Dynamics of a cytokine storm

Area of Science:

• Immunology
• Systems Biology
• Pharmacology

Background:

• A Phase I clinical trial of the monoclonal antibody TGN1412, designed to stimulate regulatory T cells, resulted in severe inflammatory responses.
• Six healthy volunteers experienced a cytokine storm, characterized by rapid increases in cytokine concentrations and decreases in lymphocytes and monocytes.

Purpose of the Study:

• To model the dynamic interactions of cytokines during a TGN1412-induced cytokine storm.
• To identify cause-and-effect relationships among cytokines and their response to TGN1412.

Main Methods:

• A set of linear ordinary differential equations was used to model the response histories of nine cytokines.
• A general search procedure identified model parameters, fitting data over a five-day period.
• Principal-component analysis was employed to cluster cytokine responses.

Main Results:

• The eighteenth-order model elucidated plausible cytokine interactions, indicating IL2, IL8, and IL10 as significant inductive factors and IFN-γ and IL12 as major inhibiting factors.
• While TNF-α is a key pro-inflammatory cytokine, IFN-γ and others showed faster initial responses to TGN1412.
• Principal-component analysis identified three distinct clusters of cytokine responses: [TNF-α, IL1, IL10], [IFN-γ, IL2, IL4, IL8, IL12], and [IL6].
• IL1, IL6, IL10, and TNF-α exhibited the highest variability in response.

Conclusions:

• The study provides detailed insights into the dynamics of a cytokine storm event.
• Linear modeling proved valuable for interpreting complex biological system dynamics from empirical data.
• Understanding these cytokine interactions is crucial for managing adverse drug reactions and developing safer immunotherapies.