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.