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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Mov Disord. Author manuscript; available in PMC 2012 April 1.
Published in final edited form as:
PMCID: PMC3082603
NIHMSID: NIHMS262307

Replication of MAPT and SNCA, but not PARK16-18, as Susceptibility Genes for Parkinson’s Disease

Abstract

Background

Recent genome-wide association studies of Parkinson’s disease have nominated three new susceptibility loci (PARK16-18) and confirmed two known risk genes (MAPT and SNCA) in populations of European ancestry. We sought to replicate these findings.

Methods

We genotyped single nucleotide polymorphisms in each of these genes/loci in 1,445 Parkinson’s disease patients and 1,161 controls from Northern Spain. Logistic regression was used to test for association between genotype and Parkinson’s disease under an additive model, adjusting for sex, age, and site. We also performed analyses stratified by age at onset.

Results

Single nucleotide polymorphisms in MAPT (rs1800547; p = 3.1 × 10−4) and SNCA (rs356219; p = 5.5 × 10−4) were significantly associated with Parkinson’s disease. However, none of the markers in PARK16-18 associated with Parkinson’s disease in the overall sample, or in any age stratum, with p values ranging from 0.09–0.88.

Conclusions

While our data further validate MAPT and SNCA as Parkinson’s disease susceptibility genes, we failed to replicate PARK16, 17, and 18. Potential reasons for the discordance between our study and previous genome-wide association studies include effects of population structure, power, and population-specific environmental interactions. Our findings suggest that additional studies of PARK16-18 are necessary to establish the role of these loci in modifying risk for Parkinson’s disease in European-derived populations.

Keywords: Parkinsons Disease, Genome-Wide, replication

INTRODUCTION

Parkinson’s disease (PD) (OMIM168600) is the second most common neurodegenerative disorder and in most instances is thought to arise from a complex interaction between genetic and environmental factors. Over the past decade, candidate gene studies firmly established that common variants in the LRRK2 (OMIM 609007), MAPT (OMIM 157140), and SNCA (OMIM 163890) genes are associated with PD in populations of Asian and/or European origin 14. Subsequently, five genome-wide association studies (GWASs) have been conducted which further validated these three genes, but also nominated three new chromosomal regions as putative PD susceptibility loci 59. However, the strength of the association signal from these three loci, designated PARK16 (OMIM 613164), PARK17 (GAK/DGKQ region on chromosome 4p), and PARK18 (HLA gene cluster on chromosome 6p), varied substantially among GWASs indicating that further replication is needed to assess the veracity of these results.

Two frequently cited reasons for inconsistencies across genetic association studies are inadequate power and confounding by population structure. Structure arises when there are differences in ancestry between case and control groups and it can lead to both false-positive and false-negative findings. Thus, there are inherent advantages in performing association analyses in genetically homogenous populations. In this study we examined single nucleotide polymorphism (SNPs) within the most significant loci reported in recent GWASs in a large PD case-control sample from Northern Spain.

SUBJECTS AND METHODS

Subjects

The study population was comprised of 1,445 PD patients (mean age at onset [AAO], 60.0 ± 12.2 years; mean age at enrollment, 68.1 ± 11.2 years; male sex, 55.8%) and 1,161 control subjects (mean age at enrollment, 68.9 ± 11.2 years; male sex, 41.6%) who were all of self-reported Spanish ancestry and resided in Spain. The vast majority (95.6%) of patients were enrolled at outpatient clinics in one of three provinces in Northern Spain (Asturias, Cantabria, and Navarra). All patients met UK PD Society Brain Bank (UKPDSBB) clinical diagnostic criteria for PD as determined by a movement disorder specialist. Controls had no history of parkinsonism and were either spouses of PD patients or community volunteers; 92.2% of the controls were enrolled in these same three provinces. The institutional review boards at each participating site approved the study, and all subjects gave informed consent.

Marker Selection and Genotyping

Genomic regions were selected for replication as follows. First, we chose all loci associated with PD at a genome-wide level of significance in one or more of four recent GWAS conducted in European-derived populations (PARK18, MAPT, and SNCA)56, 89. Next, we selected loci that approached genome-wide significance in at least one such GWAS, and were successfully replicated (PARK17), or marginally associated with PD (chromosome 8 near HAS2 gene), in at least one other 6, 9. Finally, we included the PARK16 locus, which met genome-wide significance in a GWAS of Japanese subjects 7 and was replicated in a GWAS of individuals of European origin 8.

