Cytokine gene polymorphism and asthma susceptibility, progressand control level

Saeed Daneshmandi • Ali Akbar Pourfathollah •

Zahra Pourpak • Hasan Heidarnazhad •

Parisa Amir Kalvanagh

Received: 12 May 2010 / Accepted: 24 May 2011 / Published online: 3 June 2011

� Springer Science+Business Media B.V. 2011

Abstract Asthma is a multifactor inflammatory disorder,

and its management requires understanding of its various

pathogenesis and control mechanisms. Cytokines and other

inflammatory mediators are important factors in asthma

pathophysiology. In this study, we evaluated the role of

cytokine polymorphisms in the asthma susceptibility,

progress, control, and lung functions. IL-4-C590T poly-

morphism by PCR-RFLP method, IFN-c T?874A, TNF-

a-A308G, IL-6 G-174C and TGF-b T?869C variants

by ARMS-PCR method and IgE serum level by ELISA

technique were determined in 81 asthmatic patients

and 124 normal subjects. Asthma diagnosis, treatment and

control levels were considered using standard schemes and

criteria. TNF-a-308GA genotype was more frequent in

asthmatics (P = 0.025, OR 3.352), and polymorphisms

between different asthma control levels (P [ 0.05) were

not different. IFN-c?874AT genotype had a positive cor-

relation with the familial history of asthma (P = 0.034,

OR 2.688). IL-6-174C allele (P = 0.045), TNF-a-308GG

genotype (P = 0.002) and TNF-a-308G allele (P = 0.004)

showed reduced values, and TNF-a-308GA genotype

(P = 0.002) increased FEF25-75 value in asthmatics. IFN-

c?874AA genotype caused a decrease in FVC factor

(P = 0.045). This study showed that TNF-a-308GA is a

risk factor for asthma, but cytokine gene variants do not

affect asthma control and IgE serum levels. Variants pro-

ducing lower levels of IL-6, TNF-a and IFN-c are associated

with reduced pulmonary capacities. To achieve an appro-

priate schema for asthma management, further studies with

consideration of different aspects in a larger group of patients

would be more elucidative.

Keywords Asthma � Cytokine � Polymorphism �Control level

Introduction

Asthma is a multifactor respiratory disease caused by acute

and chronic bronchial inflammation resulting in airways

obstruction in various degrees [1]. The control of asthma

and response to medication is different in patients, and

different asthmatics show various levels of asthma severity

and progress depending on multiple factors especially

genetic composition of the patients. The need for man-

agement of medication and control of asthma makes us

improve our knowledge about the pathogenesis of asthma

and role of different elements contributing to the airways

inflammation or influencing signs and symptoms [2, 3].

The airway inflammation underlying asthma is regulated

by a network of mutually interacting cytokines and

inflammatory elements which could be determined by

genetic or environmental factors [4]. Th2 and its cytokines

play a critical role in the induction and maintenance of

asthma and allergy and their characteristics such as IgE

Electronic supplementary material The online version of thisarticle (doi:10.1007/s11033-011-0927-7) contains supplementarymaterial, which is available to authorized users.

