Corresponding author: Seung-Ae Yang, College of Nursing, Sungshin Women's University, 55 Dobong-ro 76ga-gil, Gangbuk-gu, Seoul 142-732, Korea
Tel: +82-2-920-7728, E-mail: [email protected] Received May 15, 2013, Revised May 15, 2013
Accepted June 10, 2013
Association between Promoter Polymorphisms (rs1800925, −1055C/T and rs1881457, −1510A/C) of Interleukin 13 and Triglyceride
and Hypertension in Korean Population
College of Nursing, Sungshin Women's University, Seoul, Korea
Seung-Ae Yang
Interleukin 13 (IL13) is an immunoregulatory cytokine which may decrease immunologic activity and secretion of proinflammatory cytokines. Cytokines have been known to be modulators of metabolic syndrome and insulin resistance. Polymorphisms of IL13 affect various disease including dermatologic, respiratory diseases, and asthma, which are linked to features of obesity, which is an origin of many stress factors. In this study, we conducted genetic association between IL13 polymorphisms (rs1800925,
−1055C/T and rs1881457, −1510A/C) and dyslipidemia, hypertension, and obesity in a total of 265 subjects. The genotype of promoter SNP (rs1800925, −1055C/T) was associated to triglyceride (TG) level (codominant2 model, p=0.021; recessive model, p=0.022) and the genotypes and alleles of another promoter SNP (rs1881457, −1510A/C) were associated to hypertension (codominant2 model, p=0.013; recessive model, p=0.027; log-additive model, p=0.021; allele frequencies, p=0.017) and TG level (codominant2 model, p=0.021; recessive model, p=0.01). In conclusion, promoter polymorphisms (rs1800925 and rs1881457) of IL13 may be associated with the clinical features of metabolic syndrome patients, specially TG and hypertension. (Korean J
Str Res 2013;21:159∼165)Key Words: Dyslipidemia, Hypertension, Interleukin 13, Obesity, Promoter, Polymorphism
INTRODUCTION
Interleukin (IL) 13 is immunoregulatory cytokine mainly secreted by T helper (Th) 2 cells. It affects B cell differentiation, IgE switching. It also promotes CD23 and MHC II expression. With such activities, it may regulate macrophage activity and inhibit secretion of inflammatory cytokines (Ingram et al., 2012). In the
basis of the physiological roles of IL13, it was mainly studied in the aspect of asthma. Asthma shows features including relation- ship with IgE and eosinophil (Arbes et al., 2013), which may be modulated by IL13 (Ingram et al., 2012). There have been reports that asthma and obesity are closely related (Dorevitch et al., 2013; Gullon et al., 2013; Pradeepan et al., 2013). Moreover, asthma is closely related with atopic diseases (Corren, 2013;
Gullon et al., 2013), and there was also a report that atopy is
related with obesity (Luo et al., 2013). Metabolic syndrome is
majorly described as background mechanism affecting obesity
(Aballay et al., 2013). Metabolic syndrome is classified by two of
following: hypertension, dyslipidemia, abdominal obesity, and type
2 diabetes or glucose intolerance (Aballay et al., 2013). Such
criteria of metabolic syndrome were come from the evolution of the term “prediabetes” characteristics, which was formerly known as Reaven’s Syndrome X (Aballay et al., 2013). The “prediabetes”
is a form of insulin intolerance, which occurs concomitantly with chronic inflammatory state mediated by proinflammatory cytokines in adipose tissues and liver (Goran et al., 2013).
IL13 was known to have immunoregulatory function, however, may be involved in the glucose metabolism (Machado et al., 2013). Such previous results may introduce the functions of IL13 in obesity. Although it has been regarded that lifestyle modifica- tion is effective way to resolve metabolic syndrome (Yamaoka et
al., 2013), there may be individual differences in the suscep-tibility to the status of metabolic syndrome, and such differences may be caused by polymorphisms. IL13 single nucleotide polymorphisms (SNPs) are associated with both atopy and diabetes (Maier et al., 2006) and colorectal cancer development (Sainz et al., 2012). In the basis of the previous results, it is suggested that IL13 polymorphisms may affect clinical features of metabolic syndrome.
In this study, we investigated whether there are differences in the effect of IL13 SNPs in the patients within clinical criteria of metabolic syndrome.
MATERIALS AND METHODS
1. Study subjects
The study subjects comprised of a total of 265 unrelated subjects who examined a general health check-up program. The biochemical characteristics including total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and fasting plasma glucose of subjects were tested using blood samples.
