BACKGROUND Post-translational modifications represent a critical layer of protein regulation, yet their genetic control and population variation remain poorly characterized. Here we present a comprehensive analysis integrating population-scale glycoproteomics with genome-wide association study (GWAS) to uncover genetic regulatory networks controlling N-glycosylation of complement component C3. RESULTS Through LC-MS glycopeptide analysis of 816 Croatian adults, we characterize site-specific N-glycosylation at two C3 sites (N63 and N917), confirming an unusual phenotype consisting of exclusive high-mannose structures rather than complex glycans typical of secreted proteins. GWAS identifies six genetic loci significantly associated with C3 N-glycosylation patterns, including genes encoding proteins involved in maintenance of the protein secretory pathway, proteins involved in the complement pathway or regulation of complement, and regulators of gene expression. Using colocalization analysis, we discover shared causal variants between C3 glycosylation and immune diseases, particularly rheumatoid arthritis and inflammatory bowel disease, suggesting glycosylation as a mechanistic link between genetic variation and disease susceptibility. C3 N-glycoprofiling reveals significant associations with sex, age, and metabolic parameters, indicating integration of genetic and environmental factors. Structural modeling provides mechanistic insights, revealing how protein architecture constrains glycan processing and enables functional glycan-mediated interactions. CONCLUSIONS Our multiomic approach establishes a framework for understanding how genetic variation shapes post-translational modifications at population scale, demonstrating C3 N-glycosylation as both a genetically and environmentally regulated checkpoint in complement activation with implications for precision medicine approaches in immune and metabolic diseases.

Executive function is an essential cognitive domain for typical human behavior which is disrupted in neurodevelopmental and neurodegenerative disorders, but little is known about its underlying molecular basis. To address this, we perform genome-wide association studies (GWAS) using three different measures of executive function in UK Biobank (N = 84,238) and NIHR BioResource’s Genes and Cognition (N = 9932) study participants, followed by a meta-analysis. The trail-making alphanumeric (TMA) measure is the most heritable phenotype (h²=7-26%), associated with 18 independent loci that exhibit a similar direction of effect in both cohorts. Across these loci, in-silico follow-up implicates 178 genes, of which NT5DC2 and RP11-579E24.2 are independently replicated prior to meta-analysis. TMA is linked to pan-cerebral differences in brain structure, with brain-enriched genes showing a biphasic expression profile from early development through to later life. Our data implicate specific cell types, histone modifications and butyrophilin immunoglobulin family proteins as potential targets for promoting cognitive resilience. A genome-wide association meta analysis of Trail Making enriches our understanding of the genetic landscape of executive functioning, identifies cognitive and neural correlates, and reveals a cell-type specific developmental origin.

Multi-modal retrieval-augmented generation (MMRAG) promises grounded biomedical QA, but it is unclear when to (i) convert figures/tables into text versus (ii) use optical character recognition (OCR)-free visual retrieval that returns page images and leaves interpretation to the generator. We study this trade-off in glycobiology, a visually dense domain. We built a benchmark of 120 multiple-choice questions (MCQs) from 25 papers, stratified by retrieval difficulty (easy text, medium figures/tables, hard cross-evidence). We implemented four augmentations—None, Text RAG, Multi-modal conversion, and late-interaction visual retrieval (ColPali)—using Docling parsing and Qdrant indexing. We evaluated mid-size opensource and frontier proprietary models (e.g., Gemma-3-27BIT, GPT-4o family). Additional testing used the GPT-5 family and multiple visual retrievers (ColPali/ColQwen/ColFlor). Accuracy with Agresti–Coull 95% confidence intervals (CIs) was computed over 5 runs per configuration. With Gemma-3-27BIT, Text and Multi-modal augmentation outperformed OCR-free retrieval (0.722-0.740 vs. 0.510 average accuracy). With GPT-4o, Multi-modal achieved 0.808, with Text 0.782 and ColPali 0.745 close behind; within-model differences were small. In follow-on experiments with the GPT-5 family, the best results with ColPali and ColFlor improved by 2% to 0.828 in both cases. In general across the GPT-5 family, ColPali, ColQwen, and ColFlor were statistically indistinguishable; ColFlor matched ColPali while being far smaller. GPT-5-nano trailed larger GPT-5 variants by roughly 8-10%. Pipeline choice is capacity-dependent: converting visuals to text lowers the reader burden and is more reliable for mid-size models, whereas OCR-free visual retrieval becomes competitive under frontier models. Among retrievers, ColFlor offers parity with heavier options at a smaller footprint, making it an efficient default when strong generators are available.

