Mutation Research 769 (2014) 17–34

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BsmI polymorphism of vitamin D receptor gene and cancer risk: A comprehensive meta-analysis Sara Raimondi a,∗ , Elena Pasquali a , Patrizia Gnagnarella a , Davide Serrano b , Davide Disalvatore a , Harriet A. Johansson b , Sara Gandini a a b

Division of Epidemiology and Biostatistics, European Institute of Oncology, Via Ripamonti 435, 20141 Milan, Italy Division of Cancer Prevention and Genetics, European Institute of Oncology, Via Ripamonti 435, 20141 Milan, Italy

a r t i c l e

i n f o

Article history: Received 31 January 2014 Received in revised form 13 June 2014 Accepted 16 June 2014 Available online 23 June 2014 Keywords: BsmI Meta-analysis Molecular epidemiology VDR Vitamin D

a b s t r a c t The VDR gene is an important regulator of the vitamin D pathway, and the role of some of its polymorphisms on cancer risk was previously investigated. A trend of cancer risk reduction with the VDR BsmI B allele was observed for many cancer sites. We performed a comprehensive meta-analysis to investigate the role of VDR BsmI polymorphism on cancer risk, even according to different ethnicities. Summary odds ratios (SORs) were calculated with random-effects models and maximum likelihood estimation. We categorized studies into three groups (“moderate”, “high” and “very high confidence”) according to departure from Hardy–Weinberg equilibrium in controls, reported minor allele frequency and genotyping quality controls. The meta-analysis included 73 studies with 45,218 cases and 52,057 controls. We found a significant 6–7% reduction of cancer risk at any site respectively for carriers of Bb genotype (SOR; 95%CI: 0.94; 0.90–0.99) and for carriers of BsmI BB genotype (SOR; 95%CI: 0.93; 0.89–0.98) compared to bb carriers, and they remain statistically significant when we restricted the analysis to at least “high confidence” studies. For skin cancer, a significant risk reduction was observed for Bb carriers (SOR; 95%CI: 0.86; 0.76–0.98). We also found a significant reduction of colorectal cancer risk for BB and Bb + BB genotypes carriers, but these SORs were no more significant when we restricted the analysis to studies with “high confidence”. When the analysis was stratified by ethnicity, we still observed a significant decreased risk for both Bb and BB compared to bb genotype among Caucasians: SORs (95%CI) for any cancer site were 0.97 (0.93–1.00) and 0.95 (0.91–0.99), respectively. Among other ethnic groups the inverse association was still present, but did not reach statistical significance. In conclusion, we suggest a weak effect of BsmI B allele in reducing cancer risk at any site, especially of the skin. © 2014 Elsevier B.V. All rights reserved.

1. Introduction The better known role of vitamin D is in mineral metabolism and bone growth, but it plays a crucial role in many other health aspects.

Abbreviations: AA, African-American; BCC, basal cell carcinoma; CCS1-2, case–control study 1-2; CPS-II, cancer prevention study II; CI, confidence interval; DGGE, denaturing gradient gel electrophoresis; DHPLC, denaturing high performance liquid chromatography; EAC, esophageal adenocarcinoma; EPIC, European Prospective Investigation into cancer and nutrition; HCC, hepatocellular carcinoma; MAF, minor allele frequency; MEC, Hawaii–Los Angeles Multiethnic Cohort; NHL, non-Hodgkin lymphoma; NHS, nurses’ health study; NMSC, non-melanoma skin cancer; NPC, nasopharingeal carcinoma; NS, not specified; OSCC, oral squamous cell carcinoma; PLCO, prostate lung colorectal and ovarian cancer screening trial; PY, publication year; RFLP, restriction fragment length polymorphism; SCC, squamous cell carcinoma; SOR, summary odds ratio; TC, thyroid carcinoma; WHS, women’s health study. ∗ Corresponding author. Tel.: +39 02 94372711; fax: +39 02 57489922. E-mail address: [email protected] (S. Raimondi). http://dx.doi.org/10.1016/j.mrfmmm.2014.06.001 0027-5107/© 2014 Elsevier B.V. All rights reserved.

Epidemiological data have suggested a protective function both of vitamin D and of circulating 25-hydroxyvitamin D (25(OH)D3 ) levels on cancer in different sites [1–11]. Proposed mechanisms for the protective effects of vitamin D against cancer development involve reduction of invasiveness and angiogenesis, proliferation, differentiation and apoptosis of several cancer cell lines [12–15]. Vitamin D also has pleiotropic function in the immune, neural, and endocrine systems [16], all of which are involved in the regulation of tumor growth and metastasis [17]. In humans, most vitamin D is derived from the action of sunlight on the skin, converting 7-dehydrocholesterol to pre-vitamin D3 . vitamin D3 from the skin and vitamin D2 and D3 from the diet are metabolized in the liver to 25(OH)D3 (the best measure of vitamin D status) and this is subsequently hydroxylated in the kidney to form the biologically active form of vitamin D: 1,25dihydroxyvitamin D3 (1,25(OH)2 D3 ). 1,25(OH)2 D3 , or calcitriol, is the hormonal derivative of vitamin D [18] and it plays an important role in the development of cancers by regulating the expression of

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tumor-related genes or mediating inhibition of cell growth, adhesion, migration, metastases and angiogenesis in vitro and in vivo [13,19–26]. Furthermore it exerts transcriptional activation and repression of target genes by binding to the vitamin D receptor (VDR), which is a member of the steroid hormone receptor superfamily located on chromosome 12 (12q12-q14) that regulates gene expression in a ligand dependent manner [20]. VDR is active in virtually all tissues including: colon, breast, lung, ovary, bone, kidney, parathyroid gland, pancreatic b-cells, monocytes, T lymphocytes, melanocytes keratinocyte and also in cancer cells. Up to 25 polymorphisms in the VDR gene have been identified [27] that were reported to be linked to various biological processes [28] and that may influence cancer risk [29]. It has been hypothesized that for individuals with similar vitamin D intake or status, those having a less active VDR could present an increased susceptibility to cancer risk. The role of VDR within the vitamin D risk reduction mechanism has been demonstrated in several animal models. For example, skin cancer models showed that in VDR null mice there is an increased papilloma and skin cancer incidence after topical carcinogens or UVB irradiation [30–32]. One of the most frequently studied VDR polymorphisms is BsmI, located at the 3 end of the gene. It is intronic and apparently does not alter the amino acid sequence of the translated VDR protein [28]. However, in Caucasians it is in strong linkage disequilibrium with poly(A) microsatellite repeat in the 3 untranslated region that influence VDR messenger RNA stability [27] and hence affect local VDR protein levels [33,34]. Some degree of coupling with poly(A) microsatellite was observed even in non-Caucasian populations, but the strength of the linkage disequilibrium varied by ethnicity [33]. The BsmI B allele was reported to be significantly associated with a reduced risk of melanoma, colorectal and prostate cancer in previous meta-analyses [29,35,36]. Besides VDR gene polymorphisms, 25(OH)D3 levels are dependent on latitude, season of year, skin color, clothing style and ethnicity. Considerable inter-individual variations in serum 25(OH)D3 levels in health subjects having extended sun exposure suggest that genetic differences exist in the amount of vitamin D necessary to maintain optimal physiologic function [37]. Large number of case–control studies was conducted to investigate the association of variants in the VDR gene and the risk of various types of cancer. Different meta-analyses were previously performed, but most of them were limited to single cancer sites [29,36,38–42]. An overview of the role of VDR polymorphisms on any cancer sites would be fundamental since the hypothesized biological mechanisms involved in vitamin D pathway are thought to affect cancer in general. Furthermore, the still limited amount of data on some cancer sites and ethnic groups prevented subgroup analysis in our previously comprehensive meta-analysis on VDR and cancer risk [29]. We present here an updated of our previous meta-analysis with 33 additional studies emerged from 2009, to extensively address the association between VDR BsmI polymorphism and cancer risk, both with overall risk and at specific organ sites. Furthermore, the considerable sample size enables us to investigate the possible modification role of ethnicity on the association between VDR BsmI polymorphism and cancer risk.