S. Daneshmandi � A. A. Pourfathollah (&) � P. A. Kalvanagh

Department of Immunology, Tarbiat Modares University,

Faculty of Medical Sciences, Tehran, Iran

e-mail: pourfa@modares.ac.ir

Z. Pourpak

Asthma and Allergy Research Institute, Children Medical

Center, Tehran University of Medical Sciences, Tehran, Iran

H. Heidarnazhad

TB and Lung Disease Research Cancer, NRITLD, Masih

Daneshvari Hospital, Shahid Beheshti University of Medical

Sciences, Tehran, Iran

123

Mol Biol Rep (2012) 39:1845–1853

DOI 10.1007/s11033-011-0927-7

production by B cells, eosinophil activation or recruitment,

and mucus production [5, 6]. In contrast, IFN-c and other

Th1 cytokines cause a decrease in BHR and IgE produc-

tion. Furthermore, Th1 and Th2 responses counter-regulate

each other, and in addition Tregs regulate Th1, Th2 and

other immune responses [7]. TGF-b as a multifunctional

fibrogenic and immunomodulatory cytokine is considered

to have pivotal roles in the pathogenesis of airway

remodeling, and its increased expression has been shown in

bronchoalveolar lavage fluid, bronchial biopsies, and

plasma from patients with asthma [8]. TGF-b mRNA

expression in the eosinophils and the airway of asthmatic

submucosa have been associated with severity of the dis-

ease and subepithelial fibrosis [9]. TNF-a is a potent pro-

inflammatory cytokine which is released during allergic

responses by both macrophages and mast cells [10]. Ele-

vated levels of TNF-a is frequently observed in broncho-

alveolar fluid of asthmatic subjects which cause an increase

in inflammation and airway responsiveness [11]. Anti-TNF

therapy provided clinical improvement in patients with

severe asthma [11]. IL-6 is a regulatory cytokine shown to

be a cofactor that potentiates IgE production by enhancing

the effects of IL-4 [12]; elevated levels of circulating IL-6

were observed in both symptomatic and asymptomatic

asthmatic subjects [13]. Cytokines contribute to different

aspects of asthma as they determine the type, severity and

outcomes of asthma pathogenesis; therefore, the targets of

most asthma medications are inflammatory mediators as

cytokines. On the other hand, the amount of cytokine

protein synthesis or cytokine function is determined by

some polymorphisms in their genes [14]. As a result,

polymorphisms in cytokine genes might determine the

efficacy of medications and thereby progress of the disease

and degree of asthma control. Our knowledge about cyto-

kine genetics may help us to manage asthma. With atten-

tion to the role of different cytokines in asthma, in this

study we analyzed the genetic variants of TNF-a-A308G,

IL-6 G-174C, TGF-b T?869C, IFN-c T?874A and IL-4

C-590T, which was previously reported that polymor-

phisms at these positions are associated with cytokine

production or function [15–18] to evaluate the role of these

polymorphisms in asthma susceptibility, progress, control

and lung functions.

Materials and methods

Study populations

In this study, 81 adult unrelated patients (25 male and 56

female and mean ± SD age of 43.03 ± 12.76 years), whose

asthma was defined according to the criteria of the Global

Initiative for Asthma (GINA) [19] were enrolled. A complete

clinical history, physical examination, and pulmonary

function test (PFT) in a standard fashion were performed for

all the subjects. Asthmatics have had treatment in a standard

scheme as inhaled corticosteroids and/or bronchodilator

when necessary, and control levels were determined

according to American Thoracic Society criteria [20] as

Asthma Control Tests (ACT). Exclusion criteria for the study

were a history of smoking more than 10 packs-years, pres-

ence of parasitic infection, and pregnancy or breastfeeding.

A total of 124 unrelated healthy subjects (sex/age matched

with asthmatics), without respiratory symptoms or history of

asthma and allergy served as controls. Blood was taken by

venipuncture from these subjects, a questionnaire was filled,

and the total serum IgE levels were determined for each

subject. The study protocol was approved by the ethics

committee at our institution, and written informed consent

was obtained from all the participants.

Total serum IgE measurements

From 5 ml of the patients and normal subjects’ blood,

serum was separated and total serum IgE levels were

measured using the ELISA kit (Genesis Diagnostics, UK)

according to the manufacturer’s instructions.

DNA preparation

Genomic DNA was extracted from the peripheral blood,

using a DNGplus extractor WB kit (Cinagen, Iran) accord-

ing to the manufacturer’s instructions.

Determination of cytokine gene polymorphisms

Cytokine gene polymorphisms were evaluated by poly-

merase chain reaction using a thermal cycler (Techne,

Genius, UK). PCR conditions, PCR cycles and primers are

summarized in supplementary Tables 1 and 2. ARMS-PCR

method was carried out for TNF-a-A308G [15], IL-6 G-

174C, TGF-b T?869C, and IFN-c T?874A [21] in 25 ll

reaction mixtures. A beta globin gene primer was used as

an internal control. PCR-RFLP method in a final volume of

25 ll was used for determining the IL-4 C-590T gene

polymorphism [21]. After PCR, the products were digested

by Ava II restriction enzyme and the amplified products

were monitored by agarose gel electrophoresis and ethi-

dium bromide staining.

