Joraslafsky, S., Markert, A., Rack, I., Davatgarbenam, S., Kossack, V., . . . Gube, M. (2016). IL-6, a central acute-phase mediator, as an early biomarker for exposure to zinc-based metal fumes. Toxicology, 373, 63-73. doi:10.1016/j.tox.2016.11.001

Beelen, R., Stafoggia, M., Raaschou-Nielsen, O., Andersen, Z. J., Xun, W. W., Katsouyanni, K., . . . Hoek, G. (2014). Long-term exposure to air pollution and cardiovascular mortality: an analysis of 22 European cohorts. Epidemiology, 25(3), 368-378. doi:10.1097/EDE.0000000000000076

Behzadi, S., Serpooshan, V., Tao, W., Hamaly, M. A., Alkawareek, M. Y., Dreaden, E. C., . . . Mahmoudi, M. (2017). Cellular uptake of nanoparticles: journey inside the cell. Chem Soc Rev, 46(14), 4218-4244. doi:10.1039/c6cs00636a

Bendtsen, K. M., Brostrom, A., Koivisto, A. J., Koponen, I., Berthing, T., Bertram, N., . . . Vogel, U. (2019). Airport emission particles: exposure characterization and toxicity following intratracheal instillation in mice. Part Fibre Toxicol, 16(1), 23. doi:10.1186/s12989-019-0305-5

Bengtson, S., Knudsen, K. B., Kyjovska, Z. O., Berthing, T., Skaug, V., Levin, M., . . . Vogel, U. (2017). Differences in inflammation and acute phase response but similar genotoxicity in mice following pulmonary exposure to graphene oxide and reduced graphene oxide. PLoS One, 12(6), e0178355. doi:10.1371/journal.pone.0178355

Bourdon, J. A., Halappanavar, S., Saber, A. T., Jacobsen, N. R., Williams, A., Wallin, H., . . . Yauk, C. L. (2012). Hepatic and pulmonary toxicogenomic profiles in mice intratracheally instilled with carbon black nanoparticles reveal pulmonary inflammation, acute phase response, and alterations in lipid homeostasis. Toxicol Sci, 127(2), 474-484. doi:10.1093/toxsci/kfs119

Brand, P., Bauer, M., Gube, M., Lenz, K., Reisgen, U., Spiegel-Ciobanu, V. E., & Kraus, T. (2014). Relationship between welding fume concentration and systemic inflammation after controlled exposure of human subjects with welding fumes from metal inert gas brazing of zinc-coated materials. J Occup Environ Med, 56(1), 1-5. doi:10.1097/JOM.0000000000000061

Cao, Y., Jacobsen, N. R., Danielsen, P. H., Lenz, A. G., Stoeger, T., Loft, S., . . . Moller, P. (2014). Vascular effects of multiwalled carbon nanotubes in dyslipidemic ApoE-/- mice and cultured endothelial cells. Toxicol Sci, 138(1), 104-116. doi:10.1093/toxsci/kft328

Cesaroni, G., Forastiere, F., Stafoggia, M., Andersen, Z. J., Badaloni, C., Beelen, R., . . . Peters, A. (2014). 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

Chan, J. Y. W., Tsui, J. C. C., Law, P. T. W., So, W. K. W., Leung, D. Y. P., Sham, M. M. K., . . . Chan, C. W. H. (2018). Regulation of TLR4 in silica-induced inflammation: An underlying mechanism of silicosis. Int J Med Sci, 15(10), 986-991. doi:10.7150/ijms.24715

Christophersen, D. V., Moller, P., Thomsen, M. B., Lykkesfeldt, J., Loft, S., Wallin, H., . . . Jacobsen, N. R. (2021). Accelerated atherosclerosis caused by serum amyloid A response in lungs of ApoE(-/-) mice. FASEB J, 35(3), e21307. doi:10.1096/fj.202002017R

Clancy, L., Goodman, P., Sinclair, H., & Dockery, D. W. (2002). Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study. Lancet, 360(9341), 1210-1214. doi:10.1016/S0140-6736(02)11281-5

Collaboration, C. R. P. C. H. D. G., Wensley, F., Gao, P., Burgess, S., Kaptoge, S., Di Angelantonio, E., . . . Danesh, J. (2011). Association between C reactive protein and coronary heart disease: mendelian randomisation analysis based on individual participant data. BMJ, 342, d548. doi:10.1136/bmj.d548

