Preparation of Blinded Food Matrixes for Clinical Oral Challenges.

Clinically, oral food challenges have value in the diagnosis and management of food allergy. Oral food challenges are used not only for diagnostic confirmation that ingestion of a specific food elicits an adverse reaction, but also for determining individual threshold doses, tracking the progress toward desensitization during immunotherapy, determining the effect of processing on the allergenicity of a specific food, assessing the allergenicity of an ingredient derived from an allergenic source, and tracking the progress toward development of age-related tolerance to a specific food. To eliminate bias in oral challenges, the food under investigation is masked in a matrix so that it is not sensorially detectable by the patient or the clinical observer. The preparation of oral challenge foods requires care in the selection of the allergenic components, the selection of the components of the matrix, the masking of the allergenic component, and the homogeneity of the allergen in the overall matrix.

Peanut Can Be Used as a Reference Allergen for Hazard Characterization in Food Allergen Risk Management: A Rapid Evidence Assessment and Meta-Analysis.

Regional and national legislation mandates the disclosure of "priority" allergens when present as an ingredient in foods, but this does not extend to the unintended presence of allergens due to shared production facilities. This has resulted in a proliferation of precautionary allergen ("may contain") labels (PAL) that are frequently ignored by food-allergic consumers. Attempts have been made to improve allergen risk management to better inform the use of PAL, but a lack of consensus has led to variety of regulatory approaches and nonuniformity in the use of PAL by food businesses. One potential solution would be to establish internationally agreed "reference doses," below which no PAL would be needed. However, if reference doses are to be used to inform the need for PAL, then it is essential to characterize the hazard associated with these low-level exposures. For peanut, there are now published data relating to over 3000 double-blind, placebo-controlled challenges in allergic individuals, but a similar level of evidence is lacking for other priority allergens. We present the results of a rapid evidence assessment and meta-analysis for the risk of anaphylaxis to a low-level allergen exposure for priority allergens. On the basis of this analysis, we propose that peanut can and should be considered an exemplar allergen for the hazard characterization at a low-level allergen exposure.

Development of a Sandwich Enzyme-Linked Immunosorbent Assay for Detection and Quantification of Clam Residues in Food Products.

Seafood is a frequent cause of allergic reactions to food globally. The presence of undeclared trace amounts of clam can cause allergic reactions in sensitive individuals. Limited tools are available to test food products for the presence of traces of clam. We report on the development of a sandwich ELISA that can detect and quantify clam protein in food. Antisera against a mix of two commercially important clam species, Atlantic Surf (Spisula solidissima) and ocean quahog (Arctica islandica), were raised in rabbit and sheep. A sandwich ELISA was constructed with this antisera, and sensitivity and specificity were evaluated. Also, model food products spiked with clam protein were analyzed to assess the performance of the ELISA. Comparison was made with a commercially available ELISA for crustacea. The lower limit of quantification of the sandwich ELISA is 2.5 ppm clam protein in food samples, allowing the detection of low amounts of clam that may trigger a reaction in clam allergic patients. The sandwich ELISA was highly specific with cross-reactivity only noted for other molluscan shellfish (mussel and scallop). Clam protein in tomato juice and potato cream soup was detected well with recoveries ranging from 65 to 74% and from 74 to 113%, respectively. However when potato cream soup was retorted, the recover fell to 20%, imposing the risk of underestimating the clam content of a food product. A commercially available crustacean ELISA test was not suitable to detect clam protein. The sandwich ELISA described here is suitable for detection and quantification of clam protein in food products. Care should be taken with food products that have been retorted as the results may be underestimated.

Bayesian Stacked Parametric Survival with Frailty Components and Interval-Censored Failure Times: An Application to Food Allergy Risk.

To better understand the risk of exposure to food allergens, food challenge studies are designed to slowly increase the dose of an allergen delivered to allergic individuals until an objective reaction occurs. These dose-to-failure studies are used to determine acceptable intake levels and are analyzed using parametric failure time models. Though these models can provide estimates of the survival curve and risk, their parametric form may misrepresent the survival function for doses of interest. Different models that describe the data similarly may produce different dose-to-failure estimates. Motivated by predictive inference, we developed a Bayesian approach to combine survival estimates based on posterior predictive stacking, where the weights are formed to maximize posterior predictive accuracy. The approach defines a model space that is much larger than traditional parametric failure time modeling approaches. In our case, we use the approach to include random effects accounting for frailty components. The methodology is investigated in simulation, and is used to estimate allergic population eliciting doses for multiple food allergens.

Threshold Dose Distribution in Walnut Allergy.

BACKGROUND: In food allergy, eliciting doses (EDs) of foods on a population level can improve risk management and labeling strategies for the food industry and regulatory authorities. Previously, data available for walnut were unsuitable to determine EDs. OBJECTIVE: The objective of this study was to determine EDs for walnut allergic adults and to compare with previously established threshold data for peanut and tree nuts. METHODS: Prospectively, adult subjects with a suspected walnut allergy underwent a low-dose double-blind, placebo-controlled food challenge. Individual no observed and lowest observed adverse effect levels were determined and log-normal, log-logistic, and Weibull models were fit to the data. Estimated ED values were calculated for the ED5, ED10, and ED50, the dose respectively predicted to provoke an allergic reaction in 5%, 10%, and 50% of the walnut allergic population. RESULTS: Fifty-seven subjects were challenged and 33 subjects were confirmed to be walnut allergic. Objective symptoms occurred in 20 of the positive challenges (61%). The cumulative EDs in the distribution models ranged from 3.1 to 4.1 mg for the ED05, from 10.6 to 14.6 mg walnut protein for the ED10, and from 590 to 625 mg of walnut protein for the ED50. CONCLUSIONS: Our data indicate that population EDs for walnut are slightly higher compared with those for peanut and hazelnut allergy. Currently available data indicate that the ED values for hazelnut could be used as a conservative temporary placeholder when implementing risk management strategies for other tree nuts where little or no food challenge data are available.

Evaluation of Commercial Milk-Specific Lateral Flow Devices.

The requirement for validation of allergen cleaning processes is increasing. The use of lateral flow devices (LFDs) to identify allergens has rapidly expanded, but the best practices for use of these devices are still developing. The goal of this study was to compare commercially available milk-specific LFDs and a general protein identification method. Five milk proteins and seven milk-derived ingredients were tested at several concentrations with eight milk-specific LFDs and a general protein identification kit. Nonfat dry milk (NFDM) was prepared at 100 to 10,000 ppm of milk protein and analyzed by the LFDs to determine the concentration at which a false-negative result (overload concentration or hook effect) was obtained. NFDM was also prepared in 0.025 M phosphate-buffered saline (pH 7.4, 0.85% NaCl) and applied to stainless steel panels (100, 30, 10, or 3 µg of NFDM protein) with various drying methods and sampled with various swab methods to determine the level of detectability. Several total milk LFD kits did not detect whey proteins or whey-derived ingredients. The overload concentration of the various kits ranged from 100 to 10,000 ppm of milk protein. The small dynamic range observed for some kits would necessitate multiple dilutions of a sample to ensure that the result would fall within the range of detection. For swab sampling of stainless steel for LFD analysis, milk protein residues from surfaces onto which the residues were dried with high heat were more difficult to detect than were residues dried with low heat. No differences in sensitivity were observed as a result of moistening the residue or the swab before sampling. These results highlight the importance of understanding the detection capabilities of LFDs as indicated by the variability in the performance of the milk-specific LFDs tested.