Journal of Human Genetics (2012) 57, 46–51& 2012 The Japan Society of Human Genetics All rights reserved 1434-5161/12 $32.00
www.nature.com/jhg

ORIGINAL ARTICLE

Genetic variations in the CYP17A1 and NT5C2 genes
are associated with a reduction in visceral andsubcutaneous fat areas in Japanese women
Kikuko Hotta1, Aya Kitamoto1, Takuya Kitamoto1, Seiho Mizusawa2, Hajime Teranishi2, Tomoaki Matsuo3,
Yoshio Nakata3, Hideyuki Hyogo4, Hidenori Ochi4, Takahiro Nakamura5, Seika Kamohara6,
Nobuyuki Miyatake7, Kazuaki Kotani8, Ryoya Komatsu9, Naoto Itoh10, Ikuo Mineo11, Jun Wada12,
Masato Yoneda13, Atsushi Nakajima13, Tohru Funahashi14, Shigeru Miyazaki15, Katsuto Tokunaga16,
Hiroaki Masuzaki17, Takato Ueno18, Kazuaki Chayama4, Kazuyuki Hamaguchi19, Kentaro Yamada20,
Toshiaki Hanafusa21, Shinichi Oikawa22, Hironobu Yoshimatsu23, Toshiie Sakata23, Kiyoji Tanaka3,
Yuji Matsuzawa8, Kazuwa Nakao1,24 and Akihiro Sekine1,2
Visceral fat accumulation has an important role in increasing the morbidity and mortality rates, by increasing the risk ofdeveloping several metabolic disorders, such as type 2 diabetes, dyslipidemia and hypertension. New genetic loci that areassociated with increased systolic and diastolic blood pressures have been identified by genome-wide association studies in
Caucasian populations. This study investigates whether single nucleotide polymorphisms (SNPs) that confer susceptibility tohigh blood pressure are also associated with visceral fat obesity. We genotyped 1279 Japanese subjects (556 men and 723
women) who underwent computed tomography for measuring the visceral fat area (VFA) and subcutaneous fat area (SFA) atthe following SNPs: FGF5 rs16998073, CACNB2 rs11014166, C10orf107 rs1530440, CYP17A1 rs1004467, NT5C2
rs11191548, PLEKHA7 rs381815, ATP2B1 rs2681472 and rs2681492, ARID3B rs6495112, CSK rs1378942, PLCD3
rs12946454, and ZNF652 rs16948048. In an additive model, risk alleles of the CYP17A1 rs1004467 and NT5C2
rs11191548 were found to be significantly associated with reduced SFA (P¼0.00011 and 0.0016, respectively). When theanalysis was performed separately in men and women, significant associations of rs1004467 (additive model) and rs11191548(recessive model) with reduced VFA (P¼0.0018 and 0.0022, respectively) and SFA (P¼0.00039 and 0.00059, respectively)
were observed in women, but not in men. Our results suggest that polymorphisms in the CYP17A1 and NT5C2 genes influencea reduction in both visceral and subcutaneous fat mass in Japanese women.
Journal of Human Genetics (2012) 57, 46–51; doi:10.1038/jhg.2011.127; published online 10 November 2011
Keywords: computed tomography; CYP17A1; Japanese subjects; NT5C2; sexual dimorphism; subcutaneous fat area; visceral fat area

INTRODUCTION
Metabolic syndrome is a combination of multiple risk factors,
including central obesity, impaired glucose tolerance, dyslipidemia

and hypertension, which increases cardiovascular disease morbidity
and mortality.1 Several studies have indicated that the intra-abdominal
adipose tissue has a central role in metabolic syndrome, as the

