Molecular Biology Reports

, Volume 39, Issue 5, pp 5709–5717 | Cite as

Association between vitamin D receptor gene polymorphisms and bone mineral density in Chinese women

Article

Abstract

Vitamin D receptor (VDR) is implicated in the regulation of bone mineral density (BMD). In this study, we performed a meta-analysis to evaluate the association between the VDRBsmI (rs1544410) and ApaI (rs7975232) polymorphisms and BMD in Chinese women. Literature was retrieved from PubMed and other databases. The studies on the association between VDRBsmI and ApaI genotypes and BMD at the lumbar spine, the femoral neck, the trochanter or the Ward’s triangle in Han Chinese women were included in this meta-analysis. Pooled BMD differences and 95% confidence intervals (CIs) were calculated using random- or fixed- effects model. Twenty-five eligible studies, which included 4,075 Chinese women, were identified. No significant difference was observed for either genotype when the meta-analysis was limited to premenopausal women. In postmenopausal women, BMD differences were significant for BB vs. Bb [−0.029 (95% CI −0.056, −0.002) g/m2, P = 0.037] at the femoral neck, AA vs. Aa [−0.029 (95% CI −0.051, −0.006) g/m2, P = 0.012] at the lumbar spine, and Aa vs. aa [0.022(95% CI 0.011, 0.033) g/m2, P = 0.000] at the trochanter. These results suggest a modest but statistically significant association between VDR BsmI and ApaI polymorphisms and BMD in Chinese postmenopausal women, with higher BMD in heterozygous subjects. More epidemiological and mechanistic studies are needed to further investigate the role of VDR gene polymorphisms in regulating BMD and osteoporosis in the future.

Keywords

Bone mineral density Chinese Women Vitamin D receptor Polymorphism Meta-analysis 

Introduction

Osteoporosis is a common complex disease in postmenopausal women, which is characterized by decrease of bone mineral density (BMD) and deterioration of skeletal microarchitecture, leading to increased bone fragility and fracture [1, 2, 3]. Epidemiological studies have shown that BMD is influenced by many environmental factors, such as exercise and calcium intake [4]. Recent genome-wide association studies have emerged as a powerful new strategy for elucidating the underlying molecular mechanisms of common diseases [5]. Many studies have shown that genetic factors also play an important role in the pathogenesis of osteoporosis [6, 7, 8, 9, 10]. About 50–85% of heritability for BMD is determined genetically, as suggested by evidence from twin and family studies [11]. In recent years, candidate gene association studies (CGAS) have explored the association between osteoporosis and polymorphisms in candidate genes. Several genes have been characterized to be involved in bone mineral homeostasis, bone remodeling and bone matrix composition, e.g. vitamin D receptor (VDR) [12], estrogen receptor [13, 14, 15], collagen type 1α1 (COL1A1) [16], and transforming growth factor β1 (TGFB1) [17].

The VDR gene located at the long arm of chromosome 12 (12q13.11) is a member of the nuclear receptor super family. Liganded VDR binds to another transcription factor, retinoid X receptor (RXR). The heterodimer translocates to the nucleus and regulates many genes that are implicated in calcium homeostasis, bone cell growth and differentiation [18, 19]. Morrison et al. [20] first reported that polymorphisms in the VDR gene could predict spinal and femoral BMD in Caucasian women. Since then, a great number of studies regarding the association between VDR polymorphisms and BMD have been published. However, the results have been inconsistent [21, 22, 23, 24, 25, 26, 27, 28]. The reasons might be partly due to a number of factors, such as sample size, study design, different ethnic background, adjustment for confounding factors (calcium intake, physical activity, obesity, etc.), and linkage disequilibrium with other bone metabolism-related genes.

Meta-analysis is a useful method to overcome the disadvantages of individual studies by increasing the statistical power. Up to now, four meta-analyses have been published on the association between VDR polymorphisms and BMD: three concluded that VDR polymorphisms are modestly associated with BMD [28, 29, 30], while one found no significant association [31]. However, the studies included in these meta-analyses mainly focused on Caucasian populations. Considering the different ethnic backgrounds and environmental factors, it is necessary to investigate whether VDR gene polymorphisms could influence the pathogenesis of osteoporosis in other populations. In this study, we performed a meta-analysis to assess the association between VDR gene polymorphisms and BMD in Chinese women.

