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Relationship: 2497

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

IFN-I response, antagonized leads to SARS-CoV-2 production

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 leads to viral infection proliferation adjacent High Not Specified Arthur Author (send email) Under development: Not open for comment. Do not cite Under Development
Binding of SARS-CoV-2 to ACE2 in enterocytes leads to intestinal barrier disruption adjacent Low Cataia Ives (send email) Under development: Not open for comment. Do not cite Under Development
Binding of SARS-CoV-2 to ACE2 receptor leading to acute respiratory distress associated mortality adjacent High Evgeniia Kazymova (send email) Open for comment. Do not cite Under Development
Binding to ACE2 leading to thrombosis and disseminated intravascular coagulation adjacent Moderate Moderate Arthur Author (send email) Under development: Not open for comment. Do not cite Under Development
Binding of SARS-CoV-2 to ACE2 leads to hyperinflammation (via cell death) adjacent High Moderate Allie Always (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
Term Scientific Term Evidence Link
Homo sapiens Homo sapiens High NCBI
mammals mammals Not Specified NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Unspecific High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
All life stages Moderate

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 normal function of the host’s innate immune response to viruses is the expression of interferons (IFN) which in turn stimulates the expression of many interferon-stimulated gene (ISG) proteins with antiviral functions (Amor et al., 2020; Harrison et al., 2020). ISGs generally function to inhibit viral replication (Yang and Li, 2020). The SARS-CoV-2 antagonism of the IFN-I pathway delays or curtails the expression of IFN-I and ISG proteins. This results in the downstream event, SARS-CoV-2 production, increased. The increase in SARS-CoV-2 viral production can be measured as viral load, which can contribute to both transmission to new hosts and more severe disease. This KER details the specific ISGs that inhibit viral replication, and demonstrates the difference in how SARS-CoV-2 negates the function of these proteins or delays their expression compared to other viruses to successfully increase its numbers.

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 collection strategy for this KER uses the same logic as for other events and relationships in this AOP.

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

See below.

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 functional relationships between the upstream IFN-I antagonism and downstream increase in SARS-CoV-2 viral replication is biologically plausible via the suppression of IFN through interaction inhibition of the host pathway proteins by viral proteins. This in turn would lead to suppressing the expression of ISGs that have been demonstrated to inhibit replication. The effects of ISGs on viral replication has been demonstrated for several viruses (Schoggins et al., 2011). SARS-CoV-2 replication may be impacted by different ISGs than other families of viruses. A gain-of-function analysis evaluating the impacts of ISGs on SARS-CoV-2 viral replication (Martin-Sancho et al., 2021) showed that a specific subset of ISGs when stably overexpressed in cultured human cells infected with SARS-CoV-2 controlled viral infection, including RNA binding proteins that suppress viral RNA synthesis and ISGs inhibiting viral assembly and egress. Therefore, the lack of these ISGs due to antagonism of the IFN-I pathway leads to increased viral replication.

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

Schuhenn et al. (2022) found that differential immune signatures of IFNα subtypes suppress SARS-CoV-2 infection by treating primary human airway epithelial cells (hAEC) with different IFNα subtypes during SARS-CoV-2 infection. The most effective antiviral subtype was IFNα5, against both in vitro and in vivo infected mice, and additive effects with the antiviral drug remdesivir in cell culture.

Rouchka et al., (2021) found that there is not only wide variation in nasopharyngeal viral loads in COVID-19 patients early in infection, but also that viral loads were strongly correlated with host gene expression associated with IFNα-inducible cellular antiviral response genes (ISGs). Also, patients with mild symptoms were often found to have a higher viral load than those with severe disease, indicating lack of correlation between susceptibility to severe disease, and susceptibility to viral replication.

In review articles, Yang and Li (2020) and Samuel (2023) discuss the relationship between the IFN antiviral response and viral replication. Yang et al. focus on ISGs with multiple mechanisms that inhibit viral replication by sensing, degrading, or repressing expression of viral RNA. These ISGs may use a variety of co-factors, which indicates the highly complex nature of the type I IFN response. Samuel et al. report that overall genetic variability of both SARS-CoV-2 and the human host affect the IFN response, and viral replication is in turn sensitive to variation in IFN antiviral action.

