- Email: [email protected]
Associations study of vitamin D receptor gene polymorphisms with diabetic microvascular complications: a meta-analysis
Gene 546 (2014) 6–10
Contents lists available at ScienceDirect
Gene journal homepage: www.elsevier.com/locate/gene
Associations study of vitamin D receptor gene polymorphisms with diabetic microvascular complications: a meta-analysis Zhelong Liu a,1, Lei Liu b,1, Xi Chen a, Wentao He a, Xuefeng Yu a,⁎ a b
Division of Endocrinology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, China Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
a r t i c l e
i n f o
Article history: Received 5 March 2014 Received in revised form 18 May 2014 Accepted 22 May 2014 Available online 24 May 2014 Keywords: Vitamin D receptor Diabetic microvascular complications Meta-analysis
a b s t r a c t Background: Emerging evidence from preclinical and clinical studies has shown that vitamin D plays an important role in the pathogenesis of diabetic microvascular complications (DMI). Several potentially functional polymorphisms (ApaI, BsmI, FokI and TaqI) of vitamin D receptor (VDR) gene have been implicated in DMI risk, but individually published studies showed inconclusive results. The aim of this study was to quantitatively summarize the association between VDR polymorphisms and DMI risk. Methods: We searched all the publications about the associations mentioned as above from PubMed and ISI database updated in December 2013. Meta-analysis of the overall odds ratios (ORs) with 95% confidence intervals (CIs) was calculated with the fixed or random effect model. Results: Eight studies involving 2734 subjects were included. Allelic and genotypic comparisons between cases and controls were evaluated. Overall analysis suggests that no significant association was observed among the ApaI, BsmI, FokI and TaqI variants and DMI risk in diabetic patients (all P values N 0.05). In the stratified analysis, significant association was observed with diabetic nephropathy (DN) for VDR gene FokI polymorphism under a dominant model (OR 1.35, 95% CI 1.05–1.74, P = 0.02) in Caucasians. Conclusions: This meta-analysis indicated that the FokI polymorphism in VDR gene might affect individual susceptibility to DN in Caucasians. Further investigations are needed to confirm our results. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Diabetes mellitus is one of the most common chronic disorders all over the world with the condition of hyperglycemia, and its prevalence is still progressively increasing as a consequence of an aging population and changes in lifestyle. Data from prospective and cross-sectional studies consistently points to the fact that diabetic patients are more likely to develop macro- as well as microvascular conditions (Lee et al., 2001; Rosenson et al., 2011). Diabetic microvascular complications (DMI) involve the smallest blood vessels, the capillary and the pre-capillary arteries, with the profile of thickening of the capillary basement membrane, mainly in the kidneys and retina. Therefore, microvascular complications from diabetes are common and include retinopathy leading to various degrees of visual impairment blindness; and nephropathy characterized by proteinuria ultimately leading to end stage renal disease Abbreviations: DMI, diabetic microvascular complications; VDR, vitamin D receptor; OR, odds ratios; CI, confidence intervals; DR, diabetic retinopathy; DN, diabetic nephropathy; SNP, single nucleotide polymorphism; HWE, Hardy–Weinberg equilibrium. ⁎ Corresponding author at: Division of Endocrinology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Ave, Wuhan 430030, China. E-mail address: [email protected] (X. Yu). 1 These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.gene.2014.05.052 0378-1119/© 2014 Elsevier B.V. All rights reserved.
(Fong et al., 2004; Wu et al., 2005). It is well known that DMI have become major causes of chronic kidney disease and blindness, which reduce the quality of the life of patients, incur heavy burdens to the health care systems, and increase diabetic mortality (Gray and Cooper, 2011; Zhang et al., 2010). Although the precise mechanism has not been clearly elucidated yet, DMI can be partly attributed to factors such as the type or duration of diabetes, the degree of glycemic and blood pressure control and the age of the patient (Ding and Wong, 2012; Nakagawa et al., 2011; Yau et al., 2012). Recently, genetic predispositions have also been highlighted to play important roles in the mechanisms underlying the development and progression of DMI (Abhary et al., 2009; Su et al., 2013; Tian et al., 2011; Zhang et al., 2012b). Therefore, finding a genetic marker for this disease would be important in indentifying patients who could benefit from preventive treatment. Vitamin D (VD), a secosteroid hormone, is acquired and synthesized from the diet and ultraviolet radiation. Besides its calciotropic function, VD has potent non-classical properties, including immunomodulatory, antiinflammatory, antioxidant, antiangiogenic, and antiproliferative properties (Basit, 2013; Heaney, 2008). It is well known that the interaction of VD with target tissues is mediated by the VD receptor (VDR), a member of the steroid/thyroid hormone receptor family with the function of a transcriptional activator of many genes (Cronin, 2010).
Z. Liu et al. / Gene 546 (2014) 6–10
There are accumulating evidences to suggest that the vitamin D endocrine system is involved in a wide variety of biological processes including diabetes, and diabetic microvascular complications (Al-Daghri et al., 2012; Fernandez-Juarez et al., 2013; Riek et al., 2013; Thorand et al., 2011; Tian et al., 2014). The association of vitamin D receptor (VDR) gene polymorphisms with diabetes and DMI has recently become a hot topic for research (Li et al., 2013; Reis et al., 2005; Wang et al., 2012; J. Zhang et al., 2012). VDR gene is located on chromosome 12q13.1, consists of 11 exons and has an extensive promoter region capable of generating multiple tissue-specific transcripts. There are four single nucleotide polymorphisms (SNPs) in the VDR gene, FokI (rs10735810), BsmI (rs1544410), ApaI (rs7975232) and TaqI (rs731236), that have been studied most frequently. The BsmI, ApaI, and TaqI are located at the 3 untranslated region of the gene, which is involved in regulation of gene expression, especially through the modulation of mRNA stability (Uitterlinden et al., 2004b). Another polymorphism, FokI, is a T-to-C substitution at exon 2, abolishing the first translation initiation site and resulting in a peptide lacking three amino acids, which influences the transcriptional activity of VDR (Uitterlinden et al., 2004a). Considering the past establishment of the important functions of VDR gene polymorphisms, many studies have explored the association between VDR gene functional polymorphisms and DMI risk (Aterini et al., 2000; Bucan et al., 2009; Cyganek et al., 2006; Martin et al., 2010; Nosratabadi et al., 2010; Taverna et al., 2002, 2005; Zhang et al., 2012a). However, individual studies yielded inconsistent and even conflicting findings. It is still inconclusive whether VDR gene polymorphisms would be causal in determining DMI susceptibility. To shed light on these contradictory results and to get a more precise evaluation of this association, we performed a meta-analysis of eight published case–control studies covering 2734 participants. 2. Material and methods 2.1. Search strategy We searched the literature databases (PubMed and ISI Web of Science) for all available articles on the association between VDR and the DMI. The search strategy to identify all possible studies involved the use of the following key words: “VDR”, “diabetic retinopathy (DR)” or “diabetic nephropathy (DN)”, “mutation” or “single nucleotide polymorphism (SNP)” or “variant”. Both type 1 and type 2 diabetic patients were enrolled in our study. Additional studies not captured by our database searches were identified by reviewing the reference lists of retrieved articles. If more than one article were published using the
