The Sugar Language of Immunology: Glycosylation-Related Biomarkers for Severity Stratification in Post-Infectious Chronic Fatigue Syndrome

Introduction: Glycomics represents the molecular language of cells, based on sugar structures encoded on proteins, lipids, and tissues. Various diseases, including autoimmune disorders and infections, are characterized by altered glycans, which contribute to inflammation. This study aims to investigate alterations in glycan profiles in the peripheral blood of post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) patients compared to healthy controls. Objective: To test the hypothesis that changes in free sialic acid levels, serum and IgG N-Glycosylation patterns in the peripheral blood of ME/CFS patients may serve as potential biomarkers for monitoring disease severity. Methods: Peripheral blood samples were collected from 20 healthy controls and 20 post infectious ME/CFS patients (following EBV or COVID-19 infection). Total and free serum sialic acid was quantified via HPLC-FL. Serum N-Glycan profiles were analyzed by MALDI mass spectrometry. IgG antibodies were purified, and their N-glycosylation pattern were analyzed after fluorescent derivatization using HPLC. Results: A significant increase in total serum sialic acid was observed in the ME/CFS group compared to the healthy control. The N-glycan profile was characterised by an increased amount of bi- and tri-antennary sialated N-glycans (anti-inflammatory glycans) in the healthy control group compared to the ME/CFS group, on the other hand an increase of pro-inflammatory terminal galactosylated glycans in the ME/CFS group. Analysis of IgG glycosylation required method optimisation to avoid glycan damage during sample preparation, but can provide more accurate and specific information than serum glycan analysis. Conclusion: A decrease in sialylated glycans in serum glycans and an increase in total and free serum sialic acid could be due to the cleavage of sialic acid from host tissues caused by pathogenic neuraminidase activity. Targeted glycomics result a powerful approach to decoding immunological signals.