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Relationship: 1703


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

Increased proinflammatory mediators leads to Recruitment of inflammatory cells

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 the pulmonary resident cell membrane components leading to pulmonary fibrosis adjacent Moderate Low Sabina Halappanavar (send email) Under development: Not open for comment. Do not cite WPHA/WNT Endorsed
Decreased fibrinolysis and activated bradykinin system leading to hyperinflammation adjacent Penny Nymark (send email) Under development: Not open for comment. Do not cite Under Development
Frustrated phagocytosis leads to malignant mesothelioma adjacent High Not Specified Penny Nymark (send email) Under development: Not open for comment. Do not cite
Interaction with lung resident cell membrane components leads to lung cancer adjacent Moderate Low Penny Nymark (send email) Under development: Not open for comment. Do not cite
Binding of SARS-CoV-2 to ACE2 leads to hyperinflammation (via cell death) adjacent High High Laure-Alix Clerbaux (send email) Under development: Not open for comment. Do not cite

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

Pro-inflammatory mediators are the chemical and biological molecules that initiate and regulate inflammatory reactions. They are secreted following inflammation or exposure to an inflammogen. Commonly measured pro-inflammatory mediators include Interleukin (IL)-1 family cytokines, IL-4, IL-5, IL-6, Tumor necrosis factor alpha (TNF-α), Interferon gamma (IFN-γ) (KE1496)

Proinflammatory mediator increase is caused when there’s increased inflammation. This can be found in many ways, including bradykinin system activation or hypofibrinolysis (Hofman et al., 2016). With more proinflammatory mediators, this causes increased signaling from proinflammatory cytokines, which promotes leukocyte recruitment, which will differentiate into proinflammatory cells (Villeneuve et al., 2018). Increased proinflammatory mediators means this process happens more, which means increase recruitment of inflammatory cells.

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 of this KER is high. There are very well established functional relationships between the secreted signalling molecules and the chemotactic effects on pro-inflammatory cells (Harris, 1954; Petri and Sanz 2018).

Increased proinflammatory mediators means more pro-inflammatory cytokines, chemokines, vasoactive amines, and lipid mediators (Villeneuve et al., 2018). Increased signaling from these Cytokines and Chemokines promote leukocyte recruitment to areas of infection, including monocytes and neutrophils (Khatri et al., 2017; Leick et al., 2014; Marchini et al., 2016). The leukocytes will differentiate into mature pro-inflammatory cells, in response to mediators they encounter in the local tissue microenvironment (Villeneuve et al., 2018). With higher levels of leukocytes from increased pro-inflammatory mediators, it causes an increase in pro-inflammatory cells (Libby, 2015).

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

Attenuation or complete abrogation of KE1 (KE1496) and KE2 (KE1497) following inflammogenic stimuli is observed in rodents lacking functional Interleukin 1 receptor type 1 (IL-1R1) or other cell surface receptors that engage innate immune response upon stimulation (Gasse et al., 2007; Halappanavar et al., 2013). However, following exposure to MWCNTs, it has been shown that absence of IL-1R1 signalling is compensated for eventually and neutrophil influx is observed at a later post-exposure time point (Nikota et al., 2017). In another study, acute neutrophilic inflammation induced by MWCNTs was suppressed at 24 h in mice deficient in IL-1R1 signalling; however, these mice showed exacerbated neutrophilic influx and fibrotic response at 28 days post-exposure (Girtsman et al., 2014). The early defence mechanisms involving damage-associated molecular patterns is fundamental for survival, which may necessitate activation of compensatory signalling pathways. As a result, inhibition of a single biological pathway mediated by an individual cell surface receptor may not be sufficient to completely abrogate the lung inflammatory response. Forced suppression of pro-inflammatory and immune responses early after exposure to substances that cannot be effectively cleared from lungs, may enhance the injury and initiate other pathways leading to exacerbated response.

Most of the studies evaluate one dose at different time points or one-time point at different concentrations. Moreover, some studies have demonstrated that a stressor can lead to the recruitment of pro-inflammatory cells, but the presence of pro-inflammatory mediators was not determined (Westphal et al., 2015).

Recruitment of pro-inflammatory cells is a key event that is complicated to replicate in vitro conditions as cell migration is induced by cooperative chemotactic mediators (Gouwy et al., 2015) which are produced and released from different cells. Therefore, more kinetics studies in co-culture techniques are needed to fill this gap.

