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\begin{document}

\title{Association between beta 2 adrenergic receptor genetic polymorphisms and
salbutamol responsiveness in asthmatic patients: a meta-analysis}



\author[1]{Yuanmin Jia}%
\author[2]{Haixia  Wang}%
\author[2]{Mo Yi}%
\author[2]{Yizhang Li}%
\author[2]{Chenxiao Bai}%
\author[2]{Di Jiang}%
\author[2]{Ou  Chen}%
\affil[1]{Shandong University}%
\affil[2]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 22, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Aim: There are inter-individual variations in the impact of the Beta-2
adrenergic receptor (ADRB2) polymorphisms on salbutamol response in
asthmatic patients. We performed this meta-analysis to investigate the
relationship between ADRB2 Arg16Gly and Gln27Glu polymorphisms and
salbutamol responsiveness. Methods: Eight cyber databases (PubMed,
EMbase, Web of Science, The Cochrane Library, CBM, CNKI, WanFang Date
and VIP) were searched to select eligible studies until August 2020.
Odds ratio (OR) and 95\% confidence interval (CI) were calculated to
assess the strength of the association. Results: According to the
inclusion and exclusion criteria, eight studies involving 894 patients
were recruited. There was a clear relationship between the Arg16Gly
polymorphism and salbutamol response {[}AG vs. AA: OR=1.470, 95\%CI
(1.046, 2.066), P=0.026; GG+AA vs. AG: OR=0.668, 95\%CI (0.502, 0.889),
P=0.006{]}. Stratified analysis by age revealed significant association
in adult asthmatics {[}AG vs. AA: OR=1.894, 95\%CI (1.262, 2.843),
P=0.002; GG+AA vs. AG: OR=0.597, 95\%CI (0.426, 0.837), P=0.003{]}.
Caucasian and Asian patients with the AG genotype showed a good response
to salbutamol compared to those with the GG+AA or AA genotypes,
respectively. However, the association among the Gln27Glu polymorphism
and salbutamol response was not significant. Conclusions: The findings
suggest that the ADRB2 gene Arg16Gly polymorphism may predict salbutamol
responsiveness in asthmatic patients. The patients with the AG genotype
are likely to show a greater response to salbutamol in comparison to
those with the AA or GG+AA genotypes, especially in adult asthmatics.
There may be no association between the Gln27Glu polymorphism and
salbutamol response.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Asthma is a chronic inflammatory disorder with a multifactorial etiology
characterized by recurrent episodes of coughing, wheezing and dyspnea.
Asthma is a polygenic disease with complex gene-environment
interactions\textsuperscript{{[}1{]}}. Currently, about 300 million
people are affected by asthma worldwide of which about 250 000 people
die per year\textsuperscript{{[}2, 3{]}}. The prevalence of asthma
varies from 0.2 to 21.0\% around the world \textsuperscript{{[}3{]}}.

Global Initiative for Asthma (GINA) guidelines recommended inhaled
\selectlanguage{greek}β\selectlanguage{english}2-agonists as the first-line rescue treatment for managing acute
asthma\textsuperscript{{[}4{]}}. Short-acting beta-2 agonists (SABA),
the most effective and widely used bronchodilators presently, are the
primary options for treating acute exacerbations. Salbutamol, one of the
representative drugs of SABA, is an effective medicine to relieve
asthma. However, there are considerable differences in clinical response
to inhaled SABA and 70-80\% of the significant heterogeneity can be due
to differences in genetic basis \textsuperscript{{[}5{]}}. In addition,
significant variability has been observed in salbutamol response.
Genetic mutations can explain a considerable portion of this variation
and the Beta-2 adrenergic receptor (\emph{ADRB2} ) may be a significant
determinant of salbutamol responsiveness \textsuperscript{{[}5-7{]}}.

\emph{ADRB2} gene is an intronless gene located on human chromosome
5q31-32 encoding for the Beta 2 adrenergic receptor (ADRB2)--- the
molecular target for beta-2 agonists. Beta-2 agonists selectively bind
to ADRB2 within the cell membrane and relax airway smooth
muscle\textsuperscript{{[}8{]}}. At least 80 single nucleotide
polymorphisms (SNPs) in the \emph{ADRB2} (such as Arg16Gly, Gln27Glu,
Val34Met and Thr164Ile, etc.) have been identified after being
resequenced in multiple populations \textsuperscript{{[}9, 10{]}}.
Arg16Gly (rs1042713, A285G) at nucleotide position 46 and Gln27Glu
(rs1042714, C318G) at nucleotide position 79 have been extensively
studied among these SNPs and well described in asthma pharmacogenetics
\textsuperscript{{[}11, 12{]}}. These \emph{ADRB2} mutations change at
the \emph{ADRB2} amino acids sequence and alter receptor function, that
may lead to the significant variability in the response to
salbutamol\textsuperscript{{[}9{]}}. Several previous association
studies have investigated the relationship between \emph{ADRB2}
polymorphisms (Arg16Gly, Gln27Glu) and salbutamol responsiveness in
asthmatic patients. However, the results are conflicting among different
studies\textsuperscript{{[}13-20{]}}.

