The deficiency of vitamin D receptor (VDR) or its ligand, vitamin D3, is linked to the development of renal diseases. The TaqI (rs731236) and ApaI (rs7975232) polymorphisms of VDR gene are widely studied for their association with renal disease risk. However, studies have largely been ambiguous.
Methods
Meta-analysis was carried out to clarify the association of TaqI (2777 cases and 3522 controls) and ApaI (2440 cases and 3279 controls) polymorphisms with nephrolithiasis (NL), diabetic nephropathy (DN) and end stage renal disease (ESRD).
Results
The VDR TaqI C-allele under allele contrast was significantly associated with ESRD in both fixed effect and random effect models, and ApaI C-allele with ESRD only under fixed effect model. Cochrane Q-test showed no evidence of heterogeneity for TaqI polymorphism and a significant heterogeneity for Apa I polymorphism. No publication bias was observed for both the polymorphisms.
Conclusions
The present meta-analysis identifies TaqI and ApaI polymorphisms of VDR gene as risk factors for renal diseases.
Hinweise
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Abkürzungen
1,25 (OH)2D3
1,25-dihydroxyvitamin D3
25-OHD3
25-hydroxy vitamin D3
DN
diabetic nephropathy
ESRD
end stage renal disease
NL
nephrolithiasis
VDR
vitamin D receptor
Introduction
In human skin, solar rays facilitate the formation of vitamin D3 from 7-dehydrocholesterol. The vitamin D3 undergoes two-step hydroxylation to form 25-hydroxy vitamin D3 (25-OHD3) and biologically active 1,25-dihydroxyvitamin D3 (1,25-(OH)2D3) [1]. Vitamin D receptor (VDR) is a ligand-activated transcriptional factor requiring 1,25(OH)2D for its activation [2]. The deficiency of 25OHD or VDR is reported to activate renin-angiotensin system resulting in high angiotensin II levels, which damage renal parenchyma leading to increased risk for renal disease [3]. Considering the pivotal role of VDR in maintaining normal renal function, a number of studies have explored the possibility of association of VDR gene polymorphisms with renal disease risk. Among VDR polymorphisms reported to date, ApaI, and TaqI are widely studied for their association with ESRD, NL and DN [4‐6]. The ApaI variant (rs7975232), which results in A to C transition, is located in the intron 8 of VDR gene, while TaqI variant (rs731236), which results in T to C transition is located in exon 9 [7].
The rs7975232 (NG_008731.1:g.64978G > T) is an intronic variant predicted to influence splice site changes that might affect the translation of VDR. The frequency of this variant is high as evidenced by 734 and 16,751 homozygous mutants in 1000G and ExAC databases. The rs731236 (NG_008731.1:g.65058 T > C) variant is near the exon-intron boundary (GCTG/attg) and hence likely to influence splicing and thus might affect the translation of VDR. The frequency of this variant is lower than that of rs7975232 with 242 and 7505 homozygous mutants identified in 1000G and ExAC databases.
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Importantly, genetic studies examining the role of TakI and ApaI polymorphisms in the pathogeneses of NL, DN and ESRD remained ambiguous [4‐6, 8‐12]. Considering the significance of VDR signaling in the protection against renal diseases and the ambiguity in the studies relating VDR gene polymorphism with the disease etiology, present meta-analysis comprising 2669 renal disease cases and 3342 controls was carried out to clarify the association of VDR gene TaqI and ApaI polymorphisms with nephrolithiasis, ESRD and diabetic nephropathy.
Methods
Data extraction
The literature retrieval was carried out using keywords: vitamin D receptor or VDR, renal disease, nephrolithiasis or urolithiasis, diabetic nephropathy, TaqI (rs731236) and ApaI (rs7975232) in PubMed, Medline and google scholar databases. All the free full texts were retrieved and wherever full text was not available, reprint request was sent to the corresponding author of the respective article. The criteria to include in the meta-analysis were: 1) availability of full text of the article, 2) inclusion of studies involving both cases and controls (either online or through reprint from the corresponding author), 3) availability of raw data on genotypes, and 4) restricting to studies published in only English language. The information related to each study such as first author, year of study, ethnic group or population studied, distribution of genotypes in cases and controls etc. was computed. The decision on the studies to be included in meta-analysis was taken by all the authors of this study.
