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Event: 1848

Key Event Title

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Toll Like Receptor (TLR) Dysregulation

Short name
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TLR Activation/Dysregulation
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Biological Context

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Level of Biological Organization
Molecular

Cell term

The location/biological environment in which the event takes place.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help

Organ term

The location/biological environment in which the event takes place.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help

Key Event Components

The KE, as defined by a set structured ontology terms consisting of a biological process, object, and action with each term originating from one of 14 biological ontologies (Ives, et al., 2017; https://aopwiki.org/info_pages/2/info_linked_pages/7#List). Biological process describes dynamics of the underlying biological system (e.g., receptor signalling).Biological process describes dynamics of the underlying biological system (e.g., receptor signaling).  The biological object is the subject of the perturbation (e.g., a specific biological receptor that is activated or inhibited). Action represents the direction of perturbation of this system (generally increased or decreased; e.g., ‘decreased’ in the case of a receptor that is inhibited to indicate a decrease in the signaling by that receptor).  Note that when editing Event Components, clicking an existing Event Component from the Suggestions menu will autopopulate these fields, along with their source ID and description.  To clear any fields before submitting the event component, use the 'Clear process,' 'Clear object,' or 'Clear action' buttons.  If a desired term does not exist, a new term request may be made via Term Requests.  Event components may not be edited; to edit an event component, remove the existing event component and create a new one using the terms that you wish to add.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help

Key Event Overview

AOPs Including This Key Event

All of the AOPs that are linked to this KE will automatically be listed in this subsection. This table can be particularly useful for derivation of AOP networks including the KE. Clicking on the name of the AOP will bring you to the individual page for that AOP. More help
AOP Name Role of event in AOP Point of Contact Author Status OECD Status
TLR9 activation leading to Multi Organ Failure and ARDS KeyEvent Gillina Bezemer (send email) Under development: Not open for comment. Do not cite
Poor TLR function leading to high pathogen load MolecularInitiatingEvent Gillina Bezemer (send email) Under development: Not open for comment. Do not cite
SARS-CoV-2 leads to acute respiratory distress KeyEvent Young Jun Kim (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 KE.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 in relation to this KE. More help
Term Scientific Term Evidence Link
humans Homo sapiens High NCBI
mice Mus sp. High NCBI
all species all species High NCBI

Life Stages

An indication of the the relevant life stage(s) for this KE. More help
Life stage Evidence
Birth to < 1 month High
Old Age High
All life stages High

Sex Applicability

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Term Evidence
Mixed Moderate
Male High

Key Event Description

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Background

Toll-like receptors (TLRs) are a family of 13 conserved transmembrane receptors that are at the forefront of directing innate and adaptive immune responses against invading bacteria, fungi, viruses and parasites (Akira 2003, Takeda, Akira 2004, Pasare, Medzhitov 2005, Tal, Adini et al. 2020, van der Made, Simons et al. 2020). Upon activation TLRs initiate overlapping and distinct signaling pathways in various cell types such as macrophages (MP), conventinal DC (cDC), plasmacytoid DC (pDC), lamina propria DC (LPDC), and inflammatory monocytes (iMO). Engagement of TLR with specific stressors (e.g. PAMPs and DAMPs) induces conformational changes of TLRs that allow homo- or heterophilic interactions of TLRs and recruitment of adaptor proteins such as MyD88, TIRAP, TRIF, and TRAM to control intracellular signalling pathways leading to the synthesis and secretion of appropriate cytokines and chemokines by cells of the immune system. TLRs have various biological roles both in pathogen combat and tissue homeostasis.

This KE is first developed in context of COVID-19 CIAO project.