7
same case series, only the study with largest sample size was included. The literature search was updated in December, 2013. 2.2. Selection criteria The studies included in the meta-analysis must meet all the following inclusion criteria: (1) evaluated the associations of polymorphisms in the VDR gene, ApaI, BsmI, FokI or TaqI, with the risk of DN and/or DR; (2) case–control studies or cohort studies; (3) available genotype distribution or allele frequencies of cases and controls that can provide sufficient data for calculation; and (4) published in English. 2.3. Data extraction The following information was extracted independently by two authors from each study:(1) name of first author; (2) year of publication; (3) country of origin; (4) ethnicity of the study population; (5) genotype distribution or allele frequencies; and (6) sample sizes of cases and controls and the SNPs included (Table 1). The two authors independently assessed the articles for compliance with the inclusion/exclusion criteria, resolved disagreements and reached a consistent decision. 2.4. Statistical analysis The combined odds ratios (ORs) together with their corresponding 95% confidence intervals (95% CIs) were utilized to calculate and assess the strength of association between the polymorphisms of VDR (ApaI, BsmI, FokI and TaqI) and DMI risk. The dominant, recessive and additive genetic models were all used in this meta-analysis. The significance of pooled OR was determined by Z test (P b 0.05 was considered statistically significant). The Chi-square test was used to determine if the observed frequencies of genotypes in controls conformed to Hardy– Weinberg equilibrium (HWE). The I2 of Higgins and Thompson was used to test the heterogeneity between the studies. Heterogeneity assumption was examined by the Chi-square based on Q-test. The pooled OR estimation of each study was calculated with a random-effect model using the DerSimonian and Laird method (D + L) when P value was no more than 0.1, otherwise with a fixed-effect model using the Mantel– Haenszel (M–H) method. Publication bias was evaluated through the Begg's test, the Egger's Asymmetry test, and visual inspection of funnel plots, in which the standard error was plotted against the Log(OR) to form a simple scatter plot. All of the statistical analyses were performed using STATA version 11.0 software (Stata Corporation, College Station, TX, USA). All the P values were for a two-tailed test and P b 0.05 was considered as statistically significant.
Table 1 Characteristics of the studies included in the meta-analysis. Author
Year
Population
Taverna et al.
2002
French
Taverna et al.
2005
French
Cyganek et al.
2006
Polish
Bucan et al.
2009
Croatian
Martin et al.
2009
Irish
Nosratabadi et al.
2010
Iranian
Zhang et al.
2012
Chinese
Vedralová et al.
2012
Czech
Sample
Case Control Case Control Case Control Case Control Case Control Case Control Case Control Case Control
Genotypes (N) ApaI
BsmI
FokI
AA/Aa/aa
BB/Bb/bb
FF/Ff/ff
TaqI TT/Tt/tt 27/58/16 42/44/13
17/39/29 39/100/43
185/323/147 200/322/152 27/64/9 28/63/9 19/89/74 11/65/46
10/36/39 21/84/77 3/18/12 11/24/26 106/321/228 111/325/238
38/65/23 57/56/15 21/43/21 51/93/48 10/15/8 16/33/12 248/323/84 262/311/101
3/57/122 0/26/96 63/58/11 57/85/28
40/38/7 81/82/19 7/14/12 11/26/24 103/327/225 98/327/249 36/55/9
8
Z. Liu et al. / Gene 546 (2014) 6–10
Fig. 1. Flow diagram of included/excluded studies.
3. Results 3.1. Characteristics of the studies Fig. 1 describes the flow of candidate and eligible papers. Our initial search of the literature yielded 125 publications. After reading the titles and abstracts, 11 potential studies were included for full-text view. After reading full texts, three studies were excluded for not reporting the usable data. Finally, a total of 8 case–control studies in 8 articles were identified met our inclusion criteria, including 1394 DMI patients and 1340 diabetic controls. The main characteristics of these selected studies were summarized in Table 1, including first author, published year, original country and genotype distribution. 3.2. Quantitative data synthesis It has been shown in Table 2 that the risk for DMI conferred by VDR gene polymorphisms in the overall 8 studies did not reach the significant difference (all P values N0.05). We then conducted the analyses excluding the studies not in HWE. However, the significance of pooled OR under all genetic models was not influenced after excluding the study (data not shown). With regard to the specific type of DMI, we also conducted the subgroup analyses stratified by DN or DR. The results showed that the FokI polymorphism was found to be significantly associated with an increased risk of DN in a dominant model (Fig. 2) (OR = 1.35, 95% CI Table 2 Pooled measures on the relation of VDR gene polymorphisms with DMI. Polymorphisms
Inherited model
Number of cases/controls
Pooled OR (95% CI)
I2 (%)
ApaI
Dominant Recessive Additive Dominant Recessive Additive Dominant Recessive Additive Dominant Recessive Additive
1022/1078 1022/1078 1022/1078 955/1039 955/1039 955/1039 1031/1225 1031/1225 1031/1225 974/1116 974/1116 974/1116
0.95 (0.78, 1.16) 1.09 (0.89, 1.34) 0.95 (0.84, 1.08) 0.97 (0.75, 1.27) 0.91 (0.76, 1.10) 1.04 (0.91, 1.19) 1.06 (0.72, 1.56)a 1.02 (0.85, 1.23) 1.01 (0.78, 1.31)a 0.93 (0.76, 1.14) 0.99 (0.80, 1.24) 1.03 (0.91, 1.17)
0.0% 0.0% 0.0% 0.0% 44.5% 37.6% 60.3% 28.9% 64.3% 0.0% 19.8% 0.0%
BsmI
FokI
TaqI
a
OR was calculated in random-effects model.
1.05–1.74, P = 0.02). Interestingly, all of these studies were performed in Caucasians and the heterogeneity of the subgroup disappeared (I2 = 8.6%). The remaining results from these subgroup analyses were not significant (all P values N0.05). In contrast, in the subgroup of DR, no significant association with the VDR gene polymorphisms was found in all genetic models (all P values N0.05). On subgroup analysis by ethnicity, no evidence of significant association was found in all genetic models for DMI (all P values N0.05). 3.3. Publication bias Publication bias was analyzed by using the Begg's funnel plots and Egger's test. The shape of the funnel plots was symmetrical, suggesting that there was no evidence of publication bias among the studies (data not shown). We further analyzed the publication bias of each metaanalysis of these four different SNPs by Egger's test. All P values were higher than 0.05 and no publication bias was detected. The results indicated a lack of publication bias. 4. Discussion Unraveling the genes that contribute to the pathogenic risk of DMI has been one of the major foci of basic research in DMI over the past few decades. A large number of putative genes and genetic variants have been reported to be moderately associated with higher risk of DMI (Abhary et al., 2009; Zhang et al., 2012b). However, due to the high level of heterogeneity of this disease, genetic studies have therefore given very diverse results. Furthermore, studies with subjects exposed in different environmental factors may yield different results. Lack of replication has long been a big challenge in genetic association studies. Also, because of modest sample size, different populations and lifestyles, these single studies had less power to provide us with reliable and comprehensive conclusions. Meta-analysis, which has generally been used in investigating the association of genetic variation and disease, has the benefit to overcome these limitations by increasing the sample size and may generate more robust data. Therefore, to better assess the association between DMI risk and VDR gene polymorphism, we carried out a comprehensive genetic meta-analysis. In this meta-analysis, we analyzed the VDR gene functional polymorphisms (FokI, BsmI, ApaI and TaqI) as potential genetic markers for DMI. Nevertheless, the results of this meta-analysis suggest that none of these polymorphisms was significantly associated with DMI
Z. Liu et al. / Gene 546 (2014) 6–10
9
Fig. 2. Forest plot of the risk of DN associated with the VDR gene FokI polymorphism.
