A unique serum IgG glycosylation signature predicts development of Crohn's disease and is associated with pathogenic antibodies to mannose glycan.

Inflammatory bowel disease (IBD) is characterized by chronic inflammation in the gut. There is growing evidence in Crohn's disease (CD) of the existence of a preclinical period characterized by immunological changes preceding symptom onset that starts years before diagnosis. Gaining insight into this preclinical phase will allow disease prediction and prevention. Analysis of preclinical serum samples, up to 6 years before IBD diagnosis (from the PREDICTS cohort), revealed the identification of a unique glycosylation signature on circulating antibodies (IgGs) characterized by lower galactosylation levels of the IgG fragment crystallizable (Fc) domain that remained stable until disease diagnosis. This specific IgG2 Fc glycan trait correlated with increased levels of antimicrobial antibodies, specifically anti-Saccharomyces cerevisiae (ASCA), pinpointing a glycome-ASCA hub detected in serum that predates by years the development of CD. Mechanistically, we demonstrated that this agalactosylated glycoform of ASCA IgG, detected in the preclinical phase, elicits a proinflammatory immune pathway through the activation and reprogramming of innate immune cells, such as dendritic cells and natural killer cells, via an FcγR-dependent mechanism, triggering NF-κB and CARD9 signaling and leading to inflammasome activation. This proinflammatory role of ASCA was demonstrated to be dependent on mannose glycan recognition and galactosylation levels in the IgG Fc domain. The pathogenic properties of (anti-mannose) ASCA IgG were validated in vivo. Adoptive transfer of antibodies to mannan (ASCA) to recipient wild-type mice resulted in increased susceptibility to intestinal inflammation that was recovered in recipient FcγR-deficient mice. Here we identify a glycosylation signature in circulating IgGs that precedes CD onset and pinpoint a specific glycome-ASCA pathway as a central player in the initiation of inflammation many years before CD diagnosis. This pathogenic glyco-hub may constitute a promising new serum biomarker for CD prediction and a potential target for disease prevention.

The importance of IgG glycosylation-What did we learn after analyzing over 100,000 individuals.

All four subclasses of immunoglobulin G (IgG) antibodies have glycan structures attached to the protein part of the IgG molecules. Glycans linked to the Fc portion of IgG are found in all IgG antibodies, while about one-fifth of IgG antibodies in plasma also have glycans attached to the Fab portion of IgG. The IgG3 subclass is characterized by more complex glycosylation compared to other IgG subclasses. In this review, we discuss the significant influence that glycans exert on the structural and functional properties of IgG. We provide a comprehensive overview of how the composition of these glycans can affect IgG's effector functions by modulating its interactions with Fcγ receptors and other molecules such as the C1q component of complement, which in turn influence various immune responses triggered by IgG, including antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC). In addition, the importance of glycans for the efficacy of therapeutics like monoclonal antibodies and intravenous immunoglobulin (IVIg) therapy is discussed. Moreover, we offer insights into IgG glycosylation characteristics and roles derived from general population, disease-specific, and interventional studies. These studies indicate that IgG glycans are important biomarkers and functional effectors in health and disease.

N-Glycosylation Profiles of Immunoglobulin G and Future Cardiovascular Events.