The key gatekeepers in detecting and combating viral infections are TLR3, TLR7, TLR8 and TLR9 and these are predominantly localized in intracellular compartments. In the setting of COVID-19, multiple TLRs are likely relevant in viral combat. Literature covering TLR triggering via SARS-CoV-2 derived PAMPS (Pathogen Associated Molecular Patterns) include:

  • TLR7 and TLR8 (+TLR3, TLR4, TLR6)  (Khanmohammadi and Rezaei, 2021)
  • TLR1, TLR4 and TLR6 activated by SARS-CoV-2 spike proteins (Choudhury A et al, 2020)
  • TLR9: Less CpG suppression in coronavirus compared to other viruses, for SARS-CoV-2 in the Envelope (E) open reading frame (E-ORF) and ORF10 (Ng et al., 2004; Digard et al. 2020) and multidisciplinary links described in Bezemer and Garssen, 2021

TLR dysregulation can be multi-fold:

  1. Underperformance of TLR function leading to poor pathogen combat. This is covered in AOP 378
  • COVID-19 patients having poor TLR function (due to polymorphisms) could potentially have less viral clearance capability and more adverse events leading to more severe disease and mortality. This has been shown for TLR7 loss of function polymorphisms (van der Made et al 2020). Knowledge Gap: it is not known if loss of function of other TLRs has a worse outcome in COVID-19 patients.
  1. Overperformance of TLR function contributing to exaggerated immune response/cytokine storm/thrombosis/progression into ARDS and MOD. This is covered in AOP377
  • TLR7 and TLR9 expression, measured by RNAseq gene analysis, is more elevated in black Americans than white Americans, which is proposed to explain in part the racial disparity in Covid-19 mortality rates via TLR mediated DC activation (Tal et al. 2020)
  • genetic mutations leading to TLR9 gain of function in human is associated with immune-mediated disease and with a higher incidence of ICU acquired infection (Chatzietal.,2018;Ng et al.,2010).
  • Higher presence of host derived TLR stressors in vulnerable patients can contribute to TLR overstimulation/dysregulation. (Bezemer and Garssen, 2021)

Different classes of "stressors" act on TLR activation/dysregulation

1.  Pathogen associated molecular patterns (PAMPs). TLRs can sense PAMPS during infection or upon exposure to stressors containing micro-organisms or fragments thereof (e.g. cigarette smoke, bioaerosols, house dust mite)

  • TLR1 is activated by bacterial Lipopeptides
  • TLR2 is activated by bacterial lipoproteins and glycolipids, TLR2 can form conformations with TLR1 and TLR6 to distinguish between diacyl and triacyl lipopeptides.
  • TLR3 is activated by viral double stranded RNA(dsRNA)
  • TLR4 is activated by Bacterial LPS
  • TLR5 is activated by Bacterial flagellig
  • TLR6 is activated by Bacterial lipopeptides and Fungal zymosan
  • TLR7 and 8 recognize viral single stranded RNA(ssRNA) and bacterial RNA.
  • TLR9 recognizes RNA and DNAmotifs that are rich in unmethylated Cytosine-phosphate-Guanine (CpG) sequences. CpG-motifs are higher expressed in the bacterial and viral genome compared to the vertebrate genome (Hemmi et al., 2000).

2. host derived Damage-Associated Molecular Patterns (DAMPS). Note that in the context and nomenclature of AOP these DAMPS cannot be labeld as "stressors" since they are derived from inside and not from outside, however these "pseudostressors" do act on the TLR receptors in similar way as PAMPs

  • TLR2 and TLR4 are activated by heat shock proteins 60 and 70  (HSP60 and HSP70); extracellular matrix components (ECM); oligosaccharides of hyaluronic acid (HA) and heparan sulfate (HS) (Piccinini AM and Midwood KS, 2010).

