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Relationship: 2860

Title

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

Systemic acute phase response 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 adjacent High High 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 Do not cite Under Development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
All life stages 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 systemic acute phase response (Key event 1439) and atherosclerosis (Key event 1443) as the adverse outcome. The evidence of the KER presented is based on in vitro studies, animal studies (mice) and human epidemiological studies.

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 high. 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, denominated foam cells (Lindhorst, Young, Bagshaw, Hyland, & Kisilevsky, 1997; McGillicuddy et al., 2009; Meek, Urieli-Shoval, & Benditt, 1994). Foam cells are early markers of atherosclerotic lesions (Libby et al., 2019), and it has been shown that macrophages have a higher uptake of HDL containing SAA than HDL alone (Lindhorst et al., 1997).

The two major human acute phase response, SAA and C-reactive protein (CRP), have been shown to be correlated in humans (Baumann et al., 2018; Monse et al., 2018; Ridker, Hennekens, Buring, & Rifai, 2000), and both are predictors of future cardiovascular event risks (Ridker et al., 2000).

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

Mendelian randomization studies have shown that C-reactive protein (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).

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

Modulating factor

Specification

Effects on the KER

References

Life style

High body mass index

Increased level of serum amyloid A (SAA) and C reactive protein (CRP), therefore increased risk of atherosclerosis.

(Johnson et al., 2004)

Life style

Smoking

Increased level of CRP, therefore increased risk of atherosclerosis.

(Johnson et al., 2004; Willeit et al., 2000)

Medication

Intake of non-steroidal anti-inflammatory drugs

Reduction of CRP and other pro-inflammatory markers, decrease risk of atherosclerosis.

(Libby et al., 2019)

Medical conditions

Chronic inflammatory diseases

Increased level of acute phase proteins, therefore increased risk of atherosclerosis.

(Gabay & Kushner, 1999)

Medical conditions

Infectious diseases

Increased levels of CRP, therefore increased risk of atherosclerosis.

(Willeit et al., 2000)

Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help

The concentration of blood C-reactive protein (CRP) and serum amyloid A (SAA) (Key event 1439) is associated with the risk of nonfatal myocardial infarction or fatal coronary heart disease (i.e. acute events due to the progression of atherosclerosis – Key event 1443) (Pai et al., 2004; Ridker et al., 2000).

The association can be calculated from prospective, epidemiological studies. This approach was used by the Dutch Expert Committee on Occupational Safety (DECOS) when establishing a health-based occupational exposure limit for diesel engine exhaust based on risk of lung cancer (https://www.healthcouncil.nl/documents/advisory-reports/2019/03/13/diesel-engine-exhaust).

The Nurses’ Health Study (NHS) and the Health Professionals Follow-up Study (HPFS) are prospective cohort investigations respectively involving 121,700 female U.S. registered nurses who were 30 to 55 years old at baseline in 1976 and 51,529 U.S. male health professionals who were 40 to 75 years old at baseline in 1986 (Pai et al., 2004). In the NHS, among women without cardiovascular disease or cancer before 1990, 249 women had a nonfatal myocardial infarction or fatal coronary heart disease between the date of blood drawing and follow-up in June 1998. In the HPFS, 266 men had a nonfatal myocardial infarction or fatal coronary heart disease between the date of blood drawing and the return of a follow-up questionnaire in year 2000.

In the NHS and HPFS studies, the associations between CRP in blood and risk of nonfatal myocardial infarction or fatal coronary heart disease for women and men were reported in Pai et al. (2004) (Pai et al., 2004), whereas the association for both SAA and CRP in NHS was reported in Ridker et al. (2000) (Ridker et al., 2000).

The dose-response relationships are shown in Figure 1. Here, plasma levels of CRP and SAA were closely associated with future risk of coronary heart disease (CHD).

Figure 1. Association between the relative risk (RR) of CHD in NHS as function of quartiles of serum levels of CRP and SAA from Ridker et al. (Ridker et al., 2000) and quintiles of CRP from the NHS and the HPFS studies from Pai et al. (Pai et al., 2004). The trend lines are linear associations, as these gave the highest R2 values.

According to the Danish Heart Foundation (https://hjerteforeningen.dk/alt-om-dit-hjerte/noegletal/), when a person reaches the age of 55 years, the lifetime risk of a cardiovascular event is 67% in men and 66% in women. Each year, 56,379 Danes are diagnosed with a cardiovascular disease, from which, 15,087 were diagnosed with are apoplexy and 16,050 with ischemic heart disease. As these diagnoses are regarded as manifestations of plaque progression, it means that 55% of the cardiovascular diagnoses are relate to plaque progression. The lifetime risk of these diseases is thus calculated as 0.66x0.55 (lifetime risk x %cardiovascular diseases) = 0.363 = 36%.

Based on this the lifetime risk, the relative risk of 1:100 excess cardiovascular disease was calculated as

RR= (1 + 36)/36= 1.02778

The relative risk of 1:1000 excess cardiovascular disease was calculated as

RR= (1+360)/360= 1.00278

If the relative risk of 1.02778 excess is used in the equations obtained in Figure 1 and presented in the next table, it is observed that in the studies by Ridker et. al and Pai et al., 6-54% increases in blood levels of CRP or SAA were associated with 1% increased risk of cardiovascular disease.