These studies point out inconsistencies in quantity and type of IFN expression or administration in patients and COVID-19 disease outcome, but confirming the link between IFN-I response and viral replication. There is uncertainty in the fact that several IFN-I pathway components have been variously implicated. Because many different IFN subtypes and subsequently many different ISGs and cofactors may be involved, not only the specific repertoire of ISGs expressed may differ among individuals, but also the quantity of each ISG may influence viral production.

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

IFN has been the subject of studies for potential therapeutic value to enhance the antiviral response. However, IFN administered too late, in the inflammatory stage (post-symptom onset), led to long-lasting harm and worsened disease outcome (Sodeifian et al., 2021). Therapeutics used in COVID-19 patients tend to target either the ACE2 binding, downstream inflammatory response, or viral replication via inhibition of the viral RNA-dependent, RNA polymerase to block viral genome replication (i.e., Remdesivir) (Narayanan and Parimon, 2022). No other therapeutics were found to be relevant to this KER, i.e., specifically targeted to IFN components or ISGs leading to supressed viral replication (see WHO 2021 and Terracciano et al., 2021).

It is known that per- and poly-fluorinated alkyl substances (PFAS), air pollutants, and other environmental chemicals are implicated in SARS-CoV-2 susceptibility and COVID-19 disease severity (Marques et al., 2022; Nielsen et al., 2021; Xu et al., 2021). However, it is currently unknown whether or how the mechanisms of action are related to blocking IFN components or ISGs, leading to viral replication.

Genetic factors are of importance to this KER: Autoantibodies against IFN, as noted, block even exogenously administered IFN, resulting in more severe disease (Quarleri and Delpino, 2021; Bastard et al., 2021; Busnadiego et al., 2020; Lopez et al., 2021). There are 15 known clinically recessive and inborn errors of type I IFN immunity (Zhang et al., 2022). Four of these including X-linked recessive TLR7 deficiency, and autosomal recessive IFNAR1, STAT2, or TYK2 deficiencies were found in children with moderate to critical pneumonia due to COVID-19. Zhang et al. (2022) also reported enhanced SARS-CoV-2 replication measured as expression of viral nucleocapsid (N-protein) in STAT2- and TYK2-deficient patients’ cells.

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

Busnadiego et al., (2020) found an inverse, linear relationship between IFNβ or IFNλ1 concentration and viral titer, measured as plaque forming units (PFU) in primary human bronchial epithelial cells (BEpCs) differentiated and grown at an air-liquid interface (ALI). However, the upstream event of IFN antagonism is not represented by administered IFN but by antagonism of the IFN response, and does not answer the question of what dose of antagonist results in increased viral replication in a host system, where viral replication is not normal biology. Comparatively, difference in IFN expression between cells infected with influenza A virus vs. SARS-CoV-2 showed significantly higher IFNβ and IFNλ1 for influenza at both 6 and 24 hours post-infection, but this was not tied to relative viral production (Hatton et al., 2021).

The key event of IFN-I response antagonism encompasses a broad range of stressors and targets: 1) viral proteins interacting with pathway proteins leading to IFN expression, 2) the IFN subtypes that induce the expression of ISGs, and 3) the variation in type and amount of ISGs expressed, which also varies with cell/tissue type. Viral replication related to these factors is also dependent on the dose of virus to which the individual host is exposed and the genetic make-up and overall condition of that individual. These factors may explain the variable results in IFN dose-viral production response determination, and why the actual response-response relationship for this KER, between the viral dose resulting in antagonism and viral replication increase, have not been determined. Saheb Sharif-Askari et al., 2022 concluded that more mechanistic studies are needed to quantify the amount of early IFN required to overcome SARS-CoV-2 antagonism and prevent replication. Polyinosinic:polycytidylic acid [poly(I:C)] is a synthetic analog of double-strand RNA (dsRNA) that can stimulate IFN production. The use of poly(I:C) administered before and during SARS-CoV-2 infection in mice increased ISGs and lowered viral loads (Tamir et al., 2022) but was administered at different time points rather than at different dose concentrations. Poly(I:C) dosing may be a potential method to quantify the IFN stimulation needed to overcome SARS-CoV-2 antagonism.