Meta-analysis
The data computed in four columns wherein first two columns represent the number of variant alleles in cases and controls and last two columns represent the number of ancestral alleles in cases and controls. Log (odds ratio) or effect size and standard error (SE) are calculated based on these four column data. Based on these two parameters, variance (SE2), weight and 95% confidence interval of effect size were calculated. Cochrane Q test and I2 statistics were performed to test the heterogeneity in the association. The plot of 1/SE and Z-statistics was also used as an index to test heterogeneity. The publication bias was based on the rank correlation of SE and v. The fixed effect and random effect models were generated based on Mantel Haenszel and DerSimonian Lair’s methods, respectively. If no evidence of heterogeneity was found, fixed effect model was considered. If test heterogeneity was significant, random effect model was considered.
Results
Figure 1 depicts the data extraction process for the meta-analysis. Of the 16 case-control studies retrieved on the association of TaqI polymorphism with renal disease (Table 1), four studies showed deviation from Hardy-Weinberg equilibrium [7, 13‐15]. Among the different population groups included in this meta-analysis, the largest being that of Turkish representing five case-control studies [16‐20], two studies from India [21, 22] and one each from China [23], Ireland [24], Italy [25], Spain [26] and Croatia [27]. In total, the final meta-analysis was based on the data of 2777 cases and 3522 controls representing 16 case-control studies.
Table 1
Distribution of VDR1 TaqI polymorphism in different case-control studies
The following studies were shown to have deviation from HWE: Guha et al. (p < 0.0001), Nosratabadi et al. (p = 0.0008), Goknar et al. (p = 0.0008) and Han et al. (p = 0.0008)
ESRD end stage renal disease, NL nephrolithiasis, DN diabetic nephropathy
×
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Cochrane Q-test (Q: 13.72, p = 0.54) and I2 (0.00) statistics showed no evidence of heterogeneity in association. Egger’s test revealed no evidence of publication bias (p = 0.14). The VDR TaqI C-allele, under allele contrast fixed effect model, was associated with renal diseases calculated collectively for DN, ESRD and NL (OR: 1.11, 95% CI: 1.03–1.20, p = 0.008). (Figure 2) As shown Table 2, subtype analysis revealed Taql C- allele to be associated with ESRD (OR: 1.17, 95% CI: 1.02–1.34, p = 0.03) (Fig. 2). Among the different ethnic groups, Turkish population showed strong association between VDR TaqI polymorphism and renal disease in allele contrast model (C vs. T, OR: 1.19, 95% CI: 1.01–1.42, p = 0.04). Sensitivity analysis revealed that omitting either of the studies had no effect on overall outcome of disease risk.
Table 2
Subgroup analysis showing disease-specific risk with VDR TaqI polymorphism
Model
Type of disease
N
OR
95% CI
P value
Allele contrast (A vs. a)
Overall
16
1.11
[1.0262; 1.1967]
0.009
ESRD
2
1.17
[1.0171; 1.3357]
0.028
NL
11
1.09
[0.9673; 1.2356]
0.153
DN
3
1.07
[0.9250; 1.2322]
0.371
Recessive model (AA vs. Aa+aa)
Overall
16
1.19
[0.9266; 1.5392]
0.170
ESRD
2
1.14
[0.8497; 1.5235]
0.386
NL
11
1.32
[0.8084; 2.1503]
0.268
DN
3
1.11
[0.8527; 1.4432]
0.439
Dominant model (AA+Aa vs. aa)
Overall
16
1.14
[1.0234; 1.2709]
0.017
ESRD
2
1.24
[1.0367; 1.4863]
0.019
NL
11
1.09
[0.9148; 1.2930]
