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Vitamin D and vitamin D receptor (VDR) have been postulated as environmental and genetic factors in neurodegeneration disorders including multiple sclerosis (MS), Alzheimer disease (AD), and recently Parkinson disease (PD). Given the sparse data on PD, we conducted a two-stage study to evaluate the genetic effects of VDR in PD. In the discovery stage, 30 tagSNPs in VDR were tested for association with risk as a discrete trait and age-at-onset (AAO) as a quantitative trait in 770 Caucasian PD families. In the validation stage, 18 VDR SNPs were tested in an independent Caucasian cohort (267 cases and 267 controls) constructed from a genome-wide association study (GWAS). In the discovery dataset, SNPs in the 5′ end of VDR were associated with both risk and AAO with more significant evidence of association with AAO (P= 0.0008–0.02). These 5′ SNPs were also associated with AD in another study. In the validation dataset, SNPs in the 3′ end of VDR were associated with AAO (P= 0.003) but not risk. The 3′ end SNP has been associated with both MS and AD in previous studies. Our findings suggest VDR as a potential susceptibility gene and support an essential role of vitamin D in PD.
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Parkinson disease (PD) is a progressive neurodegenerative disorder that affects roughly 1.5 million people in the US. The Mendelian forms of PD comprise <10% of all cases and involve well-defined exonic mutations in the genes PARK2, SNCA, PARK7, PINK1, ATP13A2, and LRRK2. The majority of PD cases result from complex interplay between environmental and genetic factors (Thomas & Beal, 2007). Several genetic risk factors and gene–environment interactions for PD have been reported by us and others (Li et al., 2003; van der Walt et al., 2004; Oliveira et al., 2005; Hancock et al., 2006; Maraganore et al., 2006; Mizuta et al., 2006; Winkler et al., 2007; Hancock et al., 2008; McCulloch et al., 2008; Mizuta et al., 2008). Vitamin D level is an environmentally modifiable factor as it is largely determined by diet and sunlight exposure. The effects of vitamin D and genetic variants in the vitamin D receptor (VDR) gene have recently gained interest in PD and neurodegenerative research in general (Evatt et al., 2008; Smolders et al., 2009; Knekt et al., 2010). It was first noted in Japan that PD patients had lower serum vitamin D levels and higher prevalence of vitamin D deficiency than their age-matched controls (Sato et al., 2005). This observation was recently confirmed in a European Caucasian population (Evatt et al., 2008). In a longitudinal study of more than 3000 participants in Finland, higher serum vitamin D level was associated with reduced risk for PD: people in the highest quartile had one-third of the risk compared to people in the lowest quartile (Knekt et al., 2010). The serum vitamin D level was also negatively correlated with PD severity as measured by Hoehn and Yahr stages and motor symptom as measured by the motor part of the Unified Parkinson's Disease Rating Scale III (UPDRS III) (Sato et al., 1997, 2005).
To exert its biological functions, vitamin D is first converted to the active metabolite 1,25-dihydroxy vitamin D3. Upon binding to 1,25-dihydroxy vitamin D3, VDR is activated and interacts with vitamin D responsive elements in the promoters of vitamin D target genes to regulate their expression (Garcion et al., 2002). VDR is the primary mediator of vitamin D's biological actions. VDR and 1α-hydroxylase, an essential enzyme to convert vitamin D to 1,25-dihydroxy vitamin D3, are expressed in human brain. Within the brain, the highest expression was found in the hypothalamus and in the large neurons (likely to be the dopaminergic neurons) of the substantia nigra (SN) (Eyles et al., 2005). The expression pattern of VDR and 1α-hydroxylase supports an important role of vitamin D in the etiology of PD. In addition, VDR null mice have impaired locomotor activity (Burne et al., 2005). Recently, the expression level of VDR mRNA was identified as a potential blood biomarker for PD (Scherzer et al., 2007).
