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Relationship: 2303

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

TLR Activation/Dysregulation leads to Increased proinflammatory mediators

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
Binding of SARS-CoV-2 to ACE2 receptor leading to acute respiratory distress associated mortality adjacent High Not Specified Evgeniia Kazymova (send email) 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 Do not cite Under Development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

Sex Applicability

An indication of the the relevant sex for this KER. More help

Life Stage Applicability

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

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

The engagement of TLR with Pathogen-Associated Molecular Patterns (PAMPs) and host derived damage-associated molecular patterns (DAMPs) induces conformational changes of TLRs that allow recruitment of adaptor proteins such as MyD88, TIRAP, TRIF, and TRAM to control intracellular signaling pathways, including ERK, p38 and NF-B, driving the synthesis and secretion of cytokines and chemokines [Kawai, T.; Akira, S. Signaling to NF-kappaB by Toll-like receptors. Trends Mol. Med. 2007, 13, 460–469] [DOI:https://doi.org/10.1016/j.molmed.2007.09.002]. In a healthy state the amount and type of proinflammatory mediators are appropriate to required circumstances (e.g. defence against invading pathogens) and resolution of inflammation is promoted to reestablish homeostasis. Dysregulated TLR Activation can result from e.g. overabundance of PAMPS/DAMPS or over-, or under-expression of TLR protein intra- and/or extracellularly or over- or under-expression of downstream proteins. These circumstances can be modulated by a number of factors including biological/intrinsic factors (e.g. age, sex, genetic factors), pre-existing co-morbidities, lifestyle factors, environmental factors and therapeutic interventions. In context of an adverse outcome the resulting dysregulated over- or under-activation of TLRs contributes to dysproportional amounts of proinflammatory mediators (overproduction or underproduction) halting back defence and homeostasis.

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

Evidence in support of this KER in context of COVID-19:

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
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

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 (MF) MF Specification Effect(s) on the KER Reference(s)
       

Chemicals

(weak evidence)

PFAS (PFOA) 

PFOA exposure reduces TLR2 and Myd88 expression in zebrafish and induces a dose-dependent increase in IFN and B-cell-activating factor (BAFF) mRNA levels [1].

The TLR/MyD88/NF-kB pathway could be a mechanism through which PFOA interferes with BAFF and IFN expression [2].

Increasing TLR2 expression in zebrafish exposed to PFOA showed a linear correlation with increased levels of MyD88, IL-1β, and IL-21 mRNA levels [3].

1) doi: 10.1016/j.chemosphere.2020.126200

2) doi: 10.1186/2045-7022-3-S3-O5

3) doi: 10.1016/j.jhazmat.2014.08.043

SEX male sex (XY chromosome)

Male and female subjects both express functionally active TLRs, but sex differences have been reported. TLR3, TLR4 and TLR7 are coded by the X chromosome. Thus, certain TLR gain and/or loss of function polymorphisms have higher clinical prevalence in men. Particularly, TLR7 localizes to an area of the X chromosome known to escape X-chromosome inactivation [1]. TLR7 is more highly expressed at the protein level by female immune cells than by male ones [1]. A study showed that specific TLR7 loss of function variants lead to poor outcome of SARS-CoV-2, which could be explained via the role of TLR7 in responding to SARS-CoV-2 mRNA recognition by inducing the production of the antiviral cytokine interferon-a (IFN-a) [2]. An X-linked recessive TLR7 deficiency was found present in approximately 1% of men under 60 years old with life-threatening COVID-19) [2]. Plasmacytoid dendritic cells of men with these TLR7 variants produce less IFN-a ex vivo, which could explain their poor defence against SARS-CoV-2 [2]. Sex-specific associations between TLR polymorphisms and poor lung function have been reported [3]. Examples include gain of function polymorphisms of rs187084 in the TLR9 gene displaying significantly lower lung function in male swine operators than those with wild type. Additionally, the gain of function polymorphisms TLR9-1237T/C, rs5743836 is a risk for severe sepsis in pediatric critical care patients, with males having a higher risk and a more pronounced allele frequency of TLR9-1237T/C than females [4]. The sex hormone, testosterone, can reduce TLR4 expression and sensitivity, which is proposed to explain in part the less optimal defence during infection in male compared to female [5].

