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Abstract

The purpose of this systemic review and meta-analysis was to examine the relationship between VDR gene polymorphisms and breast cancer. Literature was searched through PubMed database, Google scholar, and the web of knowledge from December 2015 to January 2017 and consists of 34 studies (26,372 cases and 32,883 controls). All statistical measures were done using STATA version 11.2. The heterogeneity among studies was tested using I² statistics. Mantel–Haenszel method and DerSimonian–Laird method were used to combine data from studies using both random-effect model and fixed-effect model, respectively. Potential publication bias was evaluated by Egger’s test. Sensitivity analysis was also performed to evaluate the quality and consistency in results. The results of this meta-analysis revealed that VDR gene polymorphisms (Bsm1 bb vs BB; SOR = 1.18, 95% CI = 1.054–1.322, Apa1 aa vs AA; SOR = 1.18, 95% CI = 0.87–1.59, Poly (A) LL vs SS; SOR = 1.41, 95% CI = 1.06–1.88, Fok1 ff + Ff vs FF; SOR = 1.25, 95% CI = 0.896–1.759, Apa1 aa+Aa vs AA; SOR = 1.13, 95% CI = 0.95–1.35, Poly (A) LL + LS vs SS; SOR = 1.19, 95% CI = 1.00–1.43, Poly (A) L vs S; SOR = 1.18, 95% CI = 1.03–1.35) are associated with the breast cancer. Cdx2, Bgl1, and Taq1 do not show association with breast cancer. Thus, the finding of this meta-analysis concluded that VDR Bsm1, Apa1, Fok1, and Poly (A) gene polymorphisms may be susceptible for breast cancer development.

Keywords

Vitamin D receptor VDR genetic polymorphisms single-nucleotide polymorphisms breast cancer

Introduction

Breast cancer (BC) is a multifarious group of disease, accounts 23% of all cancers among females worldwide.¹ The incidence rate of BC has been increasing annually by more than 1 million across the globe (http://www.cancerscreening.nhs.uk/) but the etiology of BC is still not clear. Genetic and environmental factors are the most influential contributing factors that lead to the development of BC.^2–4 Sometimes, minor genes might become important to increase the chance of BC including Vitamin D receptor (VDR) gene. The VDR gene is situated at chromosome 12q13.11 which spans ~100 kb and have five promoters, eight coding exons, and six untranslated exons.⁵ VDR produces its pleiotropic effects via binding with its ligand vitamin D and operates a cascade of signaling pathways inducing various genes activation⁶ and involved in BC prevention.⁷ The gene has many polymorphic variants which influence the expression/functions of VDR which is associated with complex traits or diseases such as tuberculosis,⁸ osteoporosis,⁹ diabetes,¹⁰ and cancers^11,12 including BC.^13,14 To date, only a few VDR gene variants have been considered in relation to BC risk with contradictory results including Fok1, Bsm1, Taq1, Apa1, Cdx2, and Poly (A).^13–47 This inconsistency in results may because of small sample size, low statistical power, and clinical heterogeneity in these studies.⁴⁸ In order to resolve the inconsistencies among studies and reduce the likelihood of having false-positive or false-negative relations due to random errors, we executed a meta-analysis of 34 existing studies. So, the purpose of this study is to compare VDR gene polymorphisms in BC cases and controls which were systematically recognized, observed, and assembled in a meta-analysis.

Materials and methods

Publication search strategy

The relevant research articles were searched through PubMed database, Google scholar, Science.gov and web of knowledge from December 2015 till January 2017 to determine the link between VDR gene polymorphisms and BC risk. The following key words and their combinations were used during searching: VDR, SNP, single nucleotide polymorphisms, variants, BC, breast cancer, Cdx2, Fok1, Bsm1, Apa1, Taq1, Bgl1, Poly (A), and combinations of these key words. The bibliography was also searched in each article manually to identify more appropriate eligible studies.

Inclusion criteria

The selection of studies based on following criteria includes (1) all studies were retrospective case-control studies, (2) all data were original, (3) all studies having genotype frequencies for estimating ORs and 95% confidence interval (CI), and (4) all studies which are available in English language were included in this systematic review and meta-analysis.