Subjects were divided in accordance with each biochemical measurements of subject. Normal criteria were following: (TC,
＜250 mg/dl; TG, ＜150 mg/dl; HDL-C, ＞45 mg/dl in male/
＞50 mg/dl in female; fasting plasma glucose, ＜126 mg/dl;
HBA1c (hemoglobinA1c), ＜6.5%; hypertension, ＜140 mmHg in SBP [systolic blood pressure]/ ＜90 mmHg in DBP [diastolic blood pressure]). And Abnormal criteria were following: (TC, ＞ 250 mg/dl; TG, ＞150 mg/dl; HDL-C, ＜45 mg/dl in male/
＜50 mg/dl in female; fasting plasma glucose, ＞126 mg/dl;
HBA1c, ＞6.5%; hypertension, ＞140 mmHg in SBP/ ＞90 mmHg in DBP). Subjects were divided into two subgroups, the overweight/obese group (BMI≥23) and the normal group (18
＜BMI＜23). Subjects with BMI (body mass index)＜18 were excluded in analysis. This study was approved by the ethics review committee of Medical Research Institute, School of Medicine, Kyung Hee University, Seoul, Republic of Korea. Our study was conducted according to the guidelines of the Helsinki Declaration. All subjects gave written informed consent
2. SNP genotyping
Peripheral bloods of all subjects were collected in EDTA.
Genomic DNAs were isolated from blood using QIAamp
ⓇDNA mini kit (QIAGEN, Valencia, CA, USA). We selected promoter SNPs of IL13 gene. Individual genotypes of the SNPs (rs1800 0925, −1055 C/T and rs1881457, −1510 A/C) were performed by direct sequencing (MACROGEN, Seoul, Republic of Korea).
Polymerase chain reaction (PCR) was conducted using the follo- wing set of primer: for rs1800925 (sense, 5’-CACACCCTTGTG AGGAGGTTGA-3’; antisense, 5’-CAGCCTTAGTCCAGGTCA GAGA-3’; product size, 388 bp) and rs1881457 (sense, 5’-GCC CATCTCCCGTTACATAAGG-3’; antisense, 5’-CCCACCCTCT CTGTCCACTCTC-3’; product size, 401 bp). Conditions of PCR were 40 cycles at 94
oC for 30 sec, 58
oC for 30 sec, 72
oC for 30 sec, and 1 cycle at 72
oC for 5 min for the final reaction. The PCR products were sequenced by an ABI PRISM 3730XL analyzer (PE Applied Biosystems, Foster City, CA, USA). For the genotype analysis, SeqManII software (DNASTAR, Madison, WI, USA) was used.
3. Statistical analysis
SNPStats (http://bioinfo.iconcologia.net/index.php) and SPSS
18.0 (SPSS Inc., Chicago, IL, USA) were used for genetic
association analysis. Logistic regression analysis adjusted for age
and sex was used to calculated odds ratio (OR), 95% confidence
interval (CI), and p value adjusted for age and gender as
covariables. Multiple logistic regression models (codominant1,
codominant2, dominant, recessive, and log-additive models) were
applied. The p value with below 0.05 was considered significant
association.
Table 1. Demographic and biochemical characteristics of study subjects.
Normal Abnormal
Age (mean±SD, years) Male/Female
TC n TG n HDL-C n
Fasting plasma glucose n
HBA1c n
Hypertension n
Overweigh/obese n
38.7±13.3 136/129
≤250 mg/dl
258
≤150 mg/dl 211
≥45 mg/dl in male, ≥50 mg/dl in female 201
≤126 mg/dl 255
≤6.5%
253
＜140 mmHg in SBP＜90 mmHg in DBP 217
18≤BMI≤23 kg/m2 125
＞250 mg/dl 7
＞150 mg/dl 54
＜45 mg/dl in male, ＜50 mg/dl in female 64
＞126 mg/dl 10
＞6.5%
12
≥140 mmHg in SBP ≥90 mmHg in DBP 48
BMI＞23 kg/m2 122
n: number of subjects, TC: total cholesterol, TG: triglyceride, HDL-C: high-density lipoprotein cholesterol, HBA1c: hemoglobin A1c, SBP: systolic blood pressure, DBP: diastolic blood pressure, BMI: body mass index.
Table 2. Genotype and allele frequencies of IL13 SNPs in according to TG.