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

The viral entry MIE and early KEs coincide with the time from exposure to symptoms, within which are the latent period, or time from exposure to infectiousness, and the serial interval, or the time interval between the onset of symptoms in the primary (index) and secondary (contact) case. Pre-symptomatic transmission occurs from about 3 days after exposure to symptom onset at about day 5-7, viral load peaks from about day 5-7 to day 9-11, and the host can remain infectious to symptom clearance or death (Byrne et al. 2020). IFN administered prior to exposure or within the latent period window can stop replication (Sodeifian et al., 2021). In a study using a primary nasal cell model (differentiated at air-liquid interface), the virus did not proliferate beyond the limit of assay detection if treated with IFN beta or lambda 16 hours prior to infection, and virus was significantly reduced in cultures treated 6h post-infection compared to untreated cultures. Treatments 24h post infection were not significantly different from untreated controls for either type of IFN (Hatton et al., 2021). This would suggest that viral antagonism of IFN occurring during the first 24h post viral entry allows viral loads to be generated likely concurrently, reaching transmissible levels within 72h post viral entry.

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

RIG-Like Receptors (RLRs) including MDA5 are Pattern Recognition Receptors (PRRs) that recognize Pathogen-Associated Molecular Patterns (PAMPs) like viral RNA and start signalling cascades to express IFNs. These PRRs and other proteins in the pathway, including STAT1 and STAT2 involved in transcription of the ISGs, are also regulated by IFN, and therefore are themselves ISGs (Yang and Li, 2020). As RNA from most viruses is detected, signalling to express more ISGs increases, and more IFN is expressed (Michalska et al., 2018). However, SARS-CoV-2 inhibits these and other components of the IFN pathway to delay expression of ISGs, and viral production goes unchecked, actually disrupting the normal antiviral positive feedback loop. In fact, SARS-CoV-2 can co-opt another ISG, interferon-induced transmembrane protein 2 (IFITM2), for efficient replication in human lung, heart, and gut cells (Nchioua et al., 2022), which might also be considered a positive feedback loop (i.e., the more IFITM2 is expressed, the more the virus replicates). However, IFITM2 and 3 have also shown antiviral activity toward SARS-CoV-2 (Shi et al., 2021), therefore the conflicting results require more research.

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

Sex. In a large study modelling URT viral load dynamics drawn from measurements in 605 human subjects, variations over 5 orders of magnitude in URT viral load from the time of symptom onset was not explained by age, sex, or severity of illness. Additionally, these variables did not explain modelling results concerning control of viral load by immune responses in the early (innate) or late (adaptive) phases (Challenger et al. 2022). Other sources also support that rate of infection and measured viral load does not differ by gender (e.g., Arnold et al. 2022; Qi et al. 2021; Cheemarla et al. 2021). This evidence suggests that the components of the early antiviral response are not influenced by gender specific differences such as sex hormone levels or sex chromosomes to the extent of affecting viral load.

Life Stage. To apply to this KER, studies would need to show differences in IFN or ISGs correlated with viral load and differing by age. Saheb Sharif-Askari et al. (2022) reported that children had higher expression of IFN-I and associated ISGs than adults, but did not measure viral loads. Euser et al. (2021) found that SARS-CoV-2 viral loads increase with age, but did not measure IFN or ISGs. Literature that connects the two factors for age in humans was not found.

Taxonomic. No non-mammalian vertebrates have been found to become infected with SARS-CoV-2. Many mammals have tested positive and several are known to shed and transmit the virus, however the prevalent aspects of non-human mammalian infection and transmission found in the literature are ACE2 binding capacity and measures of viral load. For the few species for which IFN is mentioned in the literature (Mostaquil et al., 2020; Rui et al., 2021; Hameedi et al., 2022), the potential IFN antagonism is not linked to resulting increase in viral replication, except in the golden hamster, Mesocricetus auratus (Hoagland et al., 2021). The hamsters were Infected with SARS-CoV-2 resulting in high levels of virus in the upper and lower respiratory tracts and an  IFN-I response that was not sufficient to control COVID-19 progression. Direct contact resulted in inoculated hamsters transmitting the virus to naïve hamsters. When intranasal IFN-I was administered to the hamsters, viral replication was reduced and transmission was prevented (Hoagland et al., 2021). For bats, IFN and ISGs are constitutively expressed and therefore may contribute to immune tolerance and lack of replication of SARS-CoV-2 in many bat species (Irving et al., 2021). Differential susceptibility and viral shedding has been found across mammalian species (EFSA/Nielson et al., 2023), and it is likely that differences in IFN-I response may be involved. Therefore, more studies are needed in diverse taxa to assess the tDOA for IFN-I antagonism leading to increase in SARS-CoV-2 replication across the potentially susceptible species.