Thus, we conducted this meta-analysis to comprehensively investigate the
effect of the \emph{ADRB2} polymorphisms (Arg16Gly, Gln27Glu) on
salbutamol response in asthmatic patients. Then we can identify
individuals who are more likely to respond well to salbutamol and this
will provide evidence for personalized or precision treatment for asthma
improving the effectiveness of the management of asthma.

\textbf{Materials and Methods}

\textbf{Literature search strategy}

Meta-analysis was performed according to the Preferred Reporting Items
for Systematic Reviews and Meta-Analyses (PRISMA)
guidelines\textsuperscript{{[}21{]}}. We searched PubMed, EMbase, Web of
Science, The Cochrane Library, CBM, CNKI, WanFang Date and VIP from
establishment to August 2020. The search strategy included a combination
of subjects and words as follows: (`asthma') AND (`albuterol' OR
`salbutamol') AND (`Receptors, Adrenergic, beta-2' OR `\emph{ADRB2} ' OR
`adrenergic receptor' OR `Beta 2 Adrenergic Receptors' OR `Receptors,
beta-2 Adrenergic' OR `Receptors, beta 2 Adrenergic' ) AND
(`polymorphism' OR `SNP' OR `variation' OR `variant' OR `mutation'). To
find previously unconfirmed studies, we also searched references cited
in the relevant articles manually. The search results were limited to
human.

\textbf{Study selection}

The studies we included have to satisfy the inclusion criteria, as
follows: (1) observational studies; (2) studies evaluated the
relationship among \emph{ADRB2} polymorphisms (Arg16Gly, Gln27Glu) and
salbutamol responsiveness in asthmatic patients; (3) studies offered
valid data for calculating odds ratio (OR) and 95\% confidence interval
(CI); (4) studies reported short-term differences in the percentage
change in FEV\textsubscript{1} after salbutamol inhalation; and (5)
human subjects. The following studies were excluded: (1) studies
contained duplicate or unqualified data; (2) review, commentary,
abstract, editorial, case report, letter and conference report; and (3)
studies did not report the details for the assessment of good
responders.

\textbf{Quality assessment}

Two independent reviewers conducted the methodological quality
assessment of each study according to the quality of genetic studies
(Q-Genie) tool which was developed by Sohani \emph{et
al.}\textsuperscript{22} in 2015 and subsequently validated. This tool
consists of 11 items scored on a 7-point Likert scale specifically
applicable to the quality assessment of published genetic association
studies \textsuperscript{{[}22, 23{]}}. In studies without control
groups, scores [?]32 indicate poor quality studies, 33-40 indicate
moderate quality studies, and \textgreater{}40 indicate good quality
studies. For studies with control groups, scores for the parameters
listed above are [?]35, 36-45, and \textgreater{}45,
respectively\textsuperscript{{[}22{]}}.

\textbf{Data extraction}

Two independent reviewers extracted the related information. The raw
data of interest included name of the first author, publication year,
country, ethnicity, age, salbutamol dose, genotyping method, genotype
frequency distributions.