2. Materials and methods A systematic literature search and quantitative analysis were planned, conducted and reported following the meta-analysis of observational studies in epidemiology (MOOSE) guidelines [43]. Published reports were gathered from the following databases: PUBMED, Ovid Medline, EMBASE, and ISI Web of Knowledge up to April 2014. We used the following MeSH terms and text words:

“VDR”, “Vitamin D receptor”, or “BsmI” in combination with “cancer” or “tumor”, without any restriction. We also performed manual searches of references cited in the retrieved articles and preceding reviews on the topic. We screened titles and looked at abstracts when the title suggested a study possibly meeting the main criteria. If the abstract content was relevant, full copies of articles were retrieved and fully read by at least two co-authors. The articles were selected according with the following inclusion criteria: 1) Sufficient information to estimate the relative risk and 95% confidence intervals (CIs) for the association between VDR BsmI polymorphism and cancer (odds ratio (OR), relative risks or crude data and corresponding standard errors, variance, CIs or P-value of the significance of the estimates). 2) Studies had to be independent and not duplicate results published in another article. When several articles concerned the same subjects, results from the publication using the largest sample of subjects were used. Ecological studies, case reports, reviews and editorials were not considered eligible. Since the endpoint of the study is cancer at any site, we excluded studies evaluating the risk of benign conditions, like colorectal adenoma and benign prostatic hyperplasia. Furthermore, since lifestyle and genetic cancer risk factors vary greatly for children versus adults, we excluded a study evaluating the association between VDR polymorphism and risk of leukemia in children [44]. A standardized data-collection protocol was used for gathering the relevant data from each selected article. When data were reported by ethnicity or by cancer sites, the estimates were extracted separately for the two factors. Data extraction was done by one co-author (EP) in a pre-defined database, and then revised by a second co-author (SR): for each study we pulled out information on authors, journal and year of publication, country, ethnicity of study population, source of controls, number of cases and controls (separately for BB, Bb, and bb genotypes), relative risk estimates and the corresponding CI, along with possible confounders considered in the adjusted risk estimates. 2.1. Statistical analysis Reference category for the analysis was subjects with the wild type bb genotype. We retrieved from the papers fully adjusted estimates of the association between VDR polymorphism and cancer when available, and calculated crude estimates from tabular data otherwise. The summary odds ratio (SOR) for Bb, BB and Bb + BB compared to bb subjects was calculated according to cancer site and on the whole sample of studies by pooling the study-specific estimates with the random-effects models as described, with summary effect size obtained from maximum likelihood estimation [45]. We calculated the pooled estimate when at least three studies were included in each analysis. We assessed the homogeneity of the effects across studies by the I2 , that could be interpreted as the percentage of total variation across several studies that is attributable to heterogeneity: a threshold of I2 below 50% is generally considered an acceptable level of variability [46]. We used meta-regression to assess the influence on SOR of different study features, such as study design, ethnicity, type of controls, adjustment for confounding factors, publication year, departure from Hardy–Weinberg equilibrium (HWE) in controls and genotyping data confidence. For this latter variable, we categorized studies into three groups: the first one (“moderate confidence”) included studies for which genotyping frequency do

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Table 1 Characteristics of the studies included in the meta-analysis. First author, PY

Country

Ethnicity

Hospital controls

Prostate cancer Ingles, 1998 [62] Habuchi, 2000 [63] Chokkalingam, 2001 [64] Liu, 2003 [65] Nam, 2003 [66] Nam, 2003 [66] Nam, 2003 [66] Suzuki, 2003 [67] Huang, 2004 [68] Oakley-Girvan, 2004 [69] Oakley-Girvan, 2004 [69] Hayes, 2005 [70] Chaimuangraj, 2006 [71] Cicek, 2006 [72] Holick, 2007 [18] Li, 2007 [73] Mikhak, 2007 [74] Onen, 2008 [75] Bai, 2009 [76] Holt, 2009 [77] Holt, 2009 [77] Szendroi, 2011 [54] 18 STUDIES

USA Japan China China Canada Canada Canada Japan Taiwan USA USA Australia Thailand USA USA USA USA Turkey China USA USA Hungary

AA Asian Asian Asian Caucasian AA Asian Asian Asian Caucasian AA Caucasian Asian Caucasian Caucasian Caucasian Caucasian Other Asian Caucasian AA Caucasian

No Yes No Yes Yes Yes Yes Yes Yes No No No Yes No No No No Yes No No No Yes

151 222 242 103 421 45 12 81 103 232 113 862 28 439 630 1066 684 133 122 711 116 204 6720

Italy Taiwan Turkey UK Germany and Austria USA USA USA Canada Poland USA Europe USA USA USA USA USA USA USA USA Canada China USA USA USA USA USA Iran

Caucasian Asian Other Caucasian Caucasian

Yes Yes NS No NS

Mixed Caucasian AA Caucasian Caucasian Caucasian Caucasian Caucasian AA Asian Hispanic Hawaiian Caucasian Caucasian Caucasian Caucasian Asian Caucasian Hispanic Caucasian AA Hispanic Other

Mixed No No Mixed No No No No No No No No No No No No Yes No No No Yes Yes Yes

Hungary Korea Russia Bulgaria USA USA China Spain UK

Caucasian Asian Caucasian Caucasian Caucasian Caucasian Asian Caucasian Caucasian

Europe Czech Republic Iran Turkey USA

Caucasian Caucasian Other Other Mixed

Breast cancer Ruggiero, 1998 [78] Hou, 2002 [79] Buyru, 2003 [80] Guy, 2003 [81] Hefler, 2004 [82] VandeVord, 2006 [83] Trabert, 2007 [84] Trabert, 2007 [84] Sinotte, 2008 [85] Gapska, 2009 [86] McKay, 2009 [87] (CPS-II) McKay, 2009 [87] (EPIC) McKay, 2009 [87] (MEC) McKay, 2009 [87] (MEC) McKay, 2009 [87] (MEC) McKay, 2009 [87] (MEC) McKay, 2009 [87] (MEC) McKay, 2009 [87] (NHS) McKay, 2009 [87] (PLCO) McKay, 2009 [87] (WHS) Anderson, 2011 [88] Huang, 2012 [89] Rollison, 2012 [90] Rollison, 2012 [90] Fuhrman, 2013 [91] Mishra, 2013 [92] Mishra, 2013 [92] Shahbazi, 2013 [93] 16 STUDIES Colorectal cancer Speer, 2001 [94] Park, 2006 [95] Flugge, 2007 [96] Kadiyska, 2007 [97] Slattery, 2007 [98] (colon) Slattery, 2007 [98] (rectal) Li, 2008 [99] Parisi, 2008 [100] Theodoratou, 2008 [101] Jenab, 2009 [57] Hughes, 2011 [102] Mahmoudi, 2011 [103] Gunduz, 2012 [104] Sarkissyan, 2014 [105] 13 STUDIES

