A new way forward? Examining the potential of quantitative analysis of IgE datasets

Felix King, 

Robert Kaczmarczyk, 

Alexander Zink, 

Tilo Biedermann & 

Knut Brockow 

Allergy, Asthma & Clinical Immunology volume 18, Article number: 75 (2022) 

• 
  details

Abstract

Background

Allergies constitute an important public health problem, and epidemiological data is crucial to developing strategies for its prevention and therapy. Few population-based studies are available for data on allergies and sensitization. However, as these studies are expensive and time-consuming, novel approaches are searched for.

Objectives

A large monocentric IgE dataset was used to analyse quantitative sensitization data in different age and gender groups and compared the results to available epidemiological data.

Methods

A total of 14,370 patients who sought medical care at the Department for Dermatology and Allergology at the Technical University of Munich, Germany was analysed.

Total IgE and sensitization measured in specific IgE levels to common food allergens and aeroallergens were compared between females and males, age groups, and the year of testing (2003–2021).

Results

Line graphs showing the mean sensitization for ten different
allergens in kUA/l with 95% confidence intervals for females and
males in different age groups

8283 females (57.6%) and 6087 males (42.4%) were tested. The average number of specific IgE tests per patient was 12.3 ± 11.4. Total IgE increased after birth with age and reached a peak between 4–6 years in males and 10–12 years in females. Males had higher specific IgE for all common aeroallergens (house dust mite, birch, mugwort and timothy grass pollen) and food allergens (milk protein, chicken egg white, peanut, wheat flour, cod) except for cat epithelia. Data closely reflected results of population-based studies in the literature.

Conclusion

This study shows that, despite potential patient and test selection bias, the results of the quantitative IgE-dataset analysis closely reflect results of population-based data. Thus, as large cohorts can be examined with a minute amount of effort, this surrogate method appears promising to supplement epidemiology research.

Download PDF