Methods

Literature and search strategy

Searches were performed of the following literature databases: PubMed (1950–2010), ISI web of science (1975–2010), China National Knowledge Infrastructure (CNKI) (1979–2010, in Chinese), and Wanfang Data (1982–2010, in Chinese).

The search strategy to identify all possible studies involved use of combinations of the following key words: (“vitamin D receptor” or “VDR”) and (“bone mineral density” or “BMD” or “bone density”) and (“China” or “Chinese”). The subjects were limited to Han Chinese women aged 18 or over. The reference lists of reviews and retrieved articles were hand-searched. If more than one article were published using the same case series, only the study with the largest sample size was selected. The literature search was updated on Oct 10th, 2010.

Inclusion criteria and data extraction

The studies included in the meta-analysis must meet all the following inclusion criteria: (1) evaluating the association between the VDRBsmI (rs1544410) or ApaI (rs7975232) polymorphisms and BMD; (2) including number of subjects, and mean and standard deviation (SD) of BMD for each genotype of the VDR gene; (3) in Chinese women populations; (4) subjects without a history of taking drugs which affect bone metabolism, and without chronic diseases impacting BMD.

For each study, the following information was extracted: (1) name of the first author; (2) publication year; (3) age of participants; (4) menopausal status; (5) the instrument used for BMD measurement; (6) inclusion criteria; (7) the covariates used for analysis; (8) the types of polymorphisms (BsmI or ApaI); (9) the mean and SD of BMD for each genotype of polymorphisms.

The authors independently assessed the articles for inclusion/exclusion, resolved disagreements and reached consistency.

Statistical analysis

The association between VDR gene polymorphisms and BMD was estimated by calculating pooled differences in BMD at four skeletal sites (the lumbar spine, the femoral neck, the trochanter, and the Ward’s triangle) between different genotypes. The significance of the pooled differences was determined by Z test (P < 0.05 was considered statistically significant). Q test was performed to evaluate whether the variation was due to heterogeneity or by chance. A random- (DerSimonian-Laird method [32]) or fixed- (Mantel–Haenszel method [33]) effects model was used to calculate pooled effect estimates in the presence (P ≤ 0.10) or absence (P > 0.10) of heterogeneity, respectively. Publication bias was assessed by Egger’s test [34] (P < 0.05 was considered statistically significant). Subgroup analyses stratified by menopausal status were performed to examine the effect of heterogeneity between studies on the results. Sensitivity analysis was performed to evaluate the stability of the results. In sensitivity analysis, after removing one study at a time, the overall homogeneity and effect size were calculated. Data analysis was performed using STATA version 11 (StataCorp LP, College Station, Texas, USA) as described previously [35, 36, 37, 38, 39, 40].

Results

Characteristics of studies

The literature search identified a total of 105 potential relevant papers. The full text articles were retrieved and carefully reviewed to assess the eligibility according to the inclusion criteria. Twenty-five papers met the inclusion criteria, which included 4,075 Han Chinese women [41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65]. Since several studies included data with different age or menopausal status, they were regarded as separate studies in the following meta-analysis. A total of 28 studies of BsmI polymorphism [41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 53, 54, 55, 56, 57, 59, 60, 61, 62, 63, 64, 65] and 10 studies of ApaI polymorphism were included in the meta-analysis [41, 42, 43, 44, 51, 52, 58, 65]. The genotype frequencies of BsmI polymorphism were about 2.3%, 18.1% and 79.6% for BB, Bb and bb, respectively; the genotype frequencies of ApaI polymorphism were about 8.0%, 40.7% and 51.3% for AA, Aa and aa, respectively. The characteristics of the included studies are listed in Table 1.
Table 1

Characteristics of the studies included in the meta-analysis

Author

Year

Polymorphisms

Geographic region

Number of subjects

Age

Menopausal status

BMD instrument

Inclusion criteria

Covariates

Tsai

1996

BsmI and ApaI

Taiwan

113

40–53

Pre

XR-26

Population-based healthy women

Age

Zhao

1997

BsmI and ApaI

Beijing

96

30–39

Pre

DPX-L

Population-based healthy women

Age and BMI

Zhao

1997

BsmI and ApaI

Beijing

115

50–80

Post

DPX-L

Population-based healthy women

Age and BMI

Kung

1998

BsmI and ApaI

Hong Kong

144

30–40

Pre

QDR-2000

Population-based healthy women

None

Lau

1999

BsmI and ApaI

Hong Kong

272

70–79

Post

N.A.