1) doi: 10.1126/sciimmunol.aap8855

2) doi: 10.1126/sciimmunol.abl4348

3) doi: 10.1080/15287394.2018.1544523

4)  Elsherif  et al., Int J Clin Exp Med 2019;12(4):4381-4386

5)  doi.org/10.1095/biolreprod.107.063545

Age Young/old people In older people, there are studies indicating both an increase and decrease in TLR expression and signalling [1,2,3]. Renshaw et al. [4] showed a decline in TLR expression and function in aged mice, explanatory for increased susceptibility to infections and poor adaptive immune responses in aging. On the other hand, Olivieri et al. [5] reported that the effect of age on signalling events downstream of TLRs is greater than the effect of age on TLR levels. They suggested that inflammaging can be triggered by an impairment of miRNAs/TLR signalling interaction (in endothelial and immune system cells), leading to activation of immune cells over time. Inflammaging is a higher basal inflammatory state in older subjects, which is a major driving force of frailty and common severe age-related diseases. Other complex age-dependent TLRs signalling mechanism include the decreased ability of aged macrophages to fight pathogens, the accumulation of senescent cells in aged subjects, and the increased release of endogenous TLRs ligands from senescence cells.

1) 10.1007/s40520-018-1064-0

2) 10.4049/jimmunol.0901022

3) 10.1016/j.mad.2005.07.009

4) 10.4049/jimmunol.169.9.4697

5) 10.1186/1742-4933-10-11

Lipids

Obesity

Obesity influences TLR9 expression, which is higher in visceral compared to subcutaneous adipose tissue depots in mice and obese patients [1]. Obesity induced cell-free DNA fragments released from adipocytes stimulate chronic adipose tissue inflammation and insulin resistance via TLR9 activation [2]

1. doi: 10.1530/JOE-18-0326

2. doi: 10.1126/sciadv.1501332

Vitamin D (moderate evidence) Vitamin D deficiency

Vitamin D status modulates cytokine production, at least partly through the differential modulation of TLRs. Vitamin D3 down-regulates TLR9 in human monocytes but not TLR3, which resulted in less secretion of IL-6 in response to TLR9 challenge [1]. High-dose oral supplementation of vitamin D3 (4000 IU/day) in human decreased TLR9 protein levels and mRNA expression of TLR3, TLR7, and TLR9 [2].

[1] doi:10.1093/rheumatology/keq124

[2] doi: 10.1007/s11010-019-03658-w

Genetic factors  

It is well-documented that the TLR expression is determined by genetic variation within the TLR genes [1]. In addition to the already mentioned sex differences in certain TLR polymorphisms, TLR genes also exhibit a distinct population distribution pattern and are the target of selection pressure. Ethnicity disparity in COVID-19 mortality rates were suggested to be explained in part by elevated gene expression of TLR7 and TLR9. In addition, allelic variation in the TLR adaptor protein, Ticam2, influences susceptibility to SARS-CoV infection in mice as Ticam2-/- mice had high susceptibility to SARS-CoV-2 infection [2].

[1] doi: 10.1096/fj.202001115R

[2] doi: 10.1016/j.clim.2020.108481

Pre-existing heart failure  

TLRs are expressed in the myocardium, with TLR4 being the most abundantly expressed, and TLR2 and TLR3 being present to a lesser extent [1].

TLR4 is upregulated in failing hearts [2-4]. The higher expression of TLR4 in HF patients could predispose them towards pro-inflammatory responses. Evidence shows that the S proteins of SARS-CoV-2 can bind to TLR4 directly or activate it via DAMP- and PAMP-mediated pathways, and thus, induce pro-inflammatory mediators, such as IL-1, IL-6 and TNF-α  [5].

The mediator of this TLR-induced activation appears to be NF-κB [6], an essential transcription factor involved in various cardiovascular pathologies [7].

In addition, following infection by SARS-CoV-2 of adult rat cardiac tissue resident macrophage-derived fibrocytes, TLR4 was further activated with a dual effect: it caused the upregulation of ACE2 and induced a pro-inflammatory M1 polarization of macrophages [8], which can further enhance the pro-inflammatory factors secretion. However, the involvement of pre-existing HF in the modulation of COVID-19 via TLRs is still not fully elucidated but deserves further investigation.

1: https://doi.org/10.1248/bpb.28.886

2: https://e-century.us/files/ijcem/12/4/ijcem0080845.pdf

3: https://doi.org/10.1172/JCI6709

4: 10.1016/j.ijcard.2006.12.024

5: https://doi.org/10.1155/2021/8874339

6: https://doi.org/10.1155/2018/9874109

7: https://doi.org/10.3390/ijms20071599

8: doi.org/10.1101/2021.08.11.455921

Diet High-fat diets impact TLR-mediated inflammation
  • In mice, expression of TLR2 and TLR4 in circulating macrophages is upregulated by circulating free fatty acids, which are increased with consumption of high fat diets [339,340]. Circulating free fatty acids also activate the NF-kB signaling directly or by activating cellular surface TLR in the hypothalamus, in mice and primary human myotube and adipose cells, leading to increased expression of some pro-inflammatory mediators [341,342].
  • A high-fat diet was also shown to modulate inflammation via TLR9, as mice lacking TLR9 or receiving a TLR7/9 antagonist had reduced upregulation of specific pro-inflammatory cytokines compared to controls upon high fat diet [343].
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help
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

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

References

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