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Novel associations of UDP-glucuronosyltransferase 2B gene variants with prostate cancer risk in a multiethnic study

  • Adriana C Vidal1,
  • Cocoa Tucker2,
  • Joellen M Schildkraut3,
  • Ricardo M Richardson2,
  • Megan McPhail4, 5,
  • Stephen J Freedland4, 5, 6, 7,
  • Cathrine Hoyo1 and
  • Delores J Grant2Email author
BMC Cancer201313:556

https://doi.org/10.1186/1471-2407-13-556

Received: 25 February 2013

Accepted: 20 November 2013

Published: 22 November 2013

Abstract

Background

We have previously shown that a functional polymorphism of the UGT2B15 gene (rs1902023) was associated with increased risk of prostate cancer (PC). Novel functional polymorphisms of the UGT2B17 and UGT2B15 genes have been recently characterized by in vitro assays but have not been evaluated in epidemiologic studies.

Methods

Fifteen functional SNPs of the UGT2B17 and UGT2B15 genes, including cis-acting UGT2B gene SNPs, were genotyped in African American and Caucasian men (233 PC cases and 342 controls). Regression models were used to analyze the association between SNPs and PC risk.

Results

After adjusting for race, age and BMI, we found that six UGT2B15 SNPs (rs4148269, rs3100, rs9994887, rs13112099, rs7686914 and rs7696472) were associated with an increased risk of PC in log-additive models (p < 0.05). A SNP cis-acting on UGT2B17 and UGT2B15 expression (rs17147338) was also associated with increased risk of prostate cancer (OR = 1.65, 95% CI = 1.00-2.70); while a stronger association among men with high Gleason sum was observed for SNPs rs4148269 and rs3100.

Conclusions

Although small sample size limits inference, we report novel associations between UGT2B15 and UGT2B17 variants and PC risk. These associations with PC risk in men with high Gleason sum, more frequently found in African American men, support the relevance of genetic differences in the androgen metabolism pathway, which could explain, in part, the high incidence of PC among African American men. Larger studies are required.

Background

Prostate cancer is the second leading cause of cancer-related deaths in men, after lung cancer [1]. The incidence of prostate cancer has increased over the past twenty years and African American men have been disproportionally affected compared to other racial/ethnic groups [27]. In the U.S., the incidence of prostate cancer among African Americans is more than 60% higher than in Caucasians, and the mortality rate in African Americans is twice that of Caucasian men [8, 9]. Although differences in incidence and mortality rates may be due, in part, to race/ethnicity, socioeconomic conditions and availability of health care [10], familial aggregation studies suggest that genetic factors may also be contributing to prostate cancer demographic disparity. Candidate gene approaches involving hormone metabolic pathways have been examined in prostate cancer association studies, however results from these studies have not been replicated [11, 12]. Nonetheless, current therapies are primarily targeted at specific androgen biosynthetic pathways [13], thus, improved knowledge on genetic variants associated with both androgen metabolism and prostate cancer risk is important.

The UDP-glucuronosyltransferase (UGT) genes code for enzymes that convert a diverse group of xenobiotic and endobiotic substances into lipophilic compounds, facilitating clearance from the body as part of the phase II liver detoxification system [14]. These enzymes are subdivided into families according to similarities in amino acid sequence and target substrates dictated by the specificity of their amino-terminal ends [15]. A specific subfamily, UGT2B, includes two enzymes, UGT2B17 and UGT2B15, which are also expressed extrahepatically in the basal and luminal epithelium of the prostate, respectively. These enzymes exhibit specificity for androgen metabolites such as testosterone, dihydrotestosterone (DHT), androsterone (ADT), and androstane-3α,17β-diol (3β-diol) in prostate tissue and cell lines [16, 17].

Functional polymorphisms of the UGT2B gene family such as the copy number variant (CNV) of UGT2B17, and the aspartic acid (D or nucleotide G) to tyrosine substitution (Y or nucleotide T) found in codon 85 of the UGT2B15 gene (UGT2B15 D85Y , rs1902023) have been identified [18, 19]. Studies suggest that men with 0 copies of the UGT2B17 gene are unable to break down testosterone through the UGT2B pathway and subsequently secrete negligible amounts of urinary testosterone compared to men with at least one copy of UGT2B17[18, 20]. Experimental evidence showed that the minor allele (T) of the UGT2B15 variant, UGT2B15 D85Y , causes the enzyme to have an increased Vmax activity when compared to the presence of the major allele (G) [19]. Subsequently, the resulting phenotype of this UGT2B15 polymorphism is a quicker androgen metabolite clearance which may raise the “effective” amount of steroids within the prostate and decrease risk for prostate cancer [21]. These two major UGT2B variants (the CNV in UGT2B17 and the polymorphism in UGT2B15) have been evaluated in relation to prostate cancer risk, with inconsistent findings [2232]. Discrepancies could have been due to the genetic heterogeneity of the populations studied, as well as variable sample sizes of these populations. We have recently shown that individuals with a major allele (G) of the UGT2B15 D85Y polymorphism (rs1902023) have higher risk of prostate cancer when compared to individuals homozygous for the “rapid clearance” minor allele (Y) [33]. In the same study, the UGT2B17 CNV showed no association with prostate cancer risk [33]. Recently, an additional 7 novel UGT2B15 SNPs that are in strong linkage disequilibrium (LD) with the UGT2B15 D85Y gene variant, have been identified by re-sequencing the promoter and exon one regions of the UGT2B15 gene, using DNA samples from Yoruba (YRI), CEPH/European (CEU), and Japanese/Chinese (ASN) populations [34]. Most of these UGT2B variants have not been evaluated in relation to prostate cancer risk in population-based studies or in studies that included African American men. In this present work, we examined associations between functional SNPs of UGT2B17, UGT2B15 and three other related UGT2B SNPs, and prostate cancer risk among African American and Caucasian men.

Methods

Study population

The details of participant accrual for this case control study have been previously reported [35]. In brief, male subjects from the Durham Veterans Affairs Medical Center (DVAMC) in Durham, North Carolina, who were undergoing a prostate needle biopsy between January 2007 and October 2011, were consecutively contacted in a hospital-based, case control study. Eligibility criteria for cases included age >18 years, undergoing a prostate biopsy for concerns of potential prostate cancer after presentation with elevated PSA and/or abnormal digital rectal examination, and prostate cancer positive classification by pathological review of biopsy tissue. Of the 759 men with a biopsy indication who were screened for eligibility, 539 (759/539 = 71% participation rate) provided written consent to participate. Twenty two men elected not to follow through and of the 517 men that underwent a biopsy, 233 had a biopsy with histological evidence of prostate cancer. Controls were recruited from the DVAMC Internal Medicine Clinic; eligibility criteria were age >18 and having a PSA test conducted at the DVAMC within the same time frame, but not recommended to undergo biopsy. Of the 768 men who met eligibility criteria for controls, 377 provided written consent (768/377 = 49% participation rate). Questionnaires were administered to prostate cancer cases prior to biopsy and to controls to assess risk factors including race and age. Institutional Review Board approval was obtained at North Carolina Central University, Duke University, and the DVAMC and all patients signed an informed consent prior to enrollment.

Genotyping

UGT2B variants were selected for genotyping from previous published reports as well as dbSNP and SNP Tags from the Genome Variation Server (GVS) (Table 1). Eight were from the UGT2B15 gene, 4 were from the UGT2B17 gene and 3 were cis-acting on the UGT2B15 and/or UGT2B17 gene expression. UGT2B15 SNPs that were genotyped for this study include rs1580083, rs1960733 (formerly rs34050522), rs9994887 (formerly rs35513228), rs13112099, rs7866914 (formerly rs34027331), rs7696472, rs4148296, rs3100 and rs17221777. UGT2B15 SNPs rs1580083, rs1960733 (formerly rs34050522), rs9994887 (formerly rs35513228), rs13112099, rs7686914 (formerly rs34027331) and rs7696472 were identified from the re-sequencing of the UGT2B15 promoter and exon 1 in 56 HapMap samples from YRI, CEU, and East Asian (ASN) populations [34]. Other UGT2B15 SNPs genotyped, rs4148296 (T523K) and rs3100 (3′UTR) were characterized by differential allelic expression assays and re-sequencing, respectively [36]. The final UGT2B15 SNP, rs17221777, was identified in a previous study [18]. UGT2B17 SNPs that were genotyped for this study SNPs include rs72551386, rs59678213, rs7435827, rs7686008, rs7671342, rs35994121, and rs35140421. UGT2B17 SNPs rs7435827, rs7686008, rs7671342, rs35994121, and rs35140421 were identified as UGT2B17 Tag SNPs in the GVS and dbSNP databases. UGT2B17 SNP rs59678213 was identified as a novel polymorphism in a transcriptional binding site in the promoter region of UGT2B17[37]. Four SNPs were genotyped in this study, rs6822259, rs17147338, rs2168047 and rs4557343, that were identified in a SNP discovery study and characterized as cis-acting on UGT2B17 (rs6822259), UGT2B15 (rs4557343), and UGT2B17 and UGT2B15 (rs17147338, rs2168047) gene expression [38]. Of the twenty SNPs, five were excluded from analysis because they were either monoallelic (rs72551386, rs17221777, rs3599412, and rs3514942) in the study population or the genotyping assay failed (rs455734).
Table 1

