Pro-/anti-inflammatory cytokine gene polymorphisms and chronic kidney disease: a cross-sectional study.

Abstract

The aim of this study was to explore the associations between common potential functional promoter polymorphisms in pro-/anti-inflammatory cytokine genes and kidney function/chronic kidney disease (CKD) prevalence in a large Japanese population.
A total of 3,323 subjects aged 35-69 were genotyped for all 10 single nucleotide polymorphisms (SNPs) in the promoter regions of candidate genes with minor allele frequencies of > 0.100 in Japanese populations. The estimated glomerular filtration rate (eGFR) and CKD prevalence (eGFR < 60 ml/min/1.73 m2) of the subjects were compared among the genotypes.
A higher eGFR and lower prevalence of CKD were observed for the homozygous variants of IL4 -33CC (high IL-4 [anti-inflammatory cytokine]-producing genotype) and IL6 -572GG (low IL-6 [pro-inflammatory cytokine]-producing genotype). Subjects with IL4 CC + IL6 GG showed the highest mean eGFR (79.1 ml/min/1.73 m2) and lowest CKD prevalence (0.0%), while subjects carrying IL4 TT + IL6 CC showed the lowest mean eGFR (73.4 ml/min/1.73 m2) and highest CKD prevalence (17.9%).
The functional promoter polymorphisms IL4 T-33C (rs2070874) and IL6 C-572G (rs1800796), which are the only SNPs that affect the IL-4 and IL-6 levels in Japanese subjects, were associated with kidney function and CKD prevalence in a large Japanese population.

Full text

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RESEARCH ARTICLE Open Access
Pro-/anti-inflammatory cytokine gene
polymorphisms and chronic kidney disease:
a cross-sectional study
Rieko Okada1*, Kenji Wakai1, Mariko Naito1, Emi Morita1, Sayo Kawai1, Nobuyuki Hamajima1, Megumi Hara2,
Naoyuki Takashima3, Sadao Suzuki4, Toshiro Takezaki5, Keizo Ohnaka6, Kokichi Arisawa7, Hiroshi Hirohata8,
Keitaro Matsuo9, Haruo Mikami10, Michiaki Kubo11and Hideo Tanaka9, for
The Japan Multi-Institutional Collaborative Cohort (J-MICC)Study Group
Abstract
Background: The aim of this study was to explore the associations between common potential functional
promoter polymorphisms in pro-/anti-inflammatory cytokine genes and kidney function/chronic kidney disease
(CKD) prevalence in a large Japanese population.
Methods: A total of 3,323 subjects aged 35-69 were genotyped for all 10 single nucleotide polymorphisms (SNPs)
in the promoter regions of candidate genes with minor allele frequencies of > 0.100 in Japanese populations. The
estimated glomerular filtration rate (eGFR) and CKD prevalence (eGFR < 60 ml/min/1.73 m2) of the subjects were
compared among the genotypes.
Results: A higher eGFR and lower prevalence of CKD were observed for the homozygous variants of IL4 -33CC
(high IL-4 [anti-inflammatory cytokine]-producing genotype) and IL6 -572GG (low IL-6 [pro-inflammatory cytokine]-
producing genotype). Subjects with IL4 CC + IL6 GG showed the highest mean eGFR (79.1 ml/min/1.73 m2) and
lowest CKD prevalence (0.0%), while subjects carrying IL4 TT + IL6 CC showed the lowest mean eGFR (73.4 ml/min/
1.73 m2) and highest CKD prevalence (17.9%).
Conclusions: The functional promoter polymorphisms IL4 T-33C (rs2070874) and IL6 C-572G (rs1800796), which are
the only SNPs that affect the IL-4 and IL-6 levels in Japanese subjects, were associated with kidney function and
CKD prevalence in a large Japanese population.
Background
Chronic kidney disease (CKD) is common and continues
to increase. It is a risk factor for end-stage renal disease
(ESRD) and is also a strong risk factor for cardiovascular
diseases and mortality. A combined effect of environ-
ment and genotype determines the risk of CKD [1-3],
and cytokine polymorphisms play important roles [3-5].
Cytokines are known to influence atherosclerosis, which
causes CKD and subsequent ESRD [6,7]. The balance
between pro- and anti-inflammatory cytokines determines
the inflammatory response and may mediate the
progression of CKD [6]. Among the cytokines, pro-inflam-
matory (IL-1, IL-6, and TNF-a) and anti-inflammatory
(IL-4, IL-10, and IL-13) cytokines play pivotal roles [6]. IL-
2 and IL-8 are also well-known pro-inflammatory cyto-
kines that may affect CKD or ESRD progression [7,8].
Functional SNPs within the promoter area of these cyto-
kine genes have been identified in that they influence the
gene promoter activities and gene product levels [9,10].
Such polymorphisms have been demonstrated to be asso-
ciated with susceptibility to a number of atherosclerotic
diseases in CKD [3-5], but the issue of whether these cyto-
kine polymorphisms are risk factors for CKD itself has not
been fully clarified. Some studies have failed to show such
associations, possibly owing to the small sample sizes, and
their conclusions are controversial [11].
* Correspondence: rieokada@med.nagoya-u.ac.jp
1Department of Preventive Medicine, Nagoya University Graduate School of
Medicine, Nagoya, Japan
Full list of author information is available at the end of the article
Okada et al. BMC Nephrology 2012, 13:2
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© 2012 Okada et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
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This study aimed to explore the associations between
common potential functional promoter polymorphisms
of pro-/anti-inflammatory cytokines and kidney func-
tion/CKD prevalence in a large Japanese population.