Biomarker

Equation of increased IRR

Increase of biomarker associated with 1% increased risk(1)

Baseline levels

Increase of biomarker in % of baseline level associated 1% increased risk

CRP women (Ridker et al., 2000)

ΔIRR = 0.4025 CRP (mg/L)

0.07 mg/L

0.6 mg/L

0.07/0.6= 12%

SAA women (Ridker et al., 2000)

ΔIRR=  0.2013 SAA (mg/L)

0.138 mg/L

2.5 mg/L

0.138/2.5=6%

CRP women (Pai et al., 2004)

ΔIRR= 0.1015 CRP (mg/L

0.27 mg/L

0.5 mg/L

0.27/0.5=54%

CRP men (Pai et al., 2004)

ΔIRR= 0.2812 CRP (mg/L)

0.099 mg/L

0.27 mg/L

0.099/0.27=37%

(1) The biomarker level is calculated as 0.02778/slope. For example, for CRP level in women CRP = 0.02778/0.4025 = 0.07 mg/L.

Time-scale
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

Atherosclerosis is an inflammatory condition (Balci, 2011; Ross, 1999), therefore there are increased levels of pro-inflammatory factors, including acute phase proteins, than can sustain the progression of atherosclerosis (Kobiyama & Ley, 2018).

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

Although atherosclerosis is mostly observed in adult humans, this condition begins early in life, and progresses through adulthood (McGill, McMahan, & Gidding, 2008; McMahan et al., 2005). Children with chronic inflammation diseases have shown to develop atherosclerosis in early childhood. (Tyrrell et al., 2010; Yamamura et al., 2014). In addition, atherosclerosis is manifested in males and females (Libby, 2021).

References

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

Balci, B. (2011). The modification of serum lipids after acute coronary syndrome and importance in clinical practice. Curr Cardiol Rev, 7(4), 272-276. doi:10.2174/157340311799960690

Baumann, R., Brand, P., Chaker, A., Markert, A., Rack, I., Davatgarbenam, S., . . . Gube, M. (2018). Human nasal mucosal C-reactive protein responses after inhalation of ultrafine welding fume particles: positive correlation to systemic C-reactive protein responses. Nanotoxicology, 12(10), 1130-1147. doi:10.1080/17435390.2018.1498930

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

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

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

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

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

Johnson, B. D., Kip, K. E., Marroquin, O. C., Ridker, P. M., Kelsey, S. F., Shaw, L. J., . . . Blood, I. (2004). Serum amyloid A as a predictor of coronary artery disease and cardiovascular outcome in women: the National Heart, Lung, and Blood Institute-Sponsored Women's Ischemia Syndrome Evaluation (WISE). Circulation, 109(6), 726-732. doi:10.1161/01.CIR.0000115516.54550.B1

Kobiyama, K., & Ley, K. (2018). Atherosclerosis. Circ Res, 123(10), 1118-1120. doi:10.1161/CIRCRESAHA.118.313816

Lee, H. Y., Kim, S. D., Baek, S. H., Choi, J. H., Cho, K. H., Zabel, B. A., & Bae, Y. S. (2013). Serum amyloid A stimulates macrophage foam cell formation via lectin-like oxidized low-density lipoprotein receptor 1 upregulation. Biochem Biophys Res Commun, 433(1), 18-23. doi:10.1016/j.bbrc.2013.02.077

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

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

McGill, H. C., Jr., McMahan, C. A., & Gidding, S. S. (2008). Preventing heart disease in the 21st century: implications of the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study. Circulation, 117(9), 1216-1227. doi:10.1161/CIRCULATIONAHA.107.717033

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

McMahan, C. A., Gidding, S. S., Fayad, Z. A., Zieske, A. W., Malcom, G. T., Tracy, R. E., . . . McGill, H. C., Jr. (2005). Risk scores predict atherosclerotic lesions in young people. Arch Intern Med, 165(8), 883-890. doi:10.1001/archinte.165.8.883

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

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

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

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

Ross, R. (1999). Atherosclerosis--an inflammatory disease. N Engl J Med, 340(2), 115-126. doi:10.1056/NEJM199901143400207

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

Tyrrell, P. N., Beyene, J., Feldman, B. M., McCrindle, B. W., Silverman, E. D., & Bradley, T. J. (2010). Rheumatic disease and carotid intima-media thickness: a systematic review and meta-analysis. Arterioscler Thromb Vasc Biol, 30(5), 1014-1026. doi:10.1161/ATVBAHA.109.198424

Willeit, J., Kiechl, S., Oberhollenzer, F., Rungger, G., Egger, G., Bonora, E., . . . Muggeo, M. (2000). Distinct risk profiles of early and advanced atherosclerosis: prospective results from the Bruneck Study. Arterioscler Thromb Vasc Biol, 20(2), 529-537. doi:10.1161/01.atv.20.2.529

Yamamura, K., Takada, H., Uike, K., Nakashima, Y., Hirata, Y., Nagata, H., . . . Hara, T. (2014). Early progression of atherosclerosis in children with chronic infantile neurological cutaneous and articular syndrome. Rheumatology (Oxford), 53(10), 1783-1787. doi:10.1093/rheumatology/keu180