UGT2B15 and UGT2B17 genotyped SNPs and Minor alleles

SNP

Function class

Minor allele/MAF

Reference

All

Afr. American

Caucasian

UGT2B15 SNPs

    

rs1580083

Promoter

T/0.74

0.70

0.80

34

rs1960773

Promoter (Nrf2)

T/0.73

0.70

0.76

34

rs9994887

Promoter

A/0.73

0.67

0.78

34

rs13112099

Promoter

T/0.74

0.70

0.78

34

rs7686914

Promoter

T/0.73

0.68

0.78

34

rs7696472

Promoter

G/0.73

0.68

0.76

34

rs4148269

Nonsyn (T523K)

C/0.70

0.70

0.85

36

rs3100

3′UTR

T/0.72

0.53

0.85

36

UGT2B17 SNPs

    

rs59678213

Promoter (FoxA1)

C/0.32

0.24

0.67

37

rs7435827

Intron

G/0.60

0.30

0.76

GVS

rs7686008

Intron

T/0.18

0.34

0.06

GVS

rs7671342

Intron

G/0.41

0.41

0.41

GVS

Cis acting on UGT2B expression

    

rs6822259^

Intergenic

C/0.32

0.30

0.30

38

rs17147338^^

Intergenic

T/0.16

0.30

0.079

38

rs2168047^^

Distal promoter

A/0.67

0.73

0.63

38

^cis-acting on UGT2B17 expression (36).

^^cis-acting on UGT2B17 and UGT2B15 expression (36).

GVS – genome variation server.

DNA was isolated from peripheral blood by standard DNA isolation (Qiagen Inc., Valencia, CA, U.S.A.) and quantified by ultraviolet spectrophotometry. Prior to genotyping, DNA concentration was determined using PicoGreen assay (Life Technologies, Gaithersburg, MD) and measured using the fluorescence intensity measurements plotted against a standard curve that was generated from the average fluorescence intensity of standards run in replicate. Based on the PicoGreen quantification, 10 ng of genomic DNA from each sample was used in the iPlex assay for Sequenom-iPlex Genotyping (Sequenom Inc., San Diego, CA). The Sequenom Mass Array (Sequenom Inc., San Diego, CA) was used and the assays for all SNPs were designed by Sequenom online assay tools (Assay Designer 4.0) at the David H. Murdock Research Institute (DHMRI) Genomics Laboratory (Kannapolis, NC). The data were analyzed by Sequenom-Typer 4.0. The Sequenom-iPlex genotyping and analysis was validated with CEPH gDNA controls when performing the iPlex assay and scanning on the MALDI-TOF Mass Spectrometer. At the time of this analysis, 585 samples were submitted and successfully produced good spectra for genotyping at a failure rate of <2.2% for the majority of SNPs. The Post-QC (Call Rate) of SNPs rs59678213 and rs7435827 was 92.7% and 94.7%, respectively. The assays included DHMRI control DNA (CEPH) on each plate in duplicate that were checked for concordance for each SNP. Sample duplicates were individually inspected for genotype consistency. Genotypes from duplicate samples were 100% concordant.

Statistical analysis

We examined whether genetic variants of UGT2B17 and UGT2B15 genes were associated with prostate cancer risk and whether these associations varied by race and prostate cancer grade. Low grade prostate cancer was defined as Gleason sum <8 and high-grade prostate cancer was defined as Gleason ≥ 8. Potential confounders (age, height, and BMI) were normally distributed overall and were treated as continuous variables in modeling. Race was self-reported and categorized as African American, Caucasian and other (Native American and Latino). Family history of prostate cancer included maternal lineage (maternal uncle) or paternal lineage (father, brother or paternal uncle) (yes or no) and these combined. Data on tobacco use at the time of enrollment was also self-reported as yes or no.

Descriptive statistics (means, SD), and percentages for cases and controls were estimated using X 2 tests for categorical variables, and Wilcoxon rank-sum test for continuous variables. Unconditional logistic regression was used to estimate the odd ratios (ORs) and 95% confidence intervals (95% CI) for the association between genotypes and prostate cancer risk. Multinomial logistic regression models were used to explore whether associations between genotypes and prostate cancer risk varied by grade of prostate cancer at diagnosis, using controls as reference. Confounders adjusted for in all models were age, race, and BMI. All analyses were done using SAS version 9.3 (SAS Institute, Inc., Cary, NC).

Results

Table 2 describes the clinical characteristics of the study participants. Prostate cancer cases (n = 233) and controls (n = 342) were comparable in height (p = 0.31), however controls (mean BMI = 30.77, SD = 6.05) had slightly higher BMI than cases (mean BMI = 29.25, SD = 5.60, p = 0.002) and were slighter younger than cases (p = 0.005). African American men comprised 63% of the cases and 41% of the controls (p <0.0001). A family history of prostate cancer was reported by 14% of cases and 10% of the controls. (p = 0.16). Most cases and controls reported tobacco use (p = 0.43). Ninety-one percent of the cases had low-grade prostate cancer (Gleason sum < 8) vs. 9% of cases with high grade prostate cancer (Gleason sum ≥ 8).
Table 2

Risk factor characteristics for prostate cancer participants

Risk factors

Cases n = 233 n (%)

Controls n = 342 n (%)

p-value

Age - mean (SD)

63.34 (6.37)

61.32 (7.49)

p = 0.005

Height (in.)

69.65 (2.92)

69.91 (3.03)

p = 0.31

Obesity (BMI)

29.25 (5.60)

30.77 (6.05)

p = 0.002

Race

  

p = <.0001

African American

146 (62.66)

140 (40.93)

 

Caucasian

87 (37.34)

202 (59.06)

 

Family history PC

  

p = 0.16

Yes

32 (13.73)

34 (9.94)

 

No

201 (86.26)

308 (90.05)

 

Tobacco use

  

p = 0.43

Yes

225 (96.56)

334 (97.66)

 

No

8 (3.43)

8 (2.33)

 

Gleason sum <8 (134

211 (91.34)

  

Black/77 White)

 

NA

 

≥8 (10 Black/10 White)

20 (8.66)

  
The functional variants of the UGT2B15 and UGT2B17 SNPs were assessed for associations with prostate cancer risk and summarized in Table 3. After adjusting for age, race and BMI, four UGT2B15 SNPs, rs9994887, rs13112099, rs7686914 and rs7696472, were associated with increased risk of prostate cancer, when compared to the minor allele (Log additive model OR = 1.49, 95% CI = 1.09, 2.04; OR = 1.48, 95% CI = 1.08, 2.03, OR = 1.48, 95% CI = 1.08, 2.03, OR = 1.49, 95% CI = 1.06, 2.00, respectively). UGT2B15 SNPs rs4148269 and rs3100, were also associated with increased risk for prostate cancer (Log additive model OR = 1.45, 95% CI = 1.03, 2.03; OR = 1.46, 95% CI = 1.08, 1.98, respectively). These data suggest that these associations were allele dose-dependent (Table 3). None of the UGT2B17 SNPs studied were associated with prostate cancer risk, however the UGT2B17 cis-acting SNP, rs17147338, showed borderline significance for increased risk of prostate cancer in an allele dose dependent fashion (OR = 1.65, 95% CI = 1.00, 2.70), after adjusting for age, race and BMI (Table 3). SNPs in high LD with UGT2B15 D85Y , rs9994887, rs13112099, rs7686914, and rs796472 [34] were associated with increased risk of prostate cancer in an allele dose-dependent manner for both high-grade (OR = 2.34, 95% CI = 1.22, 4.49; OR = 2.31, 95% CI = 1.20, 4.44; OR = 2.31, 95% CI = 1.20, 4.44; OR = 2.26, 95% CI = 1.18, 4.33, respectively) and low-grade prostate cancer lesions (OR = 1.94, 95% CI = 1.06, 3.53; OR = 1.93, 95% CI = 1.06, 3.52; OR = 1.94, 95% CI = 1.06, 3.53; OR = 1.99, 95% CI = 1.10, 3.63, respectively) after adjusting for age, race, and BMI (Table 4). Intriguingly, SNPs rs4148269 and rs3100 were associated with increased PC risk in high grade lesions only (OR = 1.96, 95% CI = 1.01, 3.82; OR = 2.16, 95% CI = 1.18, 3.95).
Table 3

*ORs for the associations between UGT2B15 and UGT2B17 SNPs and PC

SNP # Allele

Cases n (%)

Controls n (%)

OR (95% CI)*

UGT2B15

   

rs1580083

   

TT

2 (0.86)

5 (1.47)

Reference

TA

150 (64.38)

249 (73.45)

2.32 (0.23-23.81)

AA

81 (34.76)

85 (25.07)

3.24 (0.31-33.93)

AA/TA

231 (99.14)

334 (98.52)

2.54 (0.25-26.00)

Log additive

  