In this pilot study, a subset of CALERIE Phase 2 (No. NCT00427193, registered 25th Jan 2007) participants (n = 26) were evaluated for the effects of 2 years of 25% calorie restriction (CR) on N-glycosylation of IgG, plasma, and complement C3, as well as IgG-based biological age (GlycAge). Plasma samples were collected at baseline (BL), 12 (12mo), and 24 months (24mo). IgG galactosylation was higher at 24mo compared to BL (p = 0.051) and increased from 12mo to 24mo (p = 0.016); GlycAge decreased over the same period (p = 0.027). GlycAge was positively associated with TNF-α (p = 0.030) and ICAM-1 (p = 0.017). Between BL and 24mo, plasma high-branched glycans declined (p = 0.013), bisecting GlcNAcs increased in both plasma (p < 0.001) and IgG (p = 0.01), complement C3 protein (p < 0.001), C3-Man9 (p < 0.001), and C3-Man9Glc1C3 (p = 0.046) were reduced. The absence of a control group warrants cautious interpretation.

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.

Physical inactivity and obesity are growing concerns, negatively impacting the general population. Moderate physical activity is known to have a beneficial anti-inflammatory effect. N-glycosylation of immunoglobulin G (IgG) reflects changes in the inflammatory potential of IgG. In this study, GlycanAge index of biological age (GlycanAge), one of the first commercially used biomarkers of aging, was employed to assess effects of exercise intensity in three different groups of athletes: professional competing athletes, regularly moderate active individuals and newly involved recreational individuals, compared to the group of inactive individuals. GlycanAge was significantly lower in the active group compared to the inactive group (β = -7.437, p.adj = 7.85E-03), and nominally significant and increased in professional athletes compared to the active group (β = 7.546, p = 3.20E-02). Competing female athletes had significantly higher GlycanAge comparing to active females exercising moderately (β = 20.206, p.adj = 2.71E-02), while the latter had significantly lower GlycanAge when compared with the inactive counterparts (β = -9.762, p.adj = 4.68E-02). Regular, life-long moderate exercise has an anti-inflammatory effect in both female and male population, demonstrated by lower GlycanAge index, and it has great potential to mitigate growing issues related to obesity and a sedentary lifestyle, which are relentlessly increasing world-wide.

With aging, the body’s ability to maintain regular functions declines, increasing susceptibility to age-related diseases. Therapeutic interventions targeting the underlying biological changes of aging hold promise for preventing or delaying multiple age-related diseases. Metformin, a drug commonly used for diabetes treatment, has emerged as a potential gerotherapeutic agent due to its established safety record and preclinical and clinical data on its anti-aging effects. Glycosylation, one of the most common and complex co- and post-translational protein modifications, plays a crucial role in regulating protein function and has been linked to aging and various diseases. Changes in immunoglobulin G (IgG) glycosylation patterns have been observed with age, and these alterations may serve as valuable biomarkers for disease predisposition, diagnosis, treatment monitoring, and overall health assessment. In this study, we analyzed the IgG glycosylation patterns of white men from Europe, aged 29–45 years, under treatment with metformin, testosterone, metformin plus testosterone, and placebo (trial registration number NCT02514629, 2013/07/04), and investigated the longitudinal changes in glycosylation over time. We observed statistically significant differences in the IgG glycome composition between participants on testosterone therapy and placebo, with decreased agalactosylation and increased galactosylation and sialylation. However, metformin therapy did not result in statistically significant changes in glycosylation patterns. These findings contribute to our understanding of the impact of therapeutic interventions on IgG glycosylation and confirm the value of IgG glycosylation as a significant biomarker, capable of assessing biological age using the GlycanAge index and providing insight into overall health compared to chronological age.

Background A dysregulated postprandial metabolic response is a risk factor for chronic diseases, including type 2 diabetes mellitus (T2DM). The plasma protein N-glycome is implicated in both lipid metabolism and T2DM risk. Hence, we first investigate the relationship between the N-glycome and postprandial metabolism and then explore the mediatory role of the plasma N-glycome in the relationship between postprandial lipaemia and T2DM. Methods We included 995 individuals from the ZOE-PREDICT 1 study with plasma N-glycans measured by ultra-performance liquid chromatography at fasting and triglyceride, insulin, and glucose levels measured at fasting and following a mixed-meal challenge. Linear mixed models were used to investigate the associations between plasma protein N-glycosylation and metabolic response (fasting, postprandial ( C _max), or change from fasting). A mediation analysis was used to further explore the relationship of the N-glycome in the prediabetes (HbA1c = 39–47 mmol/mol (5.7–6.5%))–postprandial lipaemia association. Results We identified 36 out of 55 glycans significantly associated with postprandial triglycerides ( C _max β ranging from -0.28 for low-branched glycans to 0.30 for GP26) after adjusting for covariates and multiple testing ( p _adjusted < 0.05). N-glycome composition explained 12.6% of the variance in postprandial triglycerides not already explained by traditional risk factors. Twenty-seven glycans were also associated with postprandial glucose and 12 with postprandial insulin. Additionally, 3 of the postprandial triglyceride–associated glycans (GP9, GP11, and GP32) also correlate with prediabetes and partially mediate the relationship between prediabetes and postprandial triglycerides. Conclusions This study provides a comprehensive overview of the interconnections between plasma protein N-glycosylation and postprandial responses, demonstrating the incremental predictive benefit of N-glycans. We also suggest a considerable proportion of the effect of prediabetes on postprandial triglycerides is mediated by some plasma N-glycans.