Methods
Study subjects
The study subjects were participants in the Japan Multi-
Institutional Collaborative Cohort (J-MICC) Study, a
large cohort study to confirm and detect gene-environ-
ment interactions in lifestyle-related diseases, in which
voluntarily enrolled participants aged 35-69 from 10
areas of Japan provided blood and lifestyle data based
on questionnaires. The details of the J-MICC Study
have been described elsewhere [12]. The participants in
this cross-sectional study were 4,519 subjects enrolled in
the 10 study areas throughout Japan between 2004 and
2008 [13]. Serum creatinine (SCr) data were available in
eight study areas. Of the 3,435 participants in these
areas, 3,323 (97%) subjects were included in the ana-
lyses. Informed consent was obtained from all subjects
and the study protocol was approved by the ethics com-
mittees of Nagoya University School of Medicine and
the participating institutions.
Selection and genotyping of polymorphisms
We selected pro-inflammatory (IL1, IL2, IL6, IL8, and
TNFA) and anti-inflammatory (IL4, IL10, and IL13)
cytokine genes as candidate genes based on the pub-
lished literature [6-8]. In addition, CD14, which encodes
a lipopolysaccharide receptor that initiates the inflam-
matory response, was selected based on our previous
report [14]. Subsequently, to the best of our knowledge,
we selected all the single nucleotide polymorphisms
(SNPs) in the promoter regions that had minor allele
frequencies in Japanese populations of > 0.100, based on
the database SNP (dbSNP) and the HapMap database,
and that had potential functional effects according to
the published literature. The selected SNPs were IL4 T-
33C (rs2070874, which is in complete linkage disequili-
brium with T-589C [rs2243250]) [9,15], IL6 C-572(-634)
G (rs1800796) [10,11], IL1B T-31C (rs1143627, linked to
C-511T [rs16944]), IL2 T-330G (rs2069762), IL13 C-
1111T (rs1800925) [16], and CD14 A-260(-159)G
(rs2569190) [14], which were proven to be functional,
and IL8 T-251A (rs4073), IL10 T-819C (rs1800871,
linkedto A-592C[rs1800872]),
(rs1799724), and TNFA T-1031C (rs1799964, linked to
C-863A [rs1800630]), which were reported to be prob-
able or presumed functional SNPs [16,17]. IL6 T-6331C
(rs10499563), A-597G (rs1800797), C-174G (rs1800795),
and IL10 A-1082G (rs1800896) were excluded because
their minor allele frequencies were < 0.100.
TNFAC-857T
DNA was extracted from buffy coat fractions using a
BioRobot M48 Workstation (Qiagen Group, Tokyo,
Japan), or from whole blood using an automatic nucleic
acid isolation system (NA-3000; KURABO, Osaka,
Japan). The SNPs were genotyped using a Multiplex
PCR-based Invader Assay (Third Wave Technologies,
Madison, WI) [18] at the Laboratory for Genotyping
Development, Center for Genomic Medicine, RIKEN.
The genotype call rates were 99.40% to 99.98%.
Estimated glomerular filtration rate (eGFR), and
definitions of CKD and comorbid diseases
SCr was measured in all participants using an enzymatic
method. The eGFR of each participant was calculated
from the SCr, age, and sex using the following Japanese
eGFR equation recently determined by the Japanese
Society of Nephrology [19]:
eGFR (ml/min/1.73m2) = 194× SCr?mg/dl?−1.094× age−0.287(× 0.739 if female).
The prevalence of CKD was determined for CKD
stages 3-5 (defined as eGFR < 60 ml/min/1.73 m2) [20].
Hypertension was defined as resting blood pressure ≥
140/90 mmHg or being under treatment for hyperten-
sion. Diabetes mellitus was defined as fasting blood glu-
cose ≥ 126 mg/dl or serum HbA1c ≥ 6.5% or being
under treatment for diabetes mellitus.
Statistical analysis
The genotype distributions were tested for Hardy-Wein-
berg equilibrium. One-way analysis of variance
(ANOVA) or the c2test was used for comparisons of
mean eGFRs and CKD prevalences between genotypes,
and the polymorphisms with a significant difference in
the mean eGFR or CKD prevalence were selected for
multivariate analyses. The mean eGFRs, adjusted for age
(continuous variable), sex, comorbid hypertension and
diabetes mellitus, and history of cardiovascular diseases
by multiple linear regression models, were compared
between genotypes using the homozygous for the major
allele as the reference. Odds ratios (ORs) for CKD pre-
valence adjusted for these covariates were estimated by
unconditional logistic regression analysis with 95% con-
fidence intervals (CIs). Standard errors were adjusted for
the study areas. The analyses were carried out using
STATA ver. 9 software (StataCorp, College Station, TX).
Results
The characteristics and the genotype frequencies of the
subjects are summarised in Table 1 and Table 2. Seven
subjects had a history of kidney disease, and two were
categorised into the CKD group. The genotype frequencies
were in Hardy-Weinberg equilibrium (data not shown),
except for IL6 C-572G (57.5% for CC, 35.7% for CG, and
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6.8% for GG, P = 0.026, in comparison with the expected
values of 57.2%, 36.9%, and 5.9%, respectively) [13].
The mean eGFRs and CKD prevalences were com-
pared among the genotypes of the 10 cytokine SNPs
(Table 3). The mean eGFRs differed for the IL4 T-33C
(rs2070874) and IL6 C-572G (rs1800796) genotypes (P =
0.012 and P = 0.004, respectively), while the CKD preva-
lences differed for the IL4 T-33C genotypes. Thus, the
IL4 and IL6 genotypes were subjected to multivariate
analyses.