BACKGROUND: Posttranslational glycosylation of IgG can modulate its inflammatory capacity through structural variations. We examined the association of baseline IgG N-glycans and an IgG glycan score with incident cardiovascular disease (CVD). METHODS: IgG N-glycans were measured in 2 nested CVD case-control studies: JUPITER (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin; NCT00239681; primary prevention; discovery; Npairs=162); and TNT trial (Treating to New Targets; NCT00327691; secondary prevention; validation; Npairs=397). Using conditional logistic regression, we investigated the association of future CVD with baseline IgG N-glycans and a glycan score adjusting for clinical risk factors (statin treatment, age, sex, race, lipids, hypertension, and smoking) in JUPITER. Significant associations were validated in TNT, using a similar model further adjusted for diabetes. Using least absolute shrinkage and selection operator regression, an IgG glycan score was derived in JUPITER as a linear combination of selected IgG N-glycans. RESULTS: Six IgG N-glycans were associated with CVD in both studies: an agalactosylated glycan (IgG-GP4) was positively associated, while 3 digalactosylated glycans (IgG glycan peaks 12, 13, 14) and 2 monosialylated glycans (IgG glycan peaks 18, 20) were negatively associated with CVD after multiple testing correction (overall false discovery rate <0.05). Four selected IgG N-glycans comprised the IgG glycan score, which was associated with CVD in JUPITER (adjusted hazard ratio per glycan score SD, 2.08 [95% CI, 1.52-2.84]) and validated in TNT (adjusted hazard ratio per SD, 1.20 [95% CI, 1.03-1.39]). The area under the curve changed from 0.693 for the model without the score to 0.728 with the score in JUPITER (PLRT=1.1×10-6) and from 0.635 to 0.637 in TNT (PLRT=0.017). CONCLUSIONS: An IgG N-glycan profile was associated with incident CVD in 2 populations (primary and secondary prevention), involving an agalactosylated glycan associated with increased risk of CVD, while several digalactosylated and sialylated IgG glycans associated with decreased risk. An IgG glycan score was positively associated with future CVD.

Salinomycin disturbs Golgi function and specifically affects cells in epithelial-to-mesenchymal transition.

Epithelial-to-mesenchymal transition (EMT) gives rise to cells with properties similar to cancer stem cells (CSCs). Targeting the EMT program to selectively eliminate CSCs is a promising way to improve cancer therapy. Salinomycin (Sal), a K+/H+ ionophore, was identified as highly selective towards CSC-like cells, but its mechanism of action and selectivity remains elusive. Here, we show that Sal, similar to monensin and nigericin, disturbs the function of the Golgi. Sal alters the expression of Golgi-related genes and leads to marked changes in Golgi morphology, particularly in cells that have undergone EMT. Moreover, Golgi-disturbing agents severely affect post-translational modifications of proteins, including protein processing, glycosylation and secretion. We discover that the alterations induced by Golgi-disturbing agents specifically affect the viability of EMT cells. Collectively, our work reveals a novel vulnerability related to the EMT, suggesting an important role for the Golgi in the EMT and that targeting the Golgi could represent a novel therapeutic approach against CSCs.

Variability of human Alpha-1-acid glycoprotein N-glycome in a Caucasian population.

AIM: Alpha-1-acid glycoprotein (AGP) is a highly glycosylated protein in human plasma and one of the most abundant acute phase proteins in humans. Glycosylation plays a crucial role in its biological functions, and alterations in AGP N-glycome have been associated with various diseases and inflammatory conditions. However, large-scale studies of AGP N-glycosylation in the general population are lacking. METHODS: Using recently developed high-throughput glycoproteomic workflow for site-specific AGP N-glycosylation analysis, 803 individuals from the Croatian island of Korcula were analyzed and their AGP N-glycome data associated with biochemical and physiological traits, as well as different environmental factors. RESULTS: After regression analysis, we found that AGP N-glycosylation is strongly associated with sex, somewhat less with age, along with multiple biochemical and physiological traits (e.g. BMI, triglycerides, uric acid, glucose, smoking status, fibrinogen). CONCLUSION: For the first time we have extensively explored the inter-individual variability of AGP N-glycome in a general human population, demonstrating its changes with sex, age, biochemical, and physiological status of individuals, providing the baseline for future population and clinical studies.

Investigation of the causal relationships between human IgG N-glycosylation and 12 common diseases associated with changes in the IgG N-glycome.