1EBM Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan; 2Center for Genomic Medicine, Unit of Genome Informatics, Kyoto University Graduate
School of Medicine, Kyoto, Japan; 3Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Japan; 4Department of Medicine and Molecular
Science, Division of Frontier Medical Science, Programs for Biomedical Research, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan; 5Laboratory
for Mathematics, National Defense Medical College, Tokorozawa, Japan; 6Health Science University, Yamanashi, Japan; 7Department of Hygiene, Faculty of Medicine, Kagawa
University, Kagawa, Japan; 8Department of Metabolic Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan; 9Rinku General Medical Center, Osaka, Japan;
10Toyonaka Municipal Hospital, Osaka, Japan; 11Otemae Hospital, Osaka, Japan; 12Department of Medicine and Clinical Science, Okayama University Graduate School of
Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan; 13Division of Gastroenterology, Yokohama City University Graduate School of Medicine, Yokohama, Japan;
14Department of Metabolism and Atherosclerosis, Graduate School of Medicine, Osaka University, Osaka, Japan; 15Tokyo Postal Services Agency Hospital, Tokyo, Japan; 16Itami
City Hospital, Hyogo, Japan; 17Division of Endocrinology and Metabolism, Second Department of Internal Medicine, University of the Ryukyus Faculty of Medicine, Okinawa,
Japan; 18Research Center for Innovative Cancer Therapy, Kurume University, Kurume, Japan; 19Department of Community Health and Gerontological Nursing, Faculty of
Medicine, Oita University, Oita, Japan; 20Division of Endocrinology and Metabolism, Department of Medicine, Kurume University, Kurume, Japan; 21Department of Internal
Medicine (I), Osaka Medical College, Osaka, Japan; 22Division of Endocrinology and Metabolism, Department of Medicine, Nippon Medical School, Tokyo, Japan; 23Department ofInternal Medicine 1, Faculty of Medicine, Oita University, Oita, Japan and 24Department of Medicine and Clinical Science, Kyoto University Graduate School of Medicine, Kyoto,
Japan
Correspondence: Dr K Hotta, EBM Research Center, Kyoto University Graduate School of Medicine, Yoshida-Konoecho, Sakyo-ku, Kyoto 606-8501, Japan.
E-mail: kikukoh@kuhp.kyoto-u.ac.jp
Received 1 August 2011; revised 4 October 2011; accepted 19 October 2011; published online 10 November 2011

CYP17A1 and NT5C2 genes, and VFA and SFA
K Hotta et al47

accumulated visceral adipose tissue leads to alterations in the plasma
levels of adipocytokines, resulting in the development of dyslipidemia,
hypertension and insulin resistance.2,3 Intra-abdominal fat accumulation (central adiposity) is determined by waist circumference, waist–
hip ratio, biological impedance or the visceral fat area (VFA) measured
using computed tomography.1,4,5 There is abundant evidence thatbody fat distribution is influenced by genetic loci.6–8 Individual
variation in waist–hip ratio is heritable, with heritability estimatesranging from 22 to 61%. Recent genome-wide association studies(GWAS) showed that genetic loci were associated with waist circumference and waist–hip ratio in the Caucasian population.9,10
We previously reported that the rs1558902 and rs1421085 genotypesof the fat mass- and obesity-associated gene (FTO) were significantly
associated with VFA, as well as with the subcutaneous fat area (SFA)
and body mass index (BMI) in the Japanese population.11
Recent progress in GWAS has increased the number of known
genetic susceptibility loci for obesity.12–16 We investigated the association between the single nucleotide polymorphisms (SNPs) underlying
susceptibility to obesity and fat distribution (as determined bycomputed tomography), and found that rs7498665 in the SH2B
adaptor protein 1 (SH2B1) gene was associated with VFA, uncovering
the genetic background of central obesity.17
GWAS, and meta-analysis of GWAS, have identified various diseaseassociated genetic variations.18 Hypertension is one of the risk factorsof metabolic syndrome and is considerably related to central obesity.
Obesity-associated allele of rs1558902 and rs1421085 in the FTO gene
were associated with hypertension, but not that of rs7498665 in theSH2B1 gene in the Japanese population.19 The genetic variations
associated with hypertension have been identified by GWAS.20,21
In this study, we investigate whether the recently reported hypertension-related loci are also associated with VFA, which is anotherimportant factor responsible for metabolic syndrome.
MATERIALS AND METHODS
Study subjects
We enrolled 1279 Japanese subjects from outpatient clinics; these patientsagreed to undergo computed tomography testing (in the supine position) to
determine VFA and SFA values at the umbilical level (L4–L5), as previously
reported.17 Both VFA and SFA values were calculated using the FatScan
software program (N2system, Osaka, Japan).22 The patients visited the hospitals to undergo treatment for obesity and/or metabolic abnormalities, such as
hypertension, dyslipidemia and type 2 diabetes. Patients with secondary obesityand obesity-related hereditary disorders were excluded from this study. Patientswith disease (such as cancer, and renal, heart and hepatic failure), or under
treatment (such as corticosteroid and chemotherapy) that strongly affects bodyweight, were also excluded. Athletes were also excluded from this study. Clinicaldata were recorded at the first visit to the hospital. The clinical characteristics ofthe subjects are summarized in Table 1. Metabolic syndrome and metabolic
abnormalities were diagnosed according to the criteria released by the JapaneseCommittee for the Diagnostic Criteria of Metabolic Syndrome in April 2005.4,5Written informed consent was obtained from each subject, and the protocol
was approved by the ethics committee of each institution and by that of Kyoto
University.