Genetic studies on VDR polymorphisms also have suggested involvement of VDR with several neurodegenerative diseases, including multiple sclerosis (MS) and Alzheimer disease (AD). Motivated by the striking correlation between MS incidence rates and latitude, vitamin D status and VDR polymorphisms have been an active research topic in MS. SNPs in VDR have been associated with both MS risk and degree of disability after disease onset (Smolders et al., 2009). In AD, one candidate gene study reported a significant association at the 3′ end of VDR in a Turkish population (Gezen-Ak et al., 2007). A recent genome-wide association study (GWAS) of late-onset AD has reported strong evidence for association in a cluster of SNPs near the 5′ end of VDR in a sample of non-Hispanic Caucasians. (Beecham et al., 2009). In PD, Kim et al. (2005) examined the BsmI polymorphism (rs1544410) in a Korean population and found that the b allele was over-represented in 85 PD patients compared to 231 controls. Given the growing body of evidence for vitamin D and VDR's involvement in several neurodegenerative disorders including PD, and the lack of any published study evaluating association between VDR and PD in Caucasians, we sought to thoroughly examine VDR polymorphisms in a large Caucasian sample of PD families and validate the association using publicly available GWAS data.
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The VDR gene has nine exons and multiple alternative first exons (Fig. 1). Thirty tagSNPs within the VDR exonic boundaries and the 5-kilobase (kb) flanking regions were genotyped to cover most of the common genetic variations surrounding VDR (Fig. 1). Using the SimpleM test, the effective number of independence tests was reduced from 30 SNPs to 24. One coding SNP in exon 9 (rs731236) is in perfect LD (r2= 1) with the BsmI polymorphism previously reported by Kim et al. (2005) Therefore, rs731236 was used as the surrogate for the BsmI polymorphism. LD between the 30 SNPs is shown in Figure 2.
Figure 1. Diagram of VDR gene structure with relative positions of genotyped SNPs. The VDR gene is located on the bottom strand of genomic DNA and therefore is displayed 3′ to 5′, left to right. Coding exons are shown as higher blocks while noncoding exons are shown as shorter blocks, introns are shown as straight lines, and the dotted line suggests alternative splicing of exons. Thirty tagSNPs were chosen and genotyped in the family dataset. The locations of them are displayed in the context of VDR gene structure. SNP shown in bold was the proxy marker for the most significant SNP (P= 0.003) in NINDS dataset using linear regression; underlined SNP was the proxy marker for the previously reported significant SNP in the Korean study; SNP shown in bold and underlined is the most significant SNP (P= 0.0008) in the family dataset using Monks–Kaplan analysis.
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Figure 2. Pairwise LD plot for examined VDR SNPs. Pairwise r2 was estimated in unrelated individuals with no PD and is displayed by gray-shaded square with the hundredths of r2 value inside (HaploView) (Barrett et al., 2005). The shades of gray are proportional to the r2 value with darker color representing higher r2 value.
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SNP associations with AAO as a quantitative trait (Table 1) and with risk as a discrete trait (Fig. 3) were evaluated using family-based association tests. The AAO analysis revealed strong evidence of association at several SNPs with the most significant association at rs4334089 (nominal P= 0.0008, corrected P= 0.02, Table 1). The risk analysis found marginal evidence for association at rs2853559 (nominal P= 0.02), which was not significant after multiple testing correction (Fig. 3). Given the strong effect of AAO, we further examined SNP association with risk in subsets with different AAO. Using AAO of 60 as the cutoff value, the overall family dataset was stratified into 459 earlier onset families and 311 later onset families. Five SNPs were significantly associated with PD risk in the earlier onset subset (nominal P < 0.05) but none in the later onset subset (Fig. 3). All five SNPs overlapped with the significant SNPs in AAO analysis including rs4434089. Further stratification using younger AAO (AAO < 40) did not reveal any significant results (data not shown), probably due to the small sample size (78 families with AAO < 40). The previously reported association with PD at BsmI polymorphism was not significant in any analysis as indicated by association tests at rs731236.
Table 1. Monks–Kaplan SNP association tests with PD AAO in the family dataset.
|SNP||Location (bp)||Minor allele frequency*||P values|
Figure 3. SNP association tests with PD risk as a discrete trait. Each bar represents an association test with PD risk in different datasets: overall (white), earlier onset (gray), and later onset (black). The dotted line depicts the P value of 0.05. The association tests were performed using APL. AAO of 60 was used to stratify the overall families (N= 770) into earlier (N= 459) and later (N= 311) onset family subsets.