No cases

No controls

B allele frequency

Genotyping method

Genotyping data confidencea

174 128 472 106 444 45 47 105 106 171 121 745 30 479 565 1618 684 157 130 718 69 102 7216

0.36 0.27b , c 0.08b 0.03 0.45b 0.37 0.17b 0.11 0.09b 0.42 0.31 0.44 0.17b 0.41 0.41 0.39 0.39 0.39b 0.09 0.40 0.39 0.31b

PCR-RFLP PCR-RFLP PCR-RFLP DHPLC PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP DGGE PCR-RFLP PCR-RFLP SNPlex PCR-RFLP Taqman PCR-RFLP PCR-RFLP SNPlex SNPlex PCR-RFLP

High Moderate Moderate High Moderate Very high Moderate High Moderate Very high Very high High Moderate Very high High High Very high Moderate Very high Very high Very high Moderate

50 34 78 398 396

167 169 27 427 1936

0.48b 0.05 0.50 0.42 0.40b

PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP

Moderate High High High Moderate

220 1136 485 859 1760 432 1596 378 316 415 323 104 1122 1065 604 1546 146 1169 571 484 115 117 140 16,059

192 965 446 1381 1510 432 2620 416 412 410 369 274 1515 1097 604 1627 320 1328 719 845 73 276 156 20,713

0.38b 0.46b 0.30b 0.40 0.37 0.39 0.40 0.41 0.29 0.14 0.25 0.20 0.40 0.39 0.42 0.41 0.06 0.40 0.27 0.41 0.32 0.26 0.46

PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP Taqman Taqman Taqman Taqman Taqman Taqman Taqman Taqman Taqman Taqman Taqman iPLEX PCR-RFLP PCR-RFLP PCR-RFLP Taqman PCR-RFLP PCR-RFLP PCR-RFLP

Moderate Moderate Moderate High High Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high Very high High High Very High High High Very high

NS No Yes NS No No Yes Yes No

56 190 256 144 1551 762 200 170 3005

112 318 256 94 1933 969 200 120 3072

0.43 0.05 0.36 0.46 0.41 0.38 0.26b 0.37 0.41b

Moderated High High High High High Moderate High Moderate

No Yes Yes Yes Yes

1077 725 452 43 78 8709

1077 1135 452 42 230 10,010

0.43 0.38 0.42 0.50b 0.31

PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP PCR-RFLP Illumina Infinium I Taqman KASPar PCR-RFLP PCR-RFLP PCR-RFLP

Very high Very high Very high Moderate High

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S. Raimondi et al. / Mutation Research 769 (2014) 17–34

Table 1 (Continued) First author, PY

Country

Ethnicity

Hospital controls

B allele frequency

Genotyping method

Genotyping data confidencea

USA USA USA Italy USA Poland UK

Caucasian Caucasian Caucasian Caucasian Caucasian Caucasian Caucasian

No No No No Yes No No

215 285 278 101 805 725 1028

854e 854e 854e 101 841 765 402

0.39 0.39 0.39 0.49 0.43 0.36 0.42

Taqman Taqman Taqman PCR-RFLP PCR-RFLP Taqman PCR-RFLP

Very high Very high Very high High Very high High High

UK

Caucasian

No

299

560

0.43

PCR-RFLP

High

Poland

Caucasian

Yes

142 3878

142 3665

0.45

PCR-RFLP

High

USA USA USA and Sweden USA USA USA Poland

Caucasian Asian Caucasian

No No No

71 93 170

144 172 323

0.42 0.12b 0.36

Taqman Very high Taqman Moderate Pyrosequencing High

Caucasian Caucasian Caucasian Caucasian

No No No No

1391 513 74 168 2480

1885 532 79 182 3317

0.40b 0.40 0.27b 0.31

Taqman Taqman Taqman PCR-RFLP

Moderate Very high Moderate High

Kidney Obara, 2007 [116] Karami, 2008 [117] Arjumand, 2012 [118] 3 STUDIES

Japan Eastern Europe India

Asian Caucasian Other

No Yes No

135 925 196 1256

150 1192 250 1592

0.14 0.35 0.59

PCR-RFLP PCR-RFLP PCR-RFLP

High Very high High

NHL Purdue, 2007 [119] Purdue, 2007 [120] Smedby, 2011 [121] 3 STUDIES

USA Australia Sweden

Caucasian Mixed Caucasian

No No No

1321 704 2303 4328

1057 694 1789 3540

0.39 0.39 0.41

Taqman Taqman iPLEX

Very high Very high Very high

Brain Anic, 2012 [122]

USA

Caucasian

No

564

605

0.41

PCR-RFLP

Very high

EAC Chang, 2012 [123]

Ireland

Caucasian

No

202

234

0.42

iPLEX

High

HCC Falleti, 2010 [124]

Italy

Caucasian

No

80

160

0.39b

PCR-RFLP

Moderate

OSCC Zeljic, 2012 [125]

Serbia

Caucasian

No

110

122

0.27b

Taqman

Moderate

Germany

Caucasian

Yes

172

321

0.48

PCR-RFLP

Very high

Multiple myeloma Shafia, 2013 [127]

India

Other

Yes

75

150

0.61b

PCR-RFLP

Moderate

Pancreas Li, 2013 [128]

China

Asian

Yes

91

80

0.42c

PCR-RFLP

Moderate

NPC Huang, 2011 [129]

China

Asian

Yes

171

176

0.10

PCR-RFLP

Very high

Turkey

Other

Yes

137 45,218

156 52,057

0.44

PCR-RFLP

High

Melanoma and NMSC Han, 2007 [106] Han, 2007 [106] (BCC) Han, 2007 [106] (SCC) Santonocito, 2007 [107] Li, 2008 [99] Gapska, 2009 [108] Randerson-Moor, 2009 [109] (CCS1) Randerson-Moor, 2009 [109] (CCS2) Lesiak, 2011 [110] (BCC) 6 STUDIES Ovary cancer Lurie, 2007 [111] Lurie, 2007 [111] Clendenen, 2008 [112] Tworoger, 2009 [113] Grant, 2013 [114] Grant, 2013 [114] Mostowska, 2013 [115] 5 STUDIES

TC Penna-Martinez, 2009 [126]

Lung Dogan, 2009 [130] 73 STUDIES

No cases

No controls

AA, African-American; BCC, basal cell carcinoma; CCS1-2, case–control study 1–2; CPS-II, cancer prevention study II; DGGE, denaturing gradient gel electrophoresis; DHPLC, denaturing high performance liquid chromatography; EAC, esophageal adenocarcinoma; EPIC, European prospective investigation into cancer and nutrition; HCC, hepatocellular carcinoma; MAF, minor allele frequency; MEC, Hawaii–Los Angeles Multiethnic Cohort; NHL, non-Hodgkin lymphoma; NHS, nurses’ health study; NMSC, non-melanoma skin cancer; NPC, nasopharingeal carcinoma; NS, not specified; OSCC, oral squamous cell carcinoma; PLCO, prostate, lung, colorectal and ovarian cancer screening trial; PY, publication year; RFLP, restriction fragment length polymorfism; SCC, squamous cell carcinoma; TC, thyroid carcinoma; WHS, women’s health study. a Moderate = studies for which genotyping frequency do not respect HWE in controls and/or MAF differed from HapMap [47] reported MAF more than ±15% for the closest ethnic group; high = studies in which HWE among controls was respected, MAF frequency was in the range ±15% from HapMap reported MAF for the closest ethnic group, but genotyping quality controls were not performed or no information was given in the paper; very high = studies that reported “high confidence” genotyping data as in the previous group, with additional information on genotyping controls performed. b Deviation from HWE. c MAF differed from HapMap reported MAF more than ±15% for the same ethnic group. d Since the genotyping was perfomed on tumor samples, we considered the polymorphism data confidence as moderate. e Control group is the same for the three skin cancer types.