Statistical analysis

Allele and genotype frequencies were calculated in patients

and control subjects by direct gene counting. Statistical

evaluation was carried out using the statistical package for

the social sciences (SPSS) version 15. The statistical

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123

significance of the difference was tested by a v2 analysis

with one difference or by the two-tailed Fisher’s exact test

when the criteria for the v2 analysis were not fulfilled. Odds

ratios and 95% confidence intervals (CIs) for relative risks

were calculated. For analysis of IgE and respiratory factors,

and differences in various gene variants, the one way

Table 1 Results of IL-6 G-174C, TNF-a G-308C, TGF-b T?869C, IL-4 C-590T and IFN-c T?874A single nucleotide polymorphisms

determined in asthmatics and normal subjects

Gene Genotype Asthma %(N) Normal %(N) P value OR %95 CI

IL-6 G-174C CCa 7.4 (6) 7.3 (9) 0.968 1.022 0.350–2.990

GCb 18.5 (15) 25.8 (32) 0.225 0.653 0.328–1.303

GGc 74.1 (60) 66.9 (83) 0.227 1.411 0.578–2.629

C alleled 16.7 (27) 20.2 (50) 0.376 0.792 0.472–1.328

G allele 83.3 (135) 79.8 (198)

TNF-a G-308A GGe 86.4 (70) 94.4 (117) 0.050 0.381 0.141–1.028

GAf 12.3 (10) 4 (5) 0.025 3.352 1.101–10.202

AAg 1.2 (1) 1.6 (2) 0.656 0.763 0.068–8.549

G alleleh 92.6 (150) 96.4 (239) 0.090 0.471 0.194–1.144

A allele 7.4 (12) 3.6 (9)

TGF-b T?869C CCi 37 (30) 29.8 (37) 0.283 1.383 0.765–2.502

CTj 46.9 (38) 47.6 (59) 0.925 0.974 0.556–1.706

TTk 16 (13) 22.6 (28) 0.253 0.655 0.317–1.357

C allelel 60.5 (98) 53.6 (133) 0.171 1.324 0.886–1.979

T allele 39.5 (64) 46.4 (115)

IL-4 C-590T CCi 77.8 (63) 75.8 (94) 0.745 1.117 0.574–2.174

CTj 18.5 (15) 21 (26) 0.668 0.857 0.422–1.739

TTk 3.7 (3) 3.2 (4) 0.854 1.154 0.251–5.294

C allelel 87 (141) 86.3 (214) 0.828 1.067 0.595–1.913

T allele 13 (21) 13.7 (34)

IFN-c T?874A TTm 23.5 (19) 23.4 (29) 0.991 1.004 0.518–1.944

ATn 38.3 (31) 42.7 (53) 0.525 0.831 0.469–1.472

AAo 38.3 (31) 33.9 (42) 0.520 1.210 0.676–2.177

T allelep 42.6 (69) 44.8 (111) 0.666 0.916 0.614–1.365

A allele 57.4 (93) 55.2 (137)

N absolute number, CI confidence Interval, OR odds ratioa CC vs. GG and GC genotypeb GC vs. GG and CC genotypec GG vs. CC and GC genotyped C vs. G allelee GG vs. GA and AA genotypef GA vs. GG and AA genotypeg AA vs. GA and GG genotypeh G vs. A allelei CC vs. TT and CT genotypej CT vs. TT and CC genotypek TT vs. CC and CT genotypel C vs. T allelem TT vs. AA and AT genotypen AT vs. AA and TT genotypeo AA vs. TT and AT genotypep T vs. A allele

Mol Biol Rep (2012) 39:1845–1853 1847

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analysis variance test (ANOVA) and t test were used.

P values\0.05 were considered as statistically significant.

An exact test was used to evaluate deviations from

expected Hardy–Weinberg genotypic proportions.

