Shade et al. demonstrate the requirement for IgE glycosylation in allergic reactions.
Approximately one-third of the world's population suffers from allergies 1. Exposure to allergens crosslinks immunoglobulin E (IgE) antibodies that are bound to mast cells and basophils, triggering the release of inflammatory mediators, including histamine 2. Although IgE is absolutely required for allergies, it is not understood why total and allergen-specific IgE concentrations do not reproducibly correlate with allergic disease 3-5. It is well-established that glycosylation of IgG dictates its effector function and has disease-specific patterns. However, whether IgE glycans differ in disease states or affect biological activity is completely unknown 6. Here we perform an unbiased examination of glycosylation patterns of total IgE from individuals with a peanut allergy and from non-atopic individuals without allergies. Our analysis reveals an increase in sialic acid content on total IgE from individuals with a peanut allergy compared with non-atopic individuals. Removal of sialic acid from IgE attenuates effector-cell degranulation and anaphylaxis in several functional models of allergic disease. Therapeutic interventions-including removing sialic acid from cell-bound IgE with a neuraminidase enzyme targeted towards the IgE receptor FcεRI, and administering asialylated IgE-markedly reduce anaphylaxis. Together, these results establish IgE glycosylation, and specifically sialylation, as an important regulator of allergic disease. IgE antibodies bind to the surface of mast cells or basophils that express the high-affinity IgE receptor FcεRI (ref. 2). Subsequent exposure to allergens crosslinks cell-bound IgE, leading to cellular activation and the release of allergic mediators, including histamine, prostaglandins and leukotrienes 2. This cascade culminates in the canonical symptoms of allergic diseases, the most severe of which is anaphylaxis. Although IgE that recognizes otherwise innocuous allergens is well-established as the causative agent of most allergic diseases 1,2 , clinical allergy diagnostics remain relatively inaccurate 3-5 , and curative therapies, including oral immunotherapy, are cumbersome and only partially effective 7,8. Further, allergen-specific IgE is detected in many people who do not experience allergic symptoms 3,5. Thus, while IgE is absolutely necessary for triggering the allergic cascade, it is not clear how IgE causes allergic disease in some circumstances and not others. The composition of the glycans attached (via a single asparagine (N) residue) to immunoglobulin G markedly influences its biological activity, and affects the outcome of many diseases, including Dengue haemorrhagic fever 9 , Mycobacterium tuberculosis latency 10 , influenza vaccination 11 , rheumatoid arthritis 6,12 , and granulomatosis with polyangiitis 13,14. There are seven N-linked glycosylation sites distributed across the heavy chains of human IgE (hIgE) 6,15. However, whether particular IgE glycans are associated with allergic diseases, or affect IgE function, is unknown. IgE is the least abundant antibody clas...
Purpose To develop and validate the positive predictive value (PPV) of an algorithm to identify anaphylaxis using health plan administrative and claims data. Previously published positive predictive values (PPVs) for anaphylaxis using ICD-9-CM codes range from 52-57%. Methods We conducted a retrospective study using administrative and claims data from eight health plans. Using diagnosis and procedure codes, we developed an algorithm to identify potential cases of anaphylaxis from the Mini-Sentinel Distributed Database between January 2009 and December 2010. A random sample of medical charts (N=150) was identified for chart abstraction. Two physician adjudicators reviewed each potential case. Using physician adjudicator judgments on whether the case met diagnostic criteria for anaphylaxis, we calculated a PPV for the algorithm. Results Of the 122 patients for whom complete charts were received, 77 were judged by physician adjudicators to have anaphylaxis. The PPV for the algorithm was 63.1% (95% CI: 53.9%-71.7%), using the clinical criteria by Sampson as the gold standard. The PPV was highest for inpatient encounters with ICD-9-CM codes of 995.0 or 999.4. By combining only the top performing ICD-9-CM codes, we identified an algorithm with a PPV of 75.0%, but only 66% of cases of anaphylaxis were identified using this modified algorithm. Conclusions The PPV for the ICD-9-CM-based algorithm for anaphylaxis was slightly higher than PPV estimates reported in prior studies, but remained low. We were able to identify an algorithm which optimized the PPV but demonstrated lower sensitivity for anaphylactic events.
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