Higher eGFRs and lower CKD prevalences were
observed for the IL4 -33CC and IL6 -572GG genotypes
(Table 4). The mean eGFRs were 75.7 and 73.4 ml/min/
1.73 m2for the IL4 CC and TT genotype carriers, and
76.9 and 74.2 ml/min/1.73 m2for the IL6 GG and CC
genotype carriers, respectively. The CKD prevalences
were 11.4% and 17.8% for the IL4 CC and TT genotype
carriers (OR = 0.59, 95% CI = 0.37-0.95, P = 0.029 after
adjustment), and 11.6% and 16.3% for the IL6 GG and
CC genotype carriers (OR = 0.67, 95% CI = 0.50-0.90, P
= 0.008 after adjustment), respectively. These differences
were greater when the two genotypes were combined
(Table 5). Subjects with both the IL4 CC and IL6 GG
genotypes showed the highest mean eGFR (79.1 ml/
min/1.73 m2) and lowest CKD prevalence (0.0%), while
subjects carrying both the IL4 TT and IL6 CC genotypes
showed the lowest mean eGFR (73.4 ml/min/1.73 m2)
and highest CKD prevalence (17.9%). There was no
interaction between the IL4 CC and IL6 GG genotypes,
and their effects were additive.
We previously reported an association between the
CD14 A-260G SNP and kidney function among a popu-
lation living in the north part of Japan using an eGFR
derived from the MDRD Study equation [14]. However,
the present study did not show such an association.
Discussion
Our explorations revealed that the subjects with the
genotypes IL4 -33CC (a genotype that produces high
levels of IL-4) and IL6 -572GG (a genotype that pro-
duces low levels of IL-6) had better kidney function and
a lower risk of CKD in a large Japanese population.
Cytokines are important modulators of inflammation,
and the balance between pro- and anti-inflammatory
cytokines determines the inflammatory response and
may mediate the progression of atherosclerosis and sub-
sequent CKD [6,7]. Genetic polymorphisms of these
cytokines have been shown to be associated with comor-
bidities, such as cardiovascular disease, in ESRD patients
[3-5], or with ESRD susceptibility [8], but there are con-
troversial results that no polymorphisms of the IL6, IL10,
and IL1 genes were associated with ESRD [11]. The evi-
dence for polymorphisms in cytokine genes affecting the
risk of CKD itself is scarce and this issue has not been
fully clarified, especially in the general population.
IL-4 is an anti-inflammatory cytokine that exerts
immunosuppressive effects on macrophages and sup-
presses pro-inflammatory cytokine production [21]. The
promoter polymorphism IL4 T-33C (which is in com-
plete linkage disequilibrium with IL4 T-589C) affects IL-
Table 1 Clinical characteristics of study subjects
CKD Non-CKD
(n = 2,777)
Total
(n = 546)(n = 3,323)
Age (years)
Male
Body mass index
Hypertension
Systolic blood pressure (mm Hg)
Diastolic blood pressure (mm Hg)
Anti-hypertensive medication
Diabetes mellitus
Fasting plasma glucose (mmol/l)
HbA1c (%)
Glucose-lowering medication
Cardiovascular diseases
Total cholesterol (mmol/l)
HDL cholesterol (mmol/l)
Lipid-lowering medication
Uric acid (μmol/l)
Current smokers
60.6 ± 7.2
252(46.2%)
23.5 ± 3.1
245(44.9%)
130.5 ± 19.8
79.1 ± 12.4
146(26.7%)
54(9.9%)
5.49 ± 1.23
5.22 ± 0.69
28(5.1%)
34(6.2%)
5.66 ± 0.88
1.60 ± 0.41
68(12.5%)
333 ± 89
68(12.5%)
55.9 ± 8.7
1,364(49.1%)
23.4 ± 3.3
1,050(37.8%)
128.1 ± 19.3
78.6 ± 11.9
503(18.1%)
220(7.9%)
5.55 ± 1.17
5.22 ± 0.66
117(4.2%)
80(2.9%)
5.46 ± 0.83
1.64 ± 0.42
233(8.4%)
303 ± 77
495(17.8%)
56.7 ± 8.6
1,616(48.6%)
23.4 ± 3.3
1,295(39.0%)
128.5 ± 19.4
78.7 ± 12.0
649(19.5%)
274(8.2%)
5.54 ± 1.17
5.22 ± 0.67
145(4.4%)
114(3.4%)
5.50 ± 0.88
1.63 ± 0.42
301(9.1%)
309 ± 83
563(16.9%)
Results are expressed as mean ± SD or number (%). CKD = chronic kidney disease. CKD is defined by eGFR < 60 ml/min/1.73 m2. Hypertension = blood pressure
≥ 140/90 mmHg or under anti-hypertensive medication. Diabetes mellitus = fasting blood glucose ≥ 126 mg/dl, HbA1c ≥ 6.5% or under glucose-lowering
medication.
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4 expression [15], and the CC genotype shows a high
level of IL-4 protein [9]. Accordingly, subjects with the
CC genotype showed a lower risk of ischemic stroke
relapse [22], consistent with our data indicating a lower
risk of CKD in CC genotype carriers.
An elevated level of the main pro-inflammatory cyto-
kine IL-6 predicts cardiovascular mortality in ESRD
patients [3]. The IL6 C to G variation at position -572
reduces the transcriptional activity of the IL6 promoter,
and the levels of IL-6 are lower in carriers of the IL6
-572GG genotype [10,11]. Accordingly, the IL6 -572GG
genotype was associated with lower risks of kidney allo-
graft survival [23] and abdominal aortic aneurysm [24],
consistent with our data showing a lower risk of CKD in
GG genotype carriers.