Results

The frequencies of cytokine gene polymorphisms in asth-

matic and normal subjects (Table 1), two levels of asthma

Table 2 Results of IL-6 G-174C, TNF-a G-308C, TGF-b T?869C, IL-4 C-590T and IFN-c T?874A single nucleotide polymorphism

distribution in asthma control levels

Gene Genotype Controlled

asthma % (N)

Uncontrolled

asthma % (N)

P value OR %95 CI

IL-6 G-174C CCa 2.8 (1) 11.1 (5) 0.219 0.229 0.025–2.051

GCb 19.4 (7) 17.8 (8) 0.848 1.116 0.362–3.438

GGc 77.8 (22) 71.1 (32) 0.496 1.422 0.515–3.929

C alleled 12.5 (9) 20 (18) 0.203 0.571 0.240–1.363

G allele 87.5 (63) 80 (72)

TNF-a G-308A GGe 83.3 (30) 88.9 (40) 0.468 0.625 0.174–2.243

GAf 13.9 (5) 11.1 (5) 0.706 1.290 0.343–4.856

AAg 2.8 (1) 0 (0) 0.444 – –

G alleleh 90.3 (65) 94.4 (85) 0.314 0.546 0.166–1.799

A allele 9.7 (7) 5.6 (5)

TGF-b T?869C CCi 44.4 (16) 31.1 (14) 0.217 1.771 0.712–4.407

CTj 44.4 (16) 48.9 (22) 0.690 0.836 0.347–2.016

TTk 11.1 (4) 20 (9) 0.279 0.500 0.140–1.781

C allelel 66.7 (48) 55.6 (50) 0.151 1.600 0.841–3.042

T allele 33.3 (72) 44.4 (40)

IL-4 C-590T CCi 83.3 (30) 73.3 (33) 0.282 1.818 0.607–5.449

CTj 13.9 (5) 22.2 (10) 0.337 0.565 0.174–1.832

TTk 2.8 (1) 4.4 (2) 0.693 0.614 0.053–7.059

C allelel 90.3 (65) 84.4 (76) 0.272 1.711 0.651–4.493

T allele 9.7 (7) 15.6 (14)

IFN-c T?874A TTm 22.2 (8) 24.4 (11) 0.815 0.883 0.312–2.496

ATn 47.2 (17) 31.1 (14) 0.138 1.981 0.798–4.918

AAo 30.6 (11) 44.4 (20) 0.201 0.550 0.219–1.382

T allelep 45.8 (33) 40 (36) 0.456 1.269 0.678–2.375

A allele 54.2 (39) 60 (54)

N absolute number, CI confidence interval, OR odds ratio, – cannot be calculated because expected \5, v2 testa CC vs. GG and GC genotypeb GC vs. GG and CC genotypec GG vs. CC and GC genotyped C vs. G allelee GG vs. GA and AA genotypef GA vs. GG and AA genotypeg AA vs. GA and GG genotypeh G vs. A allelei CC vs. TT and CT genotypej CT vs. TT and CC genotypek TT vs. CC and CT genotypel C vs. T allelem TT vs. AA and AT genotypen AT vs. AA and TT genotypeo AA vs. TT and AT genotypep T vs. A allele

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controls (Table 2), sex, allergy history and familial history

of asthma (Table 3) and serum IgE and respiratory factors

in asthma patients (Table 4) are shown. Analysis of our

results indicated that TNF-a-308GA genotype was more

frequent in asthmatics than normal controls (P = 0.025,

OR 3.352, 95% CI 1.101–10.202) and TNF-a-308GG

Table 3 Distribution and P values for IL-6 G-174C, TNF-a G-308C, TGF-b T?869C, IL-4 C-590T and IFN-c T?874A variants in sex,

