Background
Allergies affect roughly one in three people in Switzerland, ranging from mild hay fever to life-threatening anaphylaxis. At the heart of nearly every allergic reaction sits a single class of antibody: IgE. When IgE recognizes an otherwise harmless substance such as pollen, peanut, or bee venom, it triggers the cascade of symptoms we know as an allergic response. Every IgE antibody carries sugar chains (glycans) that influence how strongly it activates allergic cells; in particular, sialic acid residues can act as natural amplifiers of the allergic response. Despite this functional importance, how the IgE glycan repertoire varies across different allergic conditions and between individuals with different IgE levels remains largely unknown. This knowledge gap stems from technical challenges: IgE is exceedingly scarce in blood (<0.001% of all antibodies), and its sugar coat is both highly variable and difficult to measure. To address this, we established a high-throughput, sensitive platform that directly maps the IgE sugar code from patient plasma across a wide range of IgE levels.
Methods
We built a semi-automated platform that reads the sugar code of IgE from a single drop of blood plasma (about 0.1 mL). The workflow uses magnetic beads to capture IgE antibodies with high efficiency, enzymatically digests them into small fragments, and measures these fragments using a highly sensitive mass spectrometer, an instrument that measures molecules with extreme precision. To establish confident structural assignments, we first constructed a comprehensive IgE glycan spectral library using electron-activated dissociation (EAciD), a novel fragmentation technique on our mass spectrometer that produces diagnostic ion series uniquely informative for glycan architecture. This approach resolved previously unreported IgE glycoforms that conventional fragmentation methods cannot distinguish, providing a structural reference against which all subsequent measurements are interpreted. To make the method scalable, we adapted it to a robotic liquid-handling system that processes 96 samples per day with minimal human intervention. We further enhanced sensitivity by developing a targeted detection strategy built on these characteristic sugar fingerprints, pushing the limit of detection low enough to map the IgE glycosylation landscape even in healthy individuals with very low IgE levels.
Results
The platform reliably mapped IgE sugar decorations directly from patient plasma across an extremely wide range of IgE concentrations, spanning both trace physiological levels and highly elevated pathological values. This sensitivity was achieved without sacrificing throughput: integration with a robotic liquid-handling system enabled reproducible processing of up to 96 samples per day. Leveraging this analytical capability, we are now applying the workflow to a comprehensive clinical cohort from the University Hospital Zurich (USZ), comprising around 600 allergic patients with a wide spectrum of allergies, together with a local immune-tolerant cohort of beekeepers from Davos.
Conclusions
By making IgE sugar profiling fast, sensitive, and reproducible, this work transforms a previously inaccessible layer of antibody biology into a measurable clinical readout. In the longer term, the sugar code of IgE could serve as a new class of biomarker, helping clinicians predict who is at risk of severe reactions, who will respond to allergy immunotherapy, and ultimately guiding the development of novel treatments that target the sugars themselves.