The combined effect of high IL-4- and low IL-6-pro-
ducing genotypes has been shown to lead to a lower
risk of ESRD [8]. We also found that no CKD subjects
carried high IL-4- and low IL-6-producing (low-risk)
genotypes, and that their mean eGFR was 5.2 ml/min/
1.73 m2higher than that in carriers of the low IL-4- and
high IL-6-producing (high-risk) genotypes. This differ-
ence is almost equivalent to a 14-year difference in a
healthy Japanese population [25], and has a significant
impact with respect to cardiovascular disease prevention,
especially among healthy individuals who are not aware
of a possible risk of CKD.
The evidence for polymorphisms in cytokine genes
affecting the risk of CKD is scarce. No cytokine genes
were identified as susceptibility loci for CKD in a Cauca-
sian population in a genome-wide association study
(GWAS) [1]. However, this may simply mean that no
cytokine genes were highly statistically significantly asso-
ciated in the context of the multiple testing related to
the GWAS, and therefore not presented in the GWAS
report. Yoshida et al. [2] showed that some genetic var-
iants were associated with CKD in a large Japanese
population, but only TNFA and IL10 were included as
representative cytokine genes and did not show associa-
tions. In contrast, we selected candidate genes that are
assumed to be of physiological interest based on the
associations between pro-/anti-inflammatory cytokines
and CKD [6,7]. The other difference is that the former
study participants were mixed, and comprised patients
with various symptoms, health check-up examinees and
aged subjects [2]. In contrast, our study participants
were enrolled from the population with an age range of
35 to 69. Thus, our study contains the largest general
Japanese population investigated to date for associations
among pro-/anti-inflammatory cytokine gene variants
and CKD.
No haplotype analyses were needed because IL4 T-
33C and IL6 C-572G are the only SNPs that affect the
IL-4 and IL-6 levels in Japanese subjects. IL4 T-589C,
IL4 T-33C, and a 70-bp variable number of tandem
repeat polymorphism (VNTR) within intron 3 are in
complete linkage disequilibrium, thus there are only two
IL4 gene haplotypes in Japanese populations; -589T/-
33T/B1 (183 bp) (allele frequency, 0.670) and -589C/-
33C/B2 (253 bp) (0.330) [15]. In addition, IL6 transcrip-
tion is influenced by four promoter polymorphisms (C-
Table 2 Genotype frequencies of study subjects
Genotype
(n = 546)
CKDnon-CKD
(n = 2,777)
Total
(n = 3,323)
IL1B T-31C (rs1143627)
T T
C T
C C
163 (29.9%)
266 (48.7%)
117 (21.4%)
791 (28.5%)
1,355 (48.8%)
631 (22.7%)
954 (28.7%)
1,621 (48.8%)
748 (22.5%)
IL2 T-330G (rs2069762)
T T
T G
G G
244 (44.9%)
241 (44.3%)
59 (10.9%)
1,225 (44.1%)
1,239 (44.6%)
312 (11.2%)
1,469 (44.2%)
1,480 (44.6%)
371 (11.2%)
IL4 T-33C (rs2070874)
T T
T C
C C
259 (47.4%)
241 (44.1%)
46 (8.4%)
1,193 (43.0%)
1,226 (44.2%)
357 (12.9%)
1,452 (43.7%)
1,467 (44.2%)
403 (12.1%)
IL6 C-572G (rs1800796)
C C
G C
G G
312 (57.1%)
208 (38.1%)
26 (4.8%)
1,600 (57.6%)
977 (35.2%)
199 (7.2%)
1,912 (57.6%)
1,185 (35.7%)
225 (6.8%)
IL8 T-251A (rs4073)
T T
A T
A A
254 (46.5%)
235 (43.0%)
57 (10.4%)
1,281 (46.5%)
1,204 (43.7%)
273 (9.9%)
1,535 (46.5%)
1,439 (43.6%)
330 (10.0%)
IL10 T-819C (rs1800871)
T T
C T
C C
252 (46.2%)
239 (43.8%)
55 (10.1%)
1,175 (42.5%)
1,222 (44.2%)
370 (13.4%)
1,427 (43.1%)
1,461 (44.1%)
425 (12.8%)
IL13 C-1111T (rs1800925)
C C
T C
T T
TNFA C-857T (rs1799724)
C C
C T
T T
TNFA T-1031C (rs1799964)
T T
C T
C C
CD14 T-260C (rs2569190)
T T
T C
C C
370 (67.9%)
158 (29.0%)
17 (3.1%)
1,847 (66.5%)
840 (30.3%)
89 (3.2%)
2,217 (66.8%)
998 (30.1%)
106 (3.2%)
373 (68.3%)
155 (28.4%)
18 (3.3%)
1,788 (64.4%)
887 (31.9%)
102 (3.7%)
2,161 (65.0%)
1,042 (31.4%)
120 (3.6%)
383 (70.2%)
144 (26.4%)
19 (3.5%)
1,934 (69.6%)
764 (27.5%)
79 (2.8%)
2,317 (69.7%)
908 (27.3%)
98 (2.9%)
144 (26.4%)
275 (50.4%)
127 (23.3%)
785 (28.3%)
1,412 (50.9%)
580 (20.9%)
929 (28.0%)
1,687 (50.8%)
707 (21.3%)
Results are expressed as number (%). CKD = chronic kidney disease. CKD is
defined by eGFR < 60 ml/min/1.73 m2.