Cosnier, F., Seidel, C., Valentino, S., Schmid, O., Bau, S., Vogel, U., . . . Gate, L. (2021). Retained particle surface area dose drives inflammation in rat lungs following acute, subacute, and subchronic inhalation of nanomaterials. Part Fibre Toxicol, 18(1), 29. doi:10.1186/s12989-021-00419-w

Cray, C. (2012). Acute phase proteins in animals. Prog Mol Biol Transl Sci, 105, 113-150. doi:10.1016/B978-0-12-394596-9.00005-6

Cybulsky, M. I., Iiyama, K., Li, H., Zhu, S., Chen, M., Iiyama, M., . . . Milstone, D. S. (2001). A major role for VCAM-1, but not ICAM-1, in early atherosclerosis. J Clin Invest, 107(10), 1255-1262. doi:10.1172/JCI11871

Danielsen, P. H., Bendtsen, K. M., Knudsen, K. B., Poulsen, S. S., Stoeger, T., & Vogel, U. (2021). Nanomaterial- and shape-dependency of TLR2 and TLR4 mediated signaling following pulmonary exposure to carbonaceous nanomaterials in mice. Part Fibre Toxicol, 18(1), 40. doi:10.1186/s12989-021-00432-z

Denholm, E. M., & Phan, S. H. (1990). Bleomycin binding sites on alveolar macrophages. J Leukoc Biol, 48(6), 519-523. doi:10.1002/jlb.48.6.519

Di Ianni, E., Moller, P., Mortensen, A., Szarek, J., Clausen, P. A., Saber, A. T., . . . Jacobsen, N. R. (2020). Organomodified nanoclays induce less inflammation, acute phase response, and genotoxicity than pristine nanoclays in mice lungs. Nanotoxicology, 14(7), 869-892. doi:10.1080/17435390.2020.1771786

Dockery, D. W., Pope, C. A., 3rd, Xu, X., Spengler, J. D., Ware, J. H., Fay, M. E., . . . Speizer, F. E. (1993). An association between air pollution and mortality in six U.S. cities. N Engl J Med, 329(24), 1753-1759. doi:10.1056/NEJM199312093292401

Dong, Z., Wu, T., Qin, W., An, C., Wang, Z., Zhang, M., . . . An, F. (2011). Serum amyloid A directly accelerates the progression of atherosclerosis in apolipoprotein E-deficient mice. Mol Med, 17(11-12), 1357-1364. doi:10.2119/molmed.2011.00186

Dostert, C., Petrilli, V., Van Bruggen, R., Steele, C., Mossman, B. T., & Tschopp, J. (2008). Innate immune activation through Nalp3 inflammasome sensing of asbestos and silica. Science, 320(5876), 674-677. doi:10.1126/science.1156995

Elliott, P., Chambers, J. C., Zhang, W., Clarke, R., Hopewell, J. C., Peden, J. F., . . . Kooner, J. S. (2009). Genetic Loci associated with C-reactive protein levels and risk of coronary heart disease. JAMA, 302(1), 37-48. doi:10.1001/jama.2009.954

Erdely, A., Hulderman, T., Salmen-Muniz, R., Liston, A., Zeidler-Erdely, P. C., Chen, B. T., . . . Simeonova, P. P. (2011). Inhalation exposure of gas-metal arc stainless steel welding fume increased atherosclerotic lesions in apolipoprotein E knockout mice. Toxicol Lett, 204(1), 12-16. doi:10.1016/j.toxlet.2011.03.030

Erdely, A., Liston, A., Salmen-Muniz, R., Hulderman, T., Young, S. H., Zeidler-Erdely, P. C., . . . Simeonova, P. P. (2011). Identification of systemic markers from a pulmonary carbon nanotube exposure. J Occup Environ Med, 53(6 Suppl), S80-86. doi:10.1097/JOM.0b013e31821ad724

Gabay, C., & Kushner, I. (1999). Acute-phase proteins and other systemic responses to inflammation. N Engl J Med, 340(6), 448-454. doi:10.1056/NEJM199902113400607

Gutierrez, C. T., Loizides, C., Hafez, I., Brostrom, A., Wolff, H., Szarek, J., . . . Vogel, U. (2023). Acute phase response following pulmonary exposure to soluble and insoluble metal oxide nanomaterials in mice. Part Fibre Toxicol, 20(1), 4. doi:10.1186/s12989-023-00514-0