Population-based healthy women

BMI

Huang

2000

BsmI

Beijing

100

45–50

Peri

XR-36

Population-based healthy women

None

Huang

2000

BsmI

Beijing

41

55–65

Post

XR-36

Population-based healthy women

None

Li

2000

BsmI

Guangdong

138

48–65

Post

QDR-2000

Population-based healthy women

None

Zhang

2000

BsmI

Guangdong

112

N.A.

Post

QDR-4500

Population-based women

None

Zhang

2000

BsmI

Guangdong

52

25–35

Pre

QDR-4500

Population-based women

None

Chen

2001

BsmI

Taiwan

171

45–74

Post

DPX-L

Healthy clinic women

Age, weight and years since menopause

Miu

2002

BsmI

Shanghai

104

40–93

Mixed

XR-36

Health checkup and clinic women

None

Yang

2003

BsmI

Beijing

159

26–40

Pre

QDR-2000

Healthy volunteers

Weight

Zhang

2003

ApaI

Hunan

388

20–40

Pre

QDR-2000

Healthy clinic women

Age, age2,weight,height, and years of menstruation

Zhang

2003

ApaI

Hunan

261

48.2–76.7

Post

QDR-2000

Healthy clinic women

Age,age2,weight,height, and years of menstruation

He

2004

ApaI

Shanghai

515

19–40

Pre

QDR-2000

Population-based healthy women

Age, height and body weight

Wang

2004

BsmI

Shanxi

78

55–70

Post

DPX-L

Health checkup women

None

Wu

2004

BsmI

Guangdong

246

20–78

Mixed

QDR-2000

Health checkup women

None

Miu

2005

BsmI

Shanghai

167

28–59

Mixed

XR-36

Health checkup and healthy clinic women

None

Miu

2005

BsmI

Shanghai

160

60–69

Post

XR-36

Health checkup and healthy clinic women

None

Miu

2005

BsmI

Shanghai

98

70–79

Post

XR-36

Health checkup and healthy clinic women

None

Miu

2005

BsmI

Shanghai

30

80–97

Post

XR-36

Health checkup and healthy clinic women

None

Sun

2005

BsmI

Jilin

52

24–51

Pre

DPX-L

Healthy volunteers

None

Xu

2005

ApaI

Shanghai

260

48–69

Post

QDR-2000

Healthy volunteers

Age and BMI

Xu

2005

BsmI

Hebei

60

30–72

Mixed

N.A.

Healthy clinic women

Age, height, weight and estradiol level

Dong

2006

BsmI

Hubei

90

45–65

Post

XR-36

Population-based healthy women

Age, height, weight and menopausal age, outdoor time, E2, energy, calcium, protein, total fat, Cholesterin and carbohydrate intake

Ge

2006

BsmI

Fujian

180

45–70

Post

QDR-4500

Healthy clinic women

None

Wang

2007

BsmI

Heilongjiang

81

51–72

Post

DXP-L

Population-based women

None

Wu

2007

BsmI

Guangdong

203

43-69

Post

QDR-2000

Healthy volunteers

Age and BMI

Wu

2007

BsmI

Guangdong

193

24–48

Pre

QDR-2000

Health checkup women

Age and BMI

Li

2008

BsmI

Fujian

290

62.02 ± 5.44

Post

OSTEOCORE

Healthy clinic women

None

Ge

2009

BsmI and ApaI

Fujian

576

48–84

Post

OSTEOCORE

Population-based healthy women

None

Note: The term “healthy clinic women” indicates women recruited from clinic without history of taking drugs and without other chronic diseases that may affect bone metabolism. The drugs include glucocorticoids, thyroxine, antiepileptics, bisphosphonates, calcitonin, etc. The chronic diseases include hyperthyroidism, diabetes, cirrhosis, kidney failure, etc