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572G, A-597G, -373AnTn and C-174G) [26], but A-
597G and C-174G do not exist or are very rare in Japa-
nese populations. Only three prevalent haplotypes have
been identified in Japanese populations [10]: -572C/-
373A10T10 (allele frequency 0.733), G/A10T11 (0.136),
and G/A9T11 (0.104). The serum levels of IL-6 were
high in C/A10T10 and low in both G/A10T11 and G/
A9T11, with no difference between the IL-6 levels in G/
A10T11 and G/A9T11. Thus, IL4 T-33C and IL6 C-
572G could be the only SNPs that affect the transcrip-
tional activity of IL-4 and IL-6 in Japanese populations.
A limitation of our study was that IL6 C-572G was not
in Hardy-Weinberg equilibrium. However, the absolute
difference between the actual and expected frequencies
Table 3 Mean eGFRs and CKD prevalence with respect to cytokine polymorphism genotypes
Genotype neGFR (ml/min/1.73 m2)CKD (eGFR < 60 ml/min/1.73 m2)
mean ± SD P-value†
n (%) P-value‡
IL1B T-31C (rs1143627)
T T
C T
C C
954
1,621
748
74.0 ± 14.9
73.9 ± 14.6
74.6 ± 15.3
163 (16.6%)
266 (16.3%)
117 (15.6%)
0.5760.727
IL2 T-330G (rs2069762)
T T
T G
G G
1,469
1,480
371
74.0 ± 14.8
74.2 ± 14.9
74.3 ± 14.5
244 (16.6%)
241 (16.3%)
59 (15.9%)
0.860 0.938
IL4 T-33C (rs2070874)
T T
T C
C C
1,452
1,467
403
73.4 ± 14.6
74.4 ± 15.1
75.8 ± 14.5
259 (17.8%)
241 (16.4%)
46 (11.4%)
0.012 0.009
IL6 C-572G (rs1800796)
C C
G C
G G
1,912
1,185
225
74.2 ± 14.7
73.4 ± 14.8
76.9 ± 15.9
312 (16.3%)
208 (17.6%)
26 (11.6%)
0.004
0.082
IL8 T-251A (rs4073)
T T
A T
A A
1,535
1,439
330
74.1 ± 14.4
73.9 ± 15.2
74.6 ± 15.4
254 (17.3%)
235 (16.3%)
57 (16.5%)
0.745 0.917
IL10 T-819C (rs1800871)
T T
C T
C C
1,427
1,461
425
73.6 ± 14.7
74.2 ± 14.8
75.2 ± 15.0
252 (17.7%)
239 (16.4%)
55 (12.9%)
0.1550.070
IL13 C-1111T (rs1800925)
C C
T C
T T
2,217
998
106
74.0 ± 14.9
74.3 ± 14.7
74.7 ± 14.3
370 (16.7%)
158 (15.8%)
17 (16.0%)
0.7340.827
TNFA C-857T (rs1799724)
C C
C T
T T
2,161
1,042
120
73.6 ± 14.7
74.9 ± 15.0
75.5 ± 15.4
373 (17.3%)
155 (14.9%)
18 (15.0%)
0.0540.212
TNFA T-1031C (rs1799964)
T T
C T
C C
2,317
908
98
73.9 ± 14.6
74.5 ± 15.4
74.1 ± 14.6
383 (16.5%)
144 (15.9%)
19 (19.4%)
0.6410.652
CD14 T-260C (rs2569190)
T T
T C
C C
929
1,687
707
74.5 ± 14.5
74.2 ± 14.9
73.3 ± 14.9
144 (15.5%)
275 (16.3%)
127 (18.0%)
0.2260.403
†P for ANOVA,‡P for the c2test. eGFR = estimated glomerular filtration rate. CKD = chronic kidney disease. CKD is defined by eGFR < 60 ml/min/1.73 m2. Bold
style represents P < 0.05.
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was only 1%. Thus, the errors in genotyping seem unli-
kely to result in substantial misclassification [13],
although the large number in the study population might
account for the statistically significant deviation from
Hardy-Weinberg equilibrium. Another limitation is the
possible misclassification of CKD subjects owing to the
single measurement of SCr. As our subjects were pre-
sumably healthy volunteers or health check-up exami-
nees, their kidney function might have been stable. Thus,
the possibility that a single measurement of SCr could
result in misclassification is low. Since we lacked a repli-
cation cohort, adjustment of the p-values for the multiple
comparisons, and biomarkers of inflammation, further
confirmation using another cohort of subjects is needed
so that there is a high chance that our study results
represent a false positive finding. As this was a cross-sec-
tional study, a prospective study is needed to further con-
firm the decrease in eGFR and the incident risk of CKD.
Conclusions
The functional cytokine polymorphisms IL4 T-33C
(rs2070874) and IL6 C-572G (rs1800796), which are the
only SNPs identified to date that affect the IL-4 and IL-
6 levels in Japanese subjects, were associated with kid-
ney function and CKD prevalence in a large Japanese
population. The IL4 -33CC and IL6 -572GG genotypes
(high IL-4-and low IL-6-producing genotypes) showed
better kidney function and a lower risk of CKD com-
pared with the other variants. These differences were
greater when the two genotypes were combined. This
study supported the hypothesis that genetic variations in
the anti-inflammatory cytokine IL4 and pro-inflamma-
tory cytokine IL6 genes may predispose subjects to the
development of CKD. Determination of the genotypes
involved may prove informative for identifying indivi-
duals at a lower or higher risk of CKD. Further confir-
mation in another study is needed.