Haase, L. M., Birk, T., Poland, C. A., Holz, O., Muller, M., Bachand, A. M., & Mundt, K. A. (2022). Cross-sectional Study of Workers Employed at a Copper Smelter-Effects of Long-term Exposures to Copper on Lung Function and Chronic Inflammation. J Occup Environ Med, 64(9), e550-e558. doi:10.1097/JOM.0000000000002610

Hadrup, N., Rahmani, F., Jacobsen, N. R., Saber, A. T., Jackson, P., Bengtson, S., . . . Vogel, U. (2019). Acute phase response and inflammation following pulmonary exposure to low doses of zinc oxide nanoparticles in mice. Nanotoxicology, 13(9), 1275-1292. doi:10.1080/17435390.2019.1654004

Hagihara, K., Nishikawa, T., Isobe, T., Song, J., Sugamata, Y., & Yoshizaki, K. (2004). IL-6 plays a critical role in the synergistic induction of human serum amyloid A (SAA) gene when stimulated with proinflammatory cytokines as analyzed with an SAA isoform real-time quantitative RT-PCR assay system. Biochem Biophys Res Commun, 314(2), 363-369. doi:10.1016/j.bbrc.2003.12.096

Halappanavar, S., Saber, A. T., Decan, N., Jensen, K. A., Wu, D., Jacobsen, N. R., . . . Vogel, U. (2015). Transcriptional profiling identifies physicochemical properties of nanomaterials that are determinants of the in vivo pulmonary response. Environ Mol Mutagen, 56(2), 245-264. doi:10.1002/em.21936

Hansson, G. K., & Libby, P. (2006). The immune response in atherosclerosis: a double-edged sword. Nat Rev Immunol, 6(7), 508-519. doi:10.1038/nri1882

Herrington, W., Lacey, B., Sherliker, P., Armitage, J., & Lewington, S. (2016). Epidemiology of Atherosclerosis and the Potential to Reduce the Global Burden of Atherothrombotic Disease. Circ Res, 118(4), 535-546. doi:10.1161/CIRCRESAHA.115.307611

Kim, J. Y., Chen, J. C., Boyce, P. D., & Christiani, D. C. (2005). Exposure to welding fumes is associated with acute systemic inflammatory responses. Occup Environ Med, 62(3), 157-163. doi:10.1136/oem.2004.014795

Kopf, M., Baumann, H., Freer, G., Freudenberg, M., Lamers, M., Kishimoto, T., . . . Kohler, G. (1994). Impaired immune and acute-phase responses in interleukin-6-deficient mice. Nature, 368(6469), 339-342. doi:10.1038/368339a0

Kyjovska, Z. O., Jacobsen, N. R., Saber, A. T., Bengtson, S., Jackson, P., Wallin, H., & Vogel, U. (2015). DNA strand breaks, acute phase response and inflammation following pulmonary exposure by instillation to the diesel exhaust particle NIST1650b in mice. Mutagenesis, 30(4), 499-507. doi:10.1093/mutage/gev009

Li, Z., Hulderman, T., Salmen, R., Chapman, R., Leonard, S. S., Young, S. H., . . . Simeonova, P. P. (2007). Cardiovascular effects of pulmonary exposure to single-wall carbon nanotubes. Environ Health Perspect, 115(3), 377-382. doi:10.1289/ehp.9688

Libby, P. (2012). Inflammation in atherosclerosis. Arterioscler Thromb Vasc Biol, 32(9), 2045-2051. doi:10.1161/ATVBAHA.108.179705

Libby, P. (2021a). The changing landscape of atherosclerosis. Nature, 592(7855), 524-533. doi:10.1038/s41586-021-03392-8

Libby, P. (2021b). Inflammation during the life cycle of the atherosclerotic plaque. Cardiovasc Res, 117(13), 2525-2536. doi:10.1093/cvr/cvab303

Libby, P., Buring, J. E., Badimon, L., Hansson, G. K., Deanfield, J., Bittencourt, M. S., . . . Lewis, E. F. (2019). Atherosclerosis. Nat Rev Dis Primers, 5(1), 56. doi:10.1038/s41572-019-0106-z

