Quantitative Modeling of IgG N-Glycosylation Profiles from Population Data

Area of Science:

• Immunology
• Systems Biology
• Biochemistry

Background:

• Immunoglobulin G (IgG) glycosylation significantly impacts its biological functions.
• Age-dependent alterations in IgG glycosylation are observed but the underlying molecular mechanisms require further elucidation.

Purpose of the Study:

• To develop and validate a mathematical model for quantitative IgG N-glycosylation.
• To investigate the age-related changes in IgG glycosylation and identify key regulatory enzymes.

Main Methods:

• Utilized quantitative IgG N-glycosylation data from two independent Croatian cohorts (Korčula and Vis Islands).
• Employed ultra-high-performance liquid chromatography (UHPLC) to measure relative glycan levels.
• Developed and fitted a mathematical model to estimate enzyme concentrations in Golgi compartments.

Main Results:

• The model was successfully calibrated and validated using independent datasets.
• Estimated concentrations of seven key enzymes involved in glycan biosynthesis.
• Revealed an age-related decline in β-N-acetylglucosaminylglycopeptide β-1,4-galactosyltransferase (GalT) concentrations.

Conclusions:

• GalT concentration decline is a primary driver of age-dependent IgG glycan profile changes.
• The developed mathematical model provides insights into IgG glycosylation regulation.
• GalT shows potential as a biomarker for biological aging.