Changes in the N-glycosylation of immunoglobulin G (IgG) are often observed in pathological states, such as autoimmune, inflammatory, neurodegenerative, cardiovascular diseases and some types of cancer. However, in most cases, it is not clear if the disease onset causes these changes, or if the changes in IgG N-glycosylation are among the risk factors for the diseases. The aim of this study was to investigate the casual relationships between IgG N-glycosylation traits and 12 diseases, in which the alterations of IgG N-glycome were previously reported, using two sample Mendelian randomization (MR) approach. We have performed two sample MR using publicly available summary statistics of genome-wide association studies of IgG N-glycosylation and disease risks. Our results indicate positive causal effect of systemic lupus erythematosus (SLE) on the abundance of N-glycans with bisecting N-acetylglucosamine in the total IgG N-glycome. Therefore, we suggest regarding this IgG glycosylation trait as a biomarker of SLE. We also emphasize the need for more powerful GWAS studies of IgG N-glycosylation to further elucidate the causal effect of IgG N-glycome on the diseases.

Regular moderate physical exercise decreases Glycan Age index of biological age and reduces inflammatory potential of Immunoglobulin G.

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 (ß = -7.437, p.adj = 7.85E-03), and nominally significant and increased in professional athletes compared to the active group (ß = 7.546, p = 3.20E-02). Competing female athletes had significantly higher GlycanAge comparing to active females exercising moderately (ß = 20.206, p.adj = 2.71E-02), while the latter had significantly lower GlycanAge when compared with the inactive counterparts (ß = -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.

High-Throughput Glycomic Methods.

Glycomics aims to identify the structure and function of the glycome, the complete set of oligosaccharides (glycans), produced in a given cell or organism, as well as to identify genes and other factors that govern glycosylation. This challenging endeavor requires highly robust, sensitive, and potentially automatable analytical technologies for the analysis of hundreds or thousands of glycomes in a timely manner (termed high-throughput glycomics). This review provides a historic overview as well as highlights recent developments and challenges of glycomic profiling by the most prominent high-throughput glycomic approaches, with N-glycosylation analysis as the focal point. It describes the current state-of-the-art regarding levels of characterization and most widely used technologies, selected applications of high-throughput glycomics in deciphering glycosylation process in healthy and disease states, as well as future perspectives.

High-Throughput Human Complement C3 N-Glycoprofiling Identifies Markers of Early Onset Type 1 Diabetes Mellitus in Children.

Recently, it was shown that children at the onset of type 1 diabetes (T1D) have a higher proportion of oligomannose glycans in their total plasma protein N-glycome compared to their healthy siblings. The most abundant complement component, glycoprotein C3, contains two N-glycosylation sites occupied exclusively by this type of glycans. Furthermore, complement system, as well as C3, was previously associated with T1D. It is also known that changes in glycosylation can modulate inflammatory responses, so our aim was to characterize the glycosylation profile of C3 in T1D. For this purpose, we developed a novel high-throughput workflow for human C3 concanavalin A lectin affinity enrichment and subsequent LC-MS glycopeptide analysis which enables protein-specific N-glycosylation profiling. From the Danish Childhood Diabetes Register, plasma samples of 61 children/adolescents newly diagnosed with T1D and 84 of their unaffected siblings were C3 N-glycoprofiled. Significant changes of C3 N-glycan profiles were found. T1D was associated with an increase in the proportion of unprocessed glycan structures with more mannose units. A regression model including C3 N-glycans showed notable discriminative power between children with early onset T1D and their healthy siblings with area under curve of 0.879. This study confirmed our previous findings of plasma high-mannose glycan changes in a cohort of recent onset T1D cases, suggesting the involvement of C3 N-glycome in T1D development. Our C3 glycan-based discriminative model could be valuable in assessment of T1D risk in children.

Predicting Biochemical and Physiological Parameters: Deep Learning from IgG Glycome Composition.