\textbf{Statistical analysis}

Data analysis was conducted using STATA 15.0 (StataCorp, College
Station, TX, USA) software. Six genetic models were analysed, as for
Arg16Gly polymorphism, namely, the dominant model (GG+AG vs. AA),
recessive model (GG vs. AG+AA), allele model (G vs. A), homozygous model
(GG vs. AA), heterozygous model (AG vs. AA) and additive model (GG+AA
vs. AG). We tested whether genotypic frequencies fall within the
Hardy-Weinberg equilibrium (HWE) by the Chi-square test. The impact
of\emph{ADRB2} polymorphisms (including Arg16Gly ,Gln27Glu) on the
response to salbutamol in asthmatic patients was measured by odds ratio
(OR) and 95\% confidence interval (CI). The chi-square-based Cochran's
Q-test and Higgins (I\textsuperscript{2}) statistics were used to assess
heterogeneity among studies. The random effects model was adopted in
case of evident heterogeneity (\emph{P} \textsubscript{H}\textless{}0.10
or I\textsuperscript{2}\textgreater{}50\%). If no obvious heterogeneity
existed, the fixed effects model was applied (\emph{P}
\textsubscript{H}[?]0.10 and I\textsuperscript{2}[?]50\%). To address
significant heterogeneity, subgroup analysis and Galbraith plot analysis
\textsuperscript{{[}24{]}} were carried out. Subgroup analyses were
performed by age (adult vs. children) and ethnicity (Caucasian vs.
Asian). Sensitivity analysis was conducted by removing the study
deviating from HWE. To evaluate the robustness of these results,
sensitivity analysis was also employed by omitting one study at a time.
Publication bias was assessed according to the asymmetry of the funnel
plot. Begg's and Egger's tests \textsuperscript{{[}25{]}} were also
performed to evaluate publication bias and \emph{P} \textless{}0.05 was
interpreted as statistically significant.

\textbf{Results}

\textbf{Study characteristics}

With the searching strategy, 282 potentially relevant publications were
initially retrieved. After removing duplicates and screening the titles
and abstracts, we obtained 49 articles. Then we reviewed the full texts,
and eight eligible studies were identified. Figure 1 shows the flowchart
of the study selection. Eight studies
\textsuperscript{{[}13-20{]}}focused on the \emph{ADRB2} Arg16Gly
polymorphism involving 524 good responders and 370 poor responders to
salbutamol. As for the\emph{ADRB2} Gln27Glu polymorphism, five
articles\textsuperscript{{[}13, 16, 17, 19, 20{]}} were included with
171 good responders and 125 poor responders. Five studies
\textsuperscript{{[}13, 15-18{]}} included adult asthmatics, three
studies\textsuperscript{{[}14, 19, 20{]}} evaluated asthmatic children.
Five studies \textsuperscript{{[}14-16, 18, 19{]}} focused on Asian
populations, and three studies \textsuperscript{{[}13, 17, 20{]}}focused
on Caucasian populations. The characteristics of the involved studies
and HWE examination results are summarized in Table 1. The quality
evaluation was carried out using the Q-Genie tool. According to the
criteria for studies without control group, seven
articles\textsuperscript{{[}13-19{]}} were of ``good quality'' and
one\textsuperscript{{[}20{]}} presented ``moderate quality'' (Table 1).

\textbf{Overall findings}

One SNP, Arg16Gly, significant association and low heterogeneity were
found between Arg16Gly polymorphism and salbutamol response in two
models: heterozygous model (OR=1.470, 95\% CI: 1.046-2.066,\emph{P}
=0.026, I\textsuperscript{2}=38.6\%,\emph{P} \textsubscript{H}=0.122;
Table 2 \& Figure 2.5); and additive model (OR=0.668, 95\% CI:
0.502-0.889, \emph{P} =0.006, I\textsuperscript{2}=0.0\%, \emph{P}
\textsubscript{H}=0.470; Table 2 \& Figure 2.6). This indicated that the
patients with the AG genotype may be associated with a better response
to salbutamol in comparison to those with the AA or GG+AA genotypes.
However, statistically evident heterogeneity and non-significant
association were detected in the dominant, recessive, allele and
homozygous models (all \emph{P} -value for OR\textgreater{}0.05). Thus,
it is needed to perform further subgroup analysis and identify the
sources of heterogeneity.

Concerning the \emph{ADRB2} Gln27Glu polymorphism, non-significant
association with salbutamol response was found in any models
(all\emph{P} -value for OR\textgreater{}0.05) (Table 3 \& Figure 3). In
addition, no evidence of heterogeneity was detected between studies
under five models (dominant model: I\textsuperscript{2}=35.2\%,\emph{P}
\textsubscript{H}=0.186; recessive model: I\textsuperscript{2}=34.9\%,
\emph{P} \textsubscript{H}=0.189, homozygous model:
I\textsuperscript{2}=47.7\%, \emph{P} \textsubscript{H}=0.105;
heterozygous model: I\textsuperscript{2}=0.0\%,\emph{P}
\textsubscript{H}=0.452; and additive: I\textsuperscript{2}=0.0\%,
\emph{P} \textsubscript{H}=0.776), but not the allelic model
(I\textsuperscript{2}\textgreater{}50\%,\emph{P}
\textsubscript{H}\textless{}0.1). (Table 3)