SNP Type TG≤150 mg/dl TG＞150 mg/dl
Model OR (95% CI) p
n % n %
rs1800925
−1055C/T
rs1881457
−1510A/C
C/C C/T T/T
C T A/A A/C C/C
A C
142 64 5
348 74 104 89 16
297 121
67.3 30.3 2.4
82.5 17.5 49.8 42.6 7.7
71.1 28.9
32 16 6
80 28 25 19 10
69 39
59.3 29.6 11.1
74.1 25.9 46.3 35.2 18.5
63.9 36.1
Codominant1 Codominant2 Dominant Recessive Log-additive
Codominant1 Codominant2 Dominant Recessive Log-additive
1.07 (0.53∼2.18) 4.89 (1.27∼18.88) 1.35 (0.70∼2.61) 4.78 (1.26∼18.06) 1.56 (0.92∼2.65) 1
1.65 (1.00∼2.71) 0.79 (0.39∼1.61) 3.27 (1.20∼8.96) 1.09 (0.57∼2.07) 3.63 (1.39∼9.49) 1.42 (0.88∼2.29) 1
1.39 (0.89∼2.17)
0.85 0.021 0.37 0.022 0.10
0.05 0.52 0.021 0.79 0.01 0.16
0.15 SNP: single nucleotide polymorphism, TG: triglyceride, n: number of subjects, OR: odds ratio, CI: confidence interval.
RESULTS
The demographic and biochemical characteristics of subjects are shown in Table 1. The age of subjects (mean±standard deviation) was 38.7±13.3 years and the study subjects comprised 136 male and 129 female.
Firstly, we analyzed the correlation between TG and examined of SNPs IL13. Table 2 shows the genotype and allele frequencies of the two SNPs (rs1800925, −1055, C/T and rs1881457, −1510, A/C) in two groups according to the TG level (＜150 mg/dl and
＞150 mg/dl). The promoter SNP rs1800925 (−1055, C/T) was
associated with the TG level [OR=4.89, 95% CI=1.27∼18.88,
p=0.021 in codominant 2 model (C/C vs. T/T); OR=4.78, 95%
Table 3. Genotype and allele frequencies of IL13SNPs in two groups according to hypertension.
SNP Type Without hypertension With hypertension
Model OR (95% CI) p Fisher's
exact p
n % n %
rs1800925
−1055 C/T
rs1881457
−1510 A/C
C/C C/T T/T
C T A/A A/C C/C
A C
148 60 9
356 78 111 87 17
309 121
68.2 27.6 4.2
82.0 18.0 51.6 40.5 7.9
71.9 28.1
26 20 2
72 24 18 21 9
57 39
54.2 41.7 4.2
75.0 25.0 37.5 43.8 18.8
59.4 40.6
Codominant1 Codominant2 Dominant Recessive Log-additive
Codominant1 Codominant2 Dominant Recessive Log-additive
1.88 (0.96∼3.67) 1.01 (0.20∼5.16) 1.75 (0.92∼3.36) 0.80 (0.16∼4.00) 1.42 (0.84∼2.42) 1
1.52 (0.90∼2.57) 1.44 (0.71∼2.90) 3.53 (1.31∼9.52) 1.74 (0.91∼3.36) 2.95 (1.17∼7.42) 1.76 (1.09∼2.83) 1
1.75 (1.11∼2.76) 0.07 0.99 0.09 0.78 0.20
0.12 0.31 0.013 0.09 0.027 0.021 0.017
0.67
1.00
SNP: single nucleotide polymorphism, n: number of subjects, HDL-C: high-density lipoprotein cholesterol, OR: odds ratio, CI: confidence interval.
Table 4. Frequencies of haplotypes of IL13 SNPs in two groups according to hypertension.
Haplotype Frequency Without hypertension With hypertension
Chi square p
+ − + −
AC CT CC
0.694 0.192 0.114
310.7 78 45.3
123.3 356 388.7
57 24 15
39 72 81
5.525 2.498 2.102
0.0187 0.114 0.1471 The haplotypes were consisted of rs1881457 and rs1800925.
CI=1.26∼18.06, p=0.022 in recessive model (C/C and C/T vs.
T/T)]. T/T genotype frequency in the TG＞150 mg/dl group was higher than that of TG≤150 mg/dl group (11.1% vs 2.4%). The allele frequency did not show any differences. The promoter SNP rs1881457 (−1510, A/C) also was associated with the TG level [OR=3.27, 95% CI=1.20∼8.96, p=0.021 in codominant 2 model (A/A vs. A/C); OR=3.63, 95% CI=1.39∼9.49, p=0.01 in recessive model (A/A and A/C vs. C/C)]. C/C genotype frequency in the TG＞150 mg/dl group was higher than that of TG≤150 mg/dl group (7.7% vs. 18.5%). The allele frequency did not show any differences.