DNA extraction and SNP genotyping
Genomic DNA was extracted from the blood samples collected from eachsubject using the Genomix kit (Talent Srl, Trieste, Italy). We selected 12 SNPs
that were previously identified as susceptibility loci for hypertension by GWAS
in Caucasian populations,20,21 and constructed Invader probes (Third Wave
Technologies, Madison, WI, USA) for each. The 12 selected SNPs were as
follows: rs16998073 in the fibroblast growth factor 5 (FGF5) gene; rs11014166
in the calcium channel, voltage-dependent, b-2 subunit (CACNB2) gene;rs1530440 in the chromosome 10 open reading frame 107 (C10orf107) gene;

Table 1 Clinical characteristics of the subjects
Men

Women

Total

556
49.4±12.2
30.2±6.1723
52.2±11.3
28.1±5.31279
51.0±11.8
29.0±5.8

155.3±67.7
206.7±108.6

123.9±66.1
226.5±103.7

97.5±11.3

99.8±53.6
241.6±97.2
91.8±10.3

Dyslipidemia
Hypertension

293 (53%)379 (68%)244 (34%)452 (63%)537 (42%)831 (65%)

Impaired fasting glucose
Metabolic syndrome

177 (32%)248 (45%)176 (24%)
162 (22%)353 (28%)410 (32%)nAge (years)
BMI (kg m#2)
VFA (cm2)
SFA (cm2)
Waist circumference (cm)94.2±11.1

Prevalence of metabolic disease

Abbreviations: BMI, body mass index; SFA, subcutaneous fat area; VFA, visceral fat area.
Data are represented as mean±s.d.

rs1004467 in the cytochrome P450, family 17, subfamily A, polypeptide 1(CYP17A1) gene; rs11191548 in the 5¢-nucleotidase, cytosolic II (NT5C2) gene;rs381815 in the pleckstrin homology domain containing, family A member 7(PLEKHA7) gene; rs2681472 and rs2681492 in the ATPase, Ca2+ transporting,plasma membrane 1 (ATP2B1) gene; rs6495112 in the AT-rich interactive
domain 3B (BRIGHT-like) (ARID3B) gene; rs1378942 in the c-src tyrosine
kinase (CSK) gene; rs12946454 in the phospholipase C, delta 3 (PLCD3) gene;and rs16948048 in the zinc finger protein 652 (ZNF652) gene. The SNPs were
genotyped using Invader assays, as previously described.23 The success rate ofthese assays was 499.0%.

Statistical analysis
For the additive model, we coded the genotypes as 0, 1 or 2 depending on thenumber of copies of the risk alleles. For the recessive model, homozygosity withthe risk allele was coded as 1 and the others were coded as 0. Risk alleles refer tothe hypertension-associated alleles, according to previous reports.20,21 Multiple
linear regression analyses were performed to test the independent effect of therisk alleles on BMI, VFA and SFA, by taking into account the effects of othervariables (that is, age and gender) that were assumed to be independent of theeffect of each SNP. The values of BMI, VFA and SFA were logarithmicallytransformed before performing the multiple linear regression analysis. Differences in the quantities of anthropometric parameters among the different
genotypes were assessed by the analysis of covariance, by taking into accountthe effects of other variables (that is, age and/or institute). Hardy–Weinberg
equilibrium was assessed using the w2-test.24 To test SNP"SNP epistasis, weused a linear regression model for each SNP1 and SNP2, and fit the model in theform of Y¼b0+b1"SNP1+b2"SNP2+b3"SNP1"SNP2+b4"age+b5"gender.
Although we collected the samples at the region of Hondo (Kanto, Kinki,
Chugoku and Kyushu; Supplementary Table 1), we performed Wright’s
F-statistics25 to evaluate the difference in the population structures of oursample using randomly selected 31 SNPs. We divided our samples into twogroups (SFA 4208 cm2 and p208 cm2). Median of SFA (208 cm2) was used asa cut-off value. The results indicated that the population structure of the twogroups were almost the same in view of a very small FST value between both thegroups (mean FST¼0.00023). Statistical analysis was performed using R software (http://www.r-project.org/). P-values were assessed with a Bonferroni
correction and Po0.0042 (0.05/12) was considered statistically significant.