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)

Air pollution


Air pollution primes immunity; increases the levels of circulating IL-1β, IL-6 and TNF-α; impairs the normal functions of macrophages and alveolar cells. Exposure to particulate air pollution, such as PM2.5, is associated with pulmonary inflammation [1,2]. Both short term and chronic exposures to fine particulate matter (PM) have been shown to increase levels of circulating IL-1β, IL-6 and TNF-α [3-5]. Air pollution works as a priming factor that exacerbates the inflammatory phenotype of COVID-19 and further dysregulates immune cell activity. Dysregulation of the immune cell functions, on the other hand, plays a role in tissue damage and the ability of the immune system to fight pathogens, which increases the susceptibility to concomitant bacterial superinfection, for instance [6-9].

[1] Zhao et al., 2013

[2] Jia et al., 2021

[3] Tsai et al., 2012

[4] Ljungman et al., 2009

[5] Kido et al., 2011

[6] Knoll et al., 2021

[7] Glencross et al., 2020

[8] Yamasaki and Eeden, 2018

9) Signorini et al., 2018

Chemicals (weak evidence)

Per- and polyfluoroalkyl substances (PFAS) (Perfluorooctane sulfonate [PFOS], perfluorooctanoic acid [PFOA], perfluorobutane sulfonic acid [PFBS], perfluorooctane sulfonamide [PFOSA], and perfluorodecanoic acid [PFDA])

Several in vitro studies in human-derived cells have shown that PFAS can modify the secretion of pro-inflammatory mediators in a dose-dependent manner [1].  PFOS exposure significantly induced IL-1 IL-4, IL-6, and IL-8 in human lymphocytes and reduced chemokines CXCL8 and CXCL10 secretion in human bronchial epithelial cells while increasing of IL-1α release [2]; both PFOS and PFOA enhanced IL-1β release in response to Poly I:C [3]; PFOS, PFOA, PFBS, PFOSA, and PFDA exposure decreased PHA-induced release of IL-4, IL-10, and IL-6 and PFOS, PFOSA, and PFDA decreased IFN-γ release in human leukocytes with PFOS as a more potent inhibitor of cytokine production than other PFAS, and leukocytes obtained from female donors appeared to be more sensitive to the in vitro immunomodulating effects of PFAS, compared to leukocytes from male donors [4]. In a rat study exposed to PFOS, increased serum levels of TNF-α and IL-6 were observed. Kupffer cells exposed to PFOS showed cell activation, which was mostly inhibited by anti-TNF-α or anti-IL-6 treatment. Moreover, NF-κB inhibitor and JNK inhibitor significantly inhibited the production of IL-6 [5,6].

[1] Tian et al., 2021

[2] Li et al., 2020

[3] Sørli et al., 2020

[4] Corsini et al., 2012

[5] Han et al., 2018

[6] EFSA CONTAM Panel, 2020

Sex Female sex (XX chromosomes)

Females produce higher amounts of the antiviral infection cytokine IFN-α than men [1].  Estrogens are critical regulators of gene expression and functions in innate immune cells, including monocytes, macrophages, and dendritic cells, as well as lymphocytes such as T helper 1/2 (TH1/2) cells, regulatory T-cells (Treg cells), and B cells. One of the major forms of estrogen, estradiol, has been shown to dampen the production of excessive innate inflammatory cytokines by monocytes and macrophages [2]. In the presence of progesterone, CD4+ Th cells skew from Th-1 to Th-2 in the production of anti-inflammatory cytokines, specifically IL-4 and IL-10 [3]. The cellular types involved in male and female immune responses to SARS-CoV-2 are distinct and immune response in females is enriched with activated T-cells [1]. In lactating women, higher SARS-CoV-2 reactive memory B-cells and antibody titers have been associated with the hormone prolactin [4]. Poor T-cell response to SARS-CoV-2 correlates with worse disease progression in female patients.

[1] Takahashi et al., 2020

[2] Scully et al., 2020

[3] Mauvais-Jarvis et al., 2020

[4] Gonçalves et al., 2021

Male sex (XY chromosomes)

Males display a higher innate immune response to SARS-CoV-2 than females, which conditions their cytokine profile. Men have higher levels of the innate immune cytokines IL-8 and IL-18 in circulation  [1]. Moreover, elderly men in particular display autoantibodies against IFN-α more frequently [5]. The cellular types involved in male and female immune responses to SARS-CoV-2 are distinct. Men display higher circulating levels of non-classical monocytes [1]. Higher innate immune activation in men leads to higher plasma levels of the inflammatory cytokines IFN-α [6], IL-8 and IL-18 [1], driving hyperinflammation and more pronounced lymphopenia in males.