\textbf{Subgroup analysis}

We performed stratified analyses mainly according to age and ethnicity.
Subgroup analysis by age indicated a significant relationship
among\emph{ADRB2} Arg16Gly polymorphism and salbutamol response in adult
asthmatics {[}AG vs. AA: OR=1.894, 95\% CI: 1.262-2.843, \emph{P}
=0.002, I\textsuperscript{2}=22.1\%, \emph{P} \textsubscript{H}=0.274;
GG+AA vs. AG: OR=0.597, 95\% CI: 0.426-0.837, \emph{P} =0.003,
I\textsuperscript{2}=21.6\%, \emph{P} \textsubscript{H}=0.277{]}.
However, this relationship disappeared in asthmatic children (Table 2).

When studies were stratified by ethnicity, in Caucasian populations,
patients with the AG genotype compared to the GG+AA genotypes showed a
good response to salbutamol {[}GG+AA vs. AG: OR=0.380, 95\%CI (0.198,
0.728), \emph{P} =0.004, I\textsuperscript{2}=25.8\%,\emph{P}
\textsubscript{H}=0.260{]}. In Asian populations, patients with the AG
genotype compared to the AA genotype were associated with a better
response to salbutamol {[}AG vs. AA: OR=1.472, 95\%CI (1.018, 2.128),
\emph{P} =0.040, I\textsuperscript{2}=29.0\%,\emph{P}
\textsubscript{H}=0.228{]} (data not shown). Concerning the\emph{ADRB2}
Gln27Glu polymorphism, no effect on the response to salbutamol was
observed when studies were stratified by age or ethnicity under any
genetic models (Table 3).

\textbf{Heterogeneity analysis}

For the \emph{ADRB2} Arg16Gly polymorphism, the heterogeneity remained
high in the dominant, recessive, allele and homozygous models. To
further identify the sources of heterogeneity, Galbraith plots were
generated in four genetic models. Galbraith plot analysis identified one
outlier \textsuperscript{{[}18{]}} that was outside the CI in the
dominant model, and two \textsuperscript{{[}13, 18{]}} in the recessive,
allele and homozygous models which might contribute to the high
heterogeneity (Figure 4). After removing these outliers, the
heterogeneity was significantly reduced. However, the relationship
between Arg16Gly polymorphism and salbutamol responsiveness in these
genetic models was still non-significant: dominant model (OR=1.166, 95\%
CI: 0.850-1.601, \emph{P} =0.341, I\textsuperscript{2}=49.7\%,\emph{P}
\textsubscript{H}=0.063); recessive model (OR=0.887, 95\% CI:
0.632-1.246, \emph{P} =0.490, I\textsuperscript{2}=0.00\%,\emph{P}
\textsubscript{H}=0.631); allele model (OR=1.062, 95\% CI: 0.858-1.314,
\emph{P} =0.580, I\textsuperscript{2}=32.0\%,\emph{P}
\textsubscript{H}=0.196) and additive model (OR=1.089, 95\% CI:
0.736-1.612, \emph{P} =0.671, I\textsuperscript{2}=42.3\%,\emph{P}
\textsubscript{H}=0.123).

\textbf{Sensitivity analysis \& publication bias}

Sensitivity analyses were conducted through omitting one study at a
time. We also conducted sensitivity analysis by removing the study
deviating from HWE. No material changes of the pooled ORs were found
after omitting any single study or the HWE-violating
study\textsuperscript{{[}15{]}} in all genetic models for Arg16Gly
polymorphism and in dominant, heterozygous and additive models for
Gln27Glu polymorphism. However, as for Gln27Glu polymorphism, the
corresponding pooled ORs were considerably changed after deleting a
single study \textsuperscript{{[}17{]}} at a time in the recessive model
(OR=0.348, 95\% CI: 0.093-1.308, \emph{P} =0.118), allele model
(OR=0.700, 95\% CI: 0.428-1.145, \emph{P} =0.155) and homozygous model
(OR=0.334, 95\% CI: 0.087-1.288, \emph{P} =0.111). Egger's test and
Egger's test were performed to detect the possibility of publication
bias. The results demonstrated that publication bias under any genetic
models was inapparent (data not shown). The funnel plots showed no
obvious asymmetries (Figure 5).

