Antigen specificity determines anti‐red blood cell IgG‐Fc alloantibody glycosylation and thereby severity of haemolytic disease of the fetus and newborn. (28th November 2016)

• Record Type: Journal Article
• Authors: Sonneveld, Myrthe E.; Koelewijn, Joke; de Haas, Masja; Admiraal, Jon; Plomp, Rosina; Koeleman, Carolien A. M.; Hipgrave Ederveen, Agnes L.; Ligthart, Peter; Wuhrer, Manfred; van der Schoot, C. Ellen; Vidarsson, Gestur
• Is Part Of: British journal of haematology. Volume 176:Number 4(2017)
• Page Start: 651
• Page End: 660
• Publication Date: 2016-11-28
• Subjects: Haemolytic anaemia -- Fc‐glycosylation -- Immunology -- Antibodies -- Red cell antigens; Hematology -- Periodicals; Blood -- Diseases -- Periodicals; 616.15
• DOI: 10.1111/bjh.14438
• Languages: English
• ISSNs: 0007-1048

Abstract

Summary: Haemolytic disease of the fetus and newborn (HDFN) is a severe disease in which fetal red blood cells (RBC) are destroyed by maternal anti‐RBC IgG alloantibodies. HDFN is most often caused by anti‐D but may also occur due to anti‐K, ‐c‐ or ‐E. We recently found N ‐linked glycosylation of anti‐D to be skewed towards low fucosylation, thereby increasing the affinity to IgG‐Fc receptor IIIa and IIIb, which correlated with HDFN disease severity. Here, we analysed 230 pregnant women with anti‐c, ‐E or –K alloantibodies from a prospective screening cohort and investigated the type of Fc‐tail glycosylation of these antibodies in relation to the trigger of immunisation and pregnancy outcome. Anti‐c, ‐E and –K show – independent of the event that had led to immunisation – a different kind of Fc‐glycosylation compared to that of the total IgG fraction, but with less pronounced differences compared to anti‐D. High Fc‐galactosylation and sialylation of anti‐c correlated with HDFN disease severity, while low anti‐K Fc‐fucosylation correlated with severe fetal anaemia. IgG‐Fc glycosylation of anti‐RBC antibodies is shaped depending on the antigen. These features influence their clinical potency and may therefore be used to predict severity and identify those needing treatment.