Abstract
More than 30% of the world population suffers from allergy. Allergic individuals are characterized by the production of immunoglobulin E (IgE) antibodies against innocuous environmental allergens. Upon allergen recognition IgE mediates allergen-specific immediate and late-phase allergic inflammation in different organs. The identification of the disease-causing allergens by demonstrating the presence of allergen-specific IgE is the key to precision medicine in allergy because it allows tailoring different forms of prevention and treatment according to the sensitization profiles of individual allergic patients. More than 30 years ago molecular cloning started to accelerate the identification of the disease-causing allergen molecules and enabled their production as recombinant molecules. Based on recombinant allergen molecules, molecular allergy diagnosis was introduced into clinical practice and allowed dissecting the molecular sensitization profiles of allergic patients. In 2002 it was demonstrated that microarray technology allows assembling large numbers of allergen molecules on chips for the rapid serological testing of IgE sensitizations with small volumes of serum. Since then microarrayed allergens have revolutionized research and diagnosis in allergy, but several unmet needs remain. Here we show that detection of IgE- and IgG-reactivity to a panel of respiratory allergens microarrayed onto silicon elements is more sensitive than glass-based chips. We discuss the advantages of silicon-based allergen microarrays and how this technology will allow addressing hitherto unmet needs in microarray-based allergy diagnosis. Importantly, it described how the assembly of silicon microarray elements may create different microarray formats for suiting different diagnostic applications such as quick testing of single patients, medium scale testing and fully automated large scale testing.
Highlights
The major difference between allergic patients and healthy, non-allergic subjects is that allergic patients produce immunoglobulin E (IgE) antibodies against certain environmental antigens, termed allergens, whereas non-allergic subjects produce Immunoglobulin G (IgG) antibodies [1, 2]
Several needs for improvement have remained unmet until today limiting the broad application of microarray-aided allergy diagnosis
We introduce here a novel concept for improving allergen microarray technology by showing that microarrays prepared on silicon offer higher sensitivity for the detection of specific IgE than the currently used glass surfaces and other surfaces with similar sensitivity as Future of Microarray-Based Allergy Diagnosis B
Summary
The major difference between allergic patients and healthy, non-allergic subjects is that allergic patients produce IgE antibodies against certain environmental antigens, termed allergens, whereas non-allergic subjects produce IgG antibodies [1, 2]. A considerable number of food allergen molecules have been identified which are associated with severe, mild, or even no reactions allowing for serological testing of food allergy by microarray-based IgE testing [64] In this context a study demonstrating different IgE sensitization profiles in children suffering from severe peanut allergy and in peanut-sensitized but asymptomatic children should be mentioned [65]. There are currently two major types of allergen arrays available, the ImmunoCAP ISAC platform, using allergen molecules immobilized onto glass (Thermo Fisher ImmunoCAP ISAC Immuno-solid-phase Allergen Chip which contains 112 allergens from 51 allergen sources) [38] and an allergen macroarray prepared on the basis of a nitrocellulose membrane (e.g., MADx Allergen Explorer ALEX; containing 282 allergens: 156 extracts and 126 components) [39] Both systems allow reasonable detection of allergen-specific IgE but one may consider increasing the quality of the arrays by selecting different materials for allergen immobilization. The challenges of interpreting allergen microarray results may be met by machine learning approaches and other diagnostic algorithms in addition to continuous medical education [10, 101]
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