0.342
DN
3
1.09
[0.8737; 1.3505]
0.456
Overdominant (Aa vs. AA + aa)
Overall
16
0.99
[0.8106; 1.2040]
0.904
ESRD
2
1.19
[0.9904; 1.4233]
0.063
NL
11
0.92
[0.6575; 1.2975]
0.647
DN
3
1.01
[0.8261; 1.2289]
0.940
pairw1 (AA vs. aa)
Overall
16
1.20
[1.0117; 1.4232]
0.036
ESRD
2
1.26
[0.9280; 1.7151]
0.138
NL
11
1.23
[0.9346; 1.6077]
0.141
DN
3
1.11
[0.8081; 1.5149]
0.528
pairw2 (AA vs. Aa)
Overall
16
1.16
[0.8525; 1.5857]
0.341
ESRD
2
1.01
[0.7443; 1.3803]
0.932
NL
11
1.30
[0.7200; 2.3483]
0.384
DN
3
1.09
[0.8304; 1.4407]
0.524
pairw3 (Aa vs. aa)
Overall
16
1.09
[0.9167; 1.2888]
0.337
ESRD
2
1.24
[1.0233; 1.4966]
0.028
NL
11
1.04
[0.7873; 1.3666]
0.795
DN
3
1.07
[0.8487; 1.3425]
0.577
×
Of the 13 case-control studies (2440 cases and 3279 controls) retrieved on the association of ApaI polymorphism with renal disease (Table 3), five studies deviated from Hardy-Weinberg equilibrium [7, 15, 19, 21, 28]. Among the studies in accordance with HWE equilibrium, 3 studies were from Turkey [16, 17, 20], two from China [14, 23], and one each from Ireland [24] and Iran [29]. Cochrane Q-test (Q: 17.01, p = 0.03) and I2 (48.3) statistics showed high-degree of heterogeneity in association. Egger’s test revealed no evidence of publication bias (p = 0.54). The fixed effect model showed positive association of VDR ApaI polymorphism with all the renal disease cases (C vs. A, OR: 1.10, 95% CI: 1.01–1.19), whereas, random effect model showed null association (OR: 1.05, 95% CI: 0.93–1.19) (Fig. 3). Sensitivity analysis for ApaI polymorphism revealed that the sources of heterogeneity are two studies i.e. Wang et al. and Tripathi et al. However, overall trend suggests ApaI variant as a risk factor for renal disease. As shown in Table 4, subgroup analysis revealed association of VDR ApaI polymorphism with ESRD (C vs. A, OR: 1.31, 95% CI: 1.15–1.50, p = 0.0001) and no association with NL and DN.
Table 3
Distribution of VDR1 ApaI polymorphism across different case-controls studies
The following studies were shown to have deviation from HWE: Ozkaya et al. (p = 0.03), Nosratabadi et al. (p = 0.009), Goknar et al. (p = 0.03), Tripathi et al. (p < 0.0001) and Aykan et al. (p < 0.0001)
Subgroup analysis showing disease-specific risk with VDR ApaI polymorphism
Model
Type of disease
N
OR
95% CI
p-val
Allele contrast (A vs. a)
Overall
13
1.05
[0.9282; 1.1931]
0.4259
ESRD
2
1.31
[1.1454; 1.4996]
0.0001
NL
6
0.86
[0.7193; 1.0175]
0.0777
CH
1
1.44
[0.7974; 2.5983]
0.2268
DN
4
1.06
[0.9361; 1.1997]
0.3589
Recessive model (AA vs. Aa+aa)
Overall
13
1.10
[0.8891; 1.3548]
0.3865
ESRD
2
1.85
[1.3925; 2.4544]
0.0000
NL
6
0.77
[0.5591; 1.0553]
0.1035
CH
1
1.15
[0.4482; 2.9300]
0.7760
DN
4
1.06
[0.8695; 1.2818]
0.5840
Dominant model (AA+Aa vs. aa)
Overall
13
1.03
[0.8131; 1.3008]
0.8153
ESRD
2
1.21
[0.7844; 1.8716]
0.3868
NL
6
0.76
[0.5034; 1.1586]
0.2049
CH
1
2.13
[0.8380; 5.4311]
0.1120
DN
4
1.09
[0.8749; 1.3545]
0.4466
Overdominant (Aa vs. AA + aa)
Overall
13
0.99
[0.8143; 1.2066]
0.9300
ESRD
2
0.91
[0.4290; 1.9490]
0.8167
NL
6
0.96
[0.6559; 1.3933]
0.8147
CH
1
1.69
[0.7239; 3.9340]
0.2256
DN
4
1.03
[0.8660; 1.2221]
0.7472
pairw1 (AA vs. aa)
Overall
13
1.09
[0.8006; 1.4779]
0.5907
ESRD
2
1.81
[1.3275; 2.4638]
0.0002
NL
6
0.70
[0.4803; 1.0158]
0.0604
CH
1
1.89
[0.6130; 5.8330]
0.2677
DN
4
1.09
[0.8307; 1.4252]
0.5399
pairw2 (AA vs. Aa)
Overall
13
1.10
[0.8709; 1.3854]
0.4280
ESRD
2
1.74
[0.9540; 3.1683]
0.0709
NL
6
0.86