[5] Bastard et al., 2020

[6] Agrawal et al., 2021


Old people During aging, a subclinical chronic inflammatory response develops leading to an immune senescent state, where pathogen protective immune responses are impaired, but the production of inflammatory cytokines, such as IL-6, is increased. This process is called inflammaging. The persistent IL-6 elevation can induce lung tissue inflammation and mortality. The rate of inflammaging is higher in men and accelerated inflammaging is believed to worsen COVID-19 outcomes [1]. The chronic inflammatory status is associated with a dramatic depletion of B lymphocyte-driven acquired immunity. Aging also attenuates the upregulation of co-stimulatory molecules critical for T-cell priming and reduces antiviral IFN production by alveolar macrophages and dendritic cells in response to infection with the influenza virus [2].

[1] Bonafè et al., 2020

[2] Kovacs et al., 2017

Atherogenic dyslipidemia

Lipids impact innate and adaptive immune responses [1,2].

In COVID-19. The atherogenic dyslipidemia associated with COVID-19 severity (high tryglycerides and low total, low density lipoprotein and high density lipoprotein cholesterol) was inversely correlated with inflammatory biomarkers such as increased levels of serum C-reactive protein (CRP), IL-6, IL-8, and IL-10 [3,4].

[1] Hubler and Kennedy, 2016

[2] Bernardi et al., 2018

[3] Henry et al., 2021

[4] Caterino et al., 2021

[5] Hubler and Kennedy, 2016

[6] Winer et al., 2009

[7] Im et al., 2011

[8] Muscogiuri et al., 2020


In obesity, immune cells interact with various classes of lipids, which can control the plasticity of macrophages and T lymphocytes.

In COVID-19. Altered lipid homeostasis is associated with severe COVID-19 outcomes and, at the same time, with chronic inflammation and inflammatory polarization of macrophages and T lymphocytes [5]. Th1 lymphocytes are more prevalent in adipose tissue of obese patients [6]. In the same way, Th1 lymphocytes are elevated in visceral fat [6]. Both macrophages and T lymphocytes interact with lipids that influence their proliferation, differentiation, polarization [7] and transcriptional regulation, which is tightly controlled by Sterol regulatory element-binding protein (SREBP) and Liver X receptors (LXRs), expressed in macrophages and known regulators of cytokine release. Adipose tissue produces many pro-inflammatory adipokines and cytokines, which lead to low-grade inflammation and the recruitment of immune cells which may clarify the connection between obesity and COVID-19 severity [8].

Gut microbiota Gut dysbiosis (alteration of gut microbiota)

The gut microbiota is increasingly acknowledged to play a central role in human health and disease, notably by shaping the immune response. Notably some bacteria living in the gut produce short-chain fatty acids (SCFA), recognized as mediators of the intestinal inflammatory response [1]. SCFAs modulate inflammation by regulating immune cell cytokine production such as TNF-α, IL-12, IL-6 [2]. For example, butyrate decreased the lipopolysaccharide (LPS)-induced TNF-α expression in monocytes [4] and activated Treg cells, blocking an excessive inflammatory response [1,3].

In COVID-19. In a COVID-19 cohort, the depletion of several bacterial species (B. adolescentis, E. rectale and F. prausnitzii, known to play immunomodulatory roles in the human gastrointestinal system) was linked to increased plasma concentrations of TNF-α, CXCL10, CCL2 and IL-10 [4]. Conversely, two species enriched in the COVID-19 cohort, B. dorei and Akkermansia muciniphila, were positively correlated with IL-1β, IL-6 and CXCL8. Using a machine learning model [5], it was reported that the disruption of gut microbiota significantly correlated with pro-inflammatory cytokines and may predispose normal individuals to severe COVID-19. Decreases in the abundance of butyrate-producing bacteria and a decline in SCFA were observed in severe COVID-19 [4,6,7,8]. Reduced relative proportion of bacteria producing SCFA was observed in Syrian hamsters infected with SARS-CoV-2, compared to non-infected controls, with a transient decrease in systemic SCFA amounts [9]. However, SCFA supplementation in hamsters during infection had no effect on inflammatory parameters. Targeted analysis of fecal metabolites showed significantly lower fecal concentrations of SCFAs in COVID-19 patients, which correlated with disease severity and increased plasma concentrations of CXCL-10 and CRP [10].