For each of these six loci, we selected for replication the most significant SNP (or one highly correlated with it) from each GWAS reporting a positive association. Since the top “hit” in each region was well correlated across studies, this required genotyping of only seven SNPs in total. Genotyping was performed by TaqMan assay as previously described 3.

Data Analysis

We assessed each SNP for Hardy-Weinberg equilibrium (HWE) in cases and controls separately with an exact test. Logistic regression was used to test for association between genotype and PD under an additive model, adjusting for sex, age at enrollment, and site. Homozygotes for the more common allele were used as the baseline risk group. P-values were generated through a Wald test. Age-stratified analyses were performed as described elsewhere defining early onset PD as AAO ≤ 50 years 10. Power calculations were done using Quanto (http://hydra.usc.edu/gxe) setting the “high risk allele” frequency equal to the minor allele frequency in controls for each SNP.

RESULTS

All SNPs were in HWE in both cases and controls. In an additive model adjusting for age, sex, and site, there was a highly significant association between PD and SNPs in MAPT (rs1800547; odds ratio [OR], 0.79; 95% confidence interval [CI], 0.70–0.90; p = 3.1 × 10−4) and SNCA (rs356219; OR, 1.23; 95% CI, 1.09–1.38; p = 5.5 × 10−4), but none of the other four loci (Table 1). In the age-stratified analyses, a significant association with PD was seen only for MAPT and SNCA in the late-onset group (Supplemental Table 1).

Table 1
Association Analysis of Markers Selected for Replication in Spanish Case-Control Sample

The “A” allele of rs1800547 serves as a surrogate marker for the MAPT “H1” haplotype, which in prior candidate gene studies has typically been examined under a dominant model 1, 3. In our dataset, analysis of the A allele in an adjusted dominant model yielded an OR of 1.23 (95% CI, 1.05–1.44; p = 1.1 × 10−2).

We performed retrospective power calculations under a log-additive model, specifying a type I error rate of 0.05 (Table 2). Assuming an OR of 1.3, our sample provided adequate power for all markers examined, with the possible exception of rs11248051 within PARK17, where power was 76%. For an OR of 1.2, power was greater than 80% for all SNPs except for those in PARK16 and PARK17.

Table 2
Comparison of Results from Present Study with Recent GWASs

DISCUSSION

With the exception of MAPT and SNCA, we failed to replicate the most promising susceptibility loci from recent GWASs undertaken in European-derived populations. For MAPT and SNCA, the strength of association in our dataset was comparable to that observed in these and other studies (Table 2).

The PARK16 region on chromosome 1q32 includes several candidate genes and was originally identified in a Japanese GWAS which included replication in two independent samples 7. The most significant markers in the combined three-stage GWAS were rs947211 (OR, 1.30; p = 1.5 × 10−12) and rs823156 (OR, 1.37; p = 3.6 × 10−9). Subsequently, Tan and colleagues found that four of five PARK16 SNPs examined in 433 PD patients and 916 controls of Han Chinese ancestry were associated with PD, including rs947211 (OR, 0.71; p = 2 × 10−3) and rs823156 (OR, 0.68; p = 5 × 10−3)11. The association of PARK16 with PD in European-derived populations has been less consistent, and GWASs undertaken in individuals of European origin have yielded disparate findings 89. Simon-Sanchez and colleagues reported successful replication of PARK16 in a two-stage GWAS of subjects from the U.S., Germany, and the U.K, with the strongest signal in the combined sample emanating from two low-frequency SNPs, rs823128 (OR, 0.66; p = 7.3 × 10−8) and rs11240572 (OR, 0.67; p = 6.1 × 10−7) 8. In contrast, Hamza and colleagues reported a failure to replicate PARK16 in a single-stage, U.S.-based GWAS, with p values ranging from 0.03–0.15 9. A smaller GWAS of European-Americans with familial PD also failed to detect an association between PARK16 and PD 6. Similarly, neither of the two PARK16 SNPs we examined in this study reached significance. One possible explanation for these findings is that PARK16 might harbor a population specific PD risk variant that occurs in Asians but is rare or absent in Europeans. For example, the LRRK2 G2385R SNP conveys a risk for PD of approximately 2.5 fold in Asians, but it is essentially absent in other populations 4, 12. Another possibility is that a true but weaker association signal exists in populations of European origin such that most studies conducted to date have been under-powered. In support of this, even in studies where rs947211 and rs823156 failed to reach significance, the direction of the effect was the same, with ORs below 1.0 (Table 2). If the true effect size for these PARK16 SNPs is similar to that observed by Simon-Sanchez and colleagues (ORs of 0.85–0.88), then our sample might well have lacked adequate power.