Secondly, in blood pressure analysis, Table 3 displays the geno- type and allele frequencies of the examined SNPs in two groups according to the hypertension. The promoter SNP rsrs1881457 was associated with the hypertension [OR=3.53, 95% CI=1.31∼
9.52, p=0.013 in codominant 2 model (A/A vs. C/C), OR=2.95,
95% CI=1.17∼7.42, p=0.027 in recessive model (A/A and A/C vs. C/C), OR=1.76, 95% CI=1.09∼2.83, p=0.021 in log-additive model (A/A vs. A/C vs. C/C)]. The allele of rs1881457 was also associated to hypertension (p=0.017, OR=1.75, 95% CI=1.11∼
2.76). Linkage disequilibrium (LD) block between rs1881457 and rs1800925 was determined using Haploview version 4.2. Since the LD block was made (D'=1.00 and r2=0.54), there were three haplotypes consisted of rs1881457 and rs1800925 (Table 4).
The haplotype (AC) showed significant difference between without hypertension and with hypertension (AC haplotype frequency=
0.694, chi square=5.525, p=0.0187).
We have tested the SNP in two groups according to the
HDL-C levels and BMI. However, two SNPs were not associated
with hypertension and overweigh/obese in any of genetic associa-
tion model or allele (data not shown). However, we did not
analyze the TC, fasting plasma glucose, and HBA1c groups,
because the numbers of those groups were insufficient.
DISCUSSION
In this study, the results show the associations of promoter SNPs to each of the criteria of metabolic syndrome. As promoter SNPs do not cause direct variations in the amino acid sequence, some previous studies suggesting the effect of expression changes may reflect the biological functions of promoter SNPs. Anti-IL13 agents are used in asthma (Grunig et al., 2013). IL13 expression correlates with survival of colorectal cancer, and its receptor is involved in the local metastasis of the disease (Formentini et al., 2012). IL13 may have cytoprotective functions for pancreatic β-cells in diabetes, by modulating STAT6 of Jak/STAT signal pathway (Russell et al., 2013). Previous studies of IL13 promoter SNPs included rs2069743, which was associated to pulmonary function test in African-American asthma patients, and another promoter SNP rs2069739, however not associated (Battle et al., 2007).
Focusing the promoter SNPs tested in this study, rs1800925 was associated with the glioma risk, along with the missense SNP rs20541 (Su et al., 2013), and susceptibility to schistosomiasis (Isnard et al., 2008). In schistosomiasis, IL13 genotypes were associated with differences in allergen-specific and total IgE and eosinophilia, and aggravation of Th2 immune responses. In our result, rs1800925 was associated with TG level, which is included in dyslipidemic lipid profile. The minor allele was T in this study and it was associated to higher TG levels in metabolic syndrome patients. The T allele of rs1800925 was associated to lower infection level of schistosomiasis. Considering that the higher proinflammatory cytokine levels may be related to metabolic syndrome features (Aballay et al., 2013), we suggest that the result is converging with the previous study.
Another promoter SNP rs1881457 was associated to hyperten- sion and TG level in this study. Rs1881457 is associated with enhanced IL13 expression, and which is associated with allergic hypersensitivity (Kiesler et al., 2009). And it was associated with pulmonary function test in asthma (Beghe et al., 2009), aspirin intolerant asthma which is related to eosinophilic activation (Palikhe et al., 2010), severe manifestation of malaria infection (Naka et al., 2009). However, there were some gene studies
reported there were no significant association observed between rs1881457 and type 1 diabetes (Maier et al., 2005; Julier et al., 2009). In our results, rs1881457 was associated to hypertension and TG levels, both with OR＞1 and recessive manner, and the alleles were significant in hypertension. Therefore, rs1881457 may be associated with more features of metabolic syndrome, however, the study samples were relatively small.
In conclusion, the overall effect of IL13 in individuals with metabolic syndrome may be weak. However, we suggest that promoter polymorphisms (rs1800925 and rs1881457) of IL13 may be associated with the clinical features of metabolic syndrome, and that rs1881457 is associated with hypertension in metabolic syndrome patients. However, this study has limitations;
therefore, more study subject with metabolically normal subjects will be needed to confirm our result.
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