In immunoglobulin G (IgG), N-glycosylation plays a pivotal role in structure and function. It is often altered in different diseases, suggesting that it could be a promising health biomarker. Studies indicate that IgG glycosylation not only associates with various diseases but also has predictive capabilities. Additionally, changes in IgG glycosylation correlate with physiological and biochemical traits known to reflect overall health state. This study aimed to investigate the power of IgG glycans to predict physiological and biochemical parameters. We developed two models using IgG N-glycan data as an input: a regression model using elastic net and a machine learning model using deep learning. Data were obtained from the Korcula and Vis cohorts. The Korcula cohort data were used to train both models, while the Vis cohort was used exclusively for validation. Our results demonstrated that IgG glycome composition effectively predicts several biochemical and physiological parameters, especially those related to lipid and glucose metabolism and cardiovascular events. Both models performed similarly on the Korcula cohort; however, the deep learning model showed a higher potential for generalization when validated on the Vis cohort. This study reinforces the idea that IgG glycosylation reflects individuals' health state and brings us one step closer to implementing glycan-based diagnostics in personalized medicine. Additionally, it shows that the predictive power of IgG glycans can be used for imputing missing covariate data in deep learning frameworks.

Multivariate genome-wide analysis of immunoglobulin G N-glycosylation identifies new loci pleiotropic with immune function.

The N-glycosylation of immunoglobulin G (IgG) affects its structure and function. It has been demonstrated that IgG N-glycosylation patterns are inherited as complex quantitative traits. Genome-wide association studies identified loci harboring genes encoding enzymes directly involved in protein glycosylation as well as loci likely to be involved in regulation of glycosylation biochemical pathways. Many of these loci could be linked to immune functions and risk of inflammatory and autoimmune diseases. The aim of the present study was to discover and replicate new loci associated with IgG N-glycosylation and to investigate possible pleiotropic effects of these loci onto immune function and the risk of inflammatory and autoimmune diseases. We conducted a multivariate genome-wide association analysis of 23 IgG N-glycosylation traits measured in 8090 individuals of European ancestry. The discovery stage was followed up by replication in 3147 people and in silico functional analysis. Our study increased the total number of replicated loci from 22 to 29. For the discovered loci, we suggest a number of genes potentially involved in the control of IgG N-glycosylation. Among the new loci, two (near RNF168 and TNFRSF13B) were previously implicated in rare immune deficiencies and were associated with levels of circulating immunoglobulins. For one new locus (near AP5B1/OVOL1), we demonstrated a potential pleiotropic effect on the risk of asthma. Our findings underline an important link between IgG N-glycosylation and immune function and provide new clues to understanding their interplay.

Altered IgG glycosylation at COVID-19 diagnosis predicts disease severity.

The nature of the immune responses associated with COVID-19 pathogenesis and disease severity, as well as the breadth of vaccine coverage and duration of immunity, is still unclear. Given the unpredictability for developing a severe/complicated disease, there is an urgent need in the field for predictive biomarkers of COVID-19. We have analyzed IgG Fc N-glycan traits of 82 SARS-CoV-2+ unvaccinated patients, at diagnosis, by nano-LC-ESI-MS. We determined the impact of IgG Fc glyco-variations in the induction of NK cells activation, further evaluating the association between IgG Fc N-glycans and disease severity/prognosis. We found that SARS-CoV-2+ individuals display, at diagnosis, variations in the glycans composition of circulating IgGs. Importantly, levels of galactose and sialic acid structures on IgGs are able to predict the development of a poor COVID-19 disease. Mechanistically, we demonstrated that a deficiency on galactose structures on IgG Fc in COVID-19 patients appears to induce NK cells activation associated with increased release of IFN-γ and TNF-α, which indicates the presence of pro-inflammatory immunoglobulins and higher immune activation, associated with a poor disease course. This study brings to light a novel blood biomarker based on IgG Fc glycome composition with capacity to stratify patients at diagnosis.

Plasma protein N-glycome composition associates with postprandial lipaemic response.

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 (Cmax), 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 (Cmax ß ranging from -0.28 for low-branched glycans to 0.30 for GP26) after adjusting for covariates and multiple testing (padjusted < 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.

Correction: Site-specific analysis of N-glycans from different sheep prion strains.

[This corrects the article DOI: 10.1371/journal.ppat.1009232.].

Site-specific analysis of N-glycans from different sheep prion strains.