Quantitative data synthesis

For BsmI polymorphism, data on BMD of the lumbar spine, the femoral neck, the trochanter and the Ward’s triangle were available for 4,015, 3,934, 3,318 and 3,599 subjects, respectively. No significant BMD difference was observed for any genotype at any skeletal site (all P > 0.05), except a marginal significant difference between Bb vs. bb at the trochanter (P = 0.049)(Table 2).
Table 2

Weighted mean differences in bone mineral density (BMD) [in grams per centimeter squared (g/cm2)] at the lumbar spine, the femoral neck, the trochanter and the Ward’s triangle for the BsmI polymorphism in Han Chinese women

Genotype

Lumbar spine

Femoral neck

Trochanter

Ward’s triangle

No.

Difference (95% CI)

P

No.

Difference (95% CI)

P

No.

Difference (95% CI)

P

No.

Difference (95% CI)

P

All subjects

 BB vs. Bb

12

−0.017(−0.051,0.016)

0.313

11

−0.024(−0.048,0.001)

0.057

7

0.004(−0.023,0.031)

0.762

8

0.034(−0.022,0.091)

0.232

 BB vs. bb

12

−0.010(−0.065,0.044)

0.712

11

−0.016(−0.048, 0.015)

0.309

7

0.013(−0.013,0.038)F

0.324

8

0.033(−0.015,0.080)

0.184

 Bb vs. bb

27

0.003(−0.032,0.038)

0.859

25

0.012(−0.005, 0.029)

0.170

20

0.014(0.003,0.027)

0.049

22

0.003(−0.016,0.022)

0.761

Pre-/peri-menopausal

 BB vs. Bb

4

−0.049(−0.151,0.052)

0.339

3

0.005(−0.074,0.085)

0.894

2

0.037(−0.094,0.168)

0.580

2

0.134(−0.108,0.376)

0.279

 BB vs. bb

4

−0.040(−0.099,0.018)F

0.176

3

0.012(−0.048,0.072)

0.701

2

0.011(−0.036,0.057)F

0.652

2

0.099(−0.054,0.252)

0.204

 Bb vs. bb

8

−0.006(−0.041,0.029)

0.726

6

−0.003(−0.031,0.024)

0.816

4

0.007(−0.010,0.024)F

0.410

5

−0.028(−0.077,0.020)

0.255

Postmenopausal

 BB vs. Bb

7

−0.005(−0.041,0.031)

0.781

7

−0.029(−0.056, − 0.002)

0.037

4

0.011(−0.024,0.045)F

0.545

5

0.015(−0.031,0.061)

0.521

 BB vs. bb

7

−0.007(−0.080,0.066)

0.848

7

−0.030(−0.066,0.006)

0.105

4

0.015(−0.017,0.047)F

0.364

5

0.011(−0.041,0.063)

0.684

 Bb vs. bb

16

−0.000(−0.048,0.047)

0.992

15

0.018(−0.003,0.039)

0.100

12

0.016(−0.002,0.033)

0.079

13

0.010(0.000,0.020)F

0.052

F fixed-effects model

For ApaI polymorphism, data on BMD of the lumbar spine, the femoral neck, the trochanter and the Ward’s triangle were available for 2,724, 1,815, 1,671 and 1,815 subjects, respectively. The BMD at the femoral neck, the trochanter and the Ward’s triangle were significantly higher in the subjects with Aa genotype vs aa genotype (P = 0.036, 0.000 and 0.049, respectively), with the BMD differences being 0.021(95% CI 0.001,0.041)g/m2, 0.015(95% CI 0.007, 0.023) g/m2 and 0.021(95% CI 0.000, 0.041) g/m2, respectively (Table 3).
Table 3

Weighted mean differences in bone mineral density (BMD) [in grams per centimeter squared (g/cm2)] at the lumbar spine, the femoral neck, the trochanter and the Ward’s triangle for the ApaI polymorphism in Han Chinese women

Genotype

Lumbar spine

Femoral neck

Trochanter

Ward’s triangle

No.

Difference (95% CI)

P

No.

Difference (95% CI)

P

No.

Difference (95% CI)

P

No.