Exclusion criteria

Following research papers were excluded: (1) all review articles, abstracts, and repeated studies; (2) if the frequencies of genotypes were not reported in the original papers; (3) if the genetic polymorphisms performed on the animal or human cell lines; (4) if the cross-sectional studies were done and conducted only on cases, and (5) if the studies selected male patients instead of female BC patients.

Data extraction

All potentially relevant studies were gone through and data were extracted and tabulated by one investigator independently and checked by another senior investigator. The extracted information for all studies includes first author, year of publication, ethnicity of subjects included in studies, origin of subjects, study design, sources of controls, sample size, and genotyping method. The frequencies of VDR Cdx2, Fok1, Bsm1, Apa1, Taq1, Bgl1, and Poly (A) genotypes in all participants were retrieved and ORs along with 95% CI were calculated. Because the reference genotype of each VDR gene polymorphisms was different in all studies, we took homozygous genotype (AA for Cdx2, FF for Fok1, BB for Bsm1, AA for Apa1, tt for Taq1, TT for Bgl1 and SS for Poly (A)) as the reference genotype in this meta-analysis. Allelic frequencies were also calculated from the corresponding genotyping distribution.

Quality assessment criteria

The quality of selected studies was assessed by Newcastle Ottawa Scale (NOS).⁴⁹ In addition, the meta-analysis was performed in accordance with PRISMA (Reporting Items for Systematic reviews and Meta-Analyses) guidelines (Table S1).

Statistical analysis

All statistical measures were done using STATA version 11.2 software. Summary odds ratio (SOR) along with 95% CIs were calculated to determine the strength of association between the VDR gene polymorphisms and BC. The SOR significance was assessed using Z test with p < 0.05. The heterogeneity among studies was evaluated using I² statistics with p < 0.1. Heterogeneity ranges from 0% to 100% which indicates between-study variations. The values of I² < 5% represent low, 25%-50% represent moderate, and >50% represent high estimates.⁵⁰ Mantel–Haenszel method⁵¹ and DerSimonian–Laird method⁵² were used to combine data from studies using both random-effect model (REM) and fixed-effect model (FEM), respectively. Potential publication bias was evaluated by Egger’s test. Sensitivity analysis (SA) was also performed to evaluate the quality and consistency in results. The HWE genotype distribution among controls was determined using χ² goodness of fit model, with p > 0.05.

Results

Baseline properties of studies

In all, 150 potentially relevant research publications were searched through electronic databases. Out of these, 35 were related to vitamin D levels and BC, 25 were related to vitamin D pathway gene polymorphisms and BC, 5 were duplicated records, and 19 were not related to BC which led to the selection of 67 and exclusion of 83 publications. Out of 67 publications, 8 were reviews, 14 were not retrieved completely, 1 was abstract, 3 had insufficient genotype data, 3 had no data for controls, 3 were on BC cell lines, and 1 was on male BC patients. This left 34 research papers, which read completely (Figure 1) and satisfied the inclusion criteria and were included in this meta-analysis. This review involved a total of 26,372 cases and 32,883 controls with mixed ethnicity. The baseline characteristics of all reviewed articles along with the HWE of each SNP are described in Table 1; p value >0.05 showed SNPs were in HWE. We also assess the quality of studies included in this meta-analysis using the NOS (Table S2). The scores 5 or >5 indicate studies with good quality.

Figure 1.

Flowchart illustrating selection of research publication.

Table 1.

Baseline properties of the reviewed studies on BC and VDR gene polymorphisms.