risk in diabetic patients (all P values N0.05). Of note, in the stratified analysis, significant association was observed with DN for VDR gene FokI polymorphism under a dominant model (OR = 1.35, 95% CI 1.05–1.74, P = 0.02). However, we did not find any correlation in other subgroup. To the best of our knowledge, this is the first metaanalysis assessing the association between VDR gene polymorphisms and DMI. To date, the exact biological mechanism underlying the effects of the VDR gene FokI polymorphism on DN remains uncertain. The FokI variant can be detected by the presence or absence of a FokI restriction site within the ATG transcriptional start site of the VDR gene. Additionally, the FokI polymorphism is the only known locus affecting the structure of the VDR protein produced. The gene is transcribed into normal length when the restriction site (f allele) is present. Conversely, the gene is transcribed and into shortened length when the restriction site (f allele) is absent. In turn, the f allele encodes a 427 amino acid protein while the F allele encodes a 424 amino acid protein (Uitterlinden et al., 2004a). Previous study had demonstrated that the longer VDR protein appears to possess decreased transcriptional activity, leading to lower activation of target cells (Jurutka et al., 2000). However, due to complicated interactions of environmental factors and multiple genes, the precise role of VDR gene FokI polymorphism in DR remains elusive. Additional future studies should be performed to focus on the function of the VDR gene FokI polymorphism. Our meta-analysis did not find any association of the other three polymorphisms (BsmI, ApaI and TaqI) with an increased DMI risk in overall and subgroup analysis. It is interesting to note that significant linkage disequilibrium was found among the TaqI, ApaI and BsmI polymorphisms (Li et al., 2013). Therefore, the combined analysis of these three variants may be powerful enough to identify whether individuals are susceptible to DMI. Nevertheless, because no sufficient information could be extracted from the original papers, we could not perform the pooled analysis of haplotypes. For better interpreting of the results, several potential limitations of this meta-analysis should be acknowledged. Firstly, as no correction for multiple testing was performed in this meta-analysis, false positive results may have been induced in some fraction because of the application of multiple statistical tests, which would increase the probability of type I errors. Secondly, the overall outcomes were based on individual unadjusted genotype data, while a more precise evaluation should be made by adjusting other potentially suspected factors including age, sex, and environmental factors. Thirdly, the numbers of published studies were still not sufficiently large for the analysis of some particular DMI types. Fourthly, this meta-analysis only focused on papers published in English
language, missing some eligible studies which were unpublished or reported in other languages. Furthermore, many eligible studies included in this meta-analysis didn't consider the potential gene–gene interactions and environmental factors. Undoubtedly, these limitations may affect our final conclusions. In conclusion, this meta-analysis suggested that the VDR gene FokI polymorphism may be associated with elevated DN risk in diabetic patients. Since potential biases and confounders could not be ruled out completely in this meta-analysis, future larger scale epidemiological investigation of this topic should be conducted to confirm or refute our findings. Conflict of interest No competing interests exist. Acknowledgments This work was supported by grants from the National Natural Science Foundation of China (30772207, 81102260), the Natural Science Foundation of Hubei Province (2011CDB207) and the Fundamental Research Funds for the Central Universities (2012QN190). We thank all our colleagues working in the Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China. References Abhary, S., Hewitt, A.W., Burdon, K.P., Craig, J.E., 2009. A systematic meta-analysis of genetic association studies for diabetic retinopathy. Diabetes 58, 2137–2147. Al-Daghri, N.M., Al-Attas, O., Alokail, M.S., Alkharfy, K.M., Draz, H.M., Agliardi, C., Mohammed, A.K., Guerini, F.R., Clerici, M., 2012. Vitamin D receptor gene polymorphisms and HLA DRB1*04 cosegregation in Saudi type 2 diabetes patients. J. Immunol. 188, 1325–1332. Aterini, S., Pacini, S., Amato, M., Ruggiero, M., 2000. Vitamin D receptor gene polymorphism and diabetes mellitus prevalence in hemodialysis patients. Nephron 84, 186. Basit, S., 2013. Vitamin D in health and disease: a literature review. Br. J. Biomed. Sci. 70, 161–172. Bucan, K., Ivanisevic, M., Zemunik, T., Boraska, V., Skrabic, V., Vatavuk, Z., Galetovic, D., Znaor, L., 2009. Retinopathy and nephropathy in type 1 diabetic patients—association with polymorphisms of vitamin D-receptor, TNF, Neuro-D and IL-1 receptor 1 genes. Coll. Anthropol. 33 (Suppl. 2), 99–105. Cronin, S.C., 2010. The dual vitamin D pathways: considerations for adequate supplementation. Nephrol. Nurs. J. 37, 19–26 (36; quiz 27–8). Cyganek, K., Mirkiewicz-Sieradzka, B., Malecki, M.T., Wolkow, P., Skupien, J., Bobrek, J., Czogala, M., Klupa, T., Sieradzki, J., 2006. Clinical risk factors and the role of VDR gene polymorphisms in diabetic retinopathy in Polish type 2 diabetes patients. Acta Diabetol. 43, 114–119.
