The importance of early peanut ingestion in the prevention of peanut allergy

Voltammetric Immunosensor to Track a Major Peanut Allergen (Ara h 1) in Food Products Employing Quantum Dot Labels

Tracking unreported allergens in commercial foods can avoid acute allergic reactions. A 2-step electrochemical immunosensor was developed for the analysis of the peanut allergen Ara h 1 in a 1-h assay (<15 min hands-on time). Bare screen-printed carbon electrodes (SPCE) were used as transducers and monoclonal capture and detection antibodies were applied in a sandwich-type immunoassay. The short assay time was achieved by previously combining the target analyte and the detection antibody. Core/shell CdSe@ZnS Quantum Dots were used as electroactive label for the detection of the immunological interaction by differential pulse anodic stripping voltammetry. A linear range between 25 and 1000 ng·mL-1 (LOD = 3.5 ng·mL-1), an adequate precision of the method (Vx0 ≈ 6%), and a sensitivity of 23.0 nA·mL·ng-1·cm-2 were achieved. The immunosensor was able to detect Ara h 1 in a spiked allergen-free product down to 0.05% (m/m) of peanut. Commercial organic farming cookies and cereal and protein bars were tested to track and quantify Ara h 1. The results were validated by comparison with an ELISA kit.

Bayesian hierarchical evaluation of dose-response for peanut allergy in clinical trial screening

Risk-based labeling based on the minimal eliciting doses (EDs) in sensitized populations is a potential replacement for precautionary allergen labeling of food allergens. We estimated the dose-response distribution for peanut allergen using data from double-blind placebo-controlled food challenges (DBPCFCs) conducted in the US at multiple sites, testing a population believed to be similar to the general U.S. food allergic population. Our final (placebo-adjusted) dataset included 548 challenges of 481 subjects. Bayesian hierarchical analysis facilitated model fitting, and accounted for variability associated with various levels of data organization. The data are best described using a complex hierarchical structure that accounts for inter-individual variability and variability across study locations or substudies. Bayesian model averaging could simultaneously consider the fit of multiple models, but the Weibull model dominated so strongly that model averaging was not needed. The ED01 and ED05 (and 95% credible intervals) are 0.052 (0.021, 0.13) and 0.49 (0.22, 0.97) mg peanut protein, respectively. Accounting for challenges with severe reactions at the LOAEL, by using the dose prior to the LOAEL as the new LOAEL, the ED01 drops to 0.029 (0.014, 0.074) mg peanut protein. Our results could aid in establishing improved food labeling guidelines in the management of food allergies.