ID	Author	Year	Ethnicity	Country	Study design	Source of controls	BC cases (n)	Controls (n)	Genotyping method	Studied SNPs (p value HWE)
1	Talaneh et al.⁵³	2016	Asian	Iran	CCS	HB	95	71	PCR-RFLP	Fok1 (<0.05), Bsm1 (>0.05)
2	Colagar et al.¹⁸	2015	Asian	Iran	CCS	PB	134	127	SSCP-RFLP	Poly (A) (>0.05)
3	Guo et al.²⁰	2015	Asian	China	CCS	PB	219	321	PCR-RFLP	Bsm1 (>0.05), Apa1 (>0.05), Taq1 (>0.05)
4	Iqbal et al.¹³	2015	Asian	Pakistan	CCS	PB	103	161	T-ARM-PCR	Cdx2 (>0.05)
5	Nemenqani et al.²¹	2015	Asian	Saudi Arab	CCS	PB	95	100	PCR-RFLP	Fok1 (>0.05), Taq1 (>0.05)
6	Rashid et al.¹⁵	2015	Asian	Pakistan	CCS	HB	463	1012	PCR-RFLP	Bsm1 (<0.05), Fok1 (>0.05)
7	Reimers et al.¹⁴	2015	American white	USA	CCS	PB	967	993	TaqMan assay	Bsm1 (>0.05), Apa1 (>0.05), Taq1 (>0.05)
8	Fuhrman et al.²⁵	2013	Caucasian	USA	CSS	PB	484	845	TaqMan	Bsm1 (>0.05), Fok1 (>0.05)
9	Mishra et al.²⁴	2013	Caucasian, African-American, Hispanic	USA	CSS	HB	232	349	PCR-RFLP	Bsm1 (>0.05), Apa1 (>0.05), Fok1 (>0.05), Taq1 (>0.05)
S10	Shahbazi et al.²⁶	2013	Asian	Iran	CSS	PB	140	156	QIAamp	Bsm1 (>0.05), Fok1 (>0.05)
11	Dalessandri et al.²⁸	2012	Caucasian	Marin County	CSS	PB	164	174	–	Apa1 (>0.05)
12	Engel et al.²⁷	2012	Caucasian	Iowa and North Carolina	NCCS	PB	270	554	Pyrosequencing	Apa1 (<0.05), Fok1 (>0.05), Taq1 (<0.05), Bgl1 (<0.05)
13	Rollison et al.²²	2012	Hispanic	Southw-estern US	CCS	PB	2317	2521	PCR-RFLP	Bsm1 (>0.05), Fok1 (>0.05), Poly (A) (<0.05)
14	Yao et al.²³	2012	European, American African-American	US	CCS	HB	928	843	Sequencing	Cdx2 (<0.05)
15	Anderson et al.²⁹	2011	Caucasian	Canada	CCS	PB	1777	1839	MassARRAY iPLEX	Taq1 (>0.05), Bsm1 (>0.05), Fok1 (<0.05), Apa1 (>0.05), Cdx2 (>0.05), Bgl1 (>0.05)
16	Chakraborty et al.³⁰	2009	Asian	North India	CCS	PB	160	140	PCR-RFLP	Apa1 (>0.05), Taq1 (>0.05), Poly (A) (>0.05)
17	McKay et al.³¹	2009	Hispanic, African-American, Japanese American, Hawaiian, Caucasian	USA and Europe	CCS	PB	6300	8100	TaqMan	Bsm1 (<0.05), Fok1 (>0.05)
18	Gapska et al.⁵⁴	2009	Polish	Poland	CCS	PB	1736	1484	TaqMan	Bsm1 (>0.05), GATA (>0.05), Fok1 (>0.05), Taq1 (>0.05)
19	Abbas et al.³³	2008	German	Germany	CCS	PB	1408	2612	PCR-RFLPPyrosequencing	Fok1 (>0.05), Taq1 (>0.05), Cdx2 (>0.05), VDR-5132 (>0.05)
20	Sinotte et al.³²	2008	French Canadian	Canada	CCS	PB	859	1381	PCR-RFLP,TaqMan assay	Bsm1 (>0.05), Fok1 (>0.05)
21	McCullough et al.³⁴	2007	Caucasian, African, American, Hispanic, Asian, other/unknown	US	NCCS	PB	500	500	TaqMan	Bsm1 (>0.05), Apa1 (>0.05), Fok1 (>0.05), Taq1 (>0.05), Poly (A) (>0.05)
22	Trabert et al.⁴⁴	2007	Caucasian and African, American	USA	CCS	PB	1631	1435	PCR-RFLPNested PCR	Bsm1 (>0.05), Poly (A) (>0.05)
23	Wedren et al.⁴⁵	2007	Swedish	Sweden	CCS	PB	1801	1712	TaqMan	Poly (A) (>0.05)
24	VandeVord et al.⁴⁷	2006	African, American and white	U.S	CSS	PB	220	190	PCR-RFLP	Bsm1 (<0.05)
25	Chen et al.³⁶	2005	American	Turkey	NCCS	PB	1180	1547	TaqMan	Bsm1 (>0.05), Fok1 (>0.05)
26	Lowe et al.³⁵	2005	Caucasian	United Kingdom	CCS	HB	179	179	PCR-RFLP	Bsm1 (>0.05)
27	Hefler et al.⁴⁶	2004	Caucasian	Germany, Austria	CCS	PB	396	1936	PCR-RFLP	Bsm1 (<0.05)
28	Guy et al.⁵⁵	2004	Caucasian	United Kingdom	CCS	HB	398	427	PCR-RFLP	Bsm1 (>0.05), Fok1 (>0.05), Poly (A) (>0.05)
29	Buyru et al.³⁹	2003	Turkish	Turkey	CCS	PB	78	27	PCR-RFLP	Bsm1 (>0.05), Taq1 (<0.05)
30	Bretherton-Watt et al.⁵⁶	2001	American	UK	CCS	PB	241	181	PCR-RFLP	Bsm1 (>0.05), Fok1 (>0.05), Poly (A) (>0.05)
31	Ingles et al.⁴⁰	2000	Caucasian	Latinas, US	CCS	PB	143	300	PCR-RFLP, Nested PCR	Bsm1 (>0.05), Poly (A) (>0.05)
32	Curran et al.⁴³	1999	Australian	Australia	CCS	PB	135	110	PCR-RFLP	Apa1 (>0.05), Fok1 (>0.05), Taq1 (>0.05)
33	Lundin et al.⁴¹	1999	Swedish	Sweden	CCS	PB	111	130	PCR-RFLP	Taq1 (>0.05)
34	Dunning et al.⁴²	1999	Caucasian	UK	CCS	PB	508	426	PCR-RFLP	Taq1 (>0.05)