1.43 (0.91-2.26)

rs1960773

   

TT

1 (0.43)

5 (1.47)

Reference

GT

144 (62.61)

244 (71.98)

--

GG

85 (36.96)

90 (26.55)

--

TT/GT

229 (99.56)

334 (98.52)

--

Log additive

  

--

rs9994887

   

AA

38 (16.31)

91 (26.84)

Reference

AG

108 (46.35)

158 (46.61)

1.94 (1.06-3.53)

GG

87 (37.34)

90 (26.55)

2.38 (1.24-4.55)

GG/AG

195 (83.69)

248 (73.15)

2.10 (1.18-3.71)

Log additive

  

1.49 (1.09-2.04)

rs13112099

   

TT

38 (16.31)

91 (26.61)

Reference

GT

110 (47.21)

163 (47.66)

1.93 (1.06-3.52)

GG

85 (36.48)

88 (25.73)

2.35 (1.22-4.51)

GG/GT

195 (83.69)

251 (73.39)

2.07 (1.12-3.67)

Log additive

  

1.48 (1.08-2.03)

rs7686914

   

TT

38 (16.45)

91 (26.84)

Reference

CT

109 (47.19)

160 (47.20)

1.94 (1.06-3.55)

CC

84 (36.36)

88 (25.96)

2.34 (1.22-4.50)

CC/CT

193 (83.55)

248 (73.81)

2.10 (1.17-3.70)

Log additive

  

1.48 (1.08-2.03)

rs7696472

   

GG

38 (16.31)

92 (26.97)

Reference

AG

110 (47.21)

157 (46.04)

2.00 (1.10-3.63)

AA

85 (36.48)

90 (26.39)

2.30 (1.20-4.40)

AA/AG

195 (83.69)

249 (73.02)

2.10 (1.18-3.72)

Log additive

  

1.49 (1.06-2.00)

rs4148269

   

CC

43 (18.45)

79 (23.23)

Reference

CA

72 (30.90)

160 (47.05)

0.81 (0.45-1.46)

AA

115 (49.35)

101 (29.70)

1.98 (1.02-3.85)

AA/CA

190 (81.54)

261 (76.76)

1.10 (0.63-1.90)

Log additive

  

1.45 (1.03-2.03)

rs3100

   

TT

54 (23.78)

106 (31.08)

Reference

TC

68 (29.95)

140 (41.05)

1.04 (0.60-1.81)

CC

105 (46.25)

95 (27.85)

2.18 (1.19-3.99)

CC/TC

173 (76.21)

235 (68.91)

1.41 (0.86-2.31)

Log additive

  

1.46 (1.08-1.98)

Cis acting on UGT2B expression

   

rs2168047

   

AA

53 (22.84)

59 (17.45)

Reference

GA

112 (48.27)

169 (50.00)

0.86 (0.48-1.53)

GG

67 (28.87)

110 (32.54)

1.00 (0.52-1.88)

GG/GA

179 (77.15)

279 (82.54)

0.90 (0.52-1.57)

Log additive

  

1.01 (0.74-1.38)

rs6822259

   

CC

3 (1.29)

12 (3.52)

Reference

CT

58 (25.00)

97 (28.44)

1.48 (0.36-6.02)

TT

171 (73.70)

232 (68.03)

1.34 (0.34-5.31)

TT/CT

229 (98.70)

329 (96.48)

1.39 (0.35-5.43)

Log additive

  

1.02 (0.68-1.53)

rs17147338

   

CC

168 (72.1)

285 (83.58)

Reference

CT

55 (23.61)

51 (14.96)

1.68 (0.96-2.97)

TT

10 (4.29)

5 (1.47)

2.41 (0.42-13.94)

TT/CT

65 (27.9)

56 (16.42)

1.73 (1.00-3.00)

Log additive

  

1.65 (1.00-2.70)

UGT2B17

   

rs7435827

   

GG

53 (24.20)

106 (32.61)

Reference

GA

43 (19.63)

78 (24.00)

0.67 (0.35-1.30)

AA

123 (56.16)

141 (43.38)

0.90 (0.49-1.66)

AA/GA

166 (75.79)

219 (67.38)

0.80 (0.46-1.38)

Log additive

  

0.97 (0.71-1.36)

rs7686008

   

AA

168 (71.79)

281 (82.4)

Reference

AT

34 (14.53)

32 (9.38)

1.40 (0.69-2.79)

TT

32 (13.68)

28 (8.21)

1.40 (0.66-2.96)

TT/AT

66 (28.21)

60 (17.6)

1.39 (0.79-2.44)

Log additive

  

1.21 (0.85-1.73)

rs7671342

   

GG

37 (15.94)

56 (16.37)

Reference

GA

46 (19.83)

85 (24.85)

0.86 (0.43-1.73)

AA

149 (64.22)

201 (58.77)

1.32 (0.73-2.40)

AA/GA

195 (84.05)

286 (83.62)

1.17 (0.65-2.08)

Log additive

  

1.21 (0.91-1.61)

rs59678213

   

CC

42 (19.44)

81 (25.63)

Reference

TC

46 (21.29)

74 (23.42)

0.84 (0.43-1.63)

TT

128 (59.26)

161 (50.94)

0.85 (0.45-1.59)

TT/TC

174 (80.55)

235 (74.37)

0.84 (0.47-1.50)

Log additive

  

0.92 (0.68-1.26)

*Adjusted for age, race and BMI.

Table 4

*ORs for the associations between UGT2B15 and UGT2B17 SNPs and PC in low grade and high grade PC cases

SNP # Allele

Low gleason <8 n (%)

Adjusted OR (95% CI)

High gleason ≥8 n (%)

Adjusted OR* (95% CI)

UGT2B15

    

rs1580083

    

TT

0 (0)

Reference

2 (10.00)

Reference

TA

139 (65.88)

--

10 (50.00)

0.20 (0.02-2.42)

AA

72 (34.12)

--

8 (40.00)

0.33 (0.02-4.36)

AA/TA

211 (100.0)

--

18 (90.00)

0.13 (0.02-0.74)

Log additive

 

--

 

3.20 (0.30-33.45)

rs1960773

    

TT

0 (0)

Reference

1 (5.26)

Reference

GT

132 (63.16)

--

11 (57.89)

--

GG

77 (36.84)

--

7 (36.84)

--

GG/GT

209 (100.0)

--

18 (94.73)

--

Log additive

 

--

 

--

rs9994887

    

AA

32 (15.17)

Reference

5 (25.00)

Reference

AG

101 (47.87)

2.13 (1.13-4.00)

7 (35.00)

0.86 (0.19-3.80)

GG

78 (36.97)

2.53 (1.30-4.99)

8 (40.00)

1.27 (0.26-6.17)

GG/AG

179 (84.83)

2.27 (1.24-4.14)

15 (75.00)

1.00 (0.25-3.90)

Log additive

 

1.94 (1.06-3.53)

 

2.34 (1.22-4.49)

rs13112099

    

TT

32 (15.16)

Reference

5 (25.00)

Reference

GT

103 (48.81)

2.12 (1.13-3.98)

7 (35.00)

0.84 (0.19-3.71)

GG

76 (36.01)

2.50 (1.26-4.93)

8 (40.00)

1.30 (0.26-6.28)

GG/GT

179 (84.83)

2.25 (1.23-4.10)

15 (75.00)

1.00 (0.25-3.87)

Log additive

 

1.93 (1.06-3.52)

 

2.31 (1.20-4.44)

rs7686914

    

TT

32 (15.23)

Reference

7 (36.83)

Reference

CT

102 (48.57)

2.14 (1.14-4.02)

7 (36.84)

0.86 (0.19-3.78)

CC

76 (36.19)

2.50 (1.26-4.92)

5 (26.32)

1.30 (0.26-6.30)

CC/CT

178 (84.76)

2.25 (1.23-4.13)

12 (63.16)

1.00 (0.26-3.92)

Log additive

 

1.94 (1.06-3.54)

 

2.31 (1.20-4.44)

rs7696472

    

AA

32 (15.17)

Reference

8 (40.00)

Reference

AG

103 (48.82)

2.20 (1.16-4.12)

7 (35.00)

0.86 (0.19-3.82)

GG

76 (36.02)

2.43 (1.23-4.81)

5 (25.00)

1.26 (0.26-6.11)

GG/AG

179 (84.83)

2.30 (1.25-4.16)

12 (60.00)

1.00 (0.26-3.92)

Log additive

 

1.99 (1.10-3.63)

 

2.26 (1.18-4.33)

rs4148269

    

CC

38 (18.18)

Reference

5 (26.32)

Reference

CA

66 (31.58)

0.76 (0.42-1.40)

5 (26.32)

2.16 (0.23-20.26)

AA

105 (50.24)

1.70 (0.86-3.36)

9 (47.36)

13.55 (1.34-136.99)

AA/CA

171 (81.81)

1.00 (0.56-1.74)

14 (73.68)

3.94 (0.47-2.58)

Log additive

 

0.81 (0.45-1.47)

 

1.96 (1.01-3.82)

rs3100

    

TT

46 (22.33)