Acknowledgements
The authors thank Kyota Ashikawa, Tomomi Aoi and other members of the
Laboratory for Genotyping Development, Center for Genomic Medicine,
RIKEN, for support with genotyping, and Yoko Mitsuda, Keiko Shibata and
Etsuko Kimura at the Department of Preventative Medicine, Nagoya
University Graduate School of Medicine, for their technical assistance. This
study was supported in part by Grants-in-Aid for Scientific Research from the
Japanese Ministry of Education, Culture, Sports, Science and Technology
(Nos. 17015018 and 221S0001).
Table 4 Mean eGFRs and CKD prevalence for IL4 T-33C and IL6 C-572G genotypes
GenotypeneGFR (ml/min/1.73 m2)CKD (eGFR < 60 ml/min/1.73 m2)
OR†(95% CI)
mean ± SD
b†(95% CI)P-value†
n (%)P-value†
IL4 T-33C
TT
TC
CC
1,452
1,466
403
73.4 ± 14.6
74.4 ± 15.1
75.7 ± 14.5
0 (reference)
0.9 (-1.2-2.9)
2.2 (-1.9-6.3)
-
0.346
0.240
259 (17.8%)
241 (16.4%)
46 (11.4%)
1 (reference)
0.91 (0.78-1.07)
0.59 (0.37-0.95)
-
0.269
0.029
IL6 C-572G
CC
CG
GG
1,911
1,185
225
74.2 ± 14.7
73.4 ± 14.8
76.9 ± 15.9
0 (reference)
-1.1 (-2.3-0.1)
2.6 (-0.1-5.2)
-
0.065
0.055
312 (16.3%)
208 (17.6%)
26 (11.6%)
1 (reference)
1.13 (0.98-1.31)
0.67 (0.50-0.90)
-
0.091
0.008
†adjusted for age, sex, hypertension, diabetes mellitus, and cardiovascular diseases. Standard errors were adjusted for study areas. eGFR = estimated glomerular
filtration rate. CKD = chronic kidney disease. CKD is defined by eGFR < 60 ml/min/1.73 m2.
Table 5 Mean eGFRs and CKD prevalence for IL4 T-33C and IL6 C-572G genotypes combined
Genotypen eGFR (ml/min/1.73 m2)
b†(95% CI)
IL4 TT/ IL6 CC 84973.4 ± 14.4 0 (reference)
IL4 TC/ IL6 CC 85474.5 ± 14.91.1 (-0.3-2.4)
IL4 TT/ IL6 CG 51272.5 ± 14.5-0.8 (-2.8-1.1)
IL4 TC/ IL6 CG 512 74.0 ± 15.2 0.2 (-3.1-3.5)
IL4 CC / IL6 CG16174.0 ± 14.40.3 (-3.8-4.4)
IL4 TC/ IL6 GG
10075.6 ± 17.0 2.1 (-1.5-5.7)
IL4 CC / IL6 CC 20876.5 ± 14.63.1 (-1.2-7.4)
IL4 TT/ IL6 GG
9177.6 ± 15.4
4.2 (0.4-8.1)
IL4 CC / IL6 GG
34 79.1 ± 13.4
5.2 (0.3-10.2)
CKD (eGFR < 60 ml/min/1.73 m2)
OR†(95% CI)
mean ± SD
P-value†
n (%)P-value†
-
0.108
0.337
0.890
0.867
0.217
0.127
0.036
0.041
152 (17.9%)
140 (16.4%)
98 (19.1%)
84 (16.4%)
26 (16.1%)
17 (17.0%)
20 (9.6%)
9 (9.8%)
0 (0.0%)
1 (reference)
0.89 (0.75-1.06)
1.08 (0.90-1.30)
0.94 (0.68-1.28)
0.89 (0.42-1.90)
0.94 (0.67-1.32)
0.48 (0.39-0.58)
0.49 (0.37-0.63)
0.00 -
-
0.200
0.387
0.686
0.768
0.720
< 0.001
< 0.001
-
†adjusted for age, sex, hypertension, diabetes mellitus, and cardiovascular diseases. Standard errors were adjusted for study areas. eGFR = estimated glomerular
filtration rate. CKD = chronic kidney disease. CKD is defined by eGFR < 60 ml/min/1.73 m2.
Okada et al. BMC Nephrology 2012, 13:2
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Author details
1Department of Preventive Medicine, Nagoya University Graduate School of
Medicine, Nagoya, Japan.2Department of Preventive Medicine, Faculty of
Medicine, Saga University, Saga, Japan.3Department of Health Science, Shiga
University of Medical Science, Otsu, Japan.4Department of Public Health,
Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
5Department of International Island and Community Medicine, Kagoshima
University Graduate School of Medical and Dental Science, Kagoshima,
Japan.6Department of Geriatric Medicine, Kyushu University Graduate School
of Medical Sciences, Fukuoka, Japan.7Department of Preventive Medicine,
Institute of Health Biosciences, University of Tokushima Graduate School,
Tokushima, Japan.8Department of Epidemiology for Community Health and
Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan.9Division of
Epidemiology and Prevention, Aichi Cancer Center Research Institute,
Nagoya, Japan.10Division of Cancer Registry, Prevention and Epidemiology,
Chiba Cancer Center, Chiba, Japan.11Laboratory for Genotyping
Development, Center for Genomic Medicine, RIKEN, Yokohama, Japan.
Authors’ contributions
RO analyzed data and mainly drafted the article. KW, MN, KA, and MK were
involved in drafting the manuscript and revising it critically for important
intellectual content. EM, SK, MH, NT, SS, TT, KO, HH, KM, and HM made
substantial contributions to the conception, design, and acquisition of data.
