Food allergy (FA) is a serious public health issue afflicting millions of people globally, with an estimated prevalence ranging from 1-10%. Management of FA is challenging due to overly restrictive diets and the lack of diagnostic approaches with high accuracy and prediction. Although measurement of serum-specific antibodies combined with patient medical history and skin prick test is a useful diagnostic tool, it is still an imprecise predictor of clinical reactivity with a high false-positive rate. The double-blind placebo-controlled food challenge represents the gold standard for FA diagnosis; however, it requires large healthcare and involves the risk of acute onset of allergic reactions. Improvement in our understanding of the molecular mechanism underlying allergic disease pathology, development of omics-based methods, and advances in bioinformatics have boosted the generation of a number of robust diagnostic biomarkers of FA. In this review, we discuss how traditional diagnostic modalities guide appropriate diagnosis and management of FA in clinical practice, as well as uncover the potential of the latest biomarkers for the diagnosis, monitoring, and prediction of FA. We also raise perspectives for precise and targeted medical intervention to fill the gap in the diagnosis of FA.
Keywords: Food allergy; biomarker; diagnosis; omics; prediction.