Reference

7 (36.84)

Reference

TC

64 (31.07)

1.04 (0.60-1.83)

4 (21.05)

1.10 (0.17-6.86)

CC

96 (46.60)

1.96 (1.06-3.63)

8 (42.10)

8.22 (1.31-51.60)

CC/TC

160 (77.66)

1.34 (0.81-2.22)

12 (63.16)

2.42 (0.50-11.83)

Log additive

 

1.04 (0.60-1.81)

 

2.16 (1.18-3.95)

rs2168047

    

AA

49 (23.22)

Reference

3 (15.79)

Reference

GA

99 (46.92)

0.78 (0.43-1.42)

12 (63.16)

2.61 (0.30-22.38)

GG

63 (29.86)

0.96 (0.50-1.84)

4 (21.05)

1.92 (0.18-20.07)

GG/GA

162 (76.77)

0.84 (0.48-1.48)

16 (84.21)

2.38 (0.30-19.86)

Log additive

 

0.85 (0.51-1.40)

 

1.01 (0.53-1.91)

rs6822259

    

CC

3 (1.43)

Reference

0 (0)

Reference

CT

50 (23.81)

1.25 (0.30-5.10)

7 (35.00)

--

TT

157 (74.76)

1.27 (0.32-5.03)

13 (65.00)

--

TT/CT

207 (98.57)

1.26 (0.32-4.95)

20 (100.00)

--

Log additive

 

1.11 (0.68-1.79)

 

--

rs17147338

    

CC

154 (72.99)

Reference

12 (60.00)

Reference

CT

48 (22.75)

1.64 (0.92-2.93)

7 (35.00)

2.78 (0.65-11.96)

TT

9 (4.27)

1.92 (0.30-12.18)

1 (5.00)

12.86 (0.91-181.95)

TT/CT

57 (27.01)

1.67 (0.94-2.91)

8 (40.00)

3.41 (0.89-13.08)

Log additive

 

1.70 (1.00-3.01)

 

2.44 (0.42-12.17)

UGT2B17

    

rs7435827

    

GG

50 (25.00)

Reference

3 (16.67)

Reference

GA

38 (19.00)

0.67 (0.34-1.31)

4 (22.22)

0.73 (0.11-4.72)

AA

112 (56.00)

0.87 (0.46-1.63)

11 (61.11)

1.33 (0.26-6.84)

AA/GA

150 (75.00)

0.78 (0.44-1.37)

15 (83.33)

1.03 (0.23-4.65)

Log additive

 

0.67 (0.35-1.32)

 

0.90 (0.49-1.66)

rs7686008

    

AA

154 (72.99)

Reference

12 (60.00)

Reference

AT

29 (13.74)

1.25 (0.61-2.58)

4 (20.00)

5.42 (1.05-27.96)

TT

28 (13.27)

1.30 (0.60-2.80)

4 (20.00)

5.05 (0.72-35.66)

TT/AT

57 (27.01)

1.27 (0.71-2.28)

8 (40.00)

5.30 (1.19-23.55)

Log additive

 

1.41 (0.70-2.84)

 

1.42 (0.67-3.01)

rs7671342

    

GG

34 (16.19)

Reference

3 (14.28)

Reference

GA

43 (20.48)

0.89 (0.44-1.81)

4 (19.05)

0.61 (0.08-4.60)

AA

133 (63.33)

1.31 (0.71-2.41)

14 (66.67)

1.28 (0.26-6.35)

AA/GA

176 (83.81)

1.17 (0.64-2.11)

18 (85.71)

1.05 (0.22-5.04)

Log additive

 

0.86 (0.43-1.73)

 

1.30 (0.72-2.36)

rs59678213

    

CC

40 (20.20)

Reference

2 (11.76)

Reference

TC

41 (20.71)

0.99 (0.54-1.81)

4 (23.53)

2.77 (0.27-28.17)

TT

117 (59.09)

0.76 (0.40-1.45)

11 (64.71)

3.60 (0.38-33.75)

TT/TC

158 (79.79)

0.76 (0.42-1.38)

15 (88.23)

3.21 (0.37-27.47)

Log additive

 

1.02 (0.56-1.82)

 

1.18 (0.63-2.21)

*Adjusted for age, race and BMI.

Restricting analyses by race/ethnicity, and after adjusting for age and BMI, further revealed that these associations were present in African American men (rs9994887, OR = 1.66, 95% CI = 1.05, 2.63; rs13112099, OR = 1.66, 95% CI = 1.03, 2.63; rs7686914, OR = 1.64, 95% CI = 1.03, 2.63; rs7696472, OR = 1.64, 95% CI = 1.03, 2.63; rs4148269, OR = 2.04, 95% CI = 1.19, 3.44; and rs3100, OR = 1.89, 95% CI = 1.22, 2.94) (Table 5). However, the interaction terms for these SNPs and race were not statistically significant (p > 0.4) for all six SNPs. For both groups, carrying the UGT2B17 or cis-acting SNPs was not associated with prostate cancer risk (Table 5).
Table 5

*ORs for the associations between UGT2B15 and UGT2B17 SNPs and PC in African American and Caucasian men

 

African American

Caucasian

SNP # Allele

Cases n (%)

Controls n (%)

Adjusted OR (95% CI)*

Cases n (%)

Controls n (%)

Adjusted OR (95% CI)*

UGT2B15

      

rs1580083

      

TT

0 (0)

1 (0.72)

Reference

2 (2.30)

4 (20.9)

Reference

TA

86 (58.90)

94 (68.12)

---

64 (73.56)

155 (77.11)

1.22 (0.10-14.43)

AA

60 (41.10)

43 (31.16)

---

21 (24.14)

42 (1.99)

1.36 (0.11-16.96)

AA/TA

146 (100.0)

137 (99.27)

---

85 (97.70)

159 (79.1)

1.25 (0.11-14.73)

Log additive

  

--

  

1.12 (0.58-2.17)

rs1960773

      

TT

0 (0)

2 (1.45)

Reference

1 (1.16)

3 (23.38)

Reference

GT

82 (56.94)

93 (67.39)

--

62 (72.09)

151 (75.12)

--

GG

62 (43.06)

43 (31.16)

-

23 (26.74)

47 (1.49)

--

GG/GT

144 (100.0)

136 (98.55)

--

85 (98.83)

198 (76.62)

--

Log additive

  

--

  

--

rs9994887

      

AA

16 (10.96)

28 (20.44)

Reference

22 (25.29)

63 (31.50)

Reference

AG

65 (44.52)

63 (45.99)

1.92 (0.72-5.10)

43 (49.43)

93 (46.50)

1.93 (0.90-4.14)

GG

65 (44.52)

46 (33.58)

2.96 (1.09-8.04)

22 (25.29)

44 (22.00)

1.87 (0.77-4.54)

GG/AG

130 (89.04)

109 (79.56)

2.34 (0.93-5.88)

65 (74.71)

137 (68.50)

1.91 (0.92-3.96)

Log additive

  

1.66 (1.05-2.63)

  

1.35 (0.88-2.08)

rs13112099

      

TT

16 (10.96)

28 (20.00)

Reference

22 (25.29)

63 (31.18)

Reference

GT

67 (45.89)

68 (48.57)

1.96 (0.74-5.20)

43 (49.43)

95 (47.03)

1.88 (0.88-4.05)

GG

63 (43.15)

44 (31.43)

2.94 (1.07-8.05)

22 (25.29)

44 (21.78)

1.87 (0.77-4.54)

GG/GT

130 (89.04)

112 (80.00)

2.34 (0.93-5.88)

65 (74.71)

139 (68.81)

1.88 (0.91-3.91)

Log additive

  

1.66 (1.03-2.63)

  

1.35 (0.88-2.08)

rs7686914

      

TT

16 (11.03)

28 (20.14)

Reference

22 (25.58)

63 (31.50)

Reference

CT

67 (46.21)

67 (48.20)

2.00 (0.75-5.31)

42 (48.84)

93 (46.50)

1.88 (0.87-4.05)

CC

62 (42.75)

44 (31.65)

2.94 (1.07-8.05)

22 (25.58)

44 (22.00)

1.87 (0.77-4.54)

CC/CT

129 (88.96)

111 (79.86)

2.37 (0.94-5.96)

64 (74.42)

137 (68.50)

1.88 (0.91-3.91)

Log additive

  

1.64 (1.03-2.63)

  

1.35 (0.88-2.08

rs7696472

      

GG

16 (10.96)

29 (20.70)

Reference

22 (25.29)

63 (31.66)

Reference

AG

67 (45.89)

67 (47.86)

1.96 (0.74-5.20)

43 (49.43)

90 (45.23)

2.01 (0.93-4.32)

AA

63 (43.15)

44 (31.43)

2.94 (1.07-8.05)

22 (25.29)

46 (23.12)

1.77 (0.73-4.27)

AA/AG

130 (89.04)

111 (79.28)

2.34 (0.93-5.88)

65 (74.71)

136 (68.34)

1.93 (0.93-4.04)

Log additive

  

1.64 (1.03-2.63)

  

