Discussion
In this population-based twin study, we disentangled the genetic and environmental sources of covariation between asthma and FENO by analysing the effect of blood eosinophils and allergen-specific IgE-level. More than half (54%) in the total covariance between FENO and asthma was due to genetically driven effects of the IgE level to airborne allergens. Thus, our results indicate that genetically driven allergen-specific IgE level, but not blood eosinophil counts, is part of the same underlying construct that creates significant correlation between asthma and FENO in schoolchildren.
This study provides further understanding of genetic influence from the allergen-specific IgE level on FENO in children with asthma. Complex genetic inheritance in asthma susceptibility has been reported, where more than one hundred genetic variants have been implicated 36. Although just a subset of these genetic variants has been replicated, the genetic contribution to the asthma and FENO association seems unclear 21. Genetic studies have found a link between FENO values and a few genetic loci 37,38 and the genetics of the IL-4/IL-13 pathway have been linked to IgE levels of childhood asthma39,40. Moreover, gene expression profiles relating to eosinophilic and T cell pathway have been shown to associate with total IgE levels in children with asthma 41. Thus, genetic variants have been linked to FENO, the allergen-specific IgE level, eosinophils and (allergic) asthma, but not all have been combined in a single study in humans. Here, we show that allergen-specific IgE level, highly impacts the asthma FENO association by a genetic component. This may give us a hint of including IgE-diagnostics when treating and managing asthma according to FENO-levels in the future.
Previous twin research on asthma phenotypes has applied bivariate modelling to their data 20,42-45, thereby separating the covariance of genetic and environmental determinants from two sources. Results within these bivariate studies point to a large extent of a common genetic background between asthma phenotypes42-45. Here, we include a multivariate modelling with four different sources to investigate whether they share common genetic and/or environmental origins. The advantage of using a multivariate over a bivariate model is that the relationships between several variables can be found simultaneously. Allergen-specific IgE level can be considered a cause of allergic asthma as it is early involved in the inflammatory process which also implicates an increase in eosinophils46. Here we found significant genetic influence from allergen-specific IgE level but not from eosinophils, indicating increasing FENO level reflect dominant type 2 asthma activated by inflammatory cytokines IL-4 and IL-13, but not IL-546. Interestingly, Thomsen et al. studied the covariance between FENO and total IgE and found that 93% of the phenotypic correlation could be explained by genetic factors44. Thus, previous results point to the fact that genetics play an important role in the allergic asthma phenotype. However, caution is warranted when generalizing our results to subjects other than children, since reports show an age-dependent interaction between sensitization and elevated eosinophil levels in asthma cases47.
The major strength of our study is that we used a population-based twin sample of children. We have also used reliable objective biomarkers and the asthma status was based on definitions from the ISAAC study48. Another strength of our study is that we included both a continuous and dichotomous IgE variable on sensitization to aeroallergens. This continuous measure enabled us to utilize all the information about the allergen-specific IgE level variable by maximizing the statistical power. Levels below 0.35kUA/L can provide additional prognostic information, since results have shown that children who show low sensitization (i.e., 0.10–0.34 kUA/L) to food allergens in infancy seem to have an increased probability of sensitization to aeroallergens in later life49. Furthermore, we adjusted for age, sex and ICS use and we re-weighted the analyses by sampling probability. We assumed that the tobacco use would be minor since of the age of the children, thus we did not include it as a covariate. Limitations include the inherently low power of the classical twin method to detect effects of a shared environment. This may partly explain the absence of shared environmental factors, C, even though we used a population-based twin sample. Factors that are shared within twin pairs, such as socio-economic status, that we not did control for, would end up as C in the models. One might further question the generalizability of the results from twin studies to the general population. Twins differ from singletons in that they are, on average, born smaller; however, we have previously shown that, after taking gestational age into account, twins are not at a higher risk of asthma 50.
Asthma is a complex disease characterized by a set of genetically heterogeneous phenotypes. As new phenotypes for asthma are discovered, twin studies provide a first effort in determining the contribution of genetic and environmental factors to these traits 51. We are not aware of any other studies that have estimated the proportion of covariance by genetic and environmental effects of inflammatory markers (i.e., allergen-specific IgE level and eosinophils) on the asthma vs. FENO association. The source of the high variability in individual FENO levels in asthmatics is largely unknown, but the present study results may give a partial explanation for this heterogeneity. Thus, the biological background of inflammation should be considered for future personalized medicine.