Shreffler WG, Lencer DA, Bardina L, et al. IgE and IgG4 epitope mapping by microarray immunoassay reveals the diversity of immune response to the peanut allergen, Ara h 2

Jaffe Food Allergy Institute, Department of Pediatrics, Division of Allergy and Immunology, Mount Sinai School of Medicine, New York, NY 10029, USA.
Journal of Allergy and Clinical Immunology (Impact Factor: 11.48). 11/2005; 116(4):893-9. DOI: 10.1016/j.jaci.2005.06.033
Source: PubMed


Detailed assessment of antibody responses to allergens reveals clinically relevant information about both host response and antigen structure. Microarray technology offers advantages of scale and parallel design over previous methods of epitope mapping.
We designed a redundant peptide microarray for IgE and IgG4 epitope mapping of the previously characterized peanut allergen, Ara h 2.
Six complete sets of overlapping peptides were commercially synthesized and site-specifically bound to epoxy-derivatized glass slides in triplicate. Peptides were 10, 15, or 20 amino acids in length with an offset of either 2 or 3 amino acids. A total of 10 control and 45 peanut-allergic sera were assayed. Specific IgE and IgG4 were detected by using fluorochrome-labeled monoclonal secondary antibodies.
By using 15-mer and 20-mer peptides, we could define 11 antigenic regions, whereas only 5 were identifiable using 10-mers. Controls and patients produced IgG4 recognizing a comparable number of Ara h 2 peptides, although the dominant epitopes were distinct. As expected, patient IgE bound a larger number of Ara h 2 peptides (9.4% vs 0.9%). IgE and IgG4 epitopes recognized by patients were largely the same, and there was a positive association between IgE and IgG(4) signal, suggesting coordinate regulation. Cluster analysis of peptide binding patterns confirmed the specificity of antibody-peptide interactions and was used to define 9 core epitopes ranging from 6 to 16 residues in length-7 of which (78%) agreed with previous mapping.
Epitope mapping by microarray peptide immunoassay and cluster analysis reveals interpatient heterogeneity and a more detailed map.

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    • "The method primarily gives information on epitope specificity and affinity, the parameters reported by Flicker et al. (2008) to be decisive for studying the ability of IgG antibodies to block IgE recognition of allergens, and thereby the critical parameters to study when using this kind of molecular allergology to investigating patterns involved in clinical allergy versus involved in tolerance induction. In contrast previous studies investigated the specific antibody epitope pattern based on antibody binding to overlapping peptides covering the primary sequence of food allergens (Flinterman et al., 2008; Vickery et al., 2013; Shreffler et al., 2005; Cerecedo et al., 2008; Martinez-Botas et al., 2013; Matsumoto et al., 2009; Wang et al., 2010; Savilahti et al., 2010; Elsayed et al., 2004). The method used in the present study could in addition to linear epitopes also study the pattern of conformational epitopes and further allow for analysis of fine specificity of the antibodies. "
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    ABSTRACT: Development and maintenance of tolerance to food allergens appears to be associated with alterations in antigen specific IgE and IgG4 responses. Previous studies have focused only on comparing IgE and IgG4 linear epitope recognition patterns but take no account of conformational epitopes. The aim of this study was to compare Ara h 1-specific IgE and IgG4 epitope recognition patterns in patients with severe peanut allergy, applying a method allowing for identification of both linear and conformational epitopes. Polyclonal sera from three individual patients, suffering from severe allergic reaction to peanuts, including anaphylaxis, were used to analyse the IgE and IgG4 epitope recognition patterns of the major peanut allergen Ara h 1. Epitope identification was conducted by competitive immuno-screening of a phage-displayed random heptamer peptide library. Resulting epitope-mimicking sequences were aligned for identification of consensus sequences and localised on the surface of the Ara h 1 molecule by a computer-based algorithm. All epitope-mimicking sequences identified were found to correspond to conformational epitopes. Each individual patient had his/her own distinct IgE as well as IgG4 epitope recognition profile, though some important IgE epitopes were common to all patients. In general the IgG4 epitope pattern was more heterogeneous than the IgE pattern, did not coincide with IgE epitopes and had a lower affinity than IgE. This study demonstrated the usefulness of the phage-display technology in distinguishing between the epitope pattern of IgE and IgG4, giving detailed information on fine specificity and affinity. Competitive immuno-screening of phage-display random peptide libraries could be a future valuable tool to study the balance and dynamics of the IgE and IgG4 epitope recognition repertoire and provide a diagnostic tool giving information on the associated allergic phenotype.
    Molecular Immunology 12/2013; 58(2):169-176. DOI:10.1016/j.molimm.2013.11.014 · 2.97 Impact Factor
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    • "Sampson and colleagues have shown, using microarrays comprising sequential, linear peptides, that the number of epitopes sensed by IgEs is proportional to the severity of reaction [15]. This finding appears to be general, as testing peptides from peanuts, milk, eggs, salmon and lentils showed similar results [16] [17] [18] [19]. "
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    Acta biomaterialia 05/2013; 9(8). DOI:10.1016/j.actbio.2013.04.045 · 6.03 Impact Factor
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    • "Previous studies have found that the levels of food-specific IgGs and IgG subclasses in blood serum were significantly higher in individuals with food hypersensitivity [8], [9], [10], and that IgG-mediated immunologic responses may play an important role in the pathogenesis of adverse food reactions [11], [12], [13]. However, other studies indicate that the serum level of food-specific IgGs may also be elevated in healthy individuals, suggesting that the elevation of food-specific IgGs and IgG subclasses may merely reflect the presence of immunological tolerance to food-specific antigens, i.e., that it may only reflect a history of exposure to a certain food [14], [15]. "
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    ABSTRACT: The presence of food-specific IgG antibodies in human serum may be useful for diagnosis of adverse food reactions. However, the clinical utility of tesing for such antibodies remains very controversial. The aim of this study was to evaluate the serum levels and population distribution of food-specific IgGs and their association with chronic symptoms in a large-scale Chinese population. A total of 21305 adult participants from different regions of China had 14 type of food-specific serum IgG antibodies that were measured by enzyme-linked immunosorbent assay. Amongthese, 5,394 participants were randomly chosen to complete follow-up questionnaire surveys on their dietary characteristics and chronic symptoms. The concentrations of food-specific IgGs against 14 foods ranged from a median (interquartile range) of 7.3 (3.8, 12.6) U/mL of pork-specfic IgG to 42.3 (28.8, 60.2) U/mL of crab-specific IgG. The concentration of food-specific IgGs was closely related to gender; after adjustment for region and age, women had higher concentrations of food-specific IgGs against all of the 14 foods except chicken (regression coefficient (95% CI): 0.01 (-0.003, 0.023); P = 0.129) and corn (0.002 (-0.013, 0.016); P = 0.825). Similar results were also found in the relationship of geographic region to the food-specific IgG concentrations for the 14 foods. Chronic symptoms were negatively associated with the concentrations of a few food-specific IgGs, and were positively associated with the concentrations of other food-specific IgGs. The levels of food-specific IgGs were variable both in healthy and in symptomatic Chinese adults. These findings raise awareness that demographic factors, the type of food and specific chronic symptoms should be considered before food elimination treatment based on IgG testing in patients with chronic symptoms is used in clinical practice.
    PLoS ONE 01/2013; 8(1):e53612. DOI:10.1371/journal.pone.0053612 · 3.23 Impact Factor
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