S. Raimondi et al. / Mutation Research 769 (2014) 17–34

not respect HWE in controls and/or for which the reported Minor Allele Frequency (MAF) differed from HapMap [47] reported MAF more than ±15% for the closest ethnic group; a second group (“high confidence”) included studies for which HWE among controls was respected, MAF frequency was in the range ±15% from HapMap reported MAF for the closest ethnic group, but genotyping quality controls were not performed or no information was given in the paper; the last group (“very high confidence”) included studies that reported “high confidence” genotyping data as in the previous group, with additional information on genotyping controls performed. Reference MAF used for group classification are listed in Supplementary Table 1. Publication bias was evaluated graphically with a funnel plot and assessed by the Macaskill test [48], which is more powerful than Egger’s test when less than 20 estimates are included in the analysis. All the statistical analyses were performed using SAS software (SAS Institute Inc., Cary, NC), version 9.2. 3. Results The meta-analysis included 73 independent studies with 45,218 cases and 52,057 controls overall. Studied cancer types were prostate cancer (N = 18 studies), breast cancer (N = 16), colorectal cancer (N = 13), skin cancer (N = 6), ovary cancer (N = 5), renal cell carcinoma (N = 3), non-Hodgkin lymphoma (N = 3), brain cancer (N = 1), esophageal adenocarcinoma (EAC, N = 1), hepatocellular carcinoma (HCC, N = 1), oral squamous cell carcinoma (OSCC, N = 1), thyroid carcinoma (TC, N = 1), multiple myeloma (N = 1), pancreatic cancer (N = 1), nasopharyngeal carcinoma (NPC, N = 1), and lung cancer (N = 1). The main characteristics of the studies included in our analysis are shown in Table 1: out of 73, 27 studies were conducted in Europe, 24 in North America, 18 in Asia, 2 in Australia, and 2 were multinational. Table 1 also included study-specific information

21

on publication year, ethnicity, source of controls, frequency of the B allele in the control group, deviation from HWE in controls, and genotyping data confidence information. Study-specific risk estimates are reported in Supplementary Table 2, along with information on adjusted estimates. Cancer-specific and overall SORs for Bb, BB and Bb + BB versus bb genotype were reported in Table 2, along with heterogeneity estimates, and in Fig. 1. We found a significant reduction of cancer risk at any site for carriers of Bb, BB and Bb + BB genotype versus (vs) bb carriers: SORs (95%CI) were, respectively, 0.94 (0.90–0.99), 0.93 (0.89–0.98) and 0.93 (0.89–0.98). The SORs remained statistically significant when we restricted the analysis to the 54 studies with “high” or “very high confidence” (Table 2). Otherwise, when we considered the subgroup of 25 studies with “very high confidence”, no SOR was statistically significant (results not shown). In the cancer-specific analyses, we found a significant reduction of skin cancer risk for carriers of Bb versus bb genotype: the SOR (95%CI) was 0.86 (0.76–0.98), obtained on six studies with at least “high confidence” and with no evidence of heterogeneity (I2 = 0). Furthermore a significant reduction of colorectal cancer risk was observed for BB and Bb + BB genotypes carriers, but these SORs were no more significant when we restricted the analysis to studies with at least “high confidence”. Although no further significant association was found in the cancer-specific analysis, it is worthwhile to note that almost all the calculated SOR were smaller then 1.00, suggesting a protective effect of the BsmI B allele for all the cancer sites. We did not find evidence of publication bias for any cancer site. Otherwise a relevant heterogeneity among the risk estimates (I2 > 50%) was found for the analyses on prostate (Bb and Bb + BB), skin (BB) and renal cancer (all models), and for the analysis on all cancer sites (Bb + BB) (Table 2). We found by meta-regression that none of the investigated study features and population characteristics seemed to significantly modify the risk estimates. However, when we analyzed the subgroup of studies with at least

Table 2 Summary estimates for the association of VDR BsmI polymorphism with different types of cancer and heterogeneity estimates. Cancer site

Prostate

Breast

Colorectal

Skin

Ovary

Kidney

NHL

Other sites

All sites

Comparison

Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb

Studies with high genotyping data confidencea

All studies No. of studies

SOR (95% CI)

I %

No. of studies

SOR (95% CI)

Q test p-value (I2 %)

18

0.86 (0.69–1.08) 0.95 (0.85–1.07) 0.89 (0.71–1.11) 0.99 (0.93–1.05) 0.98 (0.91–1.05) 0.97 (0.89–1.05) 0.94 (0.87–1.01) 0.89 (0.80–0.98) 0.92 (0.86–0.99) 0.86 (0.76–0.98) 0.87 (0.70–1.08) 0.86 (0.74–1.01) 1.15 (0.96–1.37) 1.01 (0.79–1.29) 1.09 (0.93–1.29) 0.75 (0.32–1.76) 0.61 (0.19–1.92) 0.73 (0.29–1.82) 1.05 (0.83–1.34) 1.08 (0.78–1.49) 1.02 (0.81–1.28) 0.90 (0.74–1.10) 0.83 (0.57–1.21) 0.92 (0.72–1.17) 0.94 (0.90–0.99) 0.93 (0.89–0.98) 0.93 (0.89–0.98)

66 42 69 28 23 40 38 0 31 0 51 32 30 0 26 77 67 82 32 0 35 12 47 31 46 29 51

12

0.92 (0.83–1.02) 0.94 (0.82–1.08) 0.93 (0.85–1.02) 0.99 (0.90–1.08) 0.92 (0.77–1.11) 0.96 (0.85–1.08) 1.0 (0.90–1.10) 0.88 (0.77–1.01) 0.96 (0.88–1.06) 0.86 (0.76–0.98) 0.87 (0.70–1.08) 0.86 (0.74–1.01) 1.30 (0.92–1.83) 1.11 (0.68–1.80) 1.19 (0.88–1.62) 0.75 (0.32–1.76) 0.61 (0.19–1.92) 0.73 (0.29–1.82) 1.05 (0.83–1.34) 1.08 (0.78–1.49) 1.02 (0.81–1.28) 0.84 (0.62–1.15) 0.80 (0.52–1.24) 0.86 (0.65–1.14) 0.96 (0.93–1.00) 0.93 (0.87–0.98) 0.95(0.91–0.99)

10 26 12 36 29 48 0 0 0 0 51 32 0 0 13 77 67 82 32 0 35 5 22 1 30 27 37

16

13

6

5

3

3

9

73

2

12

9

6

4

3

3

5

54

CI, confidence interval; NHL, non-Hodgkin lymphoma; SOR, summary odds ratio. Note: significant ORs are in bold. a This analysis excludes studies for which genotyping data confidence was “moderate” (frequency do not respect HWE in controls and/or minor allele frequency (MAF) differed from HapMap reported MAF more than ±15% for the closest ethnic group).