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All significant SNPs in the family dataset are located in the 5′ end of the gene. The majority of them are located in intron 1A_1B and intron 1B_1C, between the alternative exon 1A, 1B, 1C that generate alternative splicing isoforms of VDR (Fig. 1). This cluster of SNPs is in moderate LD between each other (pairwise r2= 0.14–0.74 to rs4334089, Fig. 2). Haplotype analysis of these 5′ end SNPs did not define a haplotype that could explain the association better than single SNP analysis (data not shown).
Given the association between VDR and AAO in our family dataset, we further tested the association using the NINDS GWAS data deposited in dbGAP.
Eighteen SNPs in and around VDR were either genotyped or imputed in the NINDS dataset (N= 534). Sixteen of them overlapped with the SNPs studied in the family dataset, either by the SNP itself or by a tagSNP. The effective number of independence tests as estimated by SimpleM for the 18 SNPs is 15. In the NINDS dataset, three SNPs were significantly associated with AAO (Table 2) but none was associated with PD risk (data not shown). The strongest association was found at rs7968585 (nominal P= 0.003, corrected P= 0.045), which remained significant after correction for multiple testing in the NINDS dataset. None of the 5′ end SNPs or SNPs in LD with them was significant in the NINDS dataset.
Table 2. Linear regression-based SNP association tests with PD AAO in the NINDS GWAS dataset.
|SNP||Location (bp)||Beta||Lower 95% confidence interval||Upper 95% confidence interval||P value|
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We conducted a comprehensive genetic analysis of VDR in PD. Previous studies of VDR in general have focused mainly on four restriction fragment length polymorphisms (RFLPs): TaqI (rs731236), ApaI (rs7975232), BsmI (rs1544410), and FokI (rs10735810) (Niino et al., 2000; Partridge et al., 2004; Uitterlinden et al., 2004; Tajouri et al., 2005; Mamutse et al., 2008). Herein, we systematically chose tagSNPs that cover all common variants in and around VDR, including the four previously described RFLPs. We examined these SNPs in a large dataset of Udall PD families and validated the association in the NINDS GWAS case-control cohort. Since a genetic component for the age-dependent penetrance of PD has been demonstrated (Destefano et al., 2002; Li et al., 2002; Maher et al., 2002), we also analyzed SNP association with AAO in addition to risk. Evidence for association between PD AAO and VDR SNPs were found in both family dataset and case-control cohort.
The significant SNPs in the NINDS dataset are not in LD with the significant SNPs in the Udall family dataset, suggesting allelic heterogeneity, which is not unexpected for complex diseases (Horne et al., 2007; Schrauwen et al., 2009). The associations at different markers could be related to the same one or more underlying causative variants yet to be identified, although the significant markers themselves are not in strong LD with each other. Alternatively, these findings could suggest that each of the significant markers or polymorphisms in LD with them has a distinct effect on the VDR gene expression/function (as discussed below), but these functional changes lead to the same phenotype.
The most significant SNP in our family study, rs4334089, is also associated with increased AD risk in a recent GWAS of AD (Beecham et al., 2009). The most significant SNP in the validation NINDS dataset, rs7968585, is in high LD with the ApaI polymorphism (r2= 0.92), which has been associated with AD risk in a Turkish cohort (Gezen-Ak et al., 2007) and MS risk in multiple studies (Smolders et al., 2009). The mechanisms underlying the association between VDR SNPs and multiple neurodegenerative diseases are not clear. Given that vitamin D is a well-documented anti-inflammatory molecule (Garcion et al., 2002), one explanation could be the inflammatory pathways that have been reported to be important in all three disorders. Another possibility is related to VDR's role as a transcription factor. In that role, VDR regulates the transcription of many genes that are implicated in different diseases. The AD and MS studies corroborate the association we found in PD and suggest that the significant SNPs in VDR have functional consequences contributing to interindividual variations of disease susceptibility.