  • high-mobility group protein B1 (HMGB1) triggers TLR2, TLR4 and TLR9

  • Oxidative injury/Oxidized phospholipids  triggers TLR4 mediated NET formation
  • Human mitochondrial DNA (mtDNA), evolutionary derived from endosymbiont bacteria, contains unmethylated CpG-motifs and triggers inflammatory responses directly via TLR9 during injury and/or infection (Zhang et al., 2010).
  • Altered self-ligands, called carboxy-alkyl-pyrroleprotein adducts (CAPs), that are generated during oxidative stress, are known to aggravate TLR9/MyD88 pathway activation (Zhanget al., 2010;Panigrahi et al., 2013). CAPs have been shown to promote platelet activation, granule secretion, and aggregation in vitro and thrombosis in vivo (Panigrahi et al., 2013).

3. synthetic TLR triggers/blockers (agonists/antagonists) for therapeutic purposes. Examples include CpG-ODNs triggering TLR9 for vaccin adjuvants/cancer treatment/immuno-modulation

Several Modulating factors can contribute to TLR activation/dysregulation

  • Co-infection and Trauma (for instance ventilator induced damage) can induce increased levels of TLR9 stressor, mtDNA, which is known to drive worse outcome at ICU in setting of other disorders.  
  • High levels of Visceral Fat, can increase TLR9 expression levels ánd circulating mtDNA
  • Aging triggers both immunosenescence and inflammaging in part via impaired TLR function versus inappropriate triggering via increases of circulating DAMPS (Shaw et al 2011)
  • Genetic polymorphisms can lead to TLR dysregulation (TLR9 gain of function and TLR7 loss of function with worse outcome at ICU Chatzi et al 2018, van der Made et al 2020, Chen et al 2011, )
  • Circulating DAMPS such as mtDNA levels increase with age which is a familiar trait contributing to chronic inflammation, so called“inflamm-aging”in elderly people (Pinti et al., 2014).
  • Vitamin D inhibits expression levels of TLR9
  • Men, higher testosterone, higher TLR4

How It Is Measured or Detected

A description of the type(s) of measurements that can be employed to evaluate the KE and the relative level of scientific confidence in those measurements.These can range from citation of specific validated test guidelines, citation of specific methods published in the peer reviewed literature, or outlines of a general protocol or approach (e.g., a protein may be measured by ELISA). Do not provide detailed protocols. More help

Patient specific Ex vivo analysis

  • Levels of TLR specific stressors (for instance for TLR9, cell free DNA/RNA, mtDNA) are measurable in biological samples (serum, plasma)
  • TLR gain of function and loss of function polymorphisms are measurable
  • TLR expression levels on different cell types and different tissues are measurable by mRNA analysis and by protein analysis
  • TLR function in response to stressors is measurable by analysing components of downstream cascades and read outs of inflammatory mediators (IL6, IL8, IL10, Il17, INF, TNFalpha, etc). This can be done by ex vivo stimulations of cells isolated from patients for instance PBMCs.

In vitro/ in vivo models

  • TLR Reporter assays
  • TLR knock-out mice

Domain of Applicability

A description of the scientific basis for the indicated domains of applicability and the WoE calls (if provided).  More help

Cell applicability: TLRs are broadly expressed on various cell types. Examples include: epithelial cells, macrophages, neutrophils, platelets, dendritic cells, NK cells, Tcells, Bcells, neurons, Adipocytes.

Tissue/organ level : TLRs are broadly expressed in all vital tissues/organs: lung, heart, liver, spleen, kidney, brain, muscle, gut, skin

Taxonomic Applicability: TLRs are well conserved across species but between species variations are reported in terms of sensitivity towards stressors.  For instance certain CpG-ODNs have a stronger TLR9 activating potential in mice than in human and vice versa.

Life Stages: TLRs are expressed in all life stages but age variation of level of TLR activation/dysregulation are reported. In elderly immunoscenescence and inflammation are both linked to TLR dysregulation

Sex Applicability: Male and female subjects both express functionally active TLRs but sex differences have been reported. For instance certain TLR gain and/or loss of function polymorphisms have higher prevalence in men. Example of TLR7 loss of function (van der Made et al 2020) and TLR9 gain of function (Gao et al 2018, Traub et al 2012, Elsherif et al 2019). Higher testosterone in men has also been linked to higher TLR4 expression.