[1] Yoo et al., 2020

[2] Vinolo et al., 2011

[3] Atarashi et al., 2013

[4] Yeo et al., 2021

[5] Gou et al., 2021

[6] Zuo et al., 2020

[7] Gu et al., 2020

[8] Grenga et al., 2022

[9] Sencio et al., 2022

[10] Zhang et al., 2022

Vitamin D (low evidence) Vitamin D deficiency

There is a complex interplay between vitamin D and the immune response to viral infections. Low vitamin D status is proposed to induce upregulation of the TNF-α and downstream of Nuclear Factor Kappa B Subunit 1 (NF–κB1) signaling pathway, which regulates inflammatory reactions toward viral infection in macrophages [1,2]. Vitamin D was shown as a potent suppressor of IFN-γ mediated macrophages response, preventing the release of inflammatory cytokines and chemokines [3]. Thus, release of pro-inflammatory cytokines might be exacerbated in COVID-19 patients with vitamin D deficiency [4].

[1] Hassan et al., 2022

[2] Książek et al., 2021

[3] Helming et al., 2005

[4] Munshi et al., 2021

Genetic factors


The inflammatory response manifested by increased cytokine levels results in inhibition of heme oxygenase (HO-1), with a subsequent loss of cytoprotection. In the 50-non-coding regions of the HO-1 gene, there are two polymorphic sites, namely the (GT)n dinucleotide and T (-413) A sites, which regulate the transcriptional activity of HO-1. These polymorphisms have been shown to be associated with the occurrence and progression of numerous diseases, including COVID-19 [1]. The timing of the IFN response to SARS-CoV-2 infection can vary with viral load and genetic differences in host response. When the viral load is low, IFN responses are engaged and contribute to viral clearance, resulting in mild infection. When viral load is high and/or genetic factors slow antiviral responses, virus replication can delay the IFN response and cytokine storm can occur before adaptive responses clear the virus, resulting in severe disease including multisystem inflammatory syndrome in Children (MIS-C) [2].

[1] Singh et al., 2020

[2] Rowley, 2020

Therapeutic intervention against COVID-19

Tocilizumab and Sarilumab

Are anti-IL-6 receptor monoclonal antibodies, which reduce inflammation [1] by attaching to the IL-6 receptor (as IL-6 receptor inhibitors) [2]. Tocilizumab, a biological drug approved for rheumatoid arthritis, is currently being evaluated for its efficacy against the effects of systemic IL-6 elevation ( accessed on March 2022, NCT04317092, NCT04320615, NCT04306705) [3].

[1] WHO, 2021.

[2] European Medicines Agency, 2021

[3] Bonafè et al., 2020


Is an immunosuppressant that blocks the action of enzymes known as Janus kinases (JK), which play an important role in inflammatory processes (JAK inhibitor) [1–4].

[1] Jorgensen et al., 2020

[2] Bekerman et al., 2017

[3] Neveu et al., 2015

[4] Richardson et al., 2020

Low molecular weight heparins (LMWHs)

Have anti-inflammatory effects by blocking pro-inflammatory mediators (TNF-α, IL-6 and Leukotriene [LTB4]) [1].

[1] Buijsers et al., 2020

Pre-existing heart failure


Dysregulation of renin angiotensin system due to pre-existing heart failure can have detrimental inflammatory effects both locally (in the heart) and systematically.

The Angiotensin converting enzyme 2 (ACE2)/Angiotensin (Ang) (1-7) pathway is associated with the attenuation of a wide range of pro-inflammatory cytokines and chemokines, such as IL-1, IL-5, IL-6, IL-12, CCL2, TNF-α and MCP-1 [1].

[1] Rodrigues Prestes et al., 2017.                     


Dietary elements linked to pro-inflammatorymediators

High-fat diets have been linked—in multiple studies—to promote an “inflammatory status” in the gut and subsequently other organs [1].

Compounds found in many plant foods may affect COVID-19 prognosis by blocking inflammatory mediators and pathways. Bousquet et al. [2,3] identified bioactive compounds contained in spices and fermented vegetables, including capsaicin, cinnamaldehyde, curcumin, genistein, gingerol, mustard oil, piperine, wasabi, and sulforaphane, that upregulate the signaling of nuclear factor (erythroid-derived 2)-like 2 (Nrf2), a potent endogenous antioxidant which blocks oxidative stress from the Angiotensin type I receptor (AT1R) axis, inhibits overproduction of proinflammatory cytokines and chemokines (including IL-6), and limits the activation of NF-κB.