\textbf{Discussion}

The treatment options for asthma have substantially increased.
Presently, inhaled beta 2 adrenergic receptor agonists, inhaled
corticosteroids, leukotriene modifiers, inhaled anticholinergics,
theophylline, and immunosuppressive agents are the most common medicines
for the treatment of asthma \textsuperscript{{[}26{]}}. With the
development of small molecule therapy and various biological agents,
biologic therapies such as genetic therapy will play an important role
in treating asthma \textsuperscript{{[}26{]}}. Among these, short-acting
beta-2 agonists (SABA) are the primary choices for the therapy of acute
asthma \textsuperscript{{[}14, 27{]}}. SABA selectively bind to and
activate ADRB2 within the cell membrane and relax airway smooth muscle,
dilate the bronchi and improve airflow achieving remission of
symptoms\textsuperscript{{[}28{]}}.

However, there is considerable variability in inhaled SABA
responsiveness, 70-80\% of this can be due to differences in genetic
basis \textsuperscript{{[}5{]}}, and part of the variability may also be
explained by poor compliance, irregular medication and incorrect drug
selection etc \textsuperscript{{[}29{]}}. Many pharmacogenetics and
pharmacogenomics studies \textsuperscript{{[}26, 30{]}} have been
performed for assessing the association between candidate genes and the
response to SABA. A significant heterogeneity has been observed in
response to salbutamol \textsuperscript{{[}31{]}}, and \emph{ADRB2} gene
could be responsible for this which was cloned by Kobilka \emph{et
al.}\textsuperscript{{[}32{]}} in 1987 located on human chromosome
5q31-32, a region that may be linked with asthma and atopy. The
\emph{ADRB2}polymorphisms change the \emph{ADRB2} amino acids sequence
and may alter receptor function leading to the individual variability in
response to salbutamol \textsuperscript{{[}9{]}}.

Predicting patients who are likely to respond well to salbutamol will be
significant to the further development of personalized treatment. A
number of studies \textsuperscript{{[}13, 20{]}} have evaluated the
relationship between \emph{ADRB2} polymorphisms (Arg16Gly, Gln27Glu) and
salbutamol response. However, the results of these studies are
contradictory, probably contributed by ethnic and environmental
differences and the varying clinical management methods between
countries.

Thus, we conducted a meta-analysis to further quantitatively investigate
the effect of the \emph{ADRB2} polymorphisms (Arg16Gly, Gln27Glu) on
salbutamol responsiveness. Considering different age groups might affect
salbutamol responsiveness and ethnicity may be one of the factors
leading to different distribution of genetic
polymorphism\textsuperscript{{[}33-35{]}}, we performed subgroup
analyses according to age and ethnicity. We observed that as for
Arg16Gly polymorphism the patients especially in adult asthmatics with
the AG genotype in comparison with the AA or GG+AA genotypes had a
better response to salbutamol, which indicated that salbutamol may be
more effective for patients with the AG genotype. The findings are
consistent with the study performed by Mohamed-Hussein \emph{et
al.}\textsuperscript{{[}13{]}} which revealed that 75\% of patients with
the AG genotype were positive responders, and 81\% of patients carrying
the GG genotype were poor responders. Similar to these results,
Teller\selectlanguage{ngerman}ía\emph{et al.} \textsuperscript{{[}17{]}} demonstrated that G
allele carriers and especially patients with the AG genotype were
overrepresented among subjects with good responses, while patients with
the A allele were more likely to represent in the group with
tachyphylaxis. In addition, Martinez \emph{et
al.}\textsuperscript{{[}20{]}} revealed that compared to those with the
GG genotype, patients carrying the AG genotype were 2.3 times more
likely to response to salbutamol, whereas contrary to our results,
patients with the AA genotype were 5.3 times more likely to have a good
response.

However, our conclusions are inconsistent with the findings showed in
the previous meta-analysis performed by Finkelstein \emph{et al} in
2009\textsuperscript{{[}36{]}}, demonstrating that patients with the AA
genotype at Arg16Gly polymorphism had a positive response to salbutamol
compared to those with the AG or GG genotypes. There may be the
following reasons: we excluded one study
\textsuperscript{{[}7{]}}selected in the previous meta-analysis but
might not meet the quality criteria of the Q-Genie tool which was used
in this study; included more studies up to August 2020 and applied more
genetic models appropriately. Consistent with the previous meta-analysis
\textsuperscript{{[}36{]}}, our findings indicated no effect of the
Gln27Glu polymorphism on salbutamol responsiveness.