In our family dataset, all the significant SNPs located in introns are between the alternatively spliced first exons, which generate alternative transcripts with different 5′ untranslated region (UTR) (Fig. 1). Although the functions of alternative transcripts of VDR in brain have not been extensively studied, a potential mechanism underlying the intronic SNP association is the SNP-mediated allelic-specific alternative splicing. Indeed, we have observed this phenomenon in a previous study on coronary artery disease. In the limbic system associated membrane protein (LSAMP) gene, we have found that a risk haplotype located with the intron between alternative exon 1A and 1B was correlated with preferred usage of exon 1A, whose expression was associated with higher atherosclerosis burden (Wang et al., 2008a). In the NINDS dataset, the significant SNP is in strong LD with the 3′UTR SNP rs739837. 3′UTR polymorphism, when located within miRNA target site, can modulate miRNA binding efficiency and affects translation/transcription of the gene. We have shown this is the case for the FGF20 gene (Wang et al., 2008b). We did not find any predicted miRNA binding site around rs739837 but we cannot exclude the existence of such a site unless the entire 3′UTR of VDR is carefully characterized by functional tests.
Although we did not replicate the BsmI polymorphism previously reported in a Korean cohort (Kim et al., 2005) and no evidence for association was reported for PD AAO near VDR in the Progeni/GenePD GWAS study (Latourelle et al., 2009), the strength of our study lies in providing evidence for association in the VDR gene in two independent datasets. It has been shown that any replications considerably increase the positive predictive value of a research finding despite negative results in replication efforts (Moonesinghe et al., 2007). An important factor that could influence the effect size of VDR polymorphism and therefore the association result is the vitamin D status. It has been found that vitamin D status modulated the association between VDR polymorphisms and type I diabetes mellitus incidence. The odds ratio of the risk allele increased with higher vitamin D level in the studied population (Ponsonby et al., 2008). It has been speculated that a poor vitamin D status would outpace the effect of VDR polymorphism and that the VDR polymorphisms only manifest phenotypic variations in the presence of certain vitamin D level. This notion seems to be supported by the genetic studies in MS: positive association between VDR and MS was found in the studies conducted in regions with lower latitude but not in regions with higher latitude (Smolders et al., 2009). Therefore, incorporating vitamin D level in any future study is crucial in order to fully characterize the genetic effects of VDR polymorphisms in PD.
In the family dataset, we found evidence for association with AAO. However, the association was not detected in our case-control cohort constructed using probands and unrelated controls from the family dataset (Edwards et al., 2009). This might be attributed to the different study design or properties of the test statistics: family-based associations versus case-control association. It is worth pointing out that many of our initial reports of association with AAO in our family dataset have been replicated by other groups as risk associations, such as the ELAVL4, GSTO1, and USP24 genes (Li et al., 2003; MA et al., 2005; Oliveira et al., 2005; Li et al., 2006; Wahner et al., 2007; Destefano et al., 2008).
Many studies have demonstrated a beneficial role of vitamin D in PD in animal and cell culture studies (Wang et al., 2001, Smith et al., 2006). There are several plausible mechanisms for the VDR-mediated vitamin D effects on PD. In addition to its anti-inflammatory property, which plays a role in neurodegenerative diseases in general (Deluca & Cantorna, 2001; Garcion et al., 2002), vitamin D regulates the expression of glial cell line-derived neurotrophic factor (GDNF) (Evans 1988; Naveilhan et al., 1996; Ferrari et al., 1998; Garcion et al., 2002; Smith et al., 2006). Administration of GDNF has been shown to alleviate PD symptoms in a nonhuman primate model of PD and in PD patients (Gash et al., 1996; Kordower et al., 2000; Gill et al., 2003). Lastly, vitamin D is well known for its role in Ca2+ homeostasis. Chan et al. (2009) have suggested that the SN dopaminergic neuron is particularly vulnerable to cell death due to its sustained opening of L-type Ca2+ channels for its pacemaker activity. Maintaining proper intracellular Ca2+ concentration in the face of extended Ca2+ influx puts SN dopaminergic neurons under substantial cellular stress. It is intuitive that any genetic or environment changes tampering with Ca2+ homeostasis will accelerate SN dopaminergic neuron loss.