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.
摘要：
衰老是一个复杂的生物过程，个体之间存在差异，导致老化时钟的发展，以估计生物年龄。Glycans,特别是在免疫球蛋白G（IgG）中，已经成为衰老的潜在生物标志物，糖基化模式的变化与实际年龄有关。对于精度分析，在26天内分析了三个不同的血浆池，一式四份，总共312个样品。在短期变异性分析中，我们对两个队列进行了分析:由26名健康个体(中位年龄20岁)组成的阿斯利康MFO队列和由70名绝经前中国女性(中位年龄22.5岁)组成的队列,监测时间超过3个月.长期变异性分析涉及两名年龄分别为47岁和57岁的成年男性，监测时间为5年和10年，分别。每3个月和3周收集一次样品，分别。IgGN-聚糖分析遵循标准化方法，通过分离IgG，随后变性和去糖基化，然后进行聚糖净化和标记。采用激光诱导荧光（CGE-LIF）和超高效液相色谱分析的毛细管凝胶电泳进行聚糖谱分析。统计分析涉及归一化，批量校正，和线性混合模型，以评估时间对衍生聚糖性状的影响。在所有三个测试样品中，中间精度结果始终显示出非常低的变异系数值。这种一致的模式强调了用于分析衰老的聚糖时钟的CGE方法固有的高水平的精度。阿斯利康MFO队列没有显示出任何统计学上显著的趋势，而月经周期队列在digalactosyated（G2）中表现出统计学上的显着趋势，琼脂糖糖基化(G0)和岩藻糖基化(F)。这些趋势归因于月经周期的影响。长期稳定性分析确定了两个受试者的持久年龄相关趋势，在G0和二等分的N-乙酰葡糖胺中显示正时间效应，以及G2和唾液酸化的负时间效应，与先前的发现保持一致。测量单半乳糖基化的时间效应，和F保持显著低于其他性状观察到的。研究发现,使用CGE-LIF的IgGN-糖分析表现出显著高的中间精度。此外，该研究强调了IgG糖组成的短期和长期稳定性，加上显著的适应和应对生理变化和环境因素如荷尔蒙变化的能力，疾病,和干预。这项研究的发现通过加深我们对IgG糖与年龄相关的健康问题的理解，推动了个性化医疗的发展。这项研究强调了聚糖作为跟踪年龄相关变化和个体健康路径的生物标志物的可靠性。