Difference (95% CI)

P

All subjects

 AA vs. Aa

10

−0.013(−0.042,0.017)

0.398

7

−0.008(−0.029,0.013)

0.470

6

0.012(−0.024,0.048)

0.512

7

0.004(−0.031,0.039)

0.816

 AA vs. aa

10

−0.006(−0.038, 0.025)

0.693

7

0.013(−0.020, 0.046)

0.431

6

0.019(−0.016,0.055)

0.289

7

0.020(−0.020, 0.061)

0.320

 Aa vs. aa

10

0.010(−0.001, 0.020)

0.068

7

0.021(0.001, 0.041)

0.036

6

0.015(0.007, 0.023)F

0.000

7

0.021(0.000, 0.041)

0.049

Pre-/perimenopausal

          

 AA vs. Aa

5

0.012(−0.046,0.070)

0.693

4

−0.006(−0.045,0.034)

0.777

3

0.021(−0.049,0.091)

0.552

4

0.014(−0.055,0.082)

0.694

 AA vs. aa

5

0.017(−0.042,0.075)

0.576

4

0.020(−0.041,0.081)

0.522

3

0.023(−0.040,0.087)

0.474

4

0.033(−0.043,0.110)

0.397

 Aa vs. aa

5

0.005(−0.006,0.017)F

0.383

4

0.025(−0.002,0.052)

0.075

3

0.005(−0.007,0.018)F

0.415

4

0.022(−0.001,0.046)

0.060

Postmenopausal

          

 AA vs. Aa

5

−0.029(−0.051, − 0.006)F

0.012

3

−0.008(−0.031,0.015)F

0.487

3

0.004(−0.025,0.032)F

0.809

3

−0.001(−0.027,0.024)F

0.925

 AA vs. aa

5

−0.025(−0.062,0.012)

0.186

3

−0.000(−0.030,0.030)F

0.992

3

0.017(−0.027,0.062)F

0.445

3

0.003(−0.020,0.028)

0.796

 Aa vs. aa

5

0.011(−0.001,0.020)

0.265

3

0.017(−0.017,0.052)

0.328

3

0.022(0.011,0.033)F

0.000

3

0.019(−0.019,0.057)F

0.322

F fixed-effects model

Since menopausal status may affect the association between VDR gene polymorphisms and BMD, subgroup analyses stratified by menopausal status were performed. No significant BMD difference was observed among premenopausal women (Tables 2, 3). For postmenopausal women, some significant BMD differences were found at some skeletal sites. For BsmI polymorphism among postmenopausal women, the BMD difference between BB and Bb genotypes was −0.029(95% CI −0.056, −0.002) g/m2, P = 0.037 at the femoral neck (Fig. 1; Table 2). For ApaI polymorphism among postmenopausal women, the BMD difference between AA and Aa genotypes was −0.029 (95% CI −0.051, −0.006), P = 0.012 at the lumbar spine (Fig. 2; Table 3), and the BMD difference between Aa and aa genotypes was 0.022(95% CI 0.011, 0.033) g/m2, P = 0.000 at the trochanter (Fig. 3; Table 3).
Fig. 1

Meta-analysis of the association between VDR BsmI polymorphism (BB vs. Bb) and bone mineral density [in grams per centimeter squared (g/m2)] at the femoral neck in postmenopausal women

Fig. 2

Meta-analysis of the association between VDR ApaI polymorphism (AA vs. Aa) and bone mineral density [in grams per centimeter squared (g/m2)] at the lumbar spine in postmenopausal women

Fig. 3

Meta-analysis of the association between VDR ApaI polymorphism (Aa vs. aa) and bone mineral density [in grams per centimeter squared (g/m2)] at the trochanter in postmenopausal women

To address the problem of multiple comparisons, Bonferroni correction was performed (significant P < 0.05/36 = 0.0014). Using this stringent approach, the BMD difference between Aa and aa genotypes at the trochanter for ApaI polymorphism still reached significance level (P = 0.000).

Sensitivity analysis was conducted by excluding each study at a time. The analysis confirmed the stability of the association between VDR gene polymorphisms and BMD in Chinese women (data not shown).

Potential publication bias

Egger’s test was performed to assess potential publication bias. No publication bias was detected in the included studies (Egger’s test, P > 0.10 for BsmI and ApaI polymorphisms).