Some limitations still exist in this meta-analysis: (1) Our study mainly
focused on the most common variants (Arg16Gly, Gln27Glu), other
polymorphisms that have also been studied in the \emph{ADRB2}
gene\textsuperscript{{[}26, 37, 38{]}} could be reported to evaluate the
genetic effect of \emph{ADRB2} on salbutamol response; (2) The number of
articles included in this study and the sample size particularly for the
Gln27Glu polymorphism are relatively small. Thus if more datasets are
available, renewed analyses could be considered; and (3) Our research
was based on dichotomous data, while continuous outcomes showing the
percentage change in FEV\textsubscript{1} before and after salbutamol
inhalation were not collected.

\textbf{Conclusion}

Our findings suggest that the \emph{ADRB2} gene Arg16Gly polymorphism
may be a reliable predictor of the response to salbutamol in asthmatic
patients. While, we found no valid evidence to support the effect of the
Gln27Glu polymorphism on salbutamol responsiveness. These findings could
contribute to the development of individualized treatment and improve
the effectiveness of the management of asthma. However, we have to
acknowledge the limited power of our study. Therefore, we call for more
well-designed studies with larger sample size to accurately verify the
relationship among \emph{ADRB2} polymorphisms and salbutamol response in
asthmatic patients.

\selectlanguage{english}\textbf{Conflict of interest:} The authors declare that they have no
known competing financial interests or personal relationships.

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\textbf{Table 1.} Summary of articles included in this meta-analysis.\selectlanguage{english}
\begin{longtable}[]{@{}llllllllllllllllll@{}}
\toprule
Study,year & Country & Ethnicity & Age group & Salbutamol dose(\selectlanguage{greek}μ\selectlanguage{english}g) & &
Genotyping method & Good responders & Good responders & Good responders
& Good responders & Poor responders & Poor responders & Poor responders
& Poor responders & HWE(\emph{P}) & Q-Genie & Q-Genie\tabularnewline
\midrule
\endhead
Arg16Gly & Arg16Gly & Arg16Gly & Arg16Gly & Arg16Gly & Arg16Gly &
Arg16Gly & Total & AA & AG & GG & Total & AA & AG & GG & &
&\tabularnewline
Aliae Hussein, 2018 \textsuperscript{13} & Egypt & Caucasian & Adult &
200 & & TaqMan & 32 & 7 & 21 & 4 & 26 & 2 & 7 & 17 & 0.350 & 0.350 &
41\tabularnewline
Sahi PK, 2016 \textsuperscript{14} & India & Asian & Children & 600 & &
PCR- RFLP & 51 & 14 & 27 & 10 & 69 & 15 & 35 & 19 & 0.063 & 0.063 &
48\tabularnewline
Bandaru S, 2015 \textsuperscript{15} & India & Asian & Adult & 200 & &
ARMS-PCR & 261 & 87 & 90 & 84 & 137 & 57 & 38 & 42 & 0.000 & 0.000 &
46\tabularnewline
Shah NJ, 2015 \textsuperscript{16} & India & Asian & Adult & 5000 & &
TaqMan & 23 & 5 & 13 & 5 & 23 & 7 & 11 & 5 & 0.174 & 0.174 &
52\tabularnewline
Teller\selectlanguage{ngerman}ía JJ, 2005 \textsuperscript{17} & Spain & Caucasian & Adult & 400
& & PCR- RFLP & 57 & 6 & 34 & 17 & 23 & 7 & 9 & 7 & 0.302 & 0.302 &
45\tabularnewline
Kukreti R, 2005 \textsuperscript{18} & India & Asian & Adult & 200 & &
SNaPshot & 41 & 3 & 27 & 11 & 39 & 13 & 22 & 4 & 0.231 & 0.231 &
51\tabularnewline
Fu J, 2002 \textsuperscript{19} & China & Asian & Children & NA & & PCR-
RFLP & 49 & 15 & 31 & 3 & 25 & 7 & 15 & 3 & 0.247 & 0.247 &
47\tabularnewline
Martinez FD, 1997 \textsuperscript{20} & America & Caucasian & Children
& 180 & & PCR- RFLP & 10 & 3 & 5 & 2 & 28 & 2 & 13 & 13 & 0.604 & 0.604
& 39\tabularnewline
Gln27Glu & Gln27Glu & Gln27Glu & Gln27Glu & Gln27Glu & Gln27Glu &
Gln27Glu & Total & CC & CG & GG & Total & CC & CG & GG & &
&\tabularnewline
Aliae Hussein, 2018 \textsuperscript{13} & Egypt & Caucasian & Adult &
200 & & TaqMan & 32 & 18 & 13 & 1 & 26 & 12 & 11 & 3 & 0.394 & 0.394 &
41\tabularnewline
Shah NJ, 2015 \textsuperscript{16} & India & Asian & Adult & 5000 & &
TaqMan & 23 & 15 & 8 & 0 & 23 & 16 & 6 & 1 & 0.324 & 0.324 &
52\tabularnewline
Teller\selectlanguage{ngerman}ía JJ, 2005 \textsuperscript{17} & Spain & Caucasian & Adult & 400
& & PCR- RFLP & 57 & 15 & 29 & 13 & 23 & 12 & 10 & 1 & 0.390 & 0.390 &
45\tabularnewline
Fu J, 2002 \textsuperscript{19} & China & Asian & Children & NA & & PCR-
RFLP & 49 & 39 & 9 & 1 & 25 & 18 & 7 & 0 & 0.416 & 0.416 &
47\tabularnewline
Martinez FD, 1997 \textsuperscript{20} & America & Caucasian & Children
& 180 & & PCR- RFLP & 10 & 5 & 5 & 0 & 28 & 11 & 12 & 5 & 0.591 & 0.591
& 39\tabularnewline
\bottomrule
\end{longtable}