RESULTSThe clinical characteristics and genotypes of the subjects are shown in
Tables 1 and 2, respectively. All the SNPs were in Hardy–Weinberg
equilibrium and the minor allele frequencies did not diverge fromthose reported in the HapMap database. The BMI, VFA and SFA
values for each SNP genotype are reported in Table 3. Multiple linear
regression analyses of the anthropometric parameters with respect tothe 12 analyzed SNPs are shown in Table 4. The A-allele of rs1004467
Journal of Human Genetics

CYP17A1 and NT5C2 genes, and VFA and SFA
K Hotta et al
48

Table 2 Genotypic characteristics of the subjects
SNP ID

CHR

Position (Build 36.3)

Nearby gene

Allele 1/2

BP-associated allele

Genotype

HWE P-value

rs16998073
rs11014166

4
10

81 403 365
18 748 804

FGF5
CACNB2

T/A
T/A

T
A

120/514/644
4/124/1151

0.24
0.73

rs1530440
rs1004467

1010

63 194 597
104 584 497

C10orf107
CYP17A1

T/C
A/G

C
A

30/296/953
559/567/153

0.22
0.62

rs11191548
rs38181510
11

104 836 168
16 858 844

NT5C2
PLEKHA7

T/C
C/T

T
T

675/504/100
842/381/56

0.66
0.13

rs2681472
rs2681492

1212

88 533 090
88 537 220

ATP2B1ATP2B1

A/G
C/T

A
T

546/562/171
168/561/549

0.17
0.19

rs6495112
rs1378942

15
15

72 619 851
72 864 420

ARID3B
CSK

A/C
A/C

A
C

530/575/173
49/410/817

0.39
0.78

rs12946454
rs16948048

17
17

40 563 647
44 795 465

PLCD3
ZNF652

T/A
G/A

T
G

34/343/901
18/326/935

0.84
0.08

Abbreviations: BP, blood pressure; CHR, chromosome; HWE, Hardy–Weinberg equilibrium.

Table 3 Mean BMI, VFA and SFA for 12 blood pressure risk variants
Mean±s.d.

SNP ID

Nearby geners16998073

FGF5

rs11014166
rs1530440

CACNB2
C10orf107

rs1004467
rs11191548

CYP17A1
NT5C2

rs381815
rs2681472

PLEKHA7
ATP2B1

rs2681492

ATP2B1

rs6495112
rs1378942

ARID3B
CSK

rs12946454
rs16948048

PLCD3
ZNF652

BMI (kg m#2)

VFA (cm2)

SFA (cm2)

Genotype

Genotype

Genotype

11

12

22

11

12

22

11

12

22

28.8±4.7
27.0±2.729.0±5.8
29.6±6.1

29.0±6.0
28.9±5.8

126.2±66.1
123.4±82.2

121.6±66.5
136.7±68.2

125.3±65.9122.5±65.8

227.4±98.3
178.6±35.8224.5±111.0
233.7±106.4

227.7±98.7
225.8±103.6

30.8±6.5
28.4±5.6

28.6±5.4
29.5±6.1

29.1±5.929.4±5.2

129.8±63.1
117.5±64.9120.2±66.4
130.6±68.5124.9±66.2
122.5±59.3

236.4±119.2
215.5±92.7

223.0±91.4
231.4±111.5

227.2±106.9
247.9±107.9

28.6±5.829.2±5.929.2±5.829.0±7.1

29.5±5.928.7±5.728.8±5.4
28.7±5.2

28.9±5.1
27.8±4.3
29.0±7.0
29.3±5.9

119.2±65.3
124.1±64.2
127.1±67.5
121.9±66.3130.9±68.6
124.3±71.5
121.5±64.8121.4±64.8120.5±55.7
117.9±55.9
121.8±65.8
127.0±67.4

217.2±96.0
229.4±105.9

238.5±113.2
221.5±101.6

228.1±98.8
215.3±83.1

227.4±100.4
234.6±123.9

223.5±100.3
221.9±98.3

28.9±5.828.0±4.2
30.1±8.2
28.1±2.829.0±5.728.9±6.1
28.6±5.0
29.4±5.929.3±6.2
29.1±5.729.1±5.928.9±5.8

