Domain and Residue Mapping of Autoantibodies to β2GPI Reveals Differences Among Antiphospholipid Syndrome Phenotypes Available to Purchase

• Structure-based mutational studies reveal signatures of structurally distinct conformational epitopes in DI, epitope I and epitope II

• Epitope I is enriched in thrombotic obstetric APS patients; epitope diversity may help identify APS phenotypes and predict clinical outcomes

Antiphospholipid antibodies targeting b2-glycoprotein I (b2GPI) are a hallmark of antiphospholipid syndrome (APS), associated with an increased risk of thrombosis and pregnancy morbidity. Among these, antibodies targeting Domain I (DI) are common in individuals at higher risk; however, their epitopes and prevalence among APS phenotypes remain unclear. Here, we employ a large collection of 29 structurally and functionally validated b2GPI variants to provide new insights into the molecular mechanisms of autoantibody recognition in APS. Using the prototypic human-derived monoclonal anti-DI antibody MBB2, we identified positively charged residue R39 as the key driver for MBB2 binding, followed by residues R43, N56, and T57. Structural analyses revealed that, while R39 is solvent-exposed, R43 is not, as it is caged by residues N56 and T57. The narrow epitope footprint explains why MBB2 exhibits a modest affinity for soluble b2GPI. The cage structure accounts for the epitope being conformational rather than linear. Mutational analyses of IgG anti-b2GPI antibodies from 52 triple-positive APS patients, 37 with a history of thrombosis and 15 non-vascular obstetric patients, confirmed significant reactivity against DI and showed signatures of two conformational epitopes: one similar to MBB2 (epitope I), in which the presence of R39 is essential, and another that does not require R39 (epitope II). While less frequent than epitope-II in our cohort, epitope-I reactivity was notably enriched in thrombotic obstetric patients. Varying epitope specificities for DI may therefore aid in identifying different APS phenotypes and predicting clinical outcomes.