Hamza and colleagues reported an association reaching genome-wide significance for rs3129882 located in intron 1 of the HLA-DRA gene (OR, 1.31; p = 2.9 × 10−8), and designated this region PARK18 9. They observed marginal associations for this SNP in two smaller GWASs (Table 2), which when combined yielded an OR of 1.18 (p = 1.1 × 10−3), and cited this as evidence for replication. In contrast, we failed to detect an association of this SNP with PD in our sample (OR, 1.01; p = 0.88), and considered several possible explanations for this discordance. First, we do not believe that power was a major limitation, even if one takes into consideration the “winner’s curse” phenomenon in which the estimate of the genetic effect in the first positive report is biased upward 13. Our sample provided 99% power to detect an effect at the OR reported in the original study (1.31) and 84% power at the OR observed in the combined replication sample (1.18). Another possibility is that the observed association of PARK18 with PD might represent a spurious finding resulting from population structure. Structure is of particular concern for the highly polymorphic HLA region in which many markers display substantial differences in allele frequency across European subpopulations 14. Hamza and colleagues observed significant structure in their case-control sample and a frequency gradient for the PD-associated HLA-DRA allele such that individuals of Northern- and Southern-European origin had the lowest and highest allele frequencies, respectively. For example, the allele frequencies in controls of Scandinavian and Italian ancestry were 0.35 and 0.47, respectively. A popular principal component analysis-based method (EIGENSTRAT) 15 was used to address this issue, and the results remained highly significant after correction for structure. However, several authors have demonstrated that in some instances, even when EIGENSTRAT accurately detects population structure it still fails to properly correct its effect 1617. Though we did not directly test for structure in our dataset, a recent population-based study of 800 control subjects ascertained from across Spain found little to no evidence of it 18. Thus, it is unlikely that significant structure existed in our sample, which was comprised predominantly of individuals from Northern Spain. A third potential explanation for the inconsistency in results is that the risk conveyed by PARK18 might be dependent on interactions with unrecognized environmental factors that differ across populations. While this argument could be invoked for any of the loci studied here, it is particularly relevant for HLA. Variation within the HLA region is well known to influence susceptibility to a number of infectious diseases, and viral infections has long been postulated to be a risk factor for PD 1920. Thus, if a specific HLA allele increases susceptibility to a given infectious disease etiologically linked to PD, the association of that allele with PD might only be observed in populations where the infectious agent is common. A similar scenario in which Epstein-Barr virus and HLA DRB1*1501 interact to increase risk for multiple sclerosis has recently been proposed 21.

An important limitation in our study was that we only examined a limited number of markers at each locus based on results from previous studies. Had we taken a more comprehensive approach, such as genotyping a full set of tagging SNPs, we might have detected significant associations at additional loci.

GWASs have provided a wealth of data and identified a number of susceptibility genes for complex diseases in recent years. However, rigorous and repeated replication in well-designed follow-up studies is still a prerequisite before promising candidate genes can be considered bona fide risk factors for disease. In PD, MAPT and SNCA have reached that status, a process that took several years. We believe the PARK16, 17, and 18 loci require further validation. Because the effect size for PARK16 might be smaller in European-derived populations, particular care must be taken to ensure that replication samples are sufficiently large to ensure adequate power. Because of concerns for the effect of population structure, future replication efforts for PARK18 might benefit from inclusion of more genetically homogenous case-control samples and the use of family-based association analysis.

Supplementary Material

Supp Table S1

Acknowledgments

We thank Jaione Irigoyen for assistance with subject recruitment and Elena Lorenzo, Elena Alonso, and Ana Corao for technical support. This work was supported by funding from the Department of Veterans Affairs (1I01BX000531), National Institutes of Health (P50 NS062684 and R01 NS065070), Spanish Ministry of Education and Science (SAF2006-10126: 2006-2009), Fondo de