1.31 (0.86-2.00)

rs4148269

      

CC

9 (6.25)

11 (7.86)

Reference

34 (39.53)

68 (34.00)

Reference

CA

34 (23.61)

58 (41.43)

0.73 (0.20-2.70)

38 (44.19)

102 (51.00)

0.89 (0.46-1.73)

AA

101 (70.14)

71 (50.71)

2.34 (0.67-7.83)

14 (16.28)

30 (15.00)

1.46 (0.57-3.77)

AA/CA

135 (93.75)

129 (92.14)

1.65 (0.51-5.34)

52 (60.46)

132 (66.00)

0.99 (0.53-1.85)

Log additive

  

2.04 (1.19-3.44)

  

1.12 (0.71-1.75)

rs3100

      

TT

18 (12.86)

32 (23.02)

Reference

36 (41.38)

74 (36.63)

Reference

TC

31 (22.14)

42 (30.22)

1.57 (0.54-4.55)

37 (42.53)

98 (48.51)

0.91 (0.47-1.72)

CC

91 (65.00)

65 (46.76)

3.36 (1.36-8.30)

14 (16.09)

30 (14.85)

1.48 (0.58-3.78)

CC/TC

122 (87.14)

107 (76.97)

2.75 (1.15-6.58)

51 (58.62)

128 (63.36)

1.00 (0.54-1.84)

Log additive

  

1.89 (1.22-2.94)

  

1.12 (0.72-1.75)

Cis acting on UGT2B expression

      

rs2168047

      

AA

42 (28.97)

36 (26.09)

Reference

11 (12.64)

23 (11.50)

Reference

GA

69 (47.59)

65 (47.10)

0.83 (0.39-1.75)

43 (49.43)

104 (52.00)

0.92 (0.35-2.42)

GG

34 (23.44)

37 (26.81)

0.91 (0.37-2.21)

33 (37.94)

73 (36.50)

1.07 (0.39-2.93)

GG/GA

103 (71.03)

102 (73.91)

0.85 (0.42-1.72)

76 (87.35)

177 (88.50)

0.98 (0.38-2.48)

Log additive

  

0.94 (0.61-1.47)

  

1.07 (0.67-1.72)

rs6822259

      

CC

1 (0.69)

4 (2.86)

Reference

2 (2.30)

8 (3.98)

Reference

CT

25 (17.24)

38 (27.14)

0.61 (0.03-10.56)

33 (37.93)

59 (29.35)

1.60 (0.86-2.96)

TT

119 (82.07)

98 (70.00)

0.91 (0.05-14.99)

52 (59.77)

134 (66.67)

0.70 (0.14-3.54)

TT/CT

144 (99.31)

136 (97.14)

0.83(0.05-13.61)

85 (97.70)

193 (96.01)

1.47 (0.81-2.67)

Log additive

  

1.34 (0.68-2.77)

  

1.23 (0.75-2.03)

rs17147338

      

TT

91 (62.33)

100 (71.43)

Reference

77 (88.51)

0 (0)

Reference

CT

46 (31.51)

35 (25.00)

1.72 (0.84-3.54)

9 (10.34)

16 (7.96)

--

CC

9 (6.16)

5 (3.57)

1.51 (0.23-9.88)

1 (1.15)

185 (92.04)

--

CC/CT

55 (37.67)

40 (28.57)

1.70 (0.85-3.40)

10 (11.49)

16 (7.96)

--

Log additive

  

1.53 (0.84-2.82)

  

--

UGT2B17

      

rs7435827

      

GG

13 (9.35)

13 (9.56)

Reference

40 (50.00)

93 (49.21)

Reference

GA

22 (15.83)

27 (19.85)

0.47 (0.12-1.92)

21 (26.25)

51 (26.98)

0.78 (0.37-1.66)

AA

104 (74.82)

96 (70.59)

0.80 (0.24-2.68)

19 (23.75)

45 (23.81)

0.86 (0.40-1.85)

AA/GA

126 (90.65)

123 (90.44)

0.72 (0.22-2.41)

40 (50.00)

96 (50.79)

0.82 (0.44-1.52)

Log additive

  

1.08 (0.64-1.85)

  

1.08 (0.75-1.59)

rs7686008

      

AA

83 (56.85)

92 (66.19)

Reference

84 (96.55)

189 (93.56)

Reference

AT

32 (21.92)

25 (17.99)

1.65 (0.74-3.69)

2 (2.3)

7 (3.47)

0.70 (0.13-3.71)

TT

31 (21.23)

22 (15.83)

1.51 (0.67-3.44)

1 (1.15)

6 (2.97)

0.99 (0.10-10.04)

TT/AT

63 (43.15)

47 (33.81)

1.58 (0.83-3.01)

3 (3.45)

13 (6.44)

0.78 ( 0.20-3.08)

Log additive

  

1.28 (0.86-1.90)

  

0.88 (0.33-2.36)

rs7671342

      

GG

22 (15.07)

23 (16.43)

Reference

15 (17.44)

33 (16.34)

Reference

GA

25 (17.12)

35 (25.00)

0.66 (0.24-1.88)

21 (24.42)

50 (24.75)

1.06 (0.42-2.67)

AA

99 (67.81)

82 (58.57)

1.51 (0.63-3.64)

50 (58.14)

119 (58.91)

1.15 (0.51-2.59)

AA/GA

124 (84.93)

117 (83.57)

1.21 (0.52-2.84)

71 (82.55)

169 (83.66)

1.12 (0.51-2.46)

Log additive

  

1.36 (0.90-2.08)

  

1.07 (0.73-1.59)

rs59678213

      

CC

10 (7.35)

8 (5.97)

Reference

32 (40.00)

73 (40.11)

Reference

TC

19 (13.97)

24 (17.91)

0.45 (0.10-2.00)

27 (33.75)

50 (27.47)

1.04 (0.49-2.20)

TT

107 (78.68)

102 (76.12)

0.65 (0.18-2.41)

21 (26.25)

59 (32.42)

0.80 (0.37-1.71)

TT/TC

126 (92.65)

126 (94.02)

0.62 (0.17-2.24)

48 (60.00)

109 (59.89)

0.91 (0.48-1.73)

Log additive

  

0.99 (0.64-1.69)

  

1.11 (0.76-1.61)

*Adjusted for age and BMI.

To investigate the extent to which these SNPs were associated in our subjects we calculated correlation coefficients among the controls as shown in Table 6. The r2 values for the UGT2B15 variants rs1580083, rs1960773, rs13112099, rs7686914, rs7696472 and rs9994887 ranged from 0.62 to 0.99/1.00 (p < 0.0001). UGT2B15 variants rs4148269 and rs3100 were also strongly correlated (r2 = 0.85, p < 0.0001). Including both SNPs into the same regression model to evaluate whether one SNP would have a stronger association with PC risk did not yield additional insights. Notably, these two SNPs showed no correlation with the other SNPs that were highly associated with each other. UGT2B17 SNP rs7435827 was moderately correlated with UGT2B15 SNP rs2168047 (r2 = 0.36, p < 0.0001) and UGT2B17 SNP rs7671342 (r2 = 0.32, p < 0.0001), and strongly correlated with UGT2B17 SNP rs59678213 (r2 = 0.83, p < 0.0001); however these SNPs showed no association with prostate cancer risk. UGT2B17 SNP rs59678213 was inversely associated with UGT2B17 SNPs rs2168047 (r2 = −0.47, p < 0.0001), rs7686008 (r2 = −0.29, p < 0.0001) and rs7671342 (r2 = −0.49, p < 0.0001). No correlations were observed for the cis-acting UGT2B SNPs that were identified through the recent UGT2B SNPs discovery study [38]. All SNPs that showed associations with prostate cancer risk were in Hardy-Weinberg equilibrium in control samples, except for UGT2B15 SNP rs3100.
Table 6

Spearman correlation coefficients and p values for UGT2B15 and UGT2B17 SNPs

 

rs1580083

rs1960073

rs9994887

rs13112099

rs7686914

rs7696472

rs4148269

rs3100

rs2168047

rs6822259

rs17147338

rs7435827

rs7686008

rs7671342

rs1580083

1.000

0.894

0.625

0.637

0.638

0.625

0.002

0.000

0.000

0.000

0.002

0.001

0.000

0.002

  

<.0001

<.0001

<.0001

<.0001

<.0001

0.458

0.780

0.749

0.873

0.366

0.527

0.720

0.414

rs1960073

0.894

1.000

0.631

0.650

0.645

0.631

0.001

0.000

0.001

0.001

0.002

0.000

0.000

0.003

 

<.0001

 

<.0001

<.0001

<.0001

<.0001

0.669

0.931

0.634

0.614

0.366

0.946

0.686

0.284

rs9994887

0.625

0.631

1.000

0.989

0.989

0.973

0.000

0.000

0.002

0.000

0.003

0.010

0.001

0.006

 

<.0001

<.0001

 

<.0001

<.0001

<.0001

0.685

0.776

0.384

0.894

0.296

0.069

0.549

0.145

rs13112099

0.637

0.650

0.989

1.000

1.000

0.984

0.001

0.070

0.002

0.000

0.004

0.009

0.001

0.005

 

