Background:  Food allergens are proteins that collectively represent a severe risk for a relatively small percentage (<0.5%) of the population and a moderate risk to an estimated 4 to 8% of the U.S. population. Few proteins in major allergenic food sources are responsible for sensitizing (initiating the production of specific IgE) and eliciting (inducing) allergic reactions.  New proteins are being introduced into foods through genetic engineering and as functional ingredients. Regulators and the food industry would like to be able to predict whether such proteins are likely to sensitize some individuals and more importantly, present a significant risk of elicitation for those who are sensitized.  Currently the ability to predict is quite limited.Elicitation:  A new protein with an amino acid sequence identity match of >70% over the full-length to a potent allergen is likely to cause clinical cross-reactions in some individuals sensitized to the matched allergen.  Proteins with less than 50% identity are unlikely to represent a risk of cross-reactivity.  Proteins of less than 5 kDa, proteins rapidly digested in pepsin at pH 2 and low abundance proteins are unlikely to elicit systemic reactions. Sensitization:  Proteins with a high amino acid identity match to a potent allergen may represent an elevated risk of sensitization.  However, that requires both effective T-cell and B-cell epitopes, which are not accurately predicted. Proteins stable in pepsin at pH 2 may sensitize via the gastric mucosa, but other routes of sensitization include the skin and airway for unstable proteins.  Undefined food matrix components (fats, lectins and proteases) may enhance sensitization or elicitation.  So far no animal model and no cell culture systems have been demonstrated to accurately predict the gradient of high and low allergenic activities of proteins seen in the diverse population of allergic humans. Methods and results will be reviewed.

Can we predict the potential allergenicity of dietary proteins?

248th National Meeting (2014)

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