Age-related plasma N-glycosylation changes across humans, rats, and mice identify candidate glycan biomarkers for translational aging studies
Abstract
Changes in plasma protein N-glycosylation, particularly in immunoglobulin G (IgG), are closely associated with human aging. However, the extent to which established human glycan biomarkers translate to commonly used rodent models remains unclear. Here, we characterized the N-glycomes of plasma IgG and non-IgG proteins in humans, rats, and mice across multiple age groups using a TiO₂-PGC chip-MS platform and systematically compared age-related glycosylation changes across species. Quantitative analysis revealed several shared aging-associated trends, including increased agalactosylation and reduced digalactosylation and sialylation, although the magnitude and direction of these changes varied across species and between IgG and non-IgG fractions. Within the sex- and strain-specific rodent cohorts analyzed here, female BALB/c mice showed greater similarity to the mixed-sex human cohort in several broad age-related glycosylation traits, particularly galactosylation, whereas male Sprague-Dawley (SD) rats showed greater overlap with humans at the level of individual candidate biomarkers. Notably, the established human GlycoAgeTest showed limited translational applicability in rodents because similar ratio changes arose from distinct underlying glycan dynamics. Glycan compositions are denoted as Hex_HexNAc_Fuc_Sia, where Sia is NeuAc (A) or NeuGc (G). Using this notation, two IgG glycans emerged as exploratory candidate biomarkers under the present cohort design: 4_5_1_1(A)/(G), shared by humans and male SD rats, and 4_4_1_1(A)/(G), which showed age-associated increases across the mixed-sex human cohort, male SD rats, and female BALB/c mice. These findings define both the opportunities and the limitations of rodent models for glycan-based aging research and provide candidate markers for future mechanistic and intervention studies.
The paper
Macau University of Science and Technology
Experimental Gerontology, 11 Jul 2026, Open access