References

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

Amor, S., Fernández Blanco, L., & Baker, D. (2020). Innate immunity during SARS-CoV-2: Evasion strategies and activation trigger hypoxia and vascular damage. Clinical and Experimental Immunology, 202(2), 193–209. https://doi.org/10.1111/cei.13523

Arnold, C. G., Libby, A., Vest, A., Hopkinson, A., & Monte, A. A. (2022). Immune mechanisms associated with sex-based differences in severe COVID-19 clinical outcomes. Biology of Sex Differences, 13(1), 7. https://doi.org/10.1186/s13293-022-00417-3

Bastard, P., Orlova, E., Sozaeva, L., Lévy, R., James, A., Schmitt, M. M., Ochoa, S., Kareva, M., Rodina, Y., Gervais, A., Le Voyer, T., Rosain, J., Philippot, Q., Neehus, A.-L., Shaw, E., Migaud, M., Bizien, L., Ekwall, O., Berg, S., … Lionakis, M. S. (2021). Preexisting autoantibodies to type I IFNs underlie critical COVID-19 pneumonia in patients with APS-1. Journal of Experimental Medicine, 218(7), e20210554. https://doi.org/10.1084/jem.20210554

Busnadiego, I., Fernbach, S., Pohl, M. O., Karakus, U., Huber, M., Trkola, A., Stertz, S., & Hale, B. G. (2020). Antiviral Activity of Type I, II, and III Interferons Counterbalances ACE2 Inducibility and Restricts SARS-CoV-2. mBio, 11(5), e01928-20. https://doi.org/10.1128/mBio.01928-20

Byrne, A. W., McEvoy, D., Collins, A. B., Hunt, K., Casey, M., Barber, A., Butler, F., Griffin, J., Lane, E. A., McAloon, C., O’Brien, K., Wall, P., Walsh, K. A., & More, S. J. (2020). Inferred duration of infectious period of SARS-CoV-2: Rapid scoping review and analysis of available evidence for asymptomatic and symptomatic COVID-19 cases. BMJ Open, 10(8), e039856. https://doi.org/10.1136/bmjopen-2020-039856

Challenger, J. D., Foo, C. Y., Wu, Y., Yan, A. W. C., Marjaneh, M. M., Liew, F., Thwaites, R. S., Okell, L. C., & Cunnington, A. J. (2022). Modelling upper respiratory viral load dynamics of SARS-CoV-2. BMC Medicine, 20(1), 25. https://doi.org/10.1186/s12916-021-02220-0

Cheemarla, N. R., Watkins, T. A., Mihaylova, V. T., Wang, B., Zhao, D., Wang, G., Landry, M. L., & Foxman, E. F. (2021). Dynamic innate immune response determines susceptibility to SARS-CoV-2 infection and early replication kinetics. Journal of Experimental Medicine, 218(8), e20210583. https://doi.org/10.1084/jem.20210583

EFSA Panel on Animal Health and Welfare (AHAW), Nielsen, S. S., Alvarez, J., Bicout, D. J., Calistri, P., Canali, E., Drewe, J. A., Garin‐Bastuji, B., Gonzales Rojas, J. L., Gortázar, C., Herskin, M., Michel, V., Miranda Chueca, M. Á., Padalino, B., Pasquali, P., Roberts, H. C., Spoolder, H., Velarde, A., Viltrop, A., … Ståhl, K. (2023). SARS‐CoV‐2 in animals: Susceptibility of animal species, risk for animal and public health, monitoring, prevention and control. EFSA Journal, 21(2). https://doi.org/10.2903/j.efsa.2023.7822