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(a)

Author, PY, Race Bb vs. bb

Ingles, 1998 (AA) Habuchi, 2000 (A) Chokkalingam, 2001 (A) Liu, 2003 (A) Nam, 2003 (AA) Nam, 2003 (A) Nam, 2003 (C) Suzuki, 2003 (A) Huang, 2004 (A) Oakley-Girvan, 2004 (AA) Oakley-Girvan, 2004 (C) Hayes, 2005 (C) Chaimuangraj, 2006 (A) Cicek, 2006 (C) Holick, 2007 (C) Li, 2007 (C) Mikhak, 2007 (C) Onen, 2008 (O) Bai, 2009 (A) Holt, 2009 (AA) Holt, 2009 (C) Szendroi, 2011 (C) SOR 0.86 (0.69-1.08) BB vs. bb Ingles, 1998 (AA) Habuchi, 2000 (A) Chokkalingam, 2001 (A) Liu, 2003 (A) Nam, 2003 (AA) Nam, 2003 (A) Nam, 2003 (C) Suzuki, 2003 (A) Huang, 2004 (A) Oakley-Girvan, 2004 (AA) Oakley-Girvan, 2004 (C) Hayes, 2005 (C) Chaimuangraj, 2006 (A) Cicek, 2006 (C) Holick, 2007 (C) Li, 2007 (C) Mikhak, 2007 (C) Onen, 2008 (O) Bai, 2009 (A) Holt, 2009 (AA) Holt, 2009 (C) Szendroi, 2011 (C) SOR 0.95 (0.85-1.07) BB+Bb vs. bb Ingles, 1998 (AA) Habuchi, 2000 (A) Chokkalingam, 2001 (A) Liu, 2003 (A) Nam, 2003 (AA) Nam, 2003 (A) Nam, 2003 (C) Suzuki, 2003 (A) Huang, 2004 (A) Oakley-Girvan, 2004 (AA) Oakley-Girvan, 2004 (C) Hayes, 2005 (C) Chaimuangraj, 2006 (A) Cicek, 2006 (C) Holick, 2007 (C) Li, 2007 (C) Mikhak, 2007 (C) Onen, 2008 (O) Bai, 2009 (A) Holt, 2009 (AA) Holt, 2009 (C) Szendroi, 2011 (C) SOR 0.89 (0.71-1.11) 0.05

1.00 Odd ratios and 95% CI

15.00

Fig. 1. Study specific and summary odds ratio (SOR) with 95% confidence intervals (CI) for the association between BsmI genotype and (a) prostate cancer, (b) breast cancer, (c) colorectal cancer, (d) skin cancer, (e) ovarian cancer, (f) NHL, (g) kidney cancer (h) other cancer sites. AA, African-American; A, Asians; C, Caucasians; BCC, basal cell carcinoma; CCS1-2, case–control study 1–2; CPS-II, cancer prevention study II; EAC, esophageal adenocarcinoma; EPIC, European prospective investigation into cancer and nutrition; H, Hispanics; HCC, hepatocellular carcinoma; MEC, Hawaii–Los Angeles Multiethnic Cohort; NHS, nurses’ health study; O, other ethinicties/mixed; OSCC, oral squamous cell carcinoma; PLCO, prostate, lung, colorectal and ovarian cancer screening trial; PY, publication year; WHS, women’s health study; TC, thyroid carcinoma.

S. Raimondi et al. / Mutation Research 769 (2014) 17–34

(b)

23

Author, PY, Race Bb vs. bb

Ruggiero, 1998 (C) Hou, 2002 (A) Buyru, 2003 (O) Guy, 2003 (C) Hefler, 2004 (C) VandeVord, 2006 (O) Trabert, 2007 (AA) Trabert, 2007 (C) Gapska, 2008 (C) Sinotte, 2008 (C) McKay, 2009 (AA) McKay, 2009 (CPS-II) (C) McKay, 2009 (EPIC) (C) McKay, 2009 (MEC) (C) McKay, 2009 (NHS) (C) McKay, 2009 (PLCO) (C) McKay, 2009 (WHS) (C) McKay, 2009 (O) McKay, 2009 (H) McKay, 2009 (A) Anderson, 2011 (C) Huang, 2012 (A) Rollison, 2012 (C) Rollison, 2012 (H) Fuhrman, 2013 (C) Mishra, 2013 (AA) Mishra, 2013 (H) Shahbazi, 2013 (O) SOR 0.99 (0.93-1.05) BB vs. bb Ruggiero, 1998 (C) Hou, 2002 (A) Buyru, 2003 (O) Guy, 2003 (C) Hefler, 2004 (C) VandeVord, 2006 (O) Trabert, 2007 (AA) Trabert, 2007 (C) Gapska, 2008 (C) Sinotte, 2008 (C) McKay, 2009 (AA) McKay, 2009 (CPS-II) (C) McKay, 2009 (EPIC) (C) McKay, 2009 (MEC) (C) McKay, 2009 (NHS) (C) McKay, 2009 (PLCO) (C) McKay, 2009 (WHS) (C) McKay, 2009 (O) McKay, 2009 (H) McKay, 2009 (A) Anderson, 2011 (C) Huang, 2012 (A) Rollison, 2012 (C) Rollison, 2012 (H) Fuhrman, 2013 (C) Mishra, 2013 (AA) Mishra, 2013 (H) Shahbazi, 2013 (O) SOR 0.98 (0.91-1.05) BB+Bb vs. bb Ruggiero, 1998 (C) Hou, 2002 (A) Buyru, 2003 (O) Guy, 2003 (C) Hefler, 2004 (C) VandeVord, 2006 (O) Trabert, 2007 (AA) Trabert, 2007 (C) Gapska, 2008 (C) Sinotte, 2008 (C) McKay, 2009 (AA) McKay, 2009 (CPS-II) (C) McKay, 2009 (EPIC) (C) McKay, 2009 (MEC) (C) McKay, 2009 (NHS) (C) McKay, 2009 (PLCO) (C) McKay, 2009 (WHS) (C) McKay, 2009 (O) McKay, 2009 (H) McKay, 2009 (A) Anderson, 2011 (C) Huang, 2012 (A) Rollison, 2012 (C) Rollison, 2012 (H) Fuhrman, 2013 (C) Mishra, 2013 (AA) Mishra, 2013 (H) Shahbazi, 2013 (O) SOR 0.97 (0.89-1.05) 0.05

1.00 Odd ratios and 95% CI

Fig. 1. (Continued )