Lindhorst, E., Young, D., Bagshaw, W., Hyland, M., & Kisilevsky, R. (1997). Acute inflammation, acute phase serum amyloid A and cholesterol metabolism in the mouse. Biochim Biophys Acta, 1339(1), 143-154. doi:10.1016/s0167-4838(96)00227-0

Mantovani, A., & Garlanda, C. (2023). Humoral Innate Immunity and Acute-Phase Proteins. N Engl J Med, 388(5), 439-452. doi:10.1056/NEJMra2206346

McGillicuddy, F. C., de la Llera Moya, M., Hinkle, C. C., Joshi, M. R., Chiquoine, E. H., Billheimer, J. T., . . . Reilly, M. P. (2009). Inflammation impairs reverse cholesterol transport in vivo. Circulation, 119(8), 1135-1145. doi:10.1161/CIRCULATIONAHA.108.810721

Meek, R. L., Urieli-Shoval, S., & Benditt, E. P. (1994). Expression of apolipoprotein serum amyloid A mRNA in human atherosclerotic lesions and cultured vascular cells: implications for serum amyloid A function. Proc Natl Acad Sci U S A, 91(8), 3186-3190. doi:10.1073/pnas.91.8.3186

Mikkelsen, L., Sheykhzade, M., Jensen, K. A., Saber, A. T., Jacobsen, N. R., Vogel, U., . . . Moller, P. (2011). 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

Miller, K. A., Siscovick, D. S., Sheppard, L., Shepherd, K., Sullivan, J. H., Anderson, G. L., & Kaufman, J. D. (2007). Long-term exposure to air pollution and incidence of cardiovascular events in women. N Engl J Med, 356(5), 447-458. doi:10.1056/NEJMoa054409

Miller, M. R., McLean, S. G., Duffin, R., Lawal, A. O., Araujo, J. A., Shaw, C. A., . . . Hadoke, P. W. (2013). 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

Miller, M. R., & Newby, D. E. (2020). Air pollution and cardiovascular disease: car sick. Cardiovasc Res, 116(2), 279-294. doi:10.1093/cvr/cvz228

Moldoveanu, B., Otmishi, P., Jani, P., Walker, J., Sarmiento, X., Guardiola, J., . . . Yu, J. (2009). Inflammatory mechanisms in the lung. J Inflamm Res, 2, 1-11.

Moller, P., Christophersen, D. V., Jacobsen, N. R., Skovmand, A., Gouveia, A. C., Andersen, M. H., . . . Loft, S. (2016). Atherosclerosis and vasomotor dysfunction in arteries of animals after exposure to combustion-derived particulate matter or nanomaterials. Crit Rev Toxicol, 46(5), 437-476. doi:10.3109/10408444.2016.1149451

Monse, C., Hagemeyer, O., Raulf, M., Jettkant, B., van Kampen, V., Kendzia, B., . . . Merget, R. (2018). Concentration-dependent systemic response after inhalation of nano-sized zinc oxide particles in human volunteers. Part Fibre Toxicol, 15(1), 8. doi:10.1186/s12989-018-0246-4

Monse, C., Raulf, M., Jettkant, B., van Kampen, V., Kendzia, B., Schurmeyer, L., . . . Bunger, J. (2021). Health effects after inhalation of micro- and nano-sized zinc oxide particles in human volunteers. Arch Toxicol, 95(1), 53-65. doi:10.1007/s00204-020-02923-y

Mossman, B. T., & Churg, A. (1998). Mechanisms in the pathogenesis of asbestosis and silicosis. Am J Respir Crit Care Med, 157(5 Pt 1), 1666-1680. doi:10.1164/ajrccm.157.5.9707141

NCBI. (2023). Retrieved from https://www.ncbi.nlm.nih.gov/gene

Oberdorster, G., Ferin, J., Gelein, R., Soderholm, S. C., & Finkelstein, J. (1992). Role of the alveolar macrophage in lung injury: studies with ultrafine particles. Environ Health Perspect, 97, 193-199. doi:10.1289/ehp.97-1519541

Oberdorster, G., Ferin, J., & Lehnert, B. E. (1994). Correlation between particle size, in vivo particle persistence, and lung injury. Environ Health Perspect, 102 Suppl 5(Suppl 5), 173-179. doi:10.1289/ehp.102-1567252