ARMS: amplification refractory mutation system; FEV\textsubscript{1}:
forced expiratory volume in 1st second; HWE: Hardy-Weinberg equilibriu;
NA: relative data were not available; PCR: polymerase chain reaction;
Q-genie tool: Quality of genetic association studies; RFLP: restriction
fragment length polymorphism.

\textbf{Table 2.} Meta-analysis of association among Arg16Gly
polymorphism and salbutamol responsiveness.\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
Subgroup/n & Genetic~model & Analysis model & OR & 95\%CI &
\emph{P}-value(OR) & I\textsuperscript{2} &
\emph{P}-value(H)\tabularnewline
\midrule
\endhead
Overall/8 & GG+AG vs. AA & R & 1.218 & 0.666-2.228 & 0.521 & 0.600 &
0.014\tabularnewline
& GG vs. AG+AA & R & 0.680 & 0.352-1.315 & 0.252 & 0.663 &
0.004\tabularnewline
& G vs. A & R & 0.912 & 0.590-1.410 & 0.679 & 0.743 &
0.000\tabularnewline
& GG vs. AA & R & 0.878 & 0.359-2.147 & 0.776 & 0.714 &
0.001\tabularnewline
& AG vs. AA & F & 1.470 & 1.046-2.066 & 0.026 & 0.386 &
0.122\tabularnewline
& GG+AA vs. AG & F & 0.668 & 0.502-0.889 & 0.006 & 0.000 &
0.470\tabularnewline
Adult/5 & GG+AG vs. AA & R & 1.821 & 0.834-3.979 & 0.133 & 0.600 &
0.041\tabularnewline
& GG vs. AG+AA & R & 0.792 & 0.302-2.075 & 0.635 & 0.779 &
0.001\tabularnewline
& G vs. A & R & 1.068 & 0.575-1.984 & 0.835 & 0.807 &
0.000\tabularnewline
& GG vs. AA & R & 1.417 & 0.422-4.760 & 0.573 & 0.763 &
0.002\tabularnewline
& AG vs. AA & F & 1.894 & 1.262-2.843 & 0.002 & 0.221 &
0.274\tabularnewline
& GG+AA vs. AG & F & 0.597 & 0.426-0.837 & 0.003 & 0.216 &
0.277\tabularnewline
Children/3 & GG+AG vs. AA & R & 0.679 & 0.362-1.271 & 0.226 & 0.005 &
0.366\tabularnewline
& GG vs. AG+AA & R & 0.533 & 0.263-1.078 & 0.080 & 0.000 &
0.711\tabularnewline
& G vs. A & R & 0.732 & 0.489-1.098 & 0.131 & 0.063 &
0.344\tabularnewline
& GG vs. AA & R & 0.431 & 0.184-1.010 & 0.053 & 0.000 &
0.424\tabularnewline
& AG vs. AA & F & 0.777 & 0.406-1.487 & 0.447 & 0.000 &
0.528\tabularnewline
& GG+AA vs. AG & F & 0.895 & 0.520-1.538 & 0.688 & 0.000 &
0.996\tabularnewline
\bottomrule
\end{longtable}

F: Fixed effects model; R: Random effects model; OR: Odds ratio; CI:
confidence interval; \emph{P} -value(H): \emph{P} -value for
heterogeneity; \emph{P} -value(OR): \emph{P} -value for OR.