15.00

24

S. Raimondi et al. / Mutation Research 769 (2014) 17–34

(c) Author, PY, Race Bb vs. bb Speer, 2001 (C) Park, 2006 (A) Flugge, 2007 (C) Kadiyska, 2007 (C) Slattery, 2007 (Colon) (C) Slattery, 2007 (Rectal) (C) Li, 2008 (A) Parisi, 2008 (C) Theodoratou, 2008 (C) Jenab, 2009 (C) Hughes, 2011 (C) Mahmoudi, 2011 (O) Gunduz, 2012 (O) Sarkyssyan, 2014 (O) SOR 0.94 (0.87-1.01) BB vs. bb Speer, 2001 (C) Park, 2006 (A) Flugge, 2007 (C) Kadiyska, 2007 (C) Slattery, 2007 (Colon) (C) Slattery, 2007 (Rectal) (C) Li, 2008 (A) Parisi, 2008 (C) Theodoratou, 2008 (C) Jenab, 2009 (C) Hughes, 2011 (C) Mahmoudi, 2011 (O) Gunduz, 2012 (O) Sarkyssyan, 2014 (O) SOR 0.89 (0.80-0.98) BB+Bb vs. bb Speer, 2001 (C) Park, 2006 (A) Flugge, 2007 (C) Kadiyska, 2007 (C) Slattery, 2007 (Colon) (C) Slattery, 2007 (Rectal) (C) Li, 2008 (A) Parisi, 2008 (C) Theodoratou, 2008 (C) Jenab, 2009 (C) Hughes, 2011 (C) Mahmoudi, 2011 (O) Gunduz, 2012 (O) Sarkyssyan, 2014 (O) SOR 0.92 (0.86-0.99) 0.05

1.00 Odd ratios and 95% CI Fig. 1. (Continued )

.00

S. Raimondi et al. / Mutation Research 769 (2014) 17–34

25

(d) Author, PY, Race

Bb vs. bb

Santocito, 2000 (C) Han, 2007 (C) Han, 2007 (BCC) (C) Han, 2007 (SCC) (C) Li, 2008 (C) Gapska, 2009 (C) Randerson-Moor, 2009 (CCS1) (C) Randerson-Moor, 2009 (CCS2) (C) Lesiak, 2011 (BCC) (C)

SOR 0.86 (0.76-0.98)

BB vs. bb

Santocito, 2000 (C) Han, 2007 (C) Han, 2007 (BCC) (C) Han, 2007 (SCC) (C) Li, 2008 (C) Gapska, 2009 (C) Randerson-Moor, 2009 (CCS1) (C) Randerson-Moor, 2009 (CCS2) (C) Lesiak, 2011 (BCC) (C)

SOR 0.87 (0.70-1.08)

BB+Bb vs. bb

Santocito, 2000 (C) Han, 2007 (C) Han, 2007 (BCC) (C) Han, 2007 (SCC) (C) Li, 2008 (C) Gapska, 2009 (C) Randerson-Moor, 2009 (CCS1) (C) Randerson-Moor, 2009 (CCS2) (C) Lesiak, 2011 (BCC) (C)

SOR 0.86 (0.74-1.01) 0.05

1.00 Odd ratios and 95% CI Fig. 1. (Continued )

15.00

26

S. Raimondi et al. / Mutation Research 769 (2014) 17–34

(e)

Author, PY, Race

Bb vs. bb

Lurie, 2007 (A) Lurie, 2007 (C) Cleneden, 2008 (C) Tworoger, 2009 (C) Grant, 2013 (AA) Grant, 2013 (C) Mostowska, 2013 (C)

SOR 1.15 (0.96-1.37)

BB vs. bb

Lurie, 2007 (A) Lurie, 2007 (C) Cleneden, 2008 (C) Tworoger, 2009 (C) Grant, 2013 (AA) Grant, 2013 (C) Mostowska, 2013 (C)

SOR 1.01 (0.79-1.29)

BB+Bb vs. bb

Lurie, 2007 (A) Lurie, 2007 (C) Cleneden, 2008 (C) Tworoger, 2009 (C) Grant, 2013 (AA) Grant, 2013 (C) Mostowska, 2013 (C)

SOR 1.09 (0.93-1.29) 0.05

1.00 Odd ratios and 95% CI Fig. 1. (Continued )

15.00

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27

(f) Author, PY, Race

Bb vs. bb

Purdue, 2007 (C) Purdue, 2007 (C+A) Smedby, 2010 (C)

SOR 1.05 (0.83-1.34)

BB vs. bb

Purdue, 2007 (C) Purdue, 2007 (C+A) Smedby, 2010 (C)

SOR 1.08 (0.78-1.49)

BB+Bb vs. bb

Purdue, 2007 (C) Purdue, 2007 (C+A) Smedby, 2010 (C)

SOR 1.02 (0.81-1.28)

0.05

1.00 Odd ratios and 95% CI Fig. 1. (Continued )

15.00

28

S. Raimondi et al. / Mutation Research 769 (2014) 17–34

(g) Author, PY, Race

Bb vs. bb

Obara, 2007 (A) Karami, 2008 (C) Arjumand, 2011 (O)

SOR 0.75 (0.32-1.76)

BB vs. bb

Obara, 2007 (A) Karami, 2008 (C) Arjumand, 2011 (O)

SOR 0.61 (0.19-1.92)

BB+Bb vs. bb

Obara, 2007 (A) Karami, 2008 (C) Arjumand, 2011 (O)

SOR 0.73 (0.29-1.82)

0.05

1.00 Odd ratios and 95% CI Fig. 1. (Continued )

15.00

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(h) Author, PY, Tumor, Race

Bb vs. bb

Dogan, 2009 (Lung) (O) Penna-Martinez, 2009 (TC) (C) Falleti, 2010 (HCC) (C) Anic, 2012 (Brain) (C) Chang, 2012 (EAC) (C) Zeljic, 2012 (OSCC) (C) Li, 2013 (Pancreas) (A) Shafia, 2013 (Multiple Mieloma) (O)

SOR 0.90 (0.74-1.10)

BB vs. bb

Dogan, 2009 (Lung) (O) Penna-Martinez, 2009 (TC) (C) Falleti, 2010 (HCC) (C) Anic, 2012 (Brain) (C) Chang, 2012 (EAC) (C) Zeljic, 2012 (OSCC) (C) Li, 2013 (Pancreas) (A) Shafia, 2013 (Multiple Mieloma) (O)

SOR 0.83 (0.57-1.21)

BB+Bb vs. bb

Dogan, 2009 (Lung) (O) Penna-Martinez, 2009 (TC) (C) Falleti, 2010 (HCC) (C) Huang, 2011 (NPC) (A) Anic, 2012 (Brain) (C) Chang, 2012 (EAC) (C) Zeljic, 2012 (OSCC) (C) Li, 2013 (Pancreas) (A) Shafia, 2013 (Multiple Mieloma) (O)

SOR 0.92 (0.72-1.17) 0.05

1.00 Odd ratios and 95% CI Fig. 1. (Continued ).

15.00

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S. Raimondi et al. / Mutation Research 769 (2014) 17–34

Table 3 Summary estimates for the association of VDR BsmI polymorphism with different types of cancer according to ethnicity. Cancer site

Comparison

Caucasians No. of studies

Prostate

Breast

Colorectal

Skin

Ovary

NHL Kidney Other sites

All sites

Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb Bb versus bb BB versus bb Bb + BB versus bb

9

10

8

6

5

2 1 5

46

SOR (95% CI)