Pai, J. K., Pischon, T., Ma, J., Manson, J. E., Hankinson, S. E., Joshipura, K., . . . Rimm, E. B. (2004). Inflammatory markers and the risk of coronary heart disease in men and women. N Engl J Med, 351(25), 2599-2610. doi:10.1056/NEJMoa040967

Pope, C. A., 3rd, Burnett, R. T., Thurston, G. D., Thun, M. J., Calle, E. E., Krewski, D., & Godleski, J. J. (2004). Cardiovascular mortality and long-term exposure to particulate air pollution: epidemiological evidence of general pathophysiological pathways of disease. Circulation, 109(1), 71-77. doi:10.1161/01.CIR.0000108927.80044.7F

Pope, C. A., 3rd, Thun, M. J., Namboodiri, M. M., Dockery, D. W., Evans, J. S., Speizer, F. E., & Heath, C. W., Jr. (1995). Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults. Am J Respir Crit Care Med, 151(3 Pt 1), 669-674. doi:10.1164/ajrccm/151.3_Pt_1.669

Poulsen, S. S., Knudsen, K. B., Jackson, P., Weydahl, I. E., Saber, A. T., Wallin, H., & Vogel, U. (2017). Multi-walled carbon nanotube-physicochemical properties predict the systemic acute phase response following pulmonary exposure in mice. PLoS One, 12(4), e0174167. doi:10.1371/journal.pone.0174167

Poulsen, S. S., Saber, A. T., Mortensen, A., Szarek, J., Wu, D., Williams, A., . . . Vogel, U. (2015). Changes in cholesterol homeostasis and acute phase response link pulmonary exposure to multi-walled carbon nanotubes to risk of cardiovascular disease. Toxicol Appl Pharmacol, 283(3), 210-222. doi:10.1016/j.taap.2015.01.011

Poulsen, S. S., Saber, A. T., Williams, A., Andersen, O., Kobler, C., Atluri, R., . . . Vogel, U. (2015). MWCNTs of different physicochemical properties cause similar inflammatory responses, but differences in transcriptional and histological markers of fibrosis in mouse lungs. Toxicol Appl Pharmacol, 284(1), 16-32. doi:10.1016/j.taap.2014.12.011

Raitakari, O., Pahkala, K., & Magnussen, C. G. (2022). Prevention of atherosclerosis from childhood. Nat Rev Cardiol, 19(8), 543-554. doi:10.1038/s41569-021-00647-9

Ridker, P. M., Everett, B. M., Thuren, T., MacFadyen, J. G., Chang, W. H., Ballantyne, C., . . . Group, C. T. (2017). Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease. N Engl J Med, 377(12), 1119-1131. doi:10.1056/NEJMoa1707914

Ridker, P. M., Hennekens, C. H., Buring, J. E., & Rifai, N. (2000). C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med, 342(12), 836-843. doi:10.1056/NEJM200003233421202

Rivera, M. F., Lee, J. Y., Aneja, M., Goswami, V., Liu, L., Velsko, I. M., . . . Kesavalu, L. N. (2013). Polymicrobial infection with major periodontal pathogens induced periodontal disease and aortic atherosclerosis in hyperlipidemic ApoE(null) mice. PLoS One, 8(2), e57178. doi:10.1371/journal.pone.0057178

Roy, R., Singh, S. K., Das, M., Tripathi, A., & Dwivedi, P. D. (2014). Toll-like receptor 6 mediated inflammatory and functional responses of zinc oxide nanoparticles primed macrophages. Immunology, 142(3), 453-464. doi:10.1111/imm.12276

Saber, A. T., Halappanavar, S., Folkmann, J. K., Bornholdt, J., Boisen, A. M., Moller, P., . . . Wallin, H. (2009). Lack of acute phase response in the livers of mice exposed to diesel exhaust particles or carbon black by inhalation. Part Fibre Toxicol, 6, 12. doi:10.1186/1743-8977-6-12

Saber, A. T., Jacobsen, N. R., Mortensen, A., Szarek, J., Jackson, P., Madsen, A. M., . . . Wallin, H. (2012). Nanotitanium dioxide toxicity in mouse lung is reduced in sanding dust from paint. Part Fibre Toxicol, 9, 4. doi:10.1186/1743-8977-9-4

Saber, A. T., Lamson, J. S., Jacobsen, N. R., Ravn-Haren, G., Hougaard, K. S., Nyendi, A. N., . . . Vogel, U. (2013). Particle-induced pulmonary acute phase response correlates with neutrophil influx linking inhaled particles and cardiovascular risk. PLoS One, 8(7), e69020. doi:10.1371/journal.pone.0069020

Schmid, O., & Stoeger, T. (2016). Surface area is the biologically most effective dose metric for acute nanoparticle toxicity in the lung. Journal of Aerosol Science, 99, 133-143.