<.0001

<.0001

<.0001

 

<.0001

<.0001

0.033

0.627

0.461

0.970

0.263

0.093

0.510

0.176

rs7686914

0.638

0.645

0.989

1.000

1.000

0.984

0.001

0.001

0.002

0.000

0.004

0.009

0.001

0.005

 

<.0001

<.0001

<.0001

<.0001

 

<.0001

0.033

0.627

0.462

0.970

0.264

0.094

0.510

0.177

rs7696472

0.625

0.631

0.973

0.984

0.984

1.000

0.002

0.002

0.001

0.000

0.003

0.007

0.001

0.006

 

<.0001

<.0001

<.0001

<.0001

<.0001

 

0.044

0.443

0.523

0.961

0.282

0.139

0.619

0.161

rs4148269

0.002

0.001

0.000

0.001

0.001

0.002

1.000

0.849

0.000

0.000

0.007

0.046

0.059

0.021

 

0.458

0.669

0.685

0.550

0.550

0.4217

 

<.0001

0.854

0.753

0.122

0.0001

<.0001

0.008

rs3100

0.000

0.000

0.000

0.070

0.001

0.002

0.849

1.000

0.003

0.001

0.002

0.018

0.021

0.015

 

0.780

0.931

0.776

0.627

0.627

0.443

<.0001

 

0.332

0.530

0.362

0.016

0.007

0.023

rs2168047

0.000

0.001

0.002

0.002

0.002

0.001

0.000

0.003

1.000

0.007

0.001

0.356

0.043

0.139

 

0.749

0.634

0.384

0.461

0.462

0.523

0.854

0.332

 

0.135

0.549

<.0001

0.0001

<.0001

rs6822259

0.000

0.001

0.000

0.000

0.000

0.000

0.000

0.001

0.007

1.000

0.023

0.004

0.006

0.000

 

0.873

0.614

0.894

0.970

0.970

0.961

0.753

0.530

0.135

 

0.005

0.279

0.170

0.825

rs17147338

0.002

0.002

0.003

0.004

0.004

0.003

0.007

0.002

0.001

0.023

1.000

0.005

0.000

0.000

 

0.366

0.366

0.295

0.263

0.264

0.282

0.122

0.362

0.549

0.005

 

0.223

0.895

0.873

rs7435827

0.001

0.000

0.010

0.009

0.009

0.007

0.046

0.018

0.356

0.004

0.005

1.000

0.162

0.318

 

0.527

0.946

0.069

0.093

0.093

0.139

0.0001

0.016

<.0001

0.279

0.223

 

<.0001

<.0001

rs7686008

0.000

0.000

0.001

0.001

0.001

0.001

0.059

0.021

0.043

0.006

0.000

0.162

1.000

0.047

 

0.720

0.686

0.549

0.510

0.510

0.619

<.0001

0.007

0.0001

0.170

0.895

<.0001

 

<.0001

rs7671342

0.002

0.003

0.006

0.005

0.005

0.006

0.021

0.015

0.139

0.000

0.000

0.318

0.047

1.000

 

0.414

0.284

0.145

0.176

0.177

0.161

0.008

0.023

<.0001

0.825

0.873

<.0001

<.0001

 

rs59678213

0.032

−0.001

0.078

0.071

0.070

0.058

0.116

0.045

−0.473

0.086

−0.077

0.830

−0.494

1.000

 

0.577

0.985

0.170

0.211

0.213

0.303

0.034

0.42

<0.0001

0.217

0.168

<0.0001

<0.001

 

Discussion and conclusion

In this study we examined associations between functional SNPs of the UDP-glucuronosyltransferase 2B (UGT2B) genes and prostate cancer risk. After adjusting for age and BMI, we found that two UGT2B15 SNPs, rs4148269 and rs3100, were associated with a two-fold increase risk of prostate cancer and the association was more apparent in African American men. In addition, SNPs rs9994887, rs13112099, rs7686914 and rs7696472 were also associated with increased risk of prostate cancer. These associations persisted either in low or high-grade prostate cancer lesions for SNPs rs9994887, rs13112099, rs7686914, and rs7696472. However, SNPs rs4148269 and rs3100 were only associated with increased risk of prostate cancer in high-grade prostate cancer lesions. These findings are novel and support the hypothesis that these SNPs may affect UDP-glucuronosyltransferase enzyme function, presumably by increasing the efficiency of androgen metabolite clearance compared to enzyme products of the UGT2B wild type genotype, as has been shown for UGT2B15 SNP rs1902023 [21].

Associations between functional SNPs of the UGT2B15 and UGT2B17 genes and prostate cancer risk have been previously examined and have rendered conflicting results [2232]. Discrepancies could be due in part to racial/ethnic differences in the populations studied but also to sample size and allele dosage. Comparison of two studies with different sample sizes revealed contradictory results: no associations between SNP UGT2B15 D85Y and prostate cancer risk were found in a study with a large sample size [9], whereas a study with a smaller sample size found an increased risk of prostate cancer associated with the UGT2B15 D85Y variant in Caucasian subjects [32]. In reference to allele dosage, we previously concluded [33], concordant with previous reports [31, 32, 39], that homozygous carriers of the dominant UGT2B15 D85Y (G) allele missense polymorphism, (rs1902023), had an almost three-fold higher risk of prostate cancer. Our current results further confirm that associations with UGT2B15 polymorphisms are allele dose-dependent and may also be dependent on race/ethnicity. Furthermore, our study includes a large and multiethnic sample size in comparison to previous reports.

Some of our stratified analyses revealed that UGT2B15 wild type alleles were significantly associated with increased risk of prostate cancer in African American men, but not in Caucasian men, suggesting that the wild type genotype may confer protection against prostate cancer in Caucasian men. While these findings require replication in larger studies, we provide new evidence that wild type genotypes for the UGT2B15 gene more frequently found in African American men may increase the risk of prostate cancer, and thus may contribute to the present racial/ethnical disparities seen in prostate cancer incidence. Few studies have assessed the association of UGT2B genes with prostate cancer risk in African Americans. Park et al. [25] were one of the first to report that associations between UGT2B17 polymorphisms and increased risk of prostate cancer were linked to race/ethnicity; they showed that Caucasian men carrying a UGT2B17 deletion polymorphism had a two-fold increased risk of prostate cancer, but not Black men who carry the same deletion, compared to non-carriers [25]. Subsequent work supported these findings [22, 26], which were further confirmed by others [23, 24]. Our results show no significant associations of UGT2B17 polymorphisms with prostate cancer risk in neither Caucasian nor African American men. Our findings that UGT2B17 SNP rs59678213 was not associated with prostate cancer risk are consistent with those of others [22, 24].

Four of the UGT2B15 SNPs that conferred prostate cancer risk in this study are among seven SNPs (rs1580083, rs1960773, rs9994887, rs13112099, rs7686914, rs7696472, and rs1120265 [not in study]) that are in high linkage disequilibrium (LD) with UGT2B15 D85Y SNP rs1902023 [34]. The phenotype of the variations, established with reporter gene assays in the liver cancer cell line HepG2, showed that transcriptional activity was higher for constructs containing the major alleles when compared to constructs containing the minor alleles. When a construct with the minor allele of rs9994887 was transfected into a prostate cancer cell line, LNCaP, transcriptional activity was decreased by approximately 14%, compared to constructs containing the major allele [34], which suggested that rs9994887 may influence gene expression in the prostate [34]. Further experiments would have to be done to determine the impact of these variants on the kinetics and efficacy of UGT2B enzymes. Interestingly, the other three SNPs that showed associations with increased prostate cancer risk, rs13112099, rs7686914, and rs7696472 were highly correlated with rs9994887 (r2 = 0.99, 0.99, and 0.97, respectively). In addition, the three SNPs are all located upstream of rs9994887 (−1139 bp relative to translation start) while the other two SNPs are located downstream. While the impact of these variants on UGT2B15 enzyme kinetics has not been reported, the associations suggest that the phenotype of the enzyme may be similar to that of the UGT2B15 85Y variant or rs1902023 [19]. SNPs rs4148269 and rs3100 also demonstrated strong associations with decreased risk of PC, but did not show any correlation with the promoter SNPs in this study population. SNP rs4148269 has been characterized as a T523K amino acid substitution [40], however a comprehensive analysis of the enzyme phenotype has not been reported. This suggests that rs3100, which is highly correlated (r2 = 0.85) with rs4148269, may be important in the etiology of PC. Results from reporter gene assays showed that the major allele of rs3100 is associated with significantly higher gene expression in LNCaP cells when compared to constructs made with the minor allele [36].

The lack of association observed for the UGT2B17 SNPs and PC risk was unexpected, as previous reports suggested that the UGT2B17 enzyme plays a major role in testosterone glucuronidation [20]. However results from a recent report comparing UGT2B17 and UGT2B15 mRNA and protein expression, suggest that UGT2B15 may be negatively regulated in naïve and castration-resistant tumors while undetectable in lymph node metastases [41]. More in vitro analyses are required to understand the functional impact of these genetic variations. Nonetheless this is the first time these SNPs are reported in relation to prostate cancer risk.