[0.5968; 1.2327]
0.4068
CH
1
0.82
[0.2948; 2.2927]
0.7082
DN
4
1.02
[0.8306; 1.2477]
0.8635
pairw3 (Aa vs. aa)
Overall
13
1.03
[0.7832; 1.3445]
0.8515
ESRD
2
1.06
[0.5720; 1.9761]
0.8464
NL
6
0.79
[0.4507; 1.3857]
0.4113
CH
1
2.30
[0.8331; 6.3500]
0.1080
DN
4
1.10
[0.8688; 1.3802]
0.4417
×
Discussion
Deficiency of vitamin D or defective activation of VDR by its ligand, 1,25-dihydroxy vitamin D results in secondary hyperparathyroidism, angiotensin II-mediated renal damage and renal disease pathogenesis [3]. On the other hand, VDR activation suppressed inflammatory cell infiltration and inhibited nuclear factor-κB activation [30]. Likewise, active vitamin D3 and lentivirus-mediated transforming growth factor-β (TGF-β) interference effectively reduced renal fibrosis in rat models [31]. These observations highlight the importance of VDR signaling in maintaining normal renal function. Accordingly, a number of studies have investigated the effects of polymorphisms in VDR gene on renal disease etiology. Among these, TaqI, and ApaI polymorphisms are widely studied [4‐6]. However, there is a considerable ambiguity among these genetic studies, possibly stemming from sample size, ethnicity or gene-environmental interactions [4‐6, 8‐12]. To clarify whether TaqI and apaI polymorphisms have a role in renal disease pathogenesis, this meta-analysis comprising 2777 renal disease cases including DN, NL and ESRD and 3522 healthy controls was carried out. The present meta-analysis revealed an increased disease risk for subjects harboring TaqI C-allele under fixed and random effect models. Subgroup analysis based on type of renal disease showed that VDR TaqI polymorphism is associated with ESRD in allele contrast model, whereas no significant association was found between TaqI polymorphism and DN and NL. In the case of ApaI polymorphism, Apal C-allele was found to be linked to ESRD, but not with DM or NL under fixed effect model. Earlier, Yang et al. performed a meta-analysis on 1510 cases and 1812 controls and found no association of BsmI, FokI, TaqI, and ApaI polymorphisms of VDR with end-stage renal disease. Inclusion of more studies benefited the current meta-analysis.
The direct role of solar rays in the synthesis of vitamin D is well known. In human skin, solar rays facilitate the formation of vitamin D3 from 7-dehydrocholesterol, which is evident from the presence of higher mean serum vitamin D levels in summer than in winter [32]. Likewise, higher vitamin D levels were found in populations living in regions known to have longer durations of sun exposure [33].
Conclusions
This meta-analysis revealed the association of VDR TaqI and ApaI polymorphisms with ESRD risk. This is the first meta-analysis study to simultaneously evaluate the association of DN, NL and ESRD with renal disease risk. Ethnicity, sample size, gene-environmental interactions appear to be responsible for inconsistencies observed in the association studies examining VDR polymorphisms and renal diseases. The limitations of this meta-analysis include; exclusion of studies where raw data or full text were not accessible and one-to-one correlation between vitamin D3 profile and risk could not be established as no parallel studies were conducted.
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Competing interests
The authors declare that they have no competing interests.
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