10
Z. Liu et al. / Gene 546 (2014) 6–10
Ding, J., Wong, T.Y., 2012. Current epidemiology of diabetic retinopathy and diabetic macular edema. Curr. Diab. Rep. 12, 346–354. Fernandez-Juarez, G., Luno, J., Barrio, V., de Vinuesa, S.G., Praga, M., Goicoechea, M., Lahera, V., Casas, L., Oliva, J., 2013. 25 (OH) vitamin D levels and renal disease progression in patients with type 2 diabetic nephropathy and blockade of the renin–angiotensin system. Clin. J. Am. Soc. Nephrol. 8, 1870–1876. Fong, D.S., Aiello, L.P., Ferris III, F.L., Klein, R., 2004. Diabetic retinopathy. Diabetes Care 27, 2540–2553. Gray, S.P., Cooper, M.E., 2011. Diabetic nephropathy in 2010: alleviating the burden of diabetic nephropathy. Nat. Rev. Nephrol. 7, 71–73. Heaney, R.P., 2008. Vitamin D in health and disease. Clin. J. Am. Soc. Nephrol. 3, 1535–1541. Jurutka, P.W., Remus, L.S., Whitfield, G.K., Thompson, P.D., Hsieh, J.C., Zitzer, H., Tavakkoli, P., Galligan, M.A., Dang, H.T., Haussler, C.A., Haussler, M.R., 2000. The polymorphic N terminus in human vitamin D receptor isoforms influences transcriptional activity by modulating interaction with transcription factor IIB. Mol. Endocrinol. 14, 401–420. Lee, E.T., Keen, H., Bennett, P.H., Fuller, J.H., Lu, M., 2001. Follow-up of the WHO Multinational Study of Vascular Disease in Diabetes: general description and morbidity. Diabetologia 44 (Suppl. 2), S3–S13. Li, L., Wu, B., Liu, J.Y., Yang, L.B., 2013. Vitamin D receptor gene polymorphisms and type 2 diabetes: a meta-analysis. Arch. Med. Res. 44, 235–241. Martin, R.J., McKnight, A.J., Patterson, C.C., Sadlier, D.M., Maxwell, A.P., 2010. A rare haplotype of the vitamin D receptor gene is protective against diabetic nephropathy. Nephrol. Dial. Transplant. 25, 497–503. Nakagawa, T., Tanabe, K., Croker, B.P., Johnson, R.J., Grant, M.B., Kosugi, T., Li, Q., 2011. Endothelial dysfunction as a potential contributor in diabetic nephropathy. Nat. Rev. Nephrol. 7, 36–44. Nosratabadi, R., Arababadi, M.K., Salehabad, V.A., Shamsizadeh, A., Mahmoodi, M., Sayadi, A.R., Kennedy, D., 2010. Polymorphisms within exon 9 but not intron 8 of the vitamin D receptor are associated with the nephropathic complication of type-2 diabetes. Int. J. Immunogenet. 37, 493–497. Reis, A.F., Hauache, O.M., Velho, G., 2005. Vitamin D endocrine system and the genetic susceptibility to diabetes, obesity and vascular disease. A review of evidence. Diabetes Metab. 31, 318–325. Riek, A.E., Oh, J., Bernal-Mizrachi, C., 2013. 1,25(OH)2 vitamin D suppresses macrophage migration and reverses atherogenic cholesterol metabolism in type 2 diabetic patients. J. Steroid Biochem. Mol. Biol. 136, 309–312. Rosenson, R.S., Fioretto, P., Dodson, P.M., 2011. Does microvascular disease predict macrovascular events in type 2 diabetes? Atherosclerosis 218, 13–18. Su, X., Chen, X., Liu, L., Chang, X., Yu, X., Sun, K., 2013. Intracellular adhesion molecule-1 K469E gene polymorphism and risk of diabetic microvascular complications: a meta-analysis. PLoS One 8, e69940. Taverna, M.J., Sola, A., Guyot-Argenton, C., Pacher, N., Bruzzo, F., Slama, G., Reach, G., Selam, J.L., 2002. TaqI polymorphism of the vitamin D receptor and risk of severe diabetic retinopathy. Diabetologia 45, 436–442.
Taverna, M.J., Selam, J.L., Slama, G., 2005. Association between a protein polymorphism in the start codon of the vitamin D receptor gene and severe diabetic retinopathy in C-peptide-negative type 1 diabetes. J. Clin. Endocrinol. Metab. 90, 4803–4808. Thorand, B., Zierer, A., Huth, C., Linseisen, J., Meisinger, C., Roden, M., Peters, A., Koenig, W., Herder, C., 2011. Effect of serum 25-hydroxyvitamin D on risk for type 2 diabetes may be partially mediated by subclinical inflammation: results from the MONICA/KORA Augsburg study. Diabetes Care 34, 2320–2322. Tian, C., Fang, S., Du, X., Jia, C., 2011. Association of the C47T polymorphism in SOD2 with diabetes mellitus and diabetic microvascular complications: a meta-analysis. Diabetologia 54, 803–811. Tian, X.Q., Zhao, L.M., Ge, J.P., Zhang, Y., Xu, Y.C., 2014. Elevated urinary level of vitamin D-binding protein as a novel biomarker for diabetic nephropathy. Exp. Ther. Med. 7, 411–416. Uitterlinden, A.G., Fang, Y., Van Meurs, J.B., Pols, H.A., Van Leeuwen, J.P., 2004a. Genetics and biology of vitamin D receptor polymorphisms. Gene 338, 143–156. Uitterlinden, A.G., Fang, Y., van Meurs, J.B., van Leeuwen, H., Pols, H.A., 2004b. Vitamin D receptor gene polymorphisms in relation to Vitamin D related disease states. J. Steroid Biochem. Mol. Biol. 89–90, 187–193. Wang, Q., Xi, B., Reilly, K.H., Liu, M., Fu, M., 2012. Quantitative assessment of the associations between four polymorphisms (FokI, ApaI, BsmI, TaqI) of vitamin D receptor gene and risk of diabetes mellitus. Mol. Biol. Rep. 39, 9405–9414. Wu, A.Y., Kong, N.C., de Leon, F.A., Pan, C.Y., Tai, T.Y., Yeung, V.T., Yoo, S.J., Rouillon, A., Weir, M.R., 2005. An alarmingly high prevalence of diabetic nephropathy in Asian type 2 diabetic patients: the MicroAlbuminuria Prevalence (MAP) study. Diabetologia 48, 17–26. Yau, J.W., Rogers, S.L., Kawasaki, R., Lamoureux, E.L., Kowalski, J.W., Bek, T., Chen, S.J., Dekker, J.M., Fletcher, A., Grauslund, J., Haffner, S., Hamman, R.F., Ikram, M.K., Kayama, T., Klein, B.E., Klein, R., Krishnaiah, S., Mayurasakorn, K., O'Hare, J.P., Orchard, T.J., Porta, M., Rema, M., Roy, M.S., Sharma, T., Shaw, J., Taylor, H., Tielsch, J. M., Varma, R., Wang, J.J., Wang, N., West, S., Xu, L., Yasuda, M., Zhang, X., Mitchell, P., Wong, T.Y., 2012. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care 35, 556–564. Zhang, X., Saaddine, J.B., Chou, C.F., Cotch, M.F., Cheng, Y.J., Geiss, L.S., Gregg, E.W., Albright, A.L., Klein, B.E., Klein, R., 2010. Prevalence of diabetic retinopathy in the United States, 2005–2008. JAMA 304, 649–656. Zhang, H., Wang, J., Yi, B., Zhao, Y., Liu, Y., Zhang, K., Cai, X., Sun, J., Huang, L., Liao, Q., 2012a. BsmI polymorphisms in vitamin D receptor gene are associated with diabetic nephropathy in type 2 diabetes in the Han Chinese population. Gene 495, 183–188. Zhang, H., Zhu, S., Chen, J., Tang, Y., Hu, H., Mohan, V., Venkatesan, R., Wang, J., Chen, H., 2012b. Peroxisome proliferator-activated receptor gamma polymorphism Pro12Ala Is associated with nephropathy in type 2 diabetes: evidence from meta-analysis of 18 studies. Diabetes Care 35, 1388–1393. Zhang, J., Li, W., Liu, J., Wu, W., Ouyang, H., Zhang, Q., Wang, Y., Liu, L., Yang, R., Liu, X., Meng, Q., Lu, J., 2012c. Polymorphisms in the vitamin D receptor gene and type 1 diabetes mellitus risk: an update by meta-analysis. Mol. Cell. Endocrinol. 355, 135–142.
