API

This Key Event Relationship is licensed under the Creative Commons BY-SA license. This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.

Relationship: 2288

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

Neuroinflammation leads to Encephalitis

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Neuroinflammation
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help
Encephalitis

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 spike protein to ACE 2 receptors expressed on brain cells (neuronal and non-neuronal) leads to neuroinflammation resulting in encephalitis adjacent High Low Anna Price (send email) Under development: Not open for comment. Do not cite Under Development

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help

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

Coronavirus infection can infect macrophages, microglia, and astrocytes in the CNS leading to encephalitis (Wu et al. 2020; Wu and Tang. 2020) (Koralnik et al. 2020).

Patients with PCR-confirmed SARS-CoV-2 infection and encephalitis (COV-Enc), encephalitis without SARS-CoV-2 infection (ENC) and healthy controls (HC) underwent an extended panel of CSF neuronal (NfL, T-tau), glial (GFAP, TREM2, YKL-40) and inflammatory biomarkers (IL-1β, IL-6, Il-8, TNF- α, CXCL-13 and β2-microglobulin). In COV-Enc cases, CSF was negative for SARS-CoV-2 real-time PCR but exhibited increased IL-8 levels independently from presence of pleocytosis/hyperproteinorracchia. COV-Enc patients showed increased IL-6, TNF- α, and β2-microglobulin and glial markers (GFAP, sTREM-2, YKL-40) levels similar to ENC but normal CXCL13 levels. Neuronal markers NfL and T-Tau were abnormal only in severe cases. The pattern of CSF alterations suggested a cytokine-release syndrome as the main inflammatory mechanism of SARS-CoV-2 related encephalitis (Pilotto A et al. 2021).

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
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
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

Koralnik et al. COVID-19: A Global Threat to the Nervous System. Ann Neurol. 2020 Jul;88(1):1-11.

Pilotto A et al. SARS-CoV-2 encephalitis is a cytokine release syndrome: evidences from cerebrospinal fluid analyses. Clin Infect Dis. 2021 Jan 4;ciaa1933.

Wu J. and Tang Y. Revisiting the Immune Balance Theory: A Neurological Insight Into the Epidemic of COVID-19 and Its Alike. Front Neurol. 2020 Oct 15;11:566680.

Wu Y, et al. Nervous system involvement after infection with Covid-19 and other coronaviruses. Brain Behav Immun. 2020;87:18–22.