NH and HT initiated the study and gave final approval of the version to be
published. All the authors have read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Received: 30 June 2011 Accepted: 9 January 2012
Published: 9 January 2012
References
1.Köttgen A, Pattaro C, Böger CA, Fuchsberger C, Olden M, Glazer NL,
Parsa A, Gao X, Yang Q, Smith AV, O’Connell JR, Li M, Schmidt H, Tanaka T,
Isaacs A, Ketkar S, Hwang SJ, Johnson AD, Dehghan A, Teumer A, Paré G,
Atkinson EJ, Zeller T, Lohman K, Cornelis MC, Probst-Hensch NM,
Kronenberg F, Tönjes A, Hayward C, Aspelund T, Eiriksdottir G, Launer LJ,
Harris TB, Rampersaud E, Mitchell BD, Arking DE, Boerwinkle E, Struchalin M,
Cavalieri M, Singleton A, Giallauria F, Metter J, de Boer IH, Haritunians T,
Lumley T, Siscovick D, Psaty BM, Zillikens MC, Oostra BA, Feitosa M,
Province M, de Andrade M, Turner ST, Schillert A, Ziegler A, Wild PS,
Schnabel RB, Wilde S, Munzel TF, Leak TS, Illig T, Klopp N, Meisinger C,
Wichmann HE, Koenig W, Zgaga L, Zemunik T, Kolcic I, Minelli C, Hu FB,
Johansson A, Igl W, Zaboli G, Wild SH, Wright AF, Campbell H, Ellinghaus D,
Schreiber S, Aulchenko YS, Felix JF, Rivadeneira F, Uitterlinden AG,
Hofman A, Imboden M, Nitsch D, Brandstätter A, Kollerits B, Kedenko L,
Mägi R, Stumvoll M, Kovacs P, Boban M, Campbell S, Endlich K, Völzke H,
Kroemer HK, Nauck M, Völker U, Polasek O, Vitart V, Badola S, Parker AN,
Ridker PM, Kardia SL, Blankenberg S, Liu Y, Curhan GC, Franke A, Rochat T,
Paulweber B, Prokopenko I, Wang W, Gudnason V, Shuldiner AR, Coresh J,
Schmidt R, Ferrucci L, Shlipak MG, van Duijn CM, Borecki I, Krämer BK,
Rudan I, Gyllensten U, Wilson JF, Witteman JC, Pramstaller PP, Rettig R,
Hastie N, Chasman DI, Kao WH, Heid IM, Fox CS: New loci associated with
kidney function and chronic kidney disease. Nat Genet 2010, 42:376-384.
2. Yoshida T, Kato K, Fujimaki T, Yokoi K, Oguri M, Watanabe S, Metoki N,
Yoshida H, Satoh K, Aoyagi Y, Nishigaki Y, Suzuki T, Nozawa Y, Yamada Y:
Association of genetic variants with chronic kidney disease in Japanese
individuals. Clin J Am Soc Nephrol 2009, 4:883-890.
3.Luttropp K, Lindholm B, Carrero JJ, Glorieux G, Schepers E, Vanholder R,
Schalling M, Stenvinkel P, Nordfors L: Genetics/Genomics in chronic
kidney disease–towards personalized medicine? Semin Dial 2009,
22:417-422.
4. Rao M, Wong C, Kanetsky P, Girndt M, Stenvinkel P, Reilly M, Raj DS:
Cytokine gene polymorphism and progression of renal and
cardiovascular diseases. Kidney Int 2007, 72:549-556.
5.Balakrishnan VS, Guo D, Rao M, Jaber BL, Tighiouart H, Freeman RL,
Huang C, King AJ, Pereira BJ, HEMO Study Group: Cytokine gene
polymorphisms in hemodialysis patients: association with comorbidity,
functionality, and serum albumin. Kidney Int 2004, 65:1449-1460.
6. Carrero JJ, Park SH, Axelsson J, Lindholm B, Stenvinkel P: Cytokines,
atherogenesis, and hypercatabolism in chronic kidney disease: a
dreadful triad. Semin Dial 2009, 22:381-386.
Silverstein DM: Inflammation in chronic kidney disease: role in the
progression of renal and cardiovascular disease. Pediatr Nephrol 2009,
24:1445-1452.
Mittal RD, Manchanda PK: Association of interleukin (IL)-4 intron-3 and IL-
6 -174 G/C gene polymorphism with susceptibility to end-stage renal
disease. Immunogenetics 2007, 59:159-165.
Tindall EA, Severi G, Hoang HN, Ma CS, Fernandez P, Southey MC,
English DR, Hopper JL, Heyns CF, Tangye SG, Giles GG, Hayes VM:
Australian Prostate Cancer BioResource: Comprehensive analysis of the
cytokine-rich chromosome 5q31.1 region suggests a role for IL-4 gene
variants in prostate cancer risk. Carcinogenesis 2010, 31:1748-1754.
Komatsu Y, Tai H, Galicia JC, Shimada Y, Endo M, Akazawa K, Yamazaki K,
Yoshie H: Interleukin-6 (IL-6)–373 A9T11 allele is associated with reduced
susceptibility to chronic periodontitis in Japanese subjects and
decreased serum IL-6 level. Tissue Antigens 2005, 65:110-114.
Buckham TA, McKnight AJ, Benevente D, Courtney AE, Patterson CC,
Simmonds M, Gough S, Middleton D, Borrows R, Maxwell AP: Evaluation of
five interleukin genes for association with end-stage renal disease in
white Europeans. Am J Nephrol 2010, 32:103-108.