CSS: case-control studies; NCCS: nested case-control study; PB: population based; HB: hospital based.

p value >0.05 showed that SNPs were in HWE.

Test of heterogeneity

The heterogeneity of all VDR gene polymorphisms allelic models, co-dominant models, dominant models, and recessive models was made to analyze in all 34 studies (Figure S1 A–G). High-estimate heterogeneity was observed in Cdx2, Fok1, Bsm1 (except bb+Bb vs BB model), Apa1, and Poly (A) indicating between-study heterogeneity. When the co-dominant comparison was applied to genotype data Bsm1 bb versus BB (SOR = 1.18, 95% CI = 1.054–1.322, I² = 57.4%), Apa1 aa versus AA (SOR = 1.18, 95% CI = 0.87–1.59, I² = 74.1%) and Poly (A) LL versus SS (SOR = 1.41, 95% CI = 1.06–1.88, I² = 77.4%) were found based on the REM. In the recessive comparison models, Fok1 ff+Ff versus FF (SOR = 1.25, 95% CI = 0.896–1.759, I² = 98%), Apa1 aa+Aa versus AA (SOR = 1.13, 95% CI = 0.95–1.35, I² = 60.9%), and Poly (A) LL+LS versus SS (SOR = 1.19, 95% CI = 1.00–1.43, I² = 56.8%) were at risk of BC, whereas in dominant comparison model, none of genotypes were at risk. Most importantly, by allelic comparison, Poly (A) L versus S (SOR = 1.18, 95% CI = 1.03–1.35, I² = 77.4%) were at risk of having BC (Table 2). The Bsm1 showed greater degree of BC risk shown in Figure 2.

Table 2.

Meta-analysis and publication bias between VDR gene polymorphisms and BC.