allergy history and familial history of asthma groups

Gene Genotype Distribution (N) P value

Sex M/F Allergy P/N History P/N Sex Allergy History

IL-6 G-174C CCa 2/4 2/4 3/3 0.892 0.060 0.727

GCb 6/9 11/4 6/9 0.396 0.781 0.781

GGc 17/43 44/16 26/34 0.402 0.324 0.970

C alleled 10/17 15/12 12/15 0.447 0.065 0.887

G allele 40/95 99/36 58/77

TNF-a G-308A GGe 22/48 49/21 31/39 0.781 0.857 0.622

GAf 3/7 7/3 3/7 0.950 0.619 0.502

AAg 0/1 1/0 1/0 0.501 0.514 0.432

G alleleh 47/103 105/45 65/85 0.756 0.762 0.911

A allele 3/9 9/3 5/7

TGF-b T?869C CCi 11/19 22/6 14/16 0.386 0.145 0.630

CTj 10/28 25/13 15/23 0.405 0.396 0.523

TTk 4/9 8/5 6/7 0.994 0.447 0.815

C allelel 32/66 73/25 43/55 0.542 0.155 0.832

T allele 18/46 41/23 27/37

IL-4 C-590T CCi 19/44 46/17 29/34 0.797 0.329 0.337

CTj 6/9 9/6 3/12 0.396 0.330 0.081

TTk 0/3 2/1 3/0 0.549 0.886 0.077

C allelel 44/97 101/40 61/80 0.807 0.362 0.972

T allele 6/15 13/8 9/12

IFN-c T?874A TTm 6/13 13/6 6/13 0.939 0.832 0.242

ATn 8/23 23/8 18/13 0.438 0.553 0.034*

AAo 11/20 21/10 11/20 0.479 0.683 0.296

T allelep 20/49 49/20 30/39 0.656 0.877 0.953

A allele 30/63 65/28 40/53

N absolute number, CI confidence interval, OR odds ratio, * Statistically significanta CC vs. GG and GC genotypeb GC vs. GG and CC genotypec GG vs. CC and GC genotyped C vs. G allelee GG vs. GA and AA genotypef GA vs. GG and AA genotypeg AA vs. GA and GG genotypeh G vs. A allelei CC vs. TT and CT genotypej CT vs. TT and CC genotypek TT vs. CC and CT genotypel C vs. T allelem TT vs. AA and AT genotypen AT vs. AA and TT genotypeo AA vs. TT and AT genotypep T vs. A allele

Mol Biol Rep (2012) 39:1845–1853 1849

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Table 4 IgE concentrations and P values for association between IL-6 G-174C, TNF-a G-308C, TGF-b T?869C, IL-4 C-590T and IFN-cT?874A polymorphisms and serum IgE and respiratory factors of asthma patients

Gene Genotype IgE Cons.(IU/ml)

P value

IgE Age FEV1(%P)

FVC(%P)

FEV1/FVC(%P)

FEF25–75%(%P)

PEF(%P)