Contents lists available at ScienceDirect
Gene journal homepage: www.elsevier.com/locate/gene
Associations study of vitamin D receptor gene polymorphisms with diabetic microvascular complications: a meta-analysis Zhelong Liu a,1, Lei Liu b,1, Xi Chen a, Wentao He a, Xuefeng Yu a,⁎ a b
Division of Endocrinology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, China Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
a r t i c l e
i n f o
Article history: Received 5 March 2014 Received in revised form 18 May 2014 Accepted 22 May 2014 Available online 24 May 2014 Keywords: Vitamin D receptor Diabetic microvascular complications Meta-analysis
a b s t r a c t Background: Emerging evidence from preclinical and clinical studies has shown that vitamin D plays an important role in the pathogenesis of diabetic microvascular complications (DMI). Several potentially functional polymorphisms (ApaI, BsmI, FokI and TaqI) of vitamin D receptor (VDR) gene have been implicated in DMI risk, but individually published studies showed inconclusive results. The aim of this study was to quantitatively summarize the association between VDR polymorphisms and DMI risk. Methods: We searched all the publications about the associations mentioned as above from PubMed and ISI database updated in December 2013. Meta-analysis of the overall odds ratios (ORs) with 95% confidence intervals (CIs) was calculated with the fixed or random effect model. Results: Eight studies involving 2734 subjects were included. Allelic and genotypic comparisons between cases and controls were evaluated. Overall analysis suggests that no significant association was observed among the ApaI, BsmI, FokI and TaqI variants and DMI risk in diabetic patients (all P values N 0.05). In the stratified analysis, significant association was observed with diabetic nephropathy (DN) for VDR gene FokI polymorphism under a dominant model (OR 1.35, 95% CI 1.05–1.74, P = 0.02) in Caucasians. Conclusions: This meta-analysis indicated that the FokI polymorphism in VDR gene might affect individual susceptibility to DN in Caucasians. Further investigations are needed to confirm our results. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Diabetes mellitus is one of the most common chronic disorders all over the world with the condition of hyperglycemia, and its prevalence is still progressively increasing as a consequence of an aging population and changes in lifestyle. Data from prospective and cross-sectional studies consistently points to the fact that diabetic patients are more likely to develop macro- as well as microvascular conditions (Lee et al., 2001; Rosenson et al., 2011). Diabetic microvascular complications (DMI) involve the smallest blood vessels, the capillary and the pre-capillary arteries, with the profile of thickening of the capillary basement membrane, mainly in the kidneys and retina. Therefore, microvascular complications from diabetes are common and include retinopathy leading to various degrees of visual impairment blindness; and nephropathy characterized by proteinuria ultimately leading to end stage renal disease Abbreviations: DMI, diabetic microvascular complications; VDR, vitamin D receptor; OR, odds ratios; CI, confidence intervals; DR, diabetic retinopathy; DN, diabetic nephropathy; SNP, single nucleotide polymorphism; HWE, Hardy–Weinberg equilibrium. ⁎ Corresponding author at: Division of Endocrinology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Ave, Wuhan 430030, China. E-mail address: [email protected] (X. Yu). 1 These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.gene.2014.05.052 0378-1119/© 2014 Elsevier B.V. All rights reserved.
(Fong et al., 2004; Wu et al., 2005). It is well known that DMI have become major causes of chronic kidney disease and blindness, which reduce the quality of the life of patients, incur heavy burdens to the health care systems, and increase diabetic mortality (Gray and Cooper, 2011; Zhang et al., 2010). Although the precise mechanism has not been clearly elucidated yet, DMI can be partly attributed to factors such as the type or duration of diabetes, the degree of glycemic and blood pressure control and the age of the patient (Ding and Wong, 2012; Nakagawa et al., 2011; Yau et al., 2012). Recently, genetic predispositions have also been highlighted to play important roles in the mechanisms underlying the development and progression of DMI (Abhary et al., 2009; Su et al., 2013; Tian et al., 2011; Zhang et al., 2012b). Therefore, finding a genetic marker for this disease would be important in indentifying patients who could benefit from preventive treatment. Vitamin D (VD), a secosteroid hormone, is acquired and synthesized from the diet and ultraviolet radiation. Besides its calciotropic function, VD has potent non-classical properties, including immunomodulatory, antiinflammatory, antioxidant, antiangiogenic, and antiproliferative properties (Basit, 2013; Heaney, 2008). It is well known that the interaction of VD with target tissues is mediated by the VD receptor (VDR), a member of the steroid/thyroid hormone receptor family with the function of a transcriptional activator of many genes (Cronin, 2010).
Z. Liu et al. / Gene 546 (2014) 6–10
There are accumulating evidences to suggest that the vitamin D endocrine system is involved in a wide variety of biological processes including diabetes, and diabetic microvascular complications (Al-Daghri et al., 2012; Fernandez-Juarez et al., 2013; Riek et al., 2013; Thorand et al., 2011; Tian et al., 2014). The association of vitamin D receptor (VDR) gene polymorphisms with diabetes and DMI has recently become a hot topic for research (Li et al., 2013; Reis et al., 2005; Wang et al., 2012; J. Zhang et al., 2012). VDR gene is located on chromosome 12q13.1, consists of 11 exons and has an extensive promoter region capable of generating multiple tissue-specific transcripts. There are four single nucleotide polymorphisms (SNPs) in the VDR gene, FokI (rs10735810), BsmI (rs1544410), ApaI (rs7975232) and TaqI (rs731236), that have been studied most frequently. The BsmI, ApaI, and TaqI are located at the 3 untranslated region of the gene, which is involved in regulation of gene expression, especially through the modulation of mRNA stability (Uitterlinden et al., 2004b). Another polymorphism, FokI, is a T-to-C substitution at exon 2, abolishing the first translation initiation site and resulting in a peptide lacking three amino acids, which influences the transcriptional activity of VDR (Uitterlinden et al., 2004a). Considering the past establishment of the important functions of VDR gene polymorphisms, many studies have explored the association between VDR gene functional polymorphisms and DMI risk (Aterini et al., 2000; Bucan et al., 2009; Cyganek et al., 2006; Martin et al., 2010; Nosratabadi et al., 2010; Taverna et al., 2002, 2005; Zhang et al., 2012a). However, individual studies yielded inconsistent and even conflicting findings. It is still inconclusive whether VDR gene polymorphisms would be causal in determining DMI susceptibility. To shed light on these contradictory results and to get a more precise evaluation of this association, we performed a meta-analysis of eight published case–control studies covering 2734 participants. 2. Material and methods 2.1. Search strategy We searched the literature databases (PubMed and ISI Web of Science) for all available articles on the association between VDR and the DMI. The search strategy to identify all possible studies involved the use of the following key words: “VDR”, “diabetic retinopathy (DR)” or “diabetic nephropathy (DN)”, “mutation” or “single nucleotide polymorphism (SNP)” or “variant”. Both type 1 and type 2 diabetic patients were enrolled in our study. Additional studies not captured by our database searches were identified by reviewing the reference lists of retrieved articles. If more than one article were published using the
7
same case series, only the study with largest sample size was included. The literature search was updated in December, 2013. 2.2. Selection criteria The studies included in the meta-analysis must meet all the following inclusion criteria: (1) evaluated the associations of polymorphisms in the VDR gene, ApaI, BsmI, FokI or TaqI, with the risk of DN and/or DR; (2) case–control studies or cohort studies; (3) available genotype distribution or allele frequencies of cases and controls that can provide sufficient data for calculation; and (4) published in English. 2.3. Data extraction The following information was extracted independently by two authors from each study:(1) name of first author; (2) year of publication; (3) country of origin; (4) ethnicity of the study population; (5) genotype distribution or allele frequencies; and (6) sample sizes of cases and controls and the SNPs included (Table 1). The two authors independently assessed the articles for compliance with the inclusion/exclusion criteria, resolved disagreements and reached a consistent decision. 2.4. Statistical analysis The combined odds ratios (ORs) together with their corresponding 95% confidence intervals (95% CIs) were utilized to calculate and assess the strength of association between the polymorphisms of VDR (ApaI, BsmI, FokI and TaqI) and DMI risk. The dominant, recessive and additive genetic models were all used in this meta-analysis. The significance of pooled OR was determined by Z test (P b 0.05 was considered statistically significant). The Chi-square test was used to determine if the observed frequencies of genotypes in controls conformed to Hardy– Weinberg equilibrium (HWE). The I2 of Higgins and Thompson was used to test the heterogeneity between the studies. Heterogeneity assumption was examined by the Chi-square based on Q-test. The pooled OR estimation of each study was calculated with a random-effect model using the DerSimonian and Laird method (D + L) when P value was no more than 0.1, otherwise with a fixed-effect model using the Mantel– Haenszel (M–H) method. Publication bias was evaluated through the Begg's test, the Egger's Asymmetry test, and visual inspection of funnel plots, in which the standard error was plotted against the Log(OR) to form a simple scatter plot. All of the statistical analyses were performed using STATA version 11.0 software (Stata Corporation, College Station, TX, USA). All the P values were for a two-tailed test and P b 0.05 was considered as statistically significant.