The main limitation of this study is the sample size which limited our ability to simultaneously examine race/ethnicity in the associations with SNPs and prostate cancer grade. The low numbers of Caucasians may have limited our ability to detect significant associations within this group given that they were less likely to present a high grade PC tumor. The small sample size could also have been a contributing factor in the lack of significance for the cross-product term for the SNPs and race, however race/ethnicity was self-reported and we did not measure ancestral markers, which could indicate the percentage of African American ancestry of each subject. Also, we cannot exclude the possibility of potential confounding due to differences in MAFs between races. Nonetheless our study was conducted at the DVAMC which provides medical care for all former military personnel. This type of setting has important advantages. The Veterans Affairs Medical Centers (VAMC) are considered an equal-access health care settings that may control for health care availability among various U.S. ethnicities [42]. Moreover, the VAMCs provide a setting for PC case–control studies as this is the leading cancer reported in Veterans Affairs Central Registry (VACCR) [43].

Despite these limitations, in the current case–control study of African American and Caucasian men, we observed elevated risk of prostate cancer in African American men who carry the wild type of the functional UGT2B15 gene variants. Future studies with larger sample sizes are needed to confirm these findings.

Declarations

Acknowledgements

We would like to thank Gary Bradwin of the Children’s Hospital of Boston; Meredith Bostrom of the David H. Murdock Research Institute, Kannapolis, NC; Shannon Oliver of North Carolina Central University and Alexis Gaines and Katie Shuler of Duke University for assistance.

Grant support

Department of Defense PC060233, NIH P20 MD000175, S06-GM008049-33, Department of Veterans Affairs, and the AUA Foundation/Astellas Rising Star in Urology, National Institutes of Health R01CA142983, R01CA142983-02S1, and R21ES021838-01A1.

Authors’ Affiliations

(1)
Department of Obstetrics and Gynecology, and Program of Cancer Detection, Prevention and Control, Duke University School of Medicine
(2)
Department of Biology and Cancer Research Program, JLC-Biomedical/Biotechnology Research Institute, North Carolina Central University
(3)
Department of Community and Family Medicine and Program of Cancer Detection, Prevention and Control, Duke University Medical Center
(4)
Department of Surgery, Division of Urology, Duke University Medical Center
(5)
Department of Surgery, Durham VA Medical Center
(6)
Duke Prostate Center, Duke University Medical Center
(7)
Department of Pathology, Duke University Medical Center