There is some in vitro evidence that Lactobacillus, found in many fermented foods, works through the same mechanism [4].

Finally, naringin, a compound found in citrus fruits, reduced LPS-induced IL-6 expression levels in vitro [5].

[1] Duan et al., 2018

[2] Bousquet et al., 2021a

[3] Bousquet et al., 2020

[4] Bousquet et al., 2021b

[5] Liu et al., 2022

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

Activated pro-inflammatory cells secrete pro-inflammatory mediators, and those mediators' goal is to cause signalling and response, which can lead to chronic inflammation (KE1497). Chronic inflammation means proinflammatory mediators increase and increased recruitment of inflammatory cells acts in a positive feedback loop, which continues a pro-inflammatory environment.

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


List of the literature that was cited for this KER description. More help
  1. Agrawal S, Salazar J, Tran TM, Agrawal A. Sex-Related Differences in Innate and Adaptive Immune Responses to SARS-CoV-2. Front Immunol. 2021 Oct 20;12:739757. doi: 10.3389/fimmu.2021.739757. 

  2. Atarashi K, Tanoue T, Oshima K, Suda W, Nagano Y, Nishikawa H, Fukuda S, Saito T, Narushima S, Hase K, Kim S, Fritz JV, Wilmes P, Ueha S, Matsushima K, Ohno H, Olle B, Sakaguchi S, Taniguchi T, Morita H, Hattori M, Honda K. Treg induction by a rationally selected mixture of Clostridia strains from the human microbiota. Nature. 2013 Aug 8;500(7461):232-6. doi: 10.1038/nature12331.

  3. Bastard P, Rosen LB, Zhang Q, Michailidis E, Hoffmann HH, Zhang Y, Dorgham K, Philippot Q, Rosain J, Béziat V, Manry J, Shaw E, Haljasmägi L, Peterson P, Lorenzo L, Bizien L, Trouillet-Assant S, Dobbs K, de Jesus AA, Belot A, Kallaste A, Catherinot E, Tandjaoui-Lambiotte Y, Le Pen J, Kerner G, Bigio B, Seeleuthner Y, Yang R, Bolze A, Spaan AN, Delmonte OM, Abers MS, Aiuti A, Casari G, Lampasona V, Piemonti L, Ciceri F, Bilguvar K, Lifton RP, Vasse M, Smadja DM, Migaud M, Hadjadj J, Terrier B, Duffy D, Quintana-Murci L, van de Beek D, Roussel L, Vinh DC, Tangye SG, Haerynck F, Dalmau D, Martinez-Picado J, Brodin P, Nussenzweig MC, Boisson-Dupuis S, Rodríguez-Gallego C, Vogt G, Mogensen TH, Oler AJ, Gu J, Burbelo PD, Cohen JI, Biondi A, Bettini LR, D'Angio M, Bonfanti P, Rossignol P, Mayaux J, Rieux-Laucat F, Husebye ES, Fusco F, Ursini MV, Imberti L, Sottini A, Paghera S, Quiros-Roldan E, Rossi C, Castagnoli R, Montagna D, Licari A, Marseglia GL, Duval X, Ghosn J; HGID Lab; NIAID-USUHS Immune Response to COVID Group; COVID Clinicians; COVID-STORM Clinicians; Imagine COVID Group; French COVID Cohort Study Group; Milieu Intérieur Consortium; CoV-Contact Cohort; Amsterdam UMC Covid-19 Biobank; COVID Human Genetic Effort; Tsang JS, Goldbach-Mansky R, Kisand K, Lionakis MS, Puel A, Zhang SY, Holland SM, Gorochov G, Jouanguy E, Rice CM, Cobat A, Notarangelo LD, Abel L, Su HC, Casanova JL. Autoantibodies against type I IFNs in patients with life-threatening COVID-19. Science. 2020 Oct 23;370(6515):eabd4585. doi: 10.1126/science.abd4585.

  4. Bekerman E, Neveu G, Shulla A, Brannan J, Pu SY, Wang S, Xiao F, Barouch-Bentov R, Bakken RR, Mateo R, Govero J, Nagamine CM, Diamond MS, De Jonghe S, Herdewijn P, Dye JM, Randall G, Einav S. Anticancer kinase inhibitors impair intracellular viral trafficking and exert broad-spectrum antiviral effects. J Clin Invest. 2017 Apr 3;127(4):1338-1352. doi: 10.1172/JCI89857.

