DISCUSSION
In the current study, meta-analysis indicated an increased risk of T1DM
in children with asthma, but not increased risk for asthma in children
with T1DM. However, strong heterogeneity among the included studies was
noted. Subgroup analysis, meta-regression, and sensitivity analysis
failed to identify the sources of heterogeneity.
The results of MR analysis were not completely consistent with that of
the meta-analysis. Specifically, children with asthma had higher risk of
T1DM, whereas children with T1DM had lower risk of asthma. The
importance in sequential appearance of the two diseases was apparently
illustrates. However, in the majority of the included studies, it was
not clear whether an asthma diagnosis or symptoms preceded the T1DM
diagnosis, which could lead to reverse causality.27-38Only 3 cohort studies documented the sequence of disease occurrence, but
the results were still conflicting.6-8 The results of
MR analysis are consistent with a previous cohort study by Metsala et
al7. Similarly, Smew et al6indicated that childhood asthma was related to an increased risk of
subsequent T1DM, whereas T1DM was not associated with a decreased risk
of subsequent asthma. Hisiao et al8, however, reported
a markedly higher incidence of asthma in patients with T1DM in the Asian
population. It is important to note that the MR analysis data came from
European population. Whether the results of MR analysis in the current
study could be extrapolated to other populations remained unknown.
Both nurture (i.e. the environment) and nature (i.e. genetics)
contribute to the etiology of both asthma and T1DM. Asthma and T1DM tend
to be comorbid and congregate within families.6Siblings of children with one disease have higher risk of the other
disease.6 For example, TLR2 rs3804100 T allele has
been shown to be a susceptibility allele for both childhood asthma and
T1DM.39 In contrast, the T allele of rs9273349 and
rs1063355 in HLA-DQB1 seems to be a protective factor to both
diseases.16 Adding to the complexity, susceptibility
genes to one disease could be protective to the other disease. For
example, GIMAP5 SNP (rs6965571) has been associated with increased risk
for asthma but decreased risk for T1DM.40 Future GWAS
studies are required to better characterize the potential link between
them.41
At a mechanistic level, lower risk of asthma in children with T1DM could
be attributed to the anti-inflammatory properties of insulin. High
levels of insulin promote Airway smooth muscle (ASM) contraction,
enhance contractile responses to methacholine, which are likely to
result in increased airway hyperresponsiveness, bronchoconstriction, and
airway remodeling.42 Insulin deficiency in T1DM could
prevent airway remodeling.43 A recent study in a mouse
model for asthma showed that insulin deficiency could prevent the
development of allergic inflammation, eosinophilic pulmonary
infiltration, and airway hyperresponsiveness in an asthma mouse
model.44 These findings mainly explain the reduced
risk of asthma in patients with T1DM, but lacking mechanistic research
on the increased risk of T1DM in children with asthma. The use of some
anti-asthmatic drugs (inhaled corticosteroids and inhaled β-agonists)
was potentially associated with the risk of T1DM in a case-cohort study.
Therefore, future research is required to explore the underlying
biological mechanisms of this relationships.
MR analysis makes sense only when it uses IVs that are: (1) associated
with the exposure; (2) independent of factors confounding the
association of the exposure and outcome; and (3) associated with the
outcome only through exposure. With these premises, MR analysis can work
as an analogue to RCT, which is more plausible to identify causality
than observational analysis.45 To satisfy the first
assumption, we selected only SNPs with a genome-wide significant
association (P < 5*10-8) and the F statistic
at > 10.14 The second assumption is not
verifiable. To satisfy the third assumption, MR-Egger regression was
used to estimate horizontal pleiotropy.23 Since these
premises were fulfilled in our MR analysis, we believe that our findings
were reached with least likelihood of confounding effects and maximal
avoidance of reverse causality.
The meta-analysis in the current study has several limitations. First,
majority of the studies included in the analysis are of case-control
design; only three cohort studies were included. Second, due to the low
prevalence of T1DM, most included studies were based on T1DM and
considered asthma as potential risk factors. Third, there was
significant heterogeneity among the included studies, but we were unable
to identify the source of heterogeneity. The MR analysis also has
several important limitations. First, the MR analysis used only one
dataset, and lacks validation. Second, some of the SNPs (such as
rs4795399 and rs28407950) utilized in this study are potentially
correlated with confounding factors which may also influence the risk of
T1DM or childhood asthma. We were unable to completely rule out the
possible impact of pleiotropic effects on the findings. Third, the MR
analysis data came from European population only, and whether the
findings could be extrapolated to other populations remains unknown.