Prion diseases are a group of neurodegenerative diseases affecting a wide range of mammalian species, including humans. During the course of the disease, the abnormally folded scrapie prion protein (PrPSc) accumulates in the central nervous system where it causes neurodegeneration. In prion disorders, the diverse spectrum of illnesses exists because of the presence of different isoforms of PrPSc where they occupy distinct conformational states called strains. Strains are biochemically distinguished by a characteristic three-band immunoblot pattern, defined by differences in the occupancy of two glycosylation sites on the prion protein (PrP). Characterization of the exact N-glycan structures attached on either PrPC or PrPSc is lacking. Here we report the characterization and comparison of N-glycans from two different sheep prion strains. PrPSc from both strains was isolated from brain tissue and enzymatically digested with trypsin. By using liquid chromatography coupled to electrospray mass spectrometry, a site-specific analysis was performed. A total of 100 structures were detected on both glycosylation sites. The N-glycan profile was shown to be similar to the one on mouse PrP, however, with additional 40 structures reported. The results presented here show no major differences in glycan composition, suggesting that glycans may not be responsible for the differences in the two analyzed prion strains.

IgG N-glycans are associated with prevalent and incident complications of type 2 diabetes.

AIMS/HYPOTHESIS: Inflammation is important in the development of type 2 diabetes complications. The N-glycosylation of IgG influences its role in inflammation. To date, the association of plasma IgG N-glycosylation with type 2 diabetes complications has not been extensively investigated. We hypothesised that N-glycosylation of IgG may be related to the development of complications of type 2 diabetes. METHODS: In three independent type 2 diabetes cohorts, plasma IgG N-glycosylation was measured using ultra performance liquid chromatography (DiaGene n = 1815, GenodiabMar n = 640) and mass spectrometry (Hoorn Diabetes Care Study n = 1266). We investigated the associations of IgG N-glycosylation (fucosylation, galactosylation, sialylation and bisection) with incident and prevalent nephropathy, retinopathy and macrovascular disease using Cox- and logistic regression, followed by meta-analyses. The models were adjusted for age and sex and additionally for clinical risk factors. RESULTS: IgG galactosylation was negatively associated with prevalent and incident nephropathy and macrovascular disease after adjustment for clinical risk factors. Sialylation was negatively associated with incident diabetic nephropathy after adjustment for clinical risk factors. For incident retinopathy, similar associations were found for galactosylation, adjusted for age and sex. CONCLUSIONS: We showed that IgG N-glycosylation, particularly galactosylation and to a lesser extent sialylation, is associated with a higher prevalence and future development of macro- and microvascular complications of diabetes. These findings indicate the predictive potential of IgG N-glycosylation in diabetes complications and should be analysed further in additional large cohorts to obtain the power to solidify these conclusions.

Total serum N-glycans associate with response to immune checkpoint inhibition therapy and survival in patients with advanced melanoma.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of melanoma and other cancers. However, no reliable biomarker of survival or response has entered the clinic to identify those patients with melanoma who are most likely to benefit from ICIs. Glycosylation affects proteins and lipids' structure and functions. Tumours are characterized by aberrant glycosylation which may contribute to their progression and hinder an effective antitumour immune response. METHODS: We aim at identifying novel glyco-markers of response and survival by leveraging the N-glycome of total serum proteins collected in 88 ICI-naive patients with advanced melanoma from two European countries. Samples were collected before and during ICI treatment. RESULTS: We observe that responders to ICIs present with a pre-treatment N-glycome profile significantly shifted towards higher abundancy of low-branched structures containing lower abundances of antennary fucose, and that this profile is positively associated with survival and a better predictor of response than clinical variables alone. CONCLUSION: While changes in serum protein glycosylation have been previously implicated in a pro-metastatic melanoma behaviour, we show here that they are also associated with response to ICI, opening new avenues for the stratification of patients and the design of adjunct therapies aiming at improving immune response.

High-throughput immunoaffinity enrichment and N-glycan analysis of human plasma haptoglobin.