  5. Bernardi S, Marcuzzi A, Piscianz E, Tommasini A, Fabris B. The Complex Interplay between Lipids, Immune System and Interleukins in Cardio-Metabolic Diseases. Int J Mol Sci. 2018 Dec 14;19(12):4058. doi: 10.3390/ijms19124058.

  6. Bonafè M, Prattichizzo F, Giuliani A, Storci G, Sabbatinelli J, Olivieri F. Inflamm-aging: Why older men are the most susceptible to SARS-CoV-2 complicated outcomes. Cytokine Growth Factor Rev. 2020 Jun;53:33-37. doi: 10.1016/j.cytogfr.2020.04.005.

  7. Bourdon JA, Saber AT, Jacobsen NR, Jensen KA, Madsen AM, Lamson JS, Wallin H, Møller P, Loft S, Yauk CL, Vogel UB. Carbon black nanoparticle instillation induces sustained inflammation and genotoxicity in mouse lung and liver. Part Fibre Toxicol. 2012 Feb 2;9:5. doi: 10.1186/1743-8977-9-5. 

  8. Bousquet J, Cristol JP, Czarlewski W, Anto JM, Martineau A, Haahtela T, Fonseca SC, Iaccarino G, Blain H, Fiocchi A, Canonica GW, Fonseca JA, Vidal A, Choi HJ, Kim HJ, Le Moing V, Reynes J, Sheikh A, Akdis CA, Zuberbier T; ARIA group. Nrf2-interacting nutrients and COVID-19: time for research to develop adaptation strategies. Clin Transl Allergy. 2020 Dec 3;10(1):58. doi: 10.1186/s13601-020-00362-7

  9. Bousquet J, Czarlewski W, Zuberbier T, Mullol J, Blain H, Cristol JP, De La Torre R, Le Moing V, Pizarro Lozano N, Bedbrook A, Agache I, Akdis CA, Canonica GW, Cruz AA, Fiocchi A, Fonseca JA, Fonseca S, Gemicioğlu B, Haahtela T, Iaccarino G, Ivancevich JC, Jutel M, Klimek L, Kuna P, Larenas-Linnemann DE, Melén E, Okamoto Y, Papadopoulos NG, Pfaar O, Reynes J, Rolland Y, Rouadi PW, Samolinski B, Sheikh A, Toppila-Salmi S, Valiulis A, Choi HJ, Kim HJ, Anto JM. Spices to Control COVID-19 Symptoms: Yes, but Not Only…. Int Arch Allergy Immunol. 2021a;182(6):489-495. doi: 10.1159/000513538.

  10. Bousquet J, Anto JM, Czarlewski W, Haahtela T, Fonseca SC, Iaccarino G, Blain H, Vidal A, Sheikh A, Akdis CA, Zuberbier T; ARIA group. Cabbage and fermented vegetables: From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19. Allergy. 2021b Mar;76(3):735-750. doi: 10.1111/all.14549.

  11. Buijsers B, Yanginlar C, Maciej-Hulme ML, de Mast Q, van der Vlag J. Beneficial non-anticoagulant mechanisms underlying heparin treatment of COVID-19 patients. EBioMedicine. 2020 Sep;59:102969. doi: 10.1016/j.ebiom.2020.102969.

  12. Caterino M, Gelzo M, Sol S, Fedele R, Annunziata A, Calabrese C, Fiorentino G, D'Abbraccio M, Dell'Isola C, Fusco FM, Parrella R, Fabbrocini G, Gentile I, Andolfo I, Capasso M, Costanzo M, Daniele A, Marchese E, Polito R, Russo R, Missero C, Ruoppolo M, Castaldo G. Dysregulation of lipid metabolism and pathological inflammation in patients with COVID-19. Sci Rep. 2021 Feb 3;11(1):2941. doi: 10.1038/s41598-021-82426-7.

  13. Chen S, Yin R, Mutze K, Yu Y, Takenaka S, Königshoff M, Stoeger T. No involvement of alveolar macrophages in the initiation of carbon nanoparticle induced acute lung inflammation in mice. Part Fibre Toxicol. 2016 Jun 21;13(1):33. doi: 10.1186/s12989-016-0144-6. 

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