122.5±63.4
110.0±63.3
137.2±80.0
128.6±73.7

125.0±69.2
121.8±62.4
123.0±67.4
124.8±65.9

124.9±64.3
125.6±67.6
123.7±65.1
123.5±66.1

223.7±106.5
222.9±84.5
254.4±105.0
215.0±60.6

229.5±102.6
225.9±104.3
216.4±93.7
227.0±96.3

233.1±123.6
228.7±102.3
225.1±99.2
227.0±104.7
229.2±107.0
226.5±106.9

Abbreviations: BMI, body mass index; SFA, subcutaneous fat area; SNP, single nucleotide polymorphism; VFA, visceral fat area.
11, allele1/allele1; 12, allele1/allele2; 22, allele2/allele2. Allele 1 and allele 2 of each SNP is indicated in Table 2.

in the CYP17A1 gene was significantly associated with reduced BMI(P¼0.0018). The other SNPs were not significantly associated with
BMI. No SNP was significantly associated with VFA. The A-allele ofrs1004467 in the CYP17A1 and the T-allele of rs11191548 in the
NT5C2 gene were significantly associated with reduced SFA. These
SNPs are in linkage disequilibrium, as reported in the HapMap
database (D¢¼0.98, r2¼0.71), and the A-allele of rs1004467 andT-allele of rs11191548 are reported to be risk alleles for increased
blood pressure.20,21
BMI, VFA and SFA are known to be affected by gender; therefore,
we compared rs1004467 and rs11191548 alleles with anthropometricparameters (BMI, VFA and SFA) in men and women independently(Table 5). Associations of both SNPs with VFA (P¼0.0018 andP¼0.0043) and SFA (P¼0.00039 and P¼0.0021) in women weresignificant, except the association of T-allele of rs11191548 with
VFA. The VFA and SFA values of the rs11191548 genotype suggestthat the recessive model would be the best-fitted model both in men
Journal of Human Genetics

and women. By using the recessive model, results revealed significant
associations of the rs11191548 genotype with VFA (P¼0.0022) and
SFA in women (P¼0.00059). These SNPs did not show any association
with VFA or SFA in men, suggesting that they exhibit sexual
dimorphism, as has been suggested in a recent report.26 As bothrs1004467 and rs11191548 were associated with a reduction in both
VFA and SFA, we examined the association of these SNPs with total fat
area. The SNPs were significantly associated with total fat area
(P¼0.00012 at rs1004467, P¼0.00052 at rs11191548 in additivemodel) in women, but not in men, suggesting that risk allele forhigh blood pressure of these SNPs are associated with reduced
adiposity in women. The very small mean FST value (0.00023)
indicated no population structure in our subjects. As we collected
the samples from nine institutes in four regions of Japan (Supplementary Table 1), we tested multiple linear regression analysis with age
and institute as explanatory variables in men and women. Very similar
results were observed. In additive model, significant associations of theCYP17A1 and NT5C2 genes, and VFA and SFA
K Hotta et al
49

Table 4 Relationship between blood pressure-associated loci and adiposity measures
BMI
SNP IDb

Nearby geners16998073

FGF5

rs11014166
rs1530440

CACNB2
C10orf107

rs1004467
rs11191548

CYP17A1
NT5C2

rs381815
rs2681472

PLEKHA7
ATP2B1

rs2681492
rs6495112

ATP2B1
ARID3B

rs1378942

CSK

rs12946454
rs16948048

PLCD3
ZNF652

VFA

s.e.

b

P-value

SFA

s.e.

0.003

0.55

0.010

0.78

0.007
0.004

0.48
0.71

#0.043
0.010

0.021
0.014

0.043
0.48

0.003
0.003

0.0018
0.015

0.010
0.011

0.027
0.078

#0.007
0.002

0.004
0.003

0.046
0.43

#0.022#0.019#0.004
0.006

0.012
0.010

0.76
0.52

0.003
#0.002

0.003
0.003

0.34
0.45

0.006
#0.004

0.010
0.010

0.54
0.65

0.010

0.012

0.40

0.009
0.008

0.013
0.014

0.50
0.57

#0.002#0.005#0.002#0.010#0.008

0.005

0.004

0.20

#0.003
0.005

0.004
0.004

0.39
0.30

#0.003b

P-values.e.