0.99 (0.81–1.22) 1.00 (0.87–1.14) 1.02 (0.82–1.27) 0.98 (0.92–1.04) 0.97 (0.90–1.06) 0.95(0.88–1.04) 0.94 (0.86–1.02) 0.89 (0.80–1.00) 0.92(0.85–1.00) 0.86 (0.76–0.98) 0.87 (0.70–1.08) 0.86 (0.74–1.01) 1.17 (0.97–1.40) 1.00(0.78–1.29) 1.11 (0.94–1.31) nc nc 0.96 (0.74–1.24) 0.83 (0.56–1.21) 0.97 (0.77–1.23) 0.97 (0.93–1.00) 0.95 (0.91–0.99) 0.96 (0.92–0.99)

Non-Caucasians (all)

Other ethnicities

No. of studies

SOR (95% CI)

Asians

12

0.73 (0.53–1.00) 0.70 (0.48–1.01) 0.73 (0.54–1.00) 1.01 (0.89–1.15) 1.02 (0.81–1.27) 1.02 (0.89–1.17) 0.87 (0.53–1.42) 0.84 (0.54–1.32) 0.85 (0.51–1.41)

8

1

1 2 4

9

5

No. of studies

African Americans SOR (95% CI)

No. of studies

SOR (95% CI)

4

0.89 (0.55–1.44) 0.73 (0.31–1.73) 0.86 (0.55–1.35) 0.98 (0.63–1.51) 1.05 (0.53–2.08) 0.99 (0.66–1.48)

2

0.69 (0.39–1.21) 0.65 (0.34–1.23) 0.71 (0.41–1.21) 1.11 (0.28–4.49) 1.14(0.06–21.45) 1.16 (0.26–5.18) nc

nc

1

nc

0

nc nc 0.72 (0.33–1.57) 0.85 (0.15–4.75) 0.74 (0.28–1.94) 0.87 (0.75–1.00) 0.82 (0.68–1.00) 0.86 (0.74–0.99)

0 1 2

nc nc

0 0 0

3

3

0

0

34

17

0.86 (0.62–1.18) 0.81 (0.49–1.35) 0.87 (0.65–1.17)

7

0.92 (0.76–1.12) 0.93 (0.66–1.31) 0.93 (0.77–1.11)

SOR, summary odds ratio; CI, confidence interval; nc, not calculated (less than three studies). Note: significant ORs are in bold. The sum of studies on Caucasians and other ethnicities is not equal to numbers reported in Table 2 because some studies reported separate estimates for different ethnic groups. Non-Caucasians included Asians, African-Americans and other/mixed ethnicities.

“high confidence”, heterogeneity among risk estimates was no more relevant for prostate cancer (I2 ≤ 26) and for all cancer sites (I2 ≤ 37) (Table 2). When the analysis was stratified by ethnicity (Table 3), we still observed a significant decreased risk for Bb, BB and Bb + BB versus bb genotype with all the cancer sites among Caucasians: SORs were 0.97 (95%CI: 0.93, 1.00), 0.95 (95%CI: 0.91, 0.99) and 0.96 (95%CI: 0.92–0.99), respectively. The calculated SORs remained statistically significant when we restricted the analysis to the 38 Caucasian studies with at least “high confidence” (Supplementary Table 3), while they were no more significant when we restricted the analysis to the 18 studies with “very high confidence” (results not shown). Among other ethnic groups the inverse association was still observed in the whole set of studies, but it was no more statistically significant when we restricted the analysis to studies with at least “high confidence”. 4. Discussion We found a significant reduction of cancer risk at any site for carriers of BsmI BB, Bb and Bb + BB genotype compared to bb carriers. We also suggested a reduction of skin cancer risk for carriers of Bb compared to bb genotype when we considered studies with high genotyping data confidence. Furthermore, we observed a trend of cancer reduction with the presence of the B allele, although not significant, at almost all cancer site. Beyond skin cancer, this risk reduction was statistically significant for colorectal cancer, although this result was not confirmed when we restricted the analysis to studies with at least “high confidence”. Results from this study confirm the findings of our previous meta-analysis [29] and suggest a possible role of the VDR BsmI polymorphism in cancer prevention. In fact it is not clear whether the BsmI polymorphism has an effect on the expression level or activity of the translated VDR protein [49], but it is in strong linkage disequilibrium with the poly(A) microsatellite located in the 3 untranslated region [50] of the VDR gene, which appear to

influence VDR messenger RNA stability and VDR translational activity [27]. A study of 599 healthy men reported that those with the bb genotype at the BsmI locus had, on average, 2.3 pg/mL lower levels of 1,25(OH)2 D3 compared with BB carriers [51], supporting the hypothesis that BsmI polymorphism may be a mediator for the cellular effects of vitamin D. Meta-analyses of prospective studies provide evidence of a decreased cancer risk, associated with higher serum 25(OH)D3 , but only for colorectal cancer. However these are observational studies that cannot give definitive answers to question if low vitamin D status is a causal factor for increased risk of cancer, or simply an indicator of poor health status. To assess if there is a causal link, good randomized clinical trials that verify the impact of vitamin D supplementation on cancer incidence need to be performed [52,53]. In our previous meta-analysis [29], we found a significant 17% reduction of prostate cancer risk for carriers of Bb compared to bb genotype, that was not confirmed either by the present and by another recently published meta-analysis [38]. This different result could be partially attributable to the inclusion of one study published in 2011 [54], which found a surprisingly higher risk of prostate cancer with the BsmI Bb/BB genotypes. However it should be noted that the allele frequencies in the hospital controls for this study departed from HWE, therefore selection bias in this study could not been ruled out. A further study and meta-analysis on prostate cancer aggressiveness found that BsmI bb genotype was associated with high Gleason Score, indicating that BsmI polymorphism may have a role not only on prostate cancer development, but also on progression [55]. As determined in a large population based case–control study, the BsmI B allele was significantly associated with a 30% increased risk of melanoma [56]. This result was opposite to that of a previous meta-analysis, which suggested that the B allele was a protective factor for melanoma [35]. In our meta-analysis, updated with 3 more recent studies compared to that of 2009, we confirmed our previous results suggesting a significant decreased skin cancer risk carrying Bb genotype.