\textbf{Table 3.} Meta-analysis of association among Gln27Glu
polymorphism and salbutamol responsiveness.\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
Subgroup/n & Genetic~model & Analysis model & OR & 95\%CI &
\emph{P}-value(OR) & I\textsuperscript{2} &
\emph{P}-value(H)\tabularnewline
\midrule
\endhead
Overall/5 & GG+CG vs. CC & F & 1.085 & 0.657-1.793 & 0.750 & 0.352 &
0.186\tabularnewline
& GG vs. CG+CC & F & 1.076 & 0.440-2.630 & 0.873 & 0.349 &
0.189\tabularnewline
& G vs. C & R & 0.971 & 0.514-1.835 & 0.928 & 0.560 &
0.059\tabularnewline
& GG vs. CC & F & 1.194 & 0.482-2.958 & 0.702 & 0.477 &
0.105\tabularnewline
& CG vs. CC & F & 1.103 & 0.655-1.857 & 0.711 & 0.000 &
0.452\tabularnewline
& GG+CC vs. CG & F & 0.941 & 0.566-1.565 & 0.815 & 0.000 &
0.776\tabularnewline
Adult/3 & GG+CG vs. CC & F & 1.379 & 0.747-2.543 & 0.304 & 0.535 &
0.116\tabularnewline
& GG vs. CG+CC & F & 1.456 & 0.499-4.253 & 0.492 & 0.602 &
0.081\tabularnewline
& G vs. C & R & 1.212 & 0.484-3.037 & 0.682 & 0.699 &
0.036\tabularnewline
& GG vs. CC & F & 1.668 & 0.569-4.888 & 0.351 & 0.685 &
0.042\tabularnewline
& CG vs. CC & F & 1.386 & 0.730-2.632 & 0.318 & 0.000 &
0.373\tabularnewline
& GG+CC vs. CG & F & 0.821 & 0.442-1.528 & 0.534 & 0.000 &
0.819\tabularnewline
Children/2 & GG+CG vs. CC & F & 0.655 & 0.270-1.586 & 0.348 & 0.000 &
0.984\tabularnewline
& GG vs. CG+CC & F & 0.452 & 0.070-2.937 & 0.406 & 0.000 &
0.357\tabularnewline
& G vs. C & R & 0.648 & 0.303-1.386 & 0.264 & 0.000 &
0.599\tabularnewline
& GG vs. CC & F & 0.433 & 0.064-2.955 & 0.393 & 0.000 &
0.377\tabularnewline
& CG vs. CC & F & 0.699 & 0.284-1.724 & 0.437 & 0.000 &
0.648\tabularnewline
& GG+CC vs. CG & F & 1.249 & 0.512-3.045 & 0.625 & 0.000 &
0.373\tabularnewline
\bottomrule
\end{longtable}

F: Fixed effects model; R: Random effects model; OR: Odds ratio; CI:
confidence interval; \emph{P} -value(H): \emph{P} -value for
heterogeneity; \emph{P} -value(OR): \emph{P} -value for OR.

\textbf{Figure Legends:}

\textbf{Figure 1.} Flowchart of the study selection.

\textbf{Figure 2.} Forest plots showing the genetic impact of Arg16Gly
polymorphism on salbutamol response. A. Dominant model (GG+AG vs. AA);
B.recessive model (GG vs. AG+AA); C.allele model (G vs. A); D.homozygous
model (GG vs. AA); E.heterozygous model (AG vs. AA); F.additive model
(GG+AA vs. AG); OR: Odds ratio; CI: confidence interval; Weight: weight
of each study.

\textbf{Figure 3.} Forest plots showing the genetic impact of Gln27Glu
polymorphism on salbutamol response. A. Dominant model (GG+CG vs. CC);
B.recessive model (GG vs. CG+CC); C.allele model (G vs. C); D.homozygous
model (GG vs. CC); E.heterozygous model (CG vs. CC); F.additive model
(GG+CC vs. CG); OR: Odds ratio; CI: confidence interval; Weight: weight
of each study.

\textbf{Figure 4.} Galbraith plot of the Arg16Gly polymorphism and
salbutamol response. A. Dominant model (GG+AG vs. AA); B.recessive model
(GG vs. AG+AA); C.allele model (G vs. A); D.homozygous model (GG vs.
AA).

\textbf{Figure 5.} Funnel plots for the studies selected in the
meta-analyses under the dominant model. A. Arg16Gly polymorphism; B.
Gln27Glu polymorphism.

\selectlanguage{english}
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\end{document}

