Fish allergy is a significant health concern, with diagnosis and management complicated by diverse fish species and allergens. We conducted a comprehensive RNA-seq analysis of eight fish species to identify allergen profiles, integrating ImmunoCAP sIgE data to explore associations with allergen expression and diagnostic performance. Over 30 putative fish allergens were identified, with varying sequence similarities and expression levels, roughly classifying fish into two groups based on parvalbumin (PV) expression. Higher similarities in allergen expression correlated with stronger sIgE data relationships among fish extracts. High PV expression and conserved PV sequences were linked to elevated sIgE measurements, potentially indicating higher allergenicity. For diagnosis, species-specific extract sIgE remained the best indicator of corresponding fish allergy diagnosis, while incorporating multiple sIgE data enhanced performance. In component-resolved diagnosis (CRD), the current panel with PV alone showed comparable performance to fish extract for PV-high fish allergy, while PV-low fish may require the inclusion of more minor allergens for improved CRD accuracy. This RNA-seq allergen analysis helps reveal fish allergen profiles, classify fish groups, and predict allergenicity, potentially improving CRD design and food management in fish allergy.
Keywords: ImmunoCAP sIgE; RNA-seq; allergen discovery; component-resolved diagnosis; fish allergenicity ladder; fish allergy; parvalbumin.