TLR7 is located in a region on the X-chromosome which have a high chance of escaping inactivation leading to higher expression levels in women. Estrogens trigger TLR7, which is higher in women. Exposure of Peripheral blood mononuclear cells (PBMC) to TLR7 ligands will cause a higher production of type I IFN (IFN-a) in female cells than male cells.  (Kovats, 2015;  Takahashi and Iwasaki, 2021; Libert et al.,  2010; Scully et al., 2020)

References

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

AKIRA, S., 2003. Toll-like receptor signaling. Journal of Biological Chemistry, 278(40), pp. 38105-38108.

Gillina F. G. Bezemer, Seil Sagar, Jeroen van Bergenhenegouwen, Niki A. Georgiou, Johan Garssen, Aletta D. Kraneveld and Gert Folkerts
Dual role of TLRs in asthma and COPD. Pharmacological Reviews April 1, 2012, 64 (2) 337-358; DOI: https://doi.org/10.1124/pr.111.004622
 

BEZEMER, G.F.G. and GARSSEN, J., 2021. TLR9 and COVID-19: A Multidisciplinary Theory of a Multifaceted Therapeutic Target. Frontiers in pharmacology, 11, pp. 601685.

KAWAI, T. and AKIRA, S., 2011. Toll-like Receptors and Their Crosstalk with Other Innate Receptors in Infection and Immunity. Immunity, 34(5), pp. 637-650.

PASARE, C. and MEDZHITOV, R., 2005. Toll-like receptors: Linking innate and adaptive immunity. Mechanisms of Lymphocyte Activation and Immune Regulation X: Innate Immunity, 560, pp. 11-18.

Piccinini AM, Midwood KS. DAMPening inflammation by modulating TLR signalling. Mediators Inflamm. 2010;2010:672395. doi:10.1155/2010/672395

Shaw AC, Panda A, Joshi SR, Qian F, Allore HG, Montgomery RR. Dysregulation of human Toll-like receptor function in aging. Ageing Res Rev. 2011;10(3):346-353. doi:10.1016/j.arr.2010.10.007

TAKEDA, K. and AKIRA, S., 2004. TLR signaling pathways. Seminars in immunology, 16(1), pp. 3-9.

TAL, Y., ADINI, A., ERAN, A. and ADINI, I., 2020. Racial disparity in Covid-19 mortality rates - A plausible explanation. Clinical immunology (Orlando, Fla.), 217, pp. 108481.

VAN DER MADE, C.I., SIMONS, A., SCHUURS-HOEIJMAKERS, J., VAN DEN HEUVEL, G., MANTERE, T., KERSTEN, S., VAN DEUREN, R.C., STEEHOUWER, M., VAN REIJMERSDAL, S.V., JAEGER, M., HOFSTE, T., ASTUTI, G., COROMINAS GALBANY, J., VAN DER SCHOOT, V., VAN DER HOEVEN, H., HAGMOLEN OF TEN HAVE, W., KLIJN, E., VAN DEN MEER, C., FIDDELAERS, J., DE MAST, Q., BLEEKER-ROVERS, C.P., JOOSTEN, L.A.B., YNTEMA, H.G., GILISSEN, C., NELEN, M., VAN DER MEER, J.W.M., BRUNNER, H.G., NETEA, M.G., VAN DE VEERDONK, F.L. and HOISCHEN, A., 2020. Presence of Genetic Variants Among Young Men With Severe COVID-19. Jama, .

Kovats, Cell Immunol. 2015 April; 294(2): 63–69;

Takahashi and Iwasaki, Science. 2021 Jan 22;371(6527):347-348

Libert et al., Nat Rev Immunol. 2010 Aug;10(8):594-604

Scully EP, et al. Nat Rev Immunol. 2020. PMID: 32528136