Discussion

Our study suggests that for BsmI polymorphism there is a marginally significant BMD difference between Bb and bb at the trochanter, and for ApaI polymorphism, the mean BMD at the femoral neck, the trochanter and the Ward’s triangle were significantly higher in the subjects with Aa genotype than those with aa genotype. In subgroup analyses, no significant BMD difference was observed for premenopausal women, and some significant BMD differences could be found for postmenopausal women: BB < Bb at the femoral neck, AA < Aa at the lumbar spine, and Aa > aa at the trochanter. However, the effects of VDR polymorphisms on BMD seemed very modest even for the most significant differences (which were +0.021 or −0.029 g/m2). In general, higher BMD was observed in heterozygous (Bb or Aa) postmenopausal women. These results are similar to some previous studies in Finnish and Lebanese populations [66, 67], but are different from the previous meta-analyses, most of which concluded that BB carriers have lower BMD than Bb/bb carriers [28, 29, 30].

The reasons for these discrepancies may include: (1) Race/ethnicity backgrounds. The allele frequencies of BB and AA genotypes are much lower in Asians than Caucasians, according to the HapMap data and our data. For example, the frequencies of BB, Bb and bb were about 2.3%, 18.1% and 79.6%, respectively, in Chinese population included in this study; while the frequencies of BB, Bb and bb were about 15.4%, 47.4%, and 37.2%, respectively, in Caucasian population [68, 69]. Many studies, including our previous studies [35, 36, 37, 38, 39, 40], have reported on the effect of ethnic differences on genetic predisposition to human diseases. Therefore, these discrepancies may be due to different race/ethnicity backgrounds. (2) Gene–gene/gene-environment interactions. Besides VDR polymorphisms, other genes and pathways, such as estrogen signaling pathway, Wnt/β-catenin pathway, transforming growth factor superfamily, receptor activator of the nuclear factor-κB (RANK) signaling pathway, may affect BMD and modulate the effect of VDR polymorphisms on BMD [70]. In addition, environmental factors, such as diet, physical activity, smoking and alcohol consumption, have been shown to influence BMD and osteoporosis [71]. Therefore, these gene-environmental factors may act as confounders that affect the association between VDR polymorphisms and BMD.

Up to now, the mechanism by which the VDR gene affects BMD remains unknown. Vitamin D plays an important role in calcium homeostasis, bone metabolism and intestinal absorption of calcium [72, 73, 74]. VDR modulates the transcription of target genes (e.g. calcium binding protein and osteocalcin) that are critical for calcium uptake and bone formation. However, the polymorphisms in the VDR gene (BsmI and ApaI) have been inconsistently associated with BMD in different populations. Our meta-analysis shows that the BsmI and ApaI polymorphisms are weakly associated with BMD at some skeletal sites in Chinese postmenopausal women, with heterozygous subjects having a higher BMD. The mechanism underlying the difference between premenopausal and postmenopausal women is unknown. The most likely reason could be different hormone levels, which may influence the effect of VDR polymorphisms on BMD. In future studies, it is necessary to investigate the functional effects of VDR polymorphisms on BMD.

The current meta-analysis has some advantages compared to other individual studies; however, it does have some limitations. First, the present meta-analysis was based primarily on unadjusted or partially adjusted effect estimates and CIs, so the confounding factors might modify the effect estimates. Second, the recruitment of subjects varied across different studies. Some studies were population-based, while others were hospital-based. Therefore, selection bias may be introduced and the subjects may not represent the general population. Third, the effects of gene–gene/gene–environment interactions were not addressed in this meta-analysis. Fourth, the results of subgroup analyses should be interpreted with caution because of limited statistical power. We anticipate these issues will be addressed in future studies.

In summary, this meta-analysis suggests that there is a modest but statistically significant association between the VDRBsmI and ApaI polymorphisms and BMD in Chinese postmenopausal women, with heterozygous subjects having a higher BMD. More epidemiological and mechanistic studies are needed to further investigate the role of VDR gene polymorphisms in regulating BMD and osteoporosis in the future.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Department of Orthopaedics, Xiangya HospitalCentral South UniversityChangshaChina
  2. 2.Department of Maternal and Child Health Care, School of Public HealthShandong UniversityJinanChina
  3. 3.Baylor College of Medicine and The University of Texas M. D. Anderson Cancer CenterHoustonUSA

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