Defining Composition-Cytokine Relationships Enables the Design of Lipid Nanoparticles with Programmed Immunogenicity

Area of Science:

• Vaccinology
• Nanotechnology
• Immunology

Background:

• Lipid nanoparticles (LNPs) are crucial for novel vaccines, but their selection is empirical, hindering the identification of formulations linked to rare adverse events like myocarditis.
• Understanding LNP composition-immunogenicity is vital for rational vaccine design.

Purpose of the Study:

• To define mechanisms of innate immune activation and adaptive responses to LNP formulations.
• To identify LNP composition features that modulate immune responses and potential reactogenicity.

Main Methods:

• Profiling of clinically relevant LNP formulations using in vitro and in vivo models.
• Design of Experiments (DoE) framework with formulation feature analysis.
• Analysis of cytokine programs (MCP-1, IL-1β, IFNγ/IP-10) and their relationship to LNP composition.

Main Results:

• Identified three distinct cytokine programs: MCP-1-dominated, IL-1β-dependent, and IFNγ-mediated.
• Polyethylene glycol-conjugated (PEGylated) lipid content and ionizable lipid identity modulate the IFNγ/IP-10 axis, linked to myocarditis.
• In vivo, LNP lipid composition impacts innate cytokine responses, while adaptive responses correlate with transgene expression.

Conclusions:

• Established relationships between LNP composition, cytokine induction, and vaccine efficacy.
• Provided a framework for rational design and screening of LNP vaccines to optimize immunogenicity and minimize reactogenicity.