IL-6 G-174C CCa 61.76 ± 82.8 0.619 0.098 0.394 0.774 0.262 0.142 0.643

GCb 37.41 ± 62.9 0.242 0.260 0.779 0.654 0.141 0.506 0.845

GGc 134.20 ± 282.5 0.180 0.988 0.449 0.566 0.491 0.131 0.649

ANOVA 0.402 0.168 0.638 0.849 0.224 0.223 0.868

C alleled 49.10 ± 70.6 0.172 0.419 0.293 0.534 0.969 0.045* 0.538

G allele 123.26 ± 67.1

TNF-a G-308A GGe 106.02 ± 254.7 0.708 0.813 0.104 0.357 0.097 0.002* 0.161

GAf 117.30 ± 176.1 0.935 0.706 0.175 0.601 0.055 0.002* 0.206

AAg 307 ± 0 0.424 0.698 0.359 0.237 0.652 0.744 0.583

ANOVA 0.724 0.870 0.244 0.420 0.152 0.007* 0.374

G alleleh 106.62 ± 249.6 0.534 0.917 0.072 0.214 0.117 0.004* 0.140

A allele 159.45 ± 173.9

TGF-b T?869C CCi 116.40 ± 248.3 0.861 0.443 0.136 0.179 0.468 0.197 0.291

CTj 128.24 ± 290 0.606 0.355 0.249 0.770 0.411 0.882 0.647

TTk 55.63 ± 97.6 0.381 0.805 0.766 0.200 0.837 0.184 0.458

ANOVA 0.673 0.647 0.328 0.263 0.707 0.266 0.509

C allelel 120.44 ± 260.2 0.534 0.684 0.252 0.116 0.695 0.117 0.264

T allele 93.92 ± 221.8

IL-4 C-590T CCi 103.31 ± 252 0.690 0.346 0.268 0.357 0.335 0.702 0.190

CTj 120.32 ± 249.9 0.863 0.444 0.238 0.221 0.292 0.614 0.189

TTk 180.50 ± 159 0.616 0.619 0.988 0.583 0.954 0.744 0.866

ANOVA 0.860 0.635 0.500 0.430 0.577 0.845 0.408

C allelel 105.29 ± 249.7 0.579 0.303 0.328 0.540 0.369 0.800 0.219

T allele 138.37 ± 221.1

IFN-c T?874A TTm 184.38 ± 432.2 0.171 0.956 0.396 0.403 0.995 0.578 0.690

ATn 91.11 ± 194 0.625 0.373 0.388 0.226 0.277 0.719 0.960

AAo 85.08 ± 109.4 0.493 0.347 0.100 0.045* 0.270 0.383 0.693

ANOVA 0.393 0.597 0.255 0.137 0.746 0.673 0.895

T allelep 142.57 ± 342.21 0.188 0.490 0.101 0.061 0.450 0.344 0.607

A allele 86.99 ± 140.1

N absolute number, CI confidence interval, OR odds ratio, ANOVA one way analysis variance test, * Statistically significant, FEV1 forcedexpiratory volume in 1 second, FVC forced vital capacity, PEF peak expiratory flow, FEF25–75 forced expiratory flow 25–75%a CC vs. GG and GC genotypeb GC vs. GG and CC genotypec GG vs. CC and GC genotyped C vs. G allelee GG vs. GA and AA genotypef GA vs. GG and AA genotypeg AA vs. GA and GG genotypeh G vs. A allelei CC vs. TT and CT genotypej CT vs. TT and CC genotypek TT vs. CC and CT genotypel C vs. T allelem TT vs. AA and AT genotypen AT vs. AA and TT genotypeo AA vs. TT and AT genotypep T vs. A allele

1850 Mol Biol Rep (2012) 39:1845–1853

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genotype showed a borderline significance (P = 0.050, OR

0.381, 95% CI 0.141–1.028). Differences in two levels of

asthma control was not statistically significant (P [ 0.05).

We observed a positive correlation between IFN-c?874AT

genotype and familial history of asthma (P = 0.034, OR

2.688, 95% CI 1.068–6.762). IgE serum level in asthmatics

was higher than in the controls (P = 0.028), but there was

no association with cytokine variants (P [ 0.05). In the

case of pulmonary function tests, Forced Expiratory Flow

between 25 and 75% of the vital capacity (FEF25-75% pre-

dicted) in IL-6-174C versus G allele (49.51 ± 20.4 vs.

65.86 ± 36.42; P = 0.045), in TNF-a-308GG and GA

genotypes versus other genotypes (57.04 ± 31.8 vs. 96.26 ±

33.09; P = 0.002 and 99.44 ± 34.34 vs. 57.39 ± 31.56

P = 0.002, respectively) and TNF-a-308G versus A allele

(59.92 ± 33.42 vs. 93.78 ± 31.83; P = 0.004), and for

Forced Vital Capacity (FVC% predicted) in IFN-c?874 AA

versus other genotypes (73.31 ± 19.64 vs. 83.63 ± 18.65;

P = 0.045) the differences were significant.

Discussion

Asthma is a multifactor chronic inflammatory disorder of

the airways and a variety of genetic and environmental

factors contribute to its pathogenesis. Immune and

inflammatory elements are important factors in induction,

progress and clinical outcomes of asthma [4]. Management

of asthma and medication should take into consideration

the interfering factors that contribute to responses of

medications and therefore these factors determine the

outcomes of asthma [3]. The first line therapy of persistent

asthma involves the use of inhaled corticosteroids to con-

trol the underlying inflammation of the airways and inhaled

b-agonists often as short-acting bronchodilator [3, 22].

Inhaled corticosteroids as the most effective asthma control

drugs function via influencing the immune and inflamma-

tory cells and functions [22]. It is well realized that corti-

costeroids affect cytokines and other inflammatory

mediators and cytokines determine the corticosteroids’