Table 1 Characteristics of the studies included in the meta-analysis. Author
Year
Population
Taverna et al.
2002
French
Taverna et al.
2005
French
Cyganek et al.
2006
Polish
Bucan et al.
2009
Croatian
Martin et al.
2009
Irish
Nosratabadi et al.
2010
Iranian
Zhang et al.
2012
Chinese
Vedralová et al.
2012
Czech
Sample
Case Control Case Control Case Control Case Control Case Control Case Control Case Control Case Control
Genotypes (N) ApaI
BsmI
FokI
AA/Aa/aa
BB/Bb/bb
FF/Ff/ff
TaqI TT/Tt/tt 27/58/16 42/44/13
17/39/29 39/100/43
185/323/147 200/322/152 27/64/9 28/63/9 19/89/74 11/65/46
10/36/39 21/84/77 3/18/12 11/24/26 106/321/228 111/325/238
38/65/23 57/56/15 21/43/21 51/93/48 10/15/8 16/33/12 248/323/84 262/311/101
3/57/122 0/26/96 63/58/11 57/85/28
40/38/7 81/82/19 7/14/12 11/26/24 103/327/225 98/327/249 36/55/9
8
Z. Liu et al. / Gene 546 (2014) 6–10
Fig. 1. Flow diagram of included/excluded studies.
3. Results 3.1. Characteristics of the studies Fig. 1 describes the flow of candidate and eligible papers. Our initial search of the literature yielded 125 publications. After reading the titles and abstracts, 11 potential studies were included for full-text view. After reading full texts, three studies were excluded for not reporting the usable data. Finally, a total of 8 case–control studies in 8 articles were identified met our inclusion criteria, including 1394 DMI patients and 1340 diabetic controls. The main characteristics of these selected studies were summarized in Table 1, including first author, published year, original country and genotype distribution. 3.2. Quantitative data synthesis It has been shown in Table 2 that the risk for DMI conferred by VDR gene polymorphisms in the overall 8 studies did not reach the significant difference (all P values N0.05). We then conducted the analyses excluding the studies not in HWE. However, the significance of pooled OR under all genetic models was not influenced after excluding the study (data not shown). With regard to the specific type of DMI, we also conducted the subgroup analyses stratified by DN or DR. The results showed that the FokI polymorphism was found to be significantly associated with an increased risk of DN in a dominant model (Fig. 2) (OR = 1.35, 95% CI Table 2 Pooled measures on the relation of VDR gene polymorphisms with DMI. Polymorphisms
Inherited model
Number of cases/controls
Pooled OR (95% CI)
I2 (%)
ApaI
Dominant Recessive Additive Dominant Recessive Additive Dominant Recessive Additive Dominant Recessive Additive
1022/1078 1022/1078 1022/1078 955/1039 955/1039 955/1039 1031/1225 1031/1225 1031/1225 974/1116 974/1116 974/1116
0.95 (0.78, 1.16) 1.09 (0.89, 1.34) 0.95 (0.84, 1.08) 0.97 (0.75, 1.27) 0.91 (0.76, 1.10) 1.04 (0.91, 1.19) 1.06 (0.72, 1.56)a 1.02 (0.85, 1.23) 1.01 (0.78, 1.31)a 0.93 (0.76, 1.14) 0.99 (0.80, 1.24) 1.03 (0.91, 1.17)
0.0% 0.0% 0.0% 0.0% 44.5% 37.6% 60.3% 28.9% 64.3% 0.0% 19.8% 0.0%
BsmI
FokI
TaqI
a
OR was calculated in random-effects model.
1.05–1.74, P = 0.02). Interestingly, all of these studies were performed in Caucasians and the heterogeneity of the subgroup disappeared (I2 = 8.6%). The remaining results from these subgroup analyses were not significant (all P values N0.05). In contrast, in the subgroup of DR, no significant association with the VDR gene polymorphisms was found in all genetic models (all P values N0.05). On subgroup analysis by ethnicity, no evidence of significant association was found in all genetic models for DMI (all P values N0.05). 3.3. Publication bias Publication bias was analyzed by using the Begg's funnel plots and Egger's test. The shape of the funnel plots was symmetrical, suggesting that there was no evidence of publication bias among the studies (data not shown). We further analyzed the publication bias of each metaanalysis of these four different SNPs by Egger's test. All P values were higher than 0.05 and no publication bias was detected. The results indicated a lack of publication bias. 4. Discussion Unraveling the genes that contribute to the pathogenic risk of DMI has been one of the major foci of basic research in DMI over the past few decades. A large number of putative genes and genetic variants have been reported to be moderately associated with higher risk of DMI (Abhary et al., 2009; Zhang et al., 2012b). However, due to the high level of heterogeneity of this disease, genetic studies have therefore given very diverse results. Furthermore, studies with subjects exposed in different environmental factors may yield different results. Lack of replication has long been a big challenge in genetic association studies. Also, because of modest sample size, different populations and lifestyles, these single studies had less power to provide us with reliable and comprehensive conclusions. Meta-analysis, which has generally been used in investigating the association of genetic variation and disease, has the benefit to overcome these limitations by increasing the sample size and may generate more robust data. Therefore, to better assess the association between DMI risk and VDR gene polymorphism, we carried out a comprehensive genetic meta-analysis. In this meta-analysis, we analyzed the VDR gene functional polymorphisms (FokI, BsmI, ApaI and TaqI) as potential genetic markers for DMI. Nevertheless, the results of this meta-analysis suggest that none of these polymorphisms was significantly associated with DMI
Z. Liu et al. / Gene 546 (2014) 6–10
9
Fig. 2. Forest plot of the risk of DN associated with the VDR gene FokI polymorphism.