P-value

0.008

0.22

0.017
0.011

0.63
0.64

0.008
0.008

0.000110.0016#0.015
0.005

0.009
0.008

0.10
0.49

0.006
#0.007

0.008
0.008

0.40
0.36

0.005

0.009

0.61

#0.011
0.005

0.010
0.011

0.28
0.67

#0.010#0.008#0.005#0.030#0.026Abbreviations: BMI, body mass index; SFA, subcutaneous fat area; SNP, single nucleotide polymorphism; VFA, visceral fat area.
Data were derived from a linear regression analysis. The values of BMI, VFA and SFA were logarithmically transformed. Logarithmically transformed BMI, VFA and SFA were adjusted for age andgender. Tested alleles are risk alleles of increased blood pressure.

Table 5 Relationship between rs1004467 and rs11191548, and adiposity in men and women
Values at each genotype

Additive model

SNP ID (gene)

Phenotype

Gender111222

rs1004467(CYP17A1)

n

Men
Women

BMI (kg m#2)

Men
Women

233
326
29.7±6.6259
308
30.6±5.9648930.1±5.1

27.6±4.6
152.9±67.7

28.5±6.0
160.6±69.2

28.9±5.3
142.8±59.9

92.3±49.2
198.6±103.0
227.6±82.7

105.4±56.8
211.9±113.8
248.0±106.9

107.8±54.7
215.4±106.7
271.2±103.3

289

220

47

386
30.0±6.8
27.6±4.7284
30.6±5.4
28.7±6.1

5329.4±5.4
28.5±4.8

153.8±68.0
93.3±49.3

161.3±69.3
107.4±58.1

137.2±54.8
105.8±52.8

202.1±107.5
228.5±84.9

214.3±111.3
257.4±111.1

199.9±102.5
253.0±89.0

rs11191548

VFA (cm2)

Men

SFA (cm2)

Women
Men

n

Women
Men

BMI (kg m#2)

Women
Men

VFA (cm2)

Women
Men

SFA (cm2)

Women
Men

(NT5C2)

Women

Recessive modelb (s.e.)P-valueb (s.e.)P-value#0.011 (0.005)#0.010 (0.004)

0.029
0..0170.00850.019

0.004 (0.014)

0.78#0.017 (0.006)#0.013 (0.006)#0.044 (0.014)#0.028 (0.013)

0.00180.037

0.00140.047#0.033 (0.009)

0.00039#0.061 (0.019)#0.036 (0.018)#0.040 (0.013)

0.0020#0.007 (0.005)

0.19
0.021
0.65

#0.013 (0.006)

0.049#0.010 (0.004)
0.007 (0.014)#0.043 (0.015)#0.023 (0.014)

0.00430.10#0.059 (0.019)#0.035 (0.018)

0.00220.048#0.031 (0.010)

0.0021#0.012 (0.019)#0.015 (0.006)#0.008 (0.018)#0.044 (0.013)

0.52

0.00800.65

0.00059

Abbreviations: BMI, body mass index; SFA, subcutaneous fat area; SNP, single nucleotide polymorphism; VFA, visceral fat area.
Values are shown as the mean±s.d. Data were derived from a linear regression analysis. The values of BMI, VFA and SFA were logarithmically transformed. Logarithmically transformed BMI, VFA
and SFA were adjusted for age. Tested alleles (allele1 at both SNPs) are risk alleles of increased blood pressure.

rs1004467 and rs11191548 genotype with VFA (P¼0.0015 and 0.0011,
respectively) and SFA (P¼0.00021 and 0.00062, respectively) wereobserved in women (Supplementary Table 2). Statistical analysis using
analysis of covariance indicated significant associations of thers1004467 and rs11191548 genotype with VFA (P¼0.0020 and
0.0015, respectively) and SFA (P¼0.00033 and 0.00042, respectively)
in women (Supplementary Table 2). As some diabetes medications
have an effect on adiposity,27 we performed the analysis excluding 147
type 2 diabetic patients treated with sulfonylureas, biguanides andthiazolidinediones We found the similar significant associations of thers1004467 and rs11191548 genotype with VFA and SFA in women(Supplementary Table 3).
We have reported that rs1558902 in the FTO gene is associated withboth VFA and SFA,11 and that rs7498665 in the SH2B1 gene isassociated with VFA.17 Thus, we examined SNP"SNP epistasis inmen, women and all subjects. The combination of rs1004467 andrs7498665 exhibited no epistatic effect on VFA in men (P¼0.43),
women (P¼0.86) or all subjects (P¼0.76). The combination of
rs1004467 and rs1558902 did not show epistatic effect on VFA inmen (P¼0.99), women (P¼0.53) or all subjects (P¼0.60), or on SFA
in men (P¼0.63), women (P¼0.83) or all subjects (P¼0.89).
Among the SNPs tested in this study, rs16998073 in the FGF5 geneand rs11191548 in the NT5C2 gene were associated with increased
systolic blood pressure (Po0.05). Rs11191548 in the NT5C2 gene
were also associated with hypertension (Po0.05). We could replicate
the association between blood pressure and the above two SNPs thatwere reported to be strongly associated with blood pressure in theJapanese population (Supplementary Table 4).28
Journal of Human Genetics