efficacy. For example, it has been shown that a selective

Th2 cytokine inhibitor, i.e., suplatast tosilate, improves

airway inflammation and asthma control and reduces ste-

roid use in patients taking high doses of inhaled cortico-

steroid [23]. IL-4 and Th2 cytokines promote asthma and

deteriorate the outcomes; in contrast, counter regulators of

Th2 responses, i.e., IFN-c and Th1 cytokines improve

asthma features [5, 7]; TGF-b is a suppressive and fibro-

genic mediator that contributes to asthmatics’ airway

remodeling [8, 24]; IL-6 as a regulatory factor was asso-

ciated with IgE production or airway pathophysiology [12],

and its genetic variants were correlated with susceptibility

to cancer in asthmatics [25]. Anti-TNF-a therapy for

proinflammatory TNF-a cytokine is used as a therapeutic

method for asthma control [11]. On the other hand, pro-

duction of cytokine and other inflammatory mediators

depends on the patients’ genetics. So, this comment that

different patients show diverse levels of clinical outcomes

and control levels would be due to diversity of the efficacy

of ICs in comparison to the patient’s genetic complexity [3,

22, and 26]. With these backgrounds, our results in this

study indicated that these selected cytokine polymorphisms

have no correlation with the amount of asthma control. We

knew that there are other polymorphisms in these genes

and also in other genes that contribute to the production of

these mediators, and in this study they are unknown. TNF-

a-308GA genotype was more frequent in asthmatics and

was a risk factor for asthma susceptibility. Low producer

TNF-a-308GG genotype showed a borderline trend to

preventive impression on asthma susceptibility. Some

previous studies showed an association between TNF-aG-

308A polymorphisms and asthma, but the results of some

studies did not show any correlation [2, 27]. Distribution of

other polymorphisms in patients and normal subjects was

not different; therefore, these evaluated SNPs have no risk

factors for asthma susceptibility in our study population,

but with attention to the role of cytokines in asthma there

are several studies that have mentioned these polymor-

phism or other SNPs in these cytokine gene to be involved

in asthma [1, 2, 5, 24]. There are also several studies that

have shown no such association [5, 27]. These controver-

sies may be due to genetic complexity and/or nature of

asthma pathogenesis and pathophysiology with involve-

ment of various factors including genetic and environ-

mental ones. IgE levels were higher in asthmatics as

expected but did not have any correlation with polymor-

phisms. We have also seen a positive correlation between

IFN-c?874AT genotype and familial history of asthma.

Probably carriage of this genotype is a risk factor for

asthma. Other studies also mentioned a correlation between

polymorphisms, such as IL-6-174GG genotype, and

positive family history of asthma [28], but this result is not

strong enough and for elucidation of this subject and

detection of other familial risk factors further studies on

larger number of patients and consideration of different

interfering factors would be needed. In the case of respi-

ratory factors, cytokine variants had an association with

FEF25–75. It is clarified that FEF25–75 is a sensitive

marker of pulmonary abstraction of asthma [29] even in

patients without other clinically detectable abnormalities

[30]. Low producer of TNF-a (-308GG) genotype, and

TNF-a (-308G) and IL-6 (-174C) alleles was associated

with reduced FEF25–75 and higher producer genotype of

TNF-a (-308GA) was associated with increased

FEF25–75 values. So, lower producer polymorphisms of

IL-6 and TNF-a proinflammatory cytokines are correlated

Mol Biol Rep (2012) 39:1845–1853 1851

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with significant a decrease in respiratory capacity and

thereby more pulmonary obstruction. These results are

incompatible to the assumed roles of proinflammatory

cytokines in the progress of asthma inflammation. On the

other hand, a study showed among six polymorphisms in

TNF-a gene only TNF-a-308A allele was the risk factor

for asthma [31]. Another study showed that high producer

SNP of anti-inflammatory cytokine (TGF-b C-509T) was

associated with more airways obstruction [32]. Airway

wall thickening and obstruction reflects both structural

remodeling and inflammation, so in treatment strategies

and managements the complexity of cytokine functions

would be considered. We also showed low producer

genotype of IFN-c (?874AA) was associated with reduced

FVC factor concomitant with preventive functions of IFN-cin asthma. In conclusion, our results in this study indicated

TNF-a-308GA as a risk factor for asthma, but there was

no significant association between cytokine gene poly-

morphisms and the amount of asthma control and IgE

serum levels. IFN-c AT genotype may be a positive

familial risk factor for asthma, and IL-6, TNF-a and IFN-clower producer variants are associated with reduced pul-

monary capacities. Different aspects of asthma have been

studied but there are yet many complexities and contro-

versies to be understood to achieve a good schema for

asthma management. Further studies on mice models,

evaluation of polymorphisms and local, serum or culture

cytokine production in asthmatics, and examination of

several factors in the same patient group may be beneficial

for clarification of controversies in the multifactor asthma

disease.

Acknowledgment The authors are grateful to the Department of

Immunology of Tarbiat Modares University for financial support.

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