risk in diabetic patients (all P values N0.05). Of note, in the stratified analysis, significant association was observed with DN for VDR gene FokI polymorphism under a dominant model (OR = 1.35, 95% CI 1.05–1.74, P = 0.02). However, we did not find any correlation in other subgroup. To the best of our knowledge, this is the first metaanalysis assessing the association between VDR gene polymorphisms and DMI. To date, the exact biological mechanism underlying the effects of the VDR gene FokI polymorphism on DN remains uncertain. The FokI variant can be detected by the presence or absence of a FokI restriction site within the ATG transcriptional start site of the VDR gene. Additionally, the FokI polymorphism is the only known locus affecting the structure of the VDR protein produced. The gene is transcribed into normal length when the restriction site (f allele) is present. Conversely, the gene is transcribed and into shortened length when the restriction site (f allele) is absent. In turn, the f allele encodes a 427 amino acid protein while the F allele encodes a 424 amino acid protein (Uitterlinden et al., 2004a). Previous study had demonstrated that the longer VDR protein appears to possess decreased transcriptional activity, leading to lower activation of target cells (Jurutka et al., 2000). However, due to complicated interactions of environmental factors and multiple genes, the precise role of VDR gene FokI polymorphism in DR remains elusive. Additional future studies should be performed to focus on the function of the VDR gene FokI polymorphism. Our meta-analysis did not find any association of the other three polymorphisms (BsmI, ApaI and TaqI) with an increased DMI risk in overall and subgroup analysis. It is interesting to note that significant linkage disequilibrium was found among the TaqI, ApaI and BsmI polymorphisms (Li et al., 2013). Therefore, the combined analysis of these three variants may be powerful enough to identify whether individuals are susceptible to DMI. Nevertheless, because no sufficient information could be extracted from the original papers, we could not perform the pooled analysis of haplotypes. For better interpreting of the results, several potential limitations of this meta-analysis should be acknowledged. Firstly, as no correction for multiple testing was performed in this meta-analysis, false positive results may have been induced in some fraction because of the application of multiple statistical tests, which would increase the probability of type I errors. Secondly, the overall outcomes were based on individual unadjusted genotype data, while a more precise evaluation should be made by adjusting other potentially suspected factors including age, sex, and environmental factors. Thirdly, the numbers of published studies were still not sufficiently large for the analysis of some particular DMI types. Fourthly, this meta-analysis only focused on papers published in English
language, missing some eligible studies which were unpublished or reported in other languages. Furthermore, many eligible studies included in this meta-analysis didn't consider the potential gene–gene interactions and environmental factors. Undoubtedly, these limitations may affect our final conclusions. In conclusion, this meta-analysis suggested that the VDR gene FokI polymorphism may be associated with elevated DN risk in diabetic patients. Since potential biases and confounders could not be ruled out completely in this meta-analysis, future larger scale epidemiological investigation of this topic should be conducted to confirm or refute our findings. Conflict of interest No competing interests exist. Acknowledgments This work was supported by grants from the National Natural Science Foundation of China (30772207, 81102260), the Natural Science Foundation of Hubei Province (2011CDB207) and the Fundamental Research Funds for the Central Universities (2012QN190). We thank all our colleagues working in the Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China. References Abhary, S., Hewitt, A.W., Burdon, K.P., Craig, J.E., 2009. A systematic meta-analysis of genetic association studies for diabetic retinopathy. Diabetes 58, 2137–2147. Al-Daghri, N.M., Al-Attas, O., Alokail, M.S., Alkharfy, K.M., Draz, H.M., Agliardi, C., Mohammed, A.K., Guerini, F.R., Clerici, M., 2012. Vitamin D receptor gene polymorphisms and HLA DRB1*04 cosegregation in Saudi type 2 diabetes patients. J. Immunol. 188, 1325–1332. Aterini, S., Pacini, S., Amato, M., Ruggiero, M., 2000. Vitamin D receptor gene polymorphism and diabetes mellitus prevalence in hemodialysis patients. Nephron 84, 186. Basit, S., 2013. Vitamin D in health and disease: a literature review. Br. J. Biomed. Sci. 70, 161–172. Bucan, K., Ivanisevic, M., Zemunik, T., Boraska, V., Skrabic, V., Vatavuk, Z., Galetovic, D., Znaor, L., 2009. Retinopathy and nephropathy in type 1 diabetic patients—association with polymorphisms of vitamin D-receptor, TNF, Neuro-D and IL-1 receptor 1 genes. Coll. Anthropol. 33 (Suppl. 2), 99–105. Cronin, S.C., 2010. The dual vitamin D pathways: considerations for adequate supplementation. Nephrol. Nurs. J. 37, 19–26 (36; quiz 27–8). Cyganek, K., Mirkiewicz-Sieradzka, B., Malecki, M.T., Wolkow, P., Skupien, J., Bobrek, J., Czogala, M., Klupa, T., Sieradzki, J., 2006. Clinical risk factors and the role of VDR gene polymorphisms in diabetic retinopathy in Polish type 2 diabetes patients. Acta Diabetol. 43, 114–119.