SNPs	Comparison	N ^a	Test of association				Test of heterogeneity			Bias
SNPs	Comparison	N ^a	SOR	95% CI	Z	p value	I ²	Ph	Model	Egger’s test
Cdx2	GG versus AA	4	0.54	0.25–1.16	1.59	0.112	91.6	0.000	Random	0.007
	GG+GA versus AA		0.58	0.23–1.46	1.16	0.247	94.8	0.000	Random	0.007
	AA+GA versus GG		1.05	0.86–1.28	0.48	0.634	75.3	0.007	Random	0.007
	G versus A		0.75	0.42–1.34	96	0.336	98	0.000	Random	0.007
Fok1	ff versus FF	17	1.06	0.94–1.20	0.92	0.359	61	0.000	Random	0.000
	FF+Ff versus ff		0.983	0.886–1.090	0.745	0.33	54.8	0.030	Random	0.000
	ff+Ff vs FF		1.25	0.896–1.759	1.32	0.185	98	0.000	Random	0.000
	f versus F		0.898	0.717–1.123	0.94	0.345	97.9	0.000	Random	0.000
Bsm1	bb versus BB	20	1.18	1.054–1.322	2.88	0.004	57.4	0.001	Random	0.000
	BB+Bb versus bb		0.932	0.853–1.019	1.54	0.124	64.5	0.000	Random	0.000
	bb+Bb versus BB		1.09	1–1.18	1.88	0.06	46.6	0.010	Random	0.000
	b versus B		1.06	0.998–1.12	1.91	0.056	66.9	0.000	Random	0.000
Apa1	aa versus AA	8	1.18	0.87–1.59	1.06	0.289	74.1	0.000	Random	0.000
	AA+Aa versus aa		1.01	0.58–1.74	0.03	0.975	94.6	0.000	Random	0.000
	aa+Aa versus AA		1.13	0.95–1.35	1.37	0.171	60.9	0.120	Fixed	0.000
	a versus A		1.07	0.9–1.27	0.72	0.474	82.4	0.000	random	0.000
Taq1	TT versus tt	13	0.89	0.81–0.98	2.09	0.036	9.4	0.352	Fixed	0.000
	TT+Tt versus tt		0.91	0.84–0.99	2.12	0.34	13.3	0.311	Fixed	0.000
	tt+Tt versus TT		1.06	0.99–1.13	1.58	0.114	7.7	0.369	Fixed	0.000
	T versus t		0.94	0.9–0.99	2.57	0.01	16.2	0.281	Fixed	0.000
Bgl1	TT versus GG	2	0.94	0.79–1.12	2.57	0.01	0	0.336	Fixed	–
	TT+TG versus GG		1.03	0.88–1.19	0.35	0.727	0	0.378	Fixed	–
	GG+TG versus TT		0.94	0.82–1.08	0.81	0.417	0	0.650	Fixed	–
	T versus G		0.97	0.89–1.06	0.7	0.484	1.4	0.314	Fixed	–
Poly (A)	LL versus SS	8	1.41	1.06–1.88	2.38	0.01	75.6	0.000	random	0.000
	SS+LS versus LL		0.81	0.67–0.98	2.15	0.032	75.3	0.000	random	0.000
	LL+LS versus SS		1.19	1.00–1.43	1.74	0.082	56.8	0.023	random	0.000
	L versus S		1.18	1.03–1.35	2.42	0.015	77.4	0.000	random	0.000

Number of studies included in the meta-analysis.

Figure 2.

Summary estimates for the association between breast cancer and Bsm1 bb versus BB.

SA

SA was determined by sequentially eliminating each study one by one (data not shown). It was observed that SA did not very much affect the results in all cases. SA was done using both REM and FEM.

Publication bias

Egger’s tests (Table 2) were used to determine the publication bias. Significant results of Egger’s test were obtained due to varying sample size among studies which showed publication bias was present.

Discussion

In the present meta-analysis, we examined the seven polymorphisms of VDR (Cdx2, Fok1, Bsm1, Apa1, Taq1, Bgl1, and Poly (A)) gene for its association with BC risk. Our meta-analysis showed a literature survey on the seven widely studied VDR gene polymorphisms and BC risk, whereas previous meta-analyses were restricted to few polymorphisms. By extensive analysis of heterogeneity on BC, we highlighted summary estimates via REM and FEM, association between VDR gene polymorphisms and BC, SA, and publication bias. We obtained heterogeneity in the majority of models except for Taq1 and Bgl1. In the co-dominant model, Bsm1 bb, Apa1 aa, and Poly (A) LL genotypes were associated with increased BC risk. In allelic contrast models, the Poly (A) L allele has also shown association with the BC risk. The recessive contrast models of Fok1, Apa1, and Poly (A) were at risk, whereas, in dominant contrast models, none were associated with the risk.

