Glycan clock of ageing-analytical precision and time-dependent inter- and i-individual variability

Abstract

Ageing is a complex biological process with variations among individuals, leading to the development of ageing clocks to estimate biological age. Glycans, particularly in immunoglobulin G (IgG), have emerged as potential biomarkers of ageing, with changes in glycosylation patterns correlating with chronological age.For precision analysis, three different plasma pools were analysed over 26 days in tetraplicates, 312 samples in total. In short-term variability analysis, two cohorts were analysed: AstraZeneca MFO cohort of 26 healthy individuals (median age 20) and a cohort of 70 premenopausal Chinese women (median age 22.5) cohort monitored over 3 months. Long-term variability analysis involved two adult men aged 47 and 57, monitored for 5 and 10 years, respectively. Samples were collected every 3 months and 3 weeks, respectively. IgG N-glycan analysis followed a standardized approach by isolating IgG, its subsequent denaturation and deglycosylation followed by glycan cleanup and labelling. Capillary gel electrophoresis with laser-induced fluorescence (CGE-LIF) and ultra-performance liquid chromatography analyses were employed for glycan profiling. Statistical analysis involved normalization, batch correction, and linear mixed models to assess time effects on derived glycan traits.The intermediate precision results consistently exhibited very low coefficient of variation values across all three test samples. This consistent pattern underscores the high level of precision inherent in the CGE method for analysing the glycan clock of ageing. The AstraZeneca MFO cohort did not show any statistically significant trends, whereas the menstrual cycle cohort exhibited statistically significant trends in digalactosylated (G2), agalactosylated (G0) and fucosylation (F). These trends were attributed to the effects of the menstrual cycle. Long-term stability analysis identified enduring age-related trends in both subjects, showing a positive time effect in G0 and bisected N-acetylglucosamine, as well as a negative time effect in G2 and sialylation, aligning with earlier findings. Time effects measured for monogalactosylation, and F remained substantially lower than ones observed for other traits.The study found that IgG N-glycome analysis using CGE-LIF exhibited remarkably high intermediate precision. Moreover, the study highlights the short- and long-term stability of IgG glycome composition, coupled with a notable capacity to adapt and respond to physiological changes and environmental influences such as hormonal changes, disease, and interventions. The discoveries from this study propel personalized medicine forward by deepening our understanding of how IgG glycome relates to age-related health concerns. This study underscores the reliability of glycans as a biomarker for tracking age-related changes and individual health paths.

Keywords: Ageing; Biomarkers; Glycans; IgG N-glycosylation; Time-dependent stability.

Fig. 1

The plots illustrate the time-dependent trends for each derived glycan trait (G0, G1, G2, S, B, F) across the 10 men over the 90-day period. The x-axis represents time in days, while the y-axis displays the normalised values of relative abundance for each glycan trait. Data normalisation was conducted by dividing each data point value by its corresponding value at the initial point

Fig. 2

The plots illustrate the time-dependent trends for each derived glycan trait (G0, G1, G2, S, B, F) across the 28 women over the 90-day period. The x-axis represents time in days, while the y-axis displays the normalised values of relative abundance for each glycan trait. Data normalisation was conducted by dividing each data point value by its corresponding value at the initial point

Fig. 3

The plots illustrate the time-dependent trends for each derived glycan trait (G0, G1, G2, S, B, F) across the 70 women over the 12-week period. The x-axis represents time in weeks, while the y-axis displays the normalised values of relative abundance for each glycan trait. Data normalisation was conducted by dividing each data point value by its corresponding value at the initial point. Titles in green show statistically significant increase in glycan trait while the ones in red colour show statistically significant decrease in a glycan trait

Fig. 4

The plots illustrate the time-dependent trend for each derived glycan trait (G0, G1, G2, S, B, F) observed in a man over the 5-year period. The x-axis represents specific dates over time, while the y-axis displays the normalised values of relative abundance for each glycan trait. Data normalisation was conducted by dividing each data point value by its corresponding value at the initial point

Fig. 5

The plots illustrate the time-dependent trend for each derived glycan trait (G0, G1, G2, S, B, F) observed in a man over the 10-year period. The x-axis represents specific dates over time, while the y-axis displays the normalised values of relative abundance for each glycan trait. Data normalisation was conducted by dividing each data point value by its corresponding value at the initial point