Host glycosylation of immunoglobulins impairs the immune response to acute Lyme disease

• Published in: EBioMedicine 2024-02, Vol.100, p.104979, Article 104979
• Main Authors: Haslund-Gourley, Benjamin S., Hou, Jintong, Woloszczuk, Kyra, Horn, Elizabeth J., Dempsey, George, Haddad, Elias K., Wigdahl, Brian, Comunale, Mary Ann
• Format: Article
• Language: English
• Subjects: Acute immune response; Host glycosylation; IgG N-glycans; Lyme disease; Machine learning; Multiplex lectin assay
• ISSN: 2352-3964; 2352-3964
• DOI: 10.1016/j.ebiom.2024.104979

Lyme disease is caused by the bacteria Borreliella burgdorferi sensu lato (Bb) transmitted to humans from the bite of an infected Ixodes tick. Current diagnostics for Lyme disease are insensitive at the early disease stage and they cannot differentiate between active infections and people with a recent history of antibiotic-treated Lyme disease. Machine learning technology was utilized to improve the prediction of acute Lyme disease and identify sialic acid and galactose sugar structures (N-glycans) on immunoglobulins associated specifically at time points during acute Lyme disease time. A plate-based approach was developed to analyze sialylated N-glycans associated with anti-Bb immunoglobulins. This multiplexed approach quantitates the abundance of Bb-specific IgG and the associated sialic acid, yielding an accuracy of 90% in a powered study. It was demonstrated that immunoglobulin sialic acid levels increase during acute Lyme disease and following antibiotic therapy and a 3-month convalescence, the sialic acid level returned to that found in healthy control subjects (p