S. Raimondi et al. / Mutation Research 769 (2014) 17–34

BsmI B allele was significantly associated with a decreased risk of colorectal cancer in three previous meta-analyses [9,29,36], and in the European Prospective Investigation on Cancer (EPIC) study [57]. We also observed SOR significantly lower than 1.00 for both carriers of BB and Bb + BB compared to bb genotype, however the protective effect of the B allele was found to be no more significant when we restricted the analysis to the studies with at least “high confidence” genotyping data. This discordance may be due either to the biased results from studies with lower genotyping data quality, or to the reduced statistical power of the analysis restricted to the 9 studies with higher genotyping data confidence. Moreover, it should be noted that our pooling methodology, with maximum likelihood estimates [45], is more conservative than the Der-Simonian and Laird method used in two previous meta-analyses [9,36], possibly explaining, at least in part, the different results. Finally, in agreement with previously published meta-analyses [29,39,42,58] we found no evidence of an association between VDR BsmI polymorphism and both breast and ovarian cancer. When we stratified the analysis according to different ethnic groups, we confirmed the significant reduction of cancer risk at any site for Caucasian carriers of BsmI BB, Bb and Bb + BB genotypes compared to bb carriers, and the reduction of skin cancer risk for carriers of Bb genotype compared to bb carriers when we considered studies with “high confidence” genotyping data. By considering all the included studies, a significant reduction of prostate cancer risk and of cancer at any site was even observed for non-Caucasian carriers of Bb and Bb + BB genotypes, however further stratified analysis on Asians and African-Americans did not reveal any significant association. Environmental, food, and lifestyle factors may play a significant role, in combination with genetic factors, in the occurrence and development of cancer, accounting for the observed differences among the SORs of different ethnic groups. However, gene–environment interactions in prospective studies would be a more appropriate approach to reveal any ethnical difference caused by lifestyle factors. Moreover, it was observed that the strength of the linkage disequilibrium with the functional poly(A) microsatellite varied by ethnicity, being lower in African-Americans than in Caucasians or Asians [33]. Almost all the previous meta-analyses focused on single cancer sites and found inconsistent results for the association with VDR BsmI polymorphism. However, a trend of cancer risk reduction with BsmI B allele was observed for almost all the cancer sites, suggesting that the mechanisms involved in the relationship between VDR BsmI polymorphism and cancer may be the same for different tissues. A strength of the present study is that we were able to provide a complete picture of the role of VDR BsmI polymorphisms on cancer risk, even according to different ethnicities. Because genetic variants are unrelated to the many environmental characteristics that confound traditional risk factor-disease association studies, VDR polymorphisms could be used as proxies to determine the unconfounded and unbiased effect of vitamin D on cancer risk. The null association for VDR BsmI polymorphism in specific cancer sites and in the analysis stratified by non-Caucasians ethnicity could be due to the small sample size, which provides low statistical power to detect a significant association. In addition, we could not investigate the role of other important factors, such as circulating vitamin D levels, outdoor activity, sun exposure, disease stage, and vitamin D and calcium intake, that may modify the association of VDR BsmI polymorphism and risk of cancer [29]. Beside polymorphisms, VDR expression itself can be altered in cancer tissue compared to normal tissue. Also it can show opposite trend in different tumors: within ovarian cancer Thill et al. [59] found a decreased VDR expression whereas, at the mRNA level, Anderson at al [60] showed an up-regulation. Also, to identify a clinical relevant phenotype is probably necessary to include in the analysis other genes involved in the vitamin D metabolism as the

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binding protein (GC) and the anabolism and catabolism enzymes (CYP27A1, CYP27B1, CYP24A1 and CYP2R1) [37,61]. Finally, only published studies were included, therefore publication bias could occur, although the Macaskill test did not provide evidence of that. In conclusion, we were able to provide a complete and updated picture of the association of VDR BsmI polymorphism and cancer risk, and reported a weak, but significant, effect of BsmI B allele in reducing cancer risk at any site, especially in skin cancer. Conflict of interest statement The authors declare that there are no conflicts of interest. Acknowledgements The authors would like to thank William Russell-Edu for his valuable library assistance and Elena Tagliabue for assistance in tables and graphs preparation. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/ j.mrfmmm.2014.06.001. References [1] E.R. Bertone-Johnson, W.Y. Chen, M.F. Holick, B.W. Hollis, G.A. Colditz, W.C. Willett, S.E. Hankinson, Plasma 25-hydroxyvitamin D and 1,25dihydroxyvitamin D and risk of breast cancer, Cancer Epidemiol. Biomarkers Prev. 14 (2005) 1991–1997. [2] L.C. Lowe, M. Guy, J.L. Mansi, C. Peckitt, J. Bliss, R.G. Wilson, K.W. Colston, Plasma 25-hydroxy vitamin D concentrations, vitamin D receptor genotype and breast cancer risk in a UK Caucasian population, Eur. J. Cancer 41 (2005) 1164–1169. [3] C.F. Garland, F.C. Garland, E.D. Gorham, M. Lipkin, H. Newmark, S.B. Mohr, M.F. Holick, The role of vitamin D in cancer prevention, Am. J. Public Health 96 (2006) 252–261. [4] E. Giovannucci, Epidemiological evidence for vitamin D and colorectal cancer, J. Bone Miner. Res. 22 (Suppl. 2) (2007) V81–V85. [5] E.D. Gorham, C.F. Garland, F.C. Garland, W.B. Grant, S.B. Mohr, M. Lipkin, H.L. Newmark, E. Giovannucci, M. Wei, M.F. Holick, Optimal vitamin D status for colorectal cancer prevention: a quantitative meta analysis, Am. J. Prev. Med. 32 (2007) 210–216. [6] C.S. Spina, L. Ton, M. Yao, H. Maehr, M.M. Wolfe, M. Uskokovic, L. Adorini, M.F. Holick, Selective vitamin D receptor modulators and their effects on colorectal tumor growth, J. Steroid Biochem. Mol. Biol. 103 (2007) 757–762. [7] S. Abbas, J. Linseisen, T. Slanger, S. Kropp, E.J. Mutschelknauss, D. Flesch-Janys, J. Chang-Claude, Serum 25-hydroxyvitamin D and risk of post-menopausal breast cancer—results of a large case–control study, Carcinogenesis 29 (2008) 93–99. [8] P. Chen, P. Hu, D. Xie, Y. Qin, F. Wang, H. Wang, Meta-analysis of vitamin D, calcium and the prevention of breast cancer, Breast Cancer Res. Treat. 121 (2010) 469–477. [9] M. Touvier, D.S. Chan, R. Lau, D. Aune, R. Vieira, D.C. Greenwood, E. Kampman, E. Riboli, S. Hercberg, T. Norat, Meta-analyses of vitamin D intake 25-hydroxyvitamin D status, vitamin D receptor polymorphisms, and colorectal cancer risk, Cancer Epidemiol. Biomarkers Prev. 20 (2011) 1003–1016. [10] V. Fedirko, E. Riboli, A. Tjonneland, P. Ferrari, A. Olsen, H.B. Bueno-deMesquita, F.J. van Duijnhoven, T. Norat, E.H. Jansen, C.C. Dahm, K. Overvad, M.C. Boutron-Ruault, F. Clavel-Chapelon, A. Racine, A. Lukanova, B. Teucher, H. Boeing, K. Aleksandrova, A. Trichopoulou, V. Benetou, D. Trichopoulos, S. Grioni, P. Vineis, S. Panico, D. Palli, R. Tumino, P.D. Siersema, P.H. Peeters, G. Skeie, M. Brustad, M.D. Chirlaque, A. Barricarte, J. Ramon Quiros, M.J. Sanchez, M. Dorronsoro, C. Bonet, R. Palmqvist, G. Hallmans, T.J. Key, F. Crowe, K.T. Khaw, N. Wareham, I. Romieu, J. McKay, P.A. Wark, D. Romaguera, M. Jenab, Prediagnostic 25-hydroxyvitamin D, VDR and CASR polymorphisms, and survival in patients with colorectal cancer in western European populations, Cancer Epidemiol. Biomarkers Prev. 21 (2012) 582–593. [11] S.R. Bauer, S.E. Hankinson, E.R. Bertone-Johnson, E.L. Ding, Plasma vitamin D levels, menopause, and risk of breast cancer: dose–response meta-analysis of prospective studies, Medicine (Baltimore) 92 (2013) 123–131. [12] S.Y. James, M.A. Williams, S.M. Kelsey, A.C. Newland, K.W. Colston, The role of vitamin D derivatives and retinoids in the differentiation of human leukaemia cells, Biochem. Pharmacol. 54 (1997) 625–634.

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