Stoeger, T., Reinhard, C., Takenaka, S., Schroeppel, A., Karg, E., Ritter, B., . . . Schulz, H. (2006). Instillation of six different ultrafine carbon particles indicates a surface area threshold dose for acute lung inflammation in mice. Environ Health Perspect, 114(3), 328-333. doi:10.1289/ehp.8266

Tannock, L. R., De Beer, M. C., Ji, A., Shridas, P., Noffsinger, V. P., den Hartigh, L., . . . Webb, N. R. (2018). Serum amyloid A3 is a high density lipoprotein-associated acute-phase protein. J Lipid Res, 59(2), 339-347. doi:10.1194/jlr.M080887

Thompson, J. C., Jayne, C., Thompson, J., Wilson, P. G., Yoder, M. H., Webb, N., & Tannock, L. R. (2015). A brief elevation of serum amyloid A is sufficient to increase atherosclerosis. J Lipid Res, 56(2), 286-293. doi:10.1194/jlr.M054015

Thompson, J. C., Wilson, P. G., Shridas, P., Ji, A., de Beer, M., de Beer, F. C., . . . Tannock, L. R. (2018). Serum amyloid A3 is pro-atherogenic. Atherosclerosis, 268, 32-35. doi:10.1016/j.atherosclerosis.2017.11.011

Uhlar, C. M., & Whitehead, A. S. (1999). Serum amyloid A, the major vertebrate acute-phase reactant. Eur J Biochem, 265(2), 501-523. doi:10.1046/j.1432-1327.1999.00657.x

Van Eeden, S., Leipsic, J., Paul Man, S. F., & Sin, D. D. (2012). The relationship between lung inflammation and cardiovascular disease. Am J Respir Crit Care Med, 186(1), 11-16. doi:10.1164/rccm.201203-0455PP

Venteclef, N., Jakobsson, T., Steffensen, K. R., & Treuter, E. (2011). Metabolic nuclear receptor signaling and the inflammatory acute phase response. Trends Endocrinol Metab, 22(8), 333-343. doi:10.1016/j.tem.2011.04.004

Virmani, R., Kolodgie, F. D., Burke, A. P., Finn, A. V., Gold, H. K., Tulenko, T. N., . . . Narula, J. (2005). Atherosclerotic plaque progression and vulnerability to rupture: angiogenesis as a source of intraplaque hemorrhage. Arterioscler Thromb Vasc Biol, 25(10), 2054-2061. doi:10.1161/01.ATV.0000178991.71605.18

Walker, E. S., Fedak, K. M., Good, N., Balmes, J., Brook, R. D., Clark, M. L., . . . Peel, J. L. (2022). Acute differences in blood lipids and inflammatory biomarkers following controlled exposures to cookstove air pollution in the STOVES study. Int J Environ Health Res, 32(3), 565-578. doi:10.1080/09603123.2020.1785402

Wallin, H., Kyjovska, Z. O., Poulsen, S. S., Jacobsen, N. R., Saber, A. T., Bengtson, S., . . . Vogel, U. (2017). Surface modification does not influence the genotoxic and inflammatory effects of TiO2 nanoparticles after pulmonary exposure by instillation in mice. Mutagenesis, 32(1), 47-57. doi:10.1093/mutage/gew046

Westberg, H., Elihn, K., Andersson, E., Persson, B., Andersson, L., Bryngelsson, I. L., . . . Sjogren, B. (2016). Inflammatory markers and exposure to airborne particles among workers in a Swedish pulp and paper mill. Int Arch Occup Environ Health, 89(5), 813-822. doi:10.1007/s00420-016-1119-5

Wyatt, L. H., Devlin, R. B., Rappold, A. G., Case, M. W., & Diaz-Sanchez, D. (2020). Low levels of fine particulate matter increase vascular damage and reduce pulmonary function in young healthy adults. Part Fibre Toxicol, 17(1), 58. doi:10.1186/s12989-020-00389-5