References

  1. Siegel R, Naishadham D, Jemal A: Cancer statistics, 2012. CA Cancer J Clin. 2012, 62: 10-29. 10.3322/caac.20138.View ArticlePubMedGoogle Scholar
  2. Brawley OW, Jani AB, Master V: Prostate cancer and race. Curr Probl Cancer. 2007, 31: 211-225. 10.1016/j.currproblcancer.2007.01.006.View ArticlePubMedGoogle Scholar
  3. Resnick MJ, Canter DJ, Guzzo TJ, Brucker BM, Bergey M, Sonnad SS: Does race affect postoperative outcomes in patients with low-risk prostate cancer who undergo radical prostatectomy?. Urology. 2009, 73: 620-623. 10.1016/j.urology.2008.09.035.View ArticlePubMedGoogle Scholar
  4. Robbins AS, Yin D, Parikh-Patel A: Differences in prognostic factors and survival among White men and Black men with prostate cancer, California, 1995–2004. Am J Epidemiol. 2007, 166: 71-78. 10.1093/aje/kwm052.View ArticlePubMedGoogle Scholar
  5. Gilligan T: Social disparities and prostate cancer: mapping the gaps in our knowledge. Cancer Causes Control. 2005, 16: 45-53. 10.1007/s10552-004-1291-x.View ArticlePubMedGoogle Scholar
  6. Howlader N, Noone AM, Krapcho M, Neyman N, Aminou R, Waldron W: SEER Cancer Statistics Review. 1975–2008, Bethesda: National Cancer InstituteGoogle Scholar
  7. Ward E, Jemal A, Cokkinides V, Singh GK, Cardinez C, Ghafoor A, Thun M: Cancer disparities by race/ethnicity and socioeconomic status. CA Cancer J Clin. 2004, 54: 78-93. 10.3322/canjclin.54.2.78.View ArticlePubMedGoogle Scholar
  8. Jemal A, Siegel R, Xu J, Ward E: Cancer Statistics. CA Cancer J Clin. 2010, 60: 277-300. 10.3322/caac.20073.View ArticlePubMedGoogle Scholar
  9. Altekruse SF, Huang L, Cucinelli JE, McNeel TS, Wells KM, Oliver MN: Spatial patterns of localized-stage prostate cancer incidence among white and black men in southeastern United States, 1999–2001. Cancer Epidemiol Biomarkers Prev. 2010, 19: 1460-1467. 10.1158/1055-9965.EPI-09-1310.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Major JM, Oliver M, Doubeni CA, Hollenbeck AR, Graubard BI, Sinha R: Socioeconomic status, healthcare density, and risk of prostate cancer among African American and Caucasian men in a large prospective study. Cancer Causes Control. 2012, 23: 1185-1191. 10.1007/s10552-012-9988-8.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Ricke EA, Williams K, Lee Y-I, Couto S, Wang Y, Hayward SW, Cunha GR, Ricke WA: Androgen hormone action in prostatic carcinogenesis: stromal androgen receptors mediate prostate cancer progression, malignant transformation and metastasis. Carcinogenesis. 2012, 33: 1391-1398. 10.1093/carcin/bgs153.View ArticlePubMedPubMed CentralGoogle Scholar
  12. Tang L, Yao S, Till C, Goodman PJ, Tangen CM, Wu Y, Kristal AR, Platz EA, Neuhouser ML, Stanczyk FZ, Reichard JKV, Santella RM, Hsing A, Hoque A, Lippman SM, Thompson IM, Ambrosone CB: Repeat polymorphisms in estrogen metabolism genes and prostate cancer risk: results from the Prostate Cancer Prevention Trial. Carcinogenesis. 2011, 32: 1500-1506. 10.1093/carcin/bgr139.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Vasaitis TS, Bruno RD, Njar VCO: CYP17 inhibitors for prostate cancer therapy. J Steroid Biochem Mol Biol. 2011, 125: 23-31. 10.1016/j.jsbmb.2010.11.005.View ArticlePubMedGoogle Scholar
  14. Ritter JK: Roles of glucuronidation and UDP-glucuronosyltransferases in xenobiotic bioactivation reactions. Chem Biol Interact. 2000, 129: 171-193. 10.1016/S0009-2797(00)00198-8.View ArticlePubMedGoogle Scholar
  15. Belanger A, Plletier G, Labrie F, Barbier O, Chouinard S: Inactivation of androgens by UDP-glucuronosyltransferase enzymes in humans. Trends Endocrinol Metabol. 2001, 14: 473-479.View ArticleGoogle Scholar
  16. Chouinard S, Barbier O, Belanger A: UDP-glucuronosyltransferase 2B15 (UGT2B15) and UGT2B17 enzymes are major determinants of the androgen response in prostate cancer LNCaP cells. J Biol Chem. 2007, 282: 33466-33474. 10.1074/jbc.M703370200.View ArticlePubMedGoogle Scholar
  17. Turgeon D, Carrier JS, Levesque E, Hum DW, Belanger A: Relative enzymatic activity, protein stability, and tissue distribution of human steroid-metabolizing UGT2B subfamily members. Endocrinology. 2001, 142: 778-787. 10.1210/en.142.2.778.PubMedGoogle Scholar
  18. Wilson W, De Villena FP-M, Lyn-Cook BD, Chatterjee PK, Bell TA, Detwiler DA, Gilmore RC, Valladeras IC, Wright CC, Treadgill DW, Grant DJ: Characterization of a common deletion polymorphism of the UGT2B17 gene linked to UGT2B15. Genomics. 2004, 84: 707-714. 10.1016/j.ygeno.2004.06.011.View ArticlePubMedGoogle Scholar
  19. Levesque E, Beaulieu M, Green MD, Tephly TR, Belanger A, Hum DW: Isolation and characterization of UGT2B15(Y85): a UDP-glucuronosyltransferase encoded by a polymorphic gene. Pharmacogenetics. 1997, 7: 317-325. 10.1097/00008571-199708000-00007.View ArticlePubMedGoogle Scholar
  20. Jakobsson J, Ekstrom L, Inotsume N, Garle M, Ohlsson C, Roh HK, Carlstrom K, Rane A: Large differences in testosterone excretion in Korean and Swedish men are strongly associated with a UDP-glucuronosyl transferase 2B17 polymorphism. J Clin Endocrinol Metab. 2006, 91: 687-693.View ArticlePubMedGoogle Scholar
  21. Chouinard S, Yueh MF, Tukey RH, Giton F, Fiet J, Pelletier G, Barbier O, Belanger A: Inactivation by UDP-glucuronosyltransferase enzymes: the end of androgen signaling. J Steroid Biochem Mol Biol. 2008, 109: 247-253. 10.1016/j.jsbmb.2008.03.016.View ArticlePubMedGoogle Scholar
  22. Gallagher CJ, Kadlubar FF, Muscat JE, Ambrosone CB, Lang NP, Lazarus P: The UGT2B17 gene deletion polymorphism and risk of prostate cancer A case–control study in Caucasians. Cancer Detect Prev. 2007, 31: 310-315. 10.1016/j.cdp.2007.07.005.View ArticlePubMedPubMed CentralGoogle Scholar
  23. Karypidis AH, Olsson M, Andersson SO, Rane A, Ekstrom L: Deletion polymorphism of the UGT2B17 gene is associated with increased risk for prostate cancer and correlated to gene expression in the prostate. Pharmacogenomics J. 2008, 8: 147-151. 10.1038/sj.tpj.6500449.View ArticlePubMedGoogle Scholar
  24. Olsson M, Lindstrom S, Haggkvist B, Adami HO, Balter K, Stattin P, Ask B, Rane A, Ekstrom L, Gronberg H: The UGT2B17 gene deletion is not associated with prostate cancer risk. Prostate. 2008, 68: 571-575. 10.1002/pros.20700.View ArticlePubMedGoogle Scholar
  25. Park J, Chen L, Ratnashinge L, Sellers TA, Tanner JP, Lee JH, Dossett N, Lang N, Kadlubar FF, Ambrosone CB, Zachariah B, Heysek R, Patterson S, Pow-Sang J: Deletion polymorphism of UDP-glucuronosyltransferase 2B17 and risk of prostate cancer in African American and Caucasian men. Cancer Epidemiol Biomarkers Prev. 2006, 15: 1473-1478. 10.1158/1055-9965.EPI-06-0141.View ArticlePubMedGoogle Scholar
  26. Park JY, Tanner JP, Sellers TA, Huang Y, Stevens CK, Dossett N, Shankar RA, Zachariah B, Heysek R, Pow-Sang J: Association between polymorphisms in HSD3B1 and UGT2B17 and prostate cancer risk. Urology. 2007, 70: 374-379. 10.1016/j.urology.2007.03.001.View ArticlePubMedGoogle Scholar
  27. Setlur SR, Chen CX, Hossain RR, Ha JS, Van Doren VE, Stenzen B, Steiner E, Oldridge D, Kitabayashi N, Banerjee S, Chen JY, Schafer G, Horninger W, Lee C, Rubin MA, Klocker H, Demichelis F: Genetic variation of genes involved in dihydrotestosterone metabolism and the risk of prostate cancer. Cancer Epidemiol Biomarkers Prev. 2010, 19: 229-239. 10.1158/1055-9965.EPI-09-1018.View ArticlePubMedGoogle Scholar
  28. Cunningham JM, Hebbring SJ, McDonnell SK, Cicek MS, Christensen GB, Wang L, Jacobsen SJ, Cerhan JR, Blute ML, Schaid DJ, Thibodeau SN: Evaluation of genetic variations in the androgen and estrogen metabolic pathways as risk factors for sporadic and familial prostate cancer. Cancer Epidemiol Biomarkers Prev. 2007, 16: 969-978. 10.1158/1055-9965.EPI-06-0767.View ArticlePubMedGoogle Scholar
  29. Gsur A, Preyer M, Haidinger G, Schatzl G, Madersbacher S, Marberger M, Vutuc C, Micksche M: A polymorphism in the UDP-Glucuronosyltransferase 2B15 gene (D85Y) is not associated with prostate cancer risk. Cancer Epidemiol Biomarkers Prev. 2002, 11: 497-498.PubMedGoogle Scholar
  30. Hajdinjak T, Zagradisnik B: Prostate cancer and polymorphism D85Y in gene for dihydrotestosterone degrading enzyme UGT2B15: Frequency of DD homozygotes increases with Gleason score. Prostate. 2004, 59: 436-439. 10.1002/pros.20024.View ArticlePubMedGoogle Scholar
  31. MacLeod SL, Nowell S, Plaxco J, Lang NP: An allele-specific polymerase chain reaction method for the determination of the D85Y polymorphism in the human UDP-glucuronosyltransferase 2B15 gene in a case–control study of prostate cancer. Ann Surg Oncol. 2000, 7: 777-782. 10.1007/s10434-000-0777-3.View ArticlePubMedGoogle Scholar
  32. Park J, Chen L, Shade K, Lazarus P, Seigne J, Patterson S, Helal M, Pow-Sang J: Asp85tyr polymorphism in the udp-glucuronosyltransferase (UGT) 2B15 gene and the risk of prostate cancer. J Urol. 2004, 171: 2484-2488. 10.1097/01.ju.0000117748.44313.43.View ArticlePubMedGoogle Scholar
  33. Grant DJ, Hoyo C, Oliver SD, Gerber L, Shuler K, Calloway E, McPhail M, Livingston JN, Richardson RM, Schildkraut JM, Freedland SJ: Association of UridineDiphosphate-Glucuronosyltransferase 2B gene variants with serum glucuronide levels and prostate cancer risk. Genet Test Mol Biomarkers. 2012, 17: 1-7.Google Scholar
  34. Sun C, Southard C, Witonsky DB, Olopade OI, Di Renzo A: Allelic imbalance (AI) identifies novel tissue-specific cis-regulatory variation for human UGT2B15. Hum Mut. 2010, 31: 99-107. 10.1002/humu.21145.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Antonelli JA, Jones LW, Banez LL, Thomas JA, Anderson K, Taylor LA, Gerber L, Anderson T, Hoyo C, Grant DJ, Freedland SJ: Exercise and prostate cancer risk in a cohort of veterans undergoing prostate needle biopsy. J Urol. 2009, 182: 2226-2231. 10.1016/j.juro.2009.07.028.View ArticlePubMedGoogle Scholar
  36. Sun S, Southard C, Olopade OI, Di Rienzo A: Differential allelic expression of c.1568C>A at UGT2B15 is due to variation in a novel cis-regulatory element in the 3′UTR. Gene. 2011, 481: 24-28. 10.1016/j.gene.2011.04.001.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Hu DG, Gardner-Stephen D, Severi G, Gregory PA, Treolar J, Giles GG, English DR, Hopper JL, Tilley WD, Mackenzie PI: A novel polymorphism in a forkhead box A1 (FOXA1) binding site of the human UDP glucuronosyltransferase 2B17 gene modulates promoter activity and is associated with altered levels of circulating androstane-3alpha,17beta-diol glucuronide. Mol Pharmacol. 2010, 78: 714-722. 10.1124/mol.110.065953.View ArticlePubMedGoogle Scholar
  38. Sun S, Southard C, Huo D, Hernandez RD, Witonsky DB, Olopade OI, DiRienzo A: SNP discovery, expression and cis-regulatory variation in the UGT2B genes. Pharmacogenomics J. 2012, 12: 287-296. 10.1038/tpj.2011.2.View ArticlePubMedGoogle Scholar
  39. Okugi H, Nakazato H, Matsui H, Ohtake N, Nakata S, Suzuki K: Association of the polymorphisms of genes involved in androgen metabolism and signaling pathways with familial prostate cancer risk in a Japanese population. Cancer Detect Prev. 2006, 30: 262-268. 10.1016/j.cdp.2006.04.004.View ArticlePubMedGoogle Scholar
  40. Iida A, Saito S, Sekine A, Mishima C, Kitamura Y, Kondo K, Harigae S, Osawa S, Nakamura Y: Catalog of 86 single-nucleotide polymorphisms (SNPs) in three uridine diphosphate glycosyltransferase genes: UGT2A1, UGT2B15, and UGT8. J Hum Genet. 2002, 47: 505-510. 10.1007/s100380200075.View ArticlePubMedGoogle Scholar
  41. Paquet S, Fazli L, Grosse L, Verreault M, Tetu B, Rennie PS, Belanger A, Barbier O: Differential expression of the androgen-conjugating UGT2B15 and UGT2B17 enzymes in prostate tumor cells during cancer progression. J Clin Endocrinol Metab. 2012, 97: E428-E432. 10.1210/jc.2011-2064.View ArticlePubMedGoogle Scholar
  42. Chu DI, Moreira DM, Gerber L, Presti JC, Aronson WJ, Terris MK, Kane CJ, Amling CL, Freedland SJ: Effect of race and socioeconomic status on surgical margins and biochemical outcomes in an equal-access health care setting. Cancer. 2012, 118: 4999-5007. 10.1002/cncr.27456.View ArticlePubMedPubMed CentralGoogle Scholar
  43. Zullig LL, Jackson GL, Dorn RA, Provenzale DT, McNeil R, Thomas CM, Kelley MJ: Cancer incidence among patients of the U.S. Veterans Affairs Health Care System. Mil Med. 2012, 177: 693-701.View ArticlePubMedPubMed CentralGoogle Scholar
  44. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/13/556/prepub

Copyright

© Vidal et al.; licensee BioMed Central Ltd. 2013

This article is published under license to 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 any medium, provided the original work is properly cited.