This meta-analysis suggested a lack of association between VDR Cdx2 gene polymorphisms and BC risk in all models. These results were not consistent with previous reports which documented a positive association between Cdx2 polymorphism and BC risk.²⁹ While another report was found no risk among Japanese population.³³ Our results showed that Fok1-recessive models are at BC risk which differs in scope with a recent report which suggested that Fok1 polymorphism may be associated with postmenopausal BC but not with premenopausal BC.

The other functional polymorphisms are located near 3′ end of the gene including Bsm1, Apa1, Bgl1, Taq1, and Poly (A) polymorphisms. Our meta-analysis showed that Bsm1 bb, Apa1 aa, and Poly (A) LL genotypes are associated with BC, but lack of association is found between Taq1, Bgl1 and BC which could be explained in further haplotype studies. Whereas recent meta-analyses revealed no association between Fok1, Bsm1 Apa1, Taq1, and Poly (A) with BC.^57–59 It was suggested that the wild-type Poly (A) L allele corresponds to the functional marker of Bsm1 b allele. The variation in LD between these functional and marker alleles may explain the inconsistencies in the strength of associations perceived across studies.⁶⁰

The sample size has an impact on the summary estimates and power of study; if all related published data were recruited completely, the power of meta-analysis increases. HWE is another important aspect of genotyping; in present meta-analysis, majority of SNPs were in HWE. However, the deviation from HWE showed a signal that the segregation of alleles is not independent. There may be various reasons including non-randomized matching of controls with cases, biased participants selection from population, errors in genotyping, and stratification of population.

The present meta-analysis has some limitations. First, the presence of heterogeneity among patients and various confounding factors might misrepresent the meta-analysis. Second, haplotyping of genotype might provide more informative results, so it would be more influential than single SNPs. Third, due to the lack of original data of studies, we cannot be able to consider other factors, such as plasma/serum vitamin D concentration, diet, life style, body mass index (BMI), sun exposure, use of NSAIDs/Quinone, BC stages, intake of calcium, and vitamin D that could affect the subjects and modify the overall risk of BC.

Conclusion

The present meta-analysis determines that the VDR Bsm1, Apa1, Fok1, and Poly (A) polymorphisms may be susceptible for BC development. However, Cdx2, Taq1, and Bgl1 polymorphisms fail to find an association with BC incidence. Vitamin D deficiency is common throughout developed and developing countries worldwide, so vitamin D supplementation is practiced to normalize various biological processes, but the results are not promising. In fact, a mechanism may be impaired in the pathway of vitamin D or there may be an involvement of genetic polymorphisms in the VDR which may be a cause of developing BC. Thus, the findings of this study will provide a better understanding of the BC treatment since VDR SNPs along with endogenous vitamin D should be considered during therapy.

Footnotes

Acknowledgements

Mehir un Nisa Iqbal and Taseer Ahmed Khan did conception and design of study; Mehir un Nisa Iqbal did extraction, analysis, and interpretation of data; Mehir un Nisa Iqbal did drafting of the article or critical revision for important intellectual content; and Taseer Ahmed Khan did final approval of the version to be published.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

The ethical approval was not required for this study.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Association between Vitamin D receptor (Cdx2,Fok1,Bsm1,Apa1,Bgl1,Taq1,and Poly (A)) gene polymorphism and breast cancer: A systematic review and meta-analysis

Abstract

Keywords

Introduction

Materials and methods

Publication search strategy

Inclusion criteria

Exclusion criteria

Data extraction

Quality assessment criteria

Statistical analysis

Results

Baseline properties of studies

Test of heterogeneity

SA

Publication bias

Discussion

Conclusion

Footnotes

Acknowledgements

Declaration of conflicting interests

Ethical approval

Funding

References

Supplementary Material