10
Z. Liu et al. / Gene 546 (2014) 6–10
Ding, J., Wong, T.Y., 2012. Current epidemiology of diabetic retinopathy and diabetic macular edema. Curr. Diab. Rep. 12, 346–354. Fernandez-Juarez, G., Luno, J., Barrio, V., de Vinuesa, S.G., Praga, M., Goicoechea, M., Lahera, V., Casas, L., Oliva, J., 2013. 25 (OH) vitamin D levels and renal disease progression in patients with type 2 diabetic nephropathy and blockade of the renin–angiotensin system. Clin. J. Am. Soc. Nephrol. 8, 1870–1876. Fong, D.S., Aiello, L.P., Ferris III, F.L., Klein, R., 2004. Diabetic retinopathy. Diabetes Care 27, 2540–2553. Gray, S.P., Cooper, M.E., 2011. Diabetic nephropathy in 2010: alleviating the burden of diabetic nephropathy. Nat. Rev. Nephrol. 7, 71–73. Heaney, R.P., 2008. Vitamin D in health and disease. Clin. J. Am. Soc. Nephrol. 3, 1535–1541. Jurutka, P.W., Remus, L.S., Whitfield, G.K., Thompson, P.D., Hsieh, J.C., Zitzer, H., Tavakkoli, P., Galligan, M.A., Dang, H.T., Haussler, C.A., Haussler, M.R., 2000. The polymorphic N terminus in human vitamin D receptor isoforms influences transcriptional activity by modulating interaction with transcription factor IIB. Mol. Endocrinol. 14, 401–420. Lee, E.T., Keen, H., Bennett, P.H., Fuller, J.H., Lu, M., 2001. Follow-up of the WHO Multinational Study of Vascular Disease in Diabetes: general description and morbidity. Diabetologia 44 (Suppl. 2), S3–S13. Li, L., Wu, B., Liu, J.Y., Yang, L.B., 2013. Vitamin D receptor gene polymorphisms and type 2 diabetes: a meta-analysis. Arch. Med. Res. 44, 235–241. Martin, R.J., McKnight, A.J., Patterson, C.C., Sadlier, D.M., Maxwell, A.P., 2010. A rare haplotype of the vitamin D receptor gene is protective against diabetic nephropathy. Nephrol. Dial. Transplant. 25, 497–503. Nakagawa, T., Tanabe, K., Croker, B.P., Johnson, R.J., Grant, M.B., Kosugi, T., Li, Q., 2011. Endothelial dysfunction as a potential contributor in diabetic nephropathy. Nat. Rev. Nephrol. 7, 36–44. Nosratabadi, R., Arababadi, M.K., Salehabad, V.A., Shamsizadeh, A., Mahmoodi, M., Sayadi, A.R., Kennedy, D., 2010. Polymorphisms within exon 9 but not intron 8 of the vitamin D receptor are associated with the nephropathic complication of type-2 diabetes. Int. J. Immunogenet. 37, 493–497. Reis, A.F., Hauache, O.M., Velho, G., 2005. Vitamin D endocrine system and the genetic susceptibility to diabetes, obesity and vascular disease. A review of evidence. Diabetes Metab. 31, 318–325. Riek, A.E., Oh, J., Bernal-Mizrachi, C., 2013. 1,25(OH)2 vitamin D suppresses macrophage migration and reverses atherogenic cholesterol metabolism in type 2 diabetic patients. J. Steroid Biochem. Mol. Biol. 136, 309–312. Rosenson, R.S., Fioretto, P., Dodson, P.M., 2011. Does microvascular disease predict macrovascular events in type 2 diabetes? Atherosclerosis 218, 13–18. Su, X., Chen, X., Liu, L., Chang, X., Yu, X., Sun, K., 2013. Intracellular adhesion molecule-1 K469E gene polymorphism and risk of diabetic microvascular complications: a meta-analysis. PLoS One 8, e69940. Taverna, M.J., Sola, A., Guyot-Argenton, C., Pacher, N., Bruzzo, F., Slama, G., Reach, G., Selam, J.L., 2002. TaqI polymorphism of the vitamin D receptor and risk of severe diabetic retinopathy. Diabetologia 45, 436–442.
Taverna, M.J., Selam, J.L., Slama, G., 2005. Association between a protein polymorphism in the start codon of the vitamin D receptor gene and severe diabetic retinopathy in C-peptide-negative type 1 diabetes. J. Clin. Endocrinol. Metab. 90, 4803–4808. Thorand, B., Zierer, A., Huth, C., Linseisen, J., Meisinger, C., Roden, M., Peters, A., Koenig, W., Herder, C., 2011. Effect of serum 25-hydroxyvitamin D on risk for type 2 diabetes may be partially mediated by subclinical inflammation: results from the MONICA/KORA Augsburg study. Diabetes Care 34, 2320–2322. Tian, C., Fang, S., Du, X., Jia, C., 2011. Association of the C47T polymorphism in SOD2 with diabetes mellitus and diabetic microvascular complications: a meta-analysis. Diabetologia 54, 803–811. Tian, X.Q., Zhao, L.M., Ge, J.P., Zhang, Y., Xu, Y.C., 2014. Elevated urinary level of vitamin D-binding protein as a novel biomarker for diabetic nephropathy. Exp. Ther. Med. 7, 411–416. Uitterlinden, A.G., Fang, Y., Van Meurs, J.B., Pols, H.A., Van Leeuwen, J.P., 2004a. Genetics and biology of vitamin D receptor polymorphisms. Gene 338, 143–156. Uitterlinden, A.G., Fang, Y., van Meurs, J.B., van Leeuwen, H., Pols, H.A., 2004b. Vitamin D receptor gene polymorphisms in relation to Vitamin D related disease states. J. Steroid Biochem. Mol. Biol. 89–90, 187–193. Wang, Q., Xi, B., Reilly, K.H., Liu, M., Fu, M., 2012. Quantitative assessment of the associations between four polymorphisms (FokI, ApaI, BsmI, TaqI) of vitamin D receptor gene and risk of diabetes mellitus. Mol. Biol. Rep. 39, 9405–9414. Wu, A.Y., Kong, N.C., de Leon, F.A., Pan, C.Y., Tai, T.Y., Yeung, V.T., Yoo, S.J., Rouillon, A., Weir, M.R., 2005. An alarmingly high prevalence of diabetic nephropathy in Asian type 2 diabetic patients: the MicroAlbuminuria Prevalence (MAP) study. Diabetologia 48, 17–26. Yau, J.W., Rogers, S.L., Kawasaki, R., Lamoureux, E.L., Kowalski, J.W., Bek, T., Chen, S.J., Dekker, J.M., Fletcher, A., Grauslund, J., Haffner, S., Hamman, R.F., Ikram, M.K., Kayama, T., Klein, B.E., Klein, R., Krishnaiah, S., Mayurasakorn, K., O'Hare, J.P., Orchard, T.J., Porta, M., Rema, M., Roy, M.S., Sharma, T., Shaw, J., Taylor, H., Tielsch, J. M., Varma, R., Wang, J.J., Wang, N., West, S., Xu, L., Yasuda, M., Zhang, X., Mitchell, P., Wong, T.Y., 2012. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care 35, 556–564. Zhang, X., Saaddine, J.B., Chou, C.F., Cotch, M.F., Cheng, Y.J., Geiss, L.S., Gregg, E.W., Albright, A.L., Klein, B.E., Klein, R., 2010. Prevalence of diabetic retinopathy in the United States, 2005–2008. JAMA 304, 649–656. Zhang, H., Wang, J., Yi, B., Zhao, Y., Liu, Y., Zhang, K., Cai, X., Sun, J., Huang, L., Liao, Q., 2012a. BsmI polymorphisms in vitamin D receptor gene are associated with diabetic nephropathy in type 2 diabetes in the Han Chinese population. Gene 495, 183–188. Zhang, H., Zhu, S., Chen, J., Tang, Y., Hu, H., Mohan, V., Venkatesan, R., Wang, J., Chen, H., 2012b. Peroxisome proliferator-activated receptor gamma polymorphism Pro12Ala Is associated with nephropathy in type 2 diabetes: evidence from meta-analysis of 18 studies. Diabetes Care 35, 1388–1393. Zhang, J., Li, W., Liu, J., Wu, W., Ouyang, H., Zhang, Q., Wang, Y., Liu, L., Yang, R., Liu, X., Meng, Q., Lu, J., 2012c. Polymorphisms in the vitamin D receptor gene and type 1 diabetes mellitus risk: an update by meta-analysis. Mol. Cell. Endocrinol. 355, 135–142.