Euser, S., Aronson, S., Manders, I., Van Lelyveld, S., Herpers, B., Sinnige, J., Kalpoe, J., Van Gemeren, C., Snijders, D., Jansen, R., Schuurmans Stekhoven, S., Van Houten, M., Lede, I., Cohen Stuart, J., Slijkerman Megelink, F., Kapteijns, E., Den Boer, J., Sanders, E., Wagemakers, A., & Souverein, D. (2022). SARS-CoV-2 viral-load distribution reveals that viral loads increase with age: A retrospective cross-sectional cohort study. International Journal of Epidemiology, 50(6), 1795–1803. https://doi.org/10.1093/ije/dyab145

Hadjadj, J., Yatim, N., Barnabei, L., Corneau, A., Boussier, J., Smith, N., Péré, H., Charbit, B., Bondet, V., Chenevier-Gobeaux, C., Breillat, P., Carlier, N., Gauzit, R., Morbieu, C., Pène, F., Marin, N., Roche, N., Szwebel, T.-A., Merkling, S. H., … Terrier, B. (2020). Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients. Science, 369(6504), 718–724. https://doi.org/10.1126/science.abc6027

Hameedi, M. A., T. Prates, E., Garvin, M. R., Mathews, I. I., Amos, B. K., Demerdash, O., Bechthold, M., Iyer, M., Rahighi, S., Kneller, D. W., Kovalevsky, A., Irle, S., Vuong, V.-Q., Mitchell, J. C., Labbe, A., Galanie, S., Wakatsuki, S., & Jacobson, D. (2022). Structural and functional characterization of NEMO cleavage by SARS-CoV-2 3CLpro. Nature Communications, 13(1), 5285. https://doi.org/10.1038/s41467-022-32922-9

Harrison, A. G., Lin, T., & Wang, P. (2020). Mechanisms of SARS-CoV-2 Transmission and Pathogenesis. Trends in Immunology, 41(12), 1100–1115. https://doi.org/10.1016/j.it.2020.10.004

Hatton, C. F., Botting, R. A., Dueñas, M. E., Haq, I. J., Verdon, B., Thompson, B. J., Spegarova, J. S., Gothe, F., Stephenson, E., Gardner, A. I., Murphy, S., Scott, J., Garnett, J. P., Carrie, S., Powell, J., Khan, C. M. A., Huang, L., Hussain, R., Coxhead, J., … Duncan, C. J. A. (2021). Delayed induction of type I and III interferons mediates nasal epithelial cell permissiveness to SARS-CoV-2. Nature Communications, 12(1), 7092. https://doi.org/10.1038/s41467-021-27318-0

Hoagland, D. A., Møller, R., Uhl, S. A., Oishi, K., Frere, J., Golynker, I., Horiuchi, S., Panis, M., Blanco-Melo, D., Sachs, D., Arkun, K., Lim, J. K., & tenOever, B. R. (2021). Leveraging the antiviral type I interferon system as a first line of defense against SARS-CoV-2 pathogenicity. Immunity, 54(3), 557-570.e5. https://doi.org/10.1016/j.immuni.2021.01.017

Irving, A. T., Ahn, M., Goh, G., Anderson, D. E., & Wang, L.-F. (2021). Lessons from the host defences of bats, a unique viral reservoir. Nature, 589(7842), 363–370. https://doi.org/10.1038/s41586-020-03128-0

Marquès, M., & Domingo, J. L. (2022). Positive association between outdoor air pollution and the incidence and severity of COVID-19. A review of the recent scientific evidences. Environmental Research, 203, 111930. https://doi.org/10.1016/j.envres.2021.111930

Martin-Sancho, L., Lewinski, M. K., Pache, L., Stoneham, C. A., Yin, X., Becker, M. E., Pratt, D., Churas, C., Rosenthal, S. B., Liu, S., Weston, S., De Jesus, P. D., O’Neill, A. M., Gounder, A. P., Nguyen, C., Pu, Y., Curry, H. M., Oom, A. L., Miorin, L., … Chanda, S. K. (2021). Functional landscape of SARS-CoV-2 cellular restriction. Molecular Cell, 81(12), 2656-2668.e8. https://doi.org/10.1016/j.molcel.2021.04.008