CYP17A1 and NT5C2 genes, and VFA and SFA
K Hotta et al
50

DISCUSSION
In this study, we showed that the A-allele of rs1004467 in the CYP17A1
and the T-allele of rs11191548 in the NT5C2 gene were significantly
associated with reduced VFA, SFA and total fat area in women.
Association of T-allele of rs11191548 in the NT5C2 gene withincreased systolic blood pressure and hypertension was replicated inour sample, as reported previously.28 Our hypothesis was that theserisk alleles would be associated with increased VFA and/or SFA as
increased adiposity is a risk for hypertension;4,5 however, these alleles
affected decreased adiposity. The associations between SNPs andincreased blood pressure/hypertension were evaluated after being
adjusted for BMI, age and gender. Thus, the SNPs associated withvisceral fat obesity-related and gender-dependent hypertension would
be excluded in the screening stage. Indeed, recent analysis has shownthat genetic variation near insulin receptor substrate 1 (IRS1) is
associated with reduced adiposity and an impaired metabolic profile.29
Thus, it is likely that rs1004467 and rs11191548 are associated with
reduced VFA and SFA, as well as with hypertension in women.
The SNPs rs1004467 and rs11191548 were not associated withBMI in men or women, as reported for rs2943650 near IRS1.29 As
BMI represents both fat and lean body mass, our observationsuggests that these SNPs influence a reduction in VFA and SFA, or
influence an increased percentage of lean body mass. The significant
associations of rs1004467 and rs1191548 with reduced VFA and SFA
were observed in women, but not in men. The rs1004467 SNP is
located in the intron of the CYP17A1 gene. CYP17A1 is involved in thebiosynthesis of glucocorticoids, mineral corticoids, androgens andestrogens.30 The rs1004467 risk allele may reflect differences in
CYP17A1 gene expression that alter the biosynthesis of steroid
hormones, leading to hypertension and reduced adiposity inwomen. The region of linkage disequilibrium that includes
rs1004467 and rs11191548 contains a couple of genes in addition to
CYP17A1: NT5C2, arsenic (+3 oxidation state) methyltransferase(AS3MT) and cyclin M2 (CNNM2). NT5C2 is a cytosolic IMP/
GMP selective 5¢-nucleotidase and involved in nucleic acids or DNA
synthesis.31 CNNM2 (ancient conserved domain protein, ACDP2) is atransporter of magnesium, which is required for the catalytic activityof numerous metalloenzymes.32 Thus, these genes would be importantfor metabolism in adipocyte hyperplasia and hypertrophy. Further
investigation is warranted to elucidate the functional SNPs andsusceptibility genes.
We have previously reported that FTO rs1558902 is associated with
VFA and SFA, and that SH2B1 rs7498665 is associated with VFA.11,17
Epistasis, or gene–gene interaction, has recently received much attention in human genetics.33 In this study, the effect of these SNPs on
VFA and SFA was additive, and an epistatic effect was not observed.
In summary, we showed that CYP17A1 rs1004467 and NT5C2
rs11191548 SNPs are significantly associated with both reduced VFA
and SFA in women. Our results suggest that the region encompassing
CYP17A1 to NT5C2 has a role in reducing visceral and subcutaneous
fat mass. However, these results require confirmation in otherpopulations.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
ACKNOWLEDGEMENTS
This work was supported by a Grant-in-Aid from the Ministry of Education,
Science, Sports, and Culture of Japan (21591186 to Hotta, K., 23701082 to
Kitamoto, T., and 23791027 to Kitamoto, A.), and by the Mitsui Life Science
Social Welfare Foundation.
Journal of Human Genetics

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Supplementary Information accompanies the paper on Journal of Human Genetics website (http://www.nature.com/jhg)

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