Haptoglobin (Hp) is a positive acute phase protein, synthesized in the liver, with four N-glycosylation sites carrying mainly complex type N-glycans. Its glycosylation is altered in different types of diseases but still has not been extensively studied mainly due to analytical challenges, especially the lack of a fast, efficient, and robust high-throughput Hp isolation procedure. Here, we describe the development of a high-throughput method for Hp enrichment from human plasma, based on monolithic chromatographic support in immunoaffinity mode and downstream Hp N-glycome analysis by hydrophilic interaction ultrahigh-performance liquid chromatography with fluorescent detection (HILIC-UHPLC-FLR). Chromatographic monolithic supports in a 96-well format enable fast, efficient, and robust Hp enrichment directly from diluted plasma samples. The N-glycome analysis demonstrated that a degree of Hp deglycosylation differs depending on the conditions used for N-glycan release and on the specific glycosylation site, with Asn 241 being the most resistant to deglycosylation under tested conditions. HILIC-UHPLC-FLR analysis enables robust quantification of 28 individual chromatographic peaks, in which N-glycan compositions were determined by UHPLC coupled to electrospray ionization quadrupole time of flight mass spectrometry. The developed analytical approach enables fast evaluation of total Hp N-glycosylation and is applicable in large-scale studies.

Storage stability and HILIC-UHPLC-FLR analysis of immunoglobulin G N-glycome from saliva.

Immunoglobulin G (IgG) is the most abundant antibody in the blood and plays a critical role in host immune defense against infectious agents. Glycosylation is known to modulate the effector functions of IgG and is involved in disease development and progression. It is no surprise that the N-glycome of IgG from plasma has already been proposed as a biomarker for various physiological and pathological conditions. However, because saliva is easy to collect, it could be useful for exploring the functional role of salivary IgG N-glycosylation and its potential as a diagnostic biomarker. Therefore, in this study, we described a method for N-glycome analysis of IgG from saliva samples. Salivary IgG N-glycans were analyzed by ultra-high-performance liquid chromatography based on hydrophilic interactions with fluorescence detection (HILIC-UHPLC-FLR). In addition, we compared IgG N-glycan profiles from saliva with those from plasma, assessed the stability of salivary IgG N-glycan profiles under different storage conditions, and evaluated the effects of using a saliva preservation medium. This study provides an ultrasensitive UHPLC method for the analysis of total IgG N-glycosylation from saliva, gives insight into storage stability of salivary IgG, and highlights its (dis)advantages for further biomarker-related research.

Mouse milk immunoglobulin G Fc-linked N-glycosylation nano-LC-MS analysis in a model of vancomycin exposure during pregnancy.

Breast milk immunoglobulin G (IgG) plays an important role in the transfer of passive immunity in early life and in shaping the neonatal immune system through N-glycan-mediated effector functions. Currently, there are no protocols available to analyze breast milk IgG-Fc glycosylation in mouse models. Therefore, we developed and validated a glycoproteomic workflow for the medium-throughput subclass-specific nano-LC-MS analysis of IgG enriched from small milk volumes of lactating mice. With the established methods, the IgG glycopatterns in a mouse model of antibiotic use during pregnancy and increased asthma susceptibility in the offspring were analyzed. Pregnant BALB/c mice were treated with vancomycin during gestation days 8-17 and IgG1F, IgG2, and IgG3-Fc glycosylation was subsequently analyzed in maternal serum, maternal breast milk, and offspring serum on postnatal day 15. The IgG glycosylation profiles of mouse maternal milk and serum revealed no significant differences within the glycoforms quantified across subclasses. However, vancomycin use during pregnancy was associated with changes in IgG-Fc glycosylation in offspring serum, shown by the decreased relative abundance of the IgG1F-G1 and IgG3-G0 glycoforms, together with the increased relative abundance of the IgG3-G2 and S1 glycoforms. The workflow presented will aid in the emerging integrative multi-omics- and glycomics-oriented milk analyses both in rodent models and human cohorts for a better understanding of mother-infant immunological interactions.