Michalska, A., Blaszczyk, K., Wesoly, J., & Bluyssen, H. A. R. (2018). A Positive Feedback Amplifier Circuit That Regulates Interferon (IFN)-Stimulated Gene Expression and Controls Type I and Type II IFN Responses. Frontiers in Immunology, 9, 1135. https://doi.org/10.3389/fimmu.2018.01135

Moustaqil, M., Ollivier, E., Chiu, H.-P., Van Tol, S., Rudolffi-Soto, P., Stevens, C., Bhumkar, A., Hunter, D. J. B., Freiberg, A. N., Jacques, D., Lee, B., Sierecki, E., & Gambin, Y. (2021). SARS-CoV-2 proteases PLpro and 3CLpro cleave IRF3 and critical modulators of inflammatory pathways (NLRP12 and TAB1): Implications for disease presentation across species. Emerging Microbes & Infections, 10(1), 178–195. https://doi.org/10.1080/22221751.2020.1870414

Narayanan, D., & Parimon, T. (2022). Current Therapeutics for COVID-19, What We Know about the Molecular Mechanism and Efficacy of Treatments for This Novel Virus. International Journal of Molecular Sciences, 23(14), 7702. https://doi.org/10.3390/ijms23147702

Nchioua, R., Schundner, A., Kmiec, D., Prelli Bozzo, C., Zech, F., Koepke, L., Graf, A., Krebs, S., Blum, H., Frick, M., Sparrer, K. M. J., & Kirchhoff, F. (2022). SARS-CoV-2 Variants of Concern Hijack IFITM2 for Efficient Replication in Human Lung Cells. Journal of Virology, 96(11), e00594-22. https://doi.org/10.1128/jvi.00594-22

Nielsen, C., & Jöud, A. (2021). Susceptibility to COVID-19 after High Exposure to Perfluoroalkyl Substances from Contaminated Drinking Water: An Ecological Study from Ronneby, Sweden. International Journal of Environmental Research and Public Health, 18(20), 10702. https://doi.org/10.3390/ijerph182010702

Qi, S., Ngwa, C., Morales Scheihing, D. A., Al Mamun, A., Ahnstedt, H. W., Finger, C. E., Colpo, G. D., Sharmeen, R., Kim, Y., Choi, H. A., McCullough, L. D., & Liu, F. (2021). Sex differences in the immune response to acute COVID-19 respiratory tract infection. Biology of Sex Differences, 12(1), 66. https://doi.org/10.1186/s13293-021-00410-2

Quarleri, J., & Delpino, M. V. (2021). Type I and III IFN-mediated antiviral actions counteracted by SARS-CoV-2 proteins and host inherited factors. Cytokine & Growth Factor Reviews, 58, 55–65. https://doi.org/10.1016/j.cytogfr.2021.01.003

Rouchka, E. C., Chariker, J. H., Alejandro, B., Adcock, R. S., Singhal, R., Ramirez, J., Palmer, K. E., Lasnik, A. B., Carrico, R., Arnold, F. W., Furmanek, S., Zhang, M., Wolf, L. A., Waigel, S., Zacharias, W., Bordon, J., & Chung, D. (2021). Induction of interferon response by high viral loads at early stage infection may protect against severe outcomes in COVID-19 patients. Scientific Reports, 11(1), 15715. https://doi.org/10.1038/s41598-021-95197-y

Rui, Y., Su, J., Shen, S., Hu, Y., Huang, D., Zheng, W., Lou, M., Shi, Y., Wang, M., Chen, S., Zhao, N., Dong, Q., Cai, Y., Xu, R., Zheng, S., & Yu, X.-F. (2021). Unique and complementary suppression of cGAS-STING and RNA sensing- triggered innate immune responses by SARS-CoV-2 proteins. Signal Transduction and Targeted Therapy, 6(1), 123. https://doi.org/10.1038/s41392-021-00515-5

Saheb Sharif-Askari, N., Saheb Sharif-Askari, F., Hafezi, S., Kalaji, Z., Temsah, M., Almuhsen, S., Alsafar, H. S., Hamid, Q., & Halwani, R. (2022). Airways tissue expression of type I interferons and their stimulated genes is higher in children than adults. Heliyon, 8(11), e11724. https://doi.org/10.1016/j.heliyon.2022.e11724

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