Hamajima N, J-MICC Study Group: The Japan Multi-Institutional
Collaborative Cohort Study (J-MICC Study) to detect gene-environment
interactions for cancer. Asian Pac J Cancer Prev 2007, 8:317-323.
Wakai K, Hamajima N, Okada R, Naito M, Morita E, Hishida A, Kawai S,
Nishio K, Yin G, Asai Y, Matsuo K, Hosono S, Ito H, Watanabe M, Kawase T,
Suzuki T, Tajima K, Tanaka K, Higaki Y, Hara M, Imaizumi T, Taguchi N,
Nakamura K, Nanri H, Sakamoto T, Horita M, Shinchi K, Kita Y, Turin TC,
Rumana N, Matsui K, Miura K, Ueshima H, Takashima N, Nakamura Y,
Suzuki S, Ando R, Hosono A, Imaeda N, Shibata K, Goto C, Hattori N,
Fukatsu M, Yamada T, Tokudome S, Takezaki T, Niimura H, Hirasada K,
Nakamura A, Tatebo M, Ogawa S, Tsunematsu N, Chiba S, Mikami H,
Kono S, Ohnaka K, Takayanagi R, Watanabe Y, Ozaki E, Shigeta M,
Kuriyama N, Yoshikawa A, Matsui D, Watanabe I, Inoue K, Ozasa K, Mitani S,
Arisawa K, Uemura H, Hiyoshi M, Takami H, Yamaguchi M, Nakamoto M,
Takeda H, Kubo M, Tanaka H, J-MICC Study Group: Profile of participants
and genotype distributions of 108 polymorphisms in a cross-sectional
study of associations of genotypes with lifestyle and clinical factors: A
Project in the Japan Multi-institutional Collaborative Cohort (J-MICC)
Study. J Epidemiol 2011, 21:223-235.
Okada R, Suzuki K, Ito Y, Nishio K, Ishida Y, Kawai S, Goto Y, Naito M,
Wakai K, Hamajima N: Association between decreased kidney function
and endotoxin receptor CD14 C-159T polymorphism among Japanese
health check-up examinees. Ren Fail 2007, 29:967-972.
Nakashima H, Miyake K, Inoue Y, Shimizu S, Akahoshi M, Tanaka Y, Otsuka T,
Harada M: Association between IL-4 genotype and IL-4 production in the
Japanese population. Genes Immun 2002, 3:107-109.
Hamajima N, Naito M, Kondo T, Goto Y: Genetic factors involved in the
development of Helicobacter pylori-related gastric cancer. Cancer Sci
2006, 97:1129-1138.
Oda K, Tanaka N, Arai T, Araki J, Song Y, Zhang L, Kuchiba A, Hosoi T,
Shirasawa T, Muramatsu M, Sawabe M: Polymorphisms in pro- and anti-
inflammatory cytokine genes and susceptibility to atherosclerosis: a
pathological study of 1503 consecutive autopsy cases. Hum Mol Genet
2007, 16:592-599.
Ohnishi Y, Tanaka T, Ozaki K, Yamada R, Suzuki H, Nakamura Y: A high-
throughput SNP typing system for genome-wide association studies.
J Hum Genet 2001, 46:471-477.
Matsuo S, Imai E, Horio M, Yasuda Y, Tomita K, Nitta K, Yamagata K,
Tomino Y, Yokoyama H, Hishida A, Collaborators developing the Japanese
equation for estimated GFR: Revised Equations for Estimated GFR From
Serum Creatinine in Japan. Am J Kidney Dis 2009, 53:982-992.
National Kidney Foundation: K/DOQI clinical practice guidelines for
chronic kidney disease: evaluation, classification, and stratification. Am J
Kidney Dis 2002, 39:S1-266.
von der Thüsen JH, Kuiper J, van Berkel TJ, Biessen EA: Interleukins in
atherosclerosis: molecular pathways and therapeutic potential.
Pharmacol Rev 2003, 55:133-166.
Marousi S, Ellul J, Antonacopoulou A, Gogos C, Papathanasopoulos P,
Karakantza M: Functional polymorphisms of interleukin 4 and interleukin
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
Okada et al. BMC Nephrology 2012, 13:2
http://www.biomedcentral.com/1471-2369/13/2
Page 7 of 8

Page 8

10 may predict evolution and functional outcome of an ischaemic
stroke. Eur J Neurol 2011, 18:637-643.
Müller-Steinhardt M, Fricke L, Müller B, Ebel B, Kirchner H, Härtel C:
Cooperative influence of the interleukin-6 promoter polymorphisms
-597, -572 and -174 on long-term kidney allograft survival. Am J
Transplant 2004, 4:402-406.
Smallwood L, Allcock R, van Bockxmeer F, Warrington N, Palmer LJ,
Iacopetta B, Norman PE: Polymorphisms of the interleukin-6 gene
promoter and abdominal aortic aneurysm. Eur J Vasc Endovasc Surg 2008,
35:31-36.
Imai E, Horio M, Yamagata K, Iseki K, Hara S, Ura N, Kiyohara Y, Makino H,
Hishida A, Matsuo S: Slower decline of glomerular filtration rate in the
Japanese general population: a longitudinal 10-year follow-up study.
Hypertens Res 2008, 31:433-441.
Terry CF, Loukaci V, Green FR: Cooperative influence of genetic
polymorphisms on interleukin 6 transcriptional regulation. J Biol Chem
2000, 275:18138-18144.
23.
24.
25.
26.
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Cite this article as: Okada et al.: Pro-/anti-inflammatory cytokine gene
polymorphisms and chronic kidney disease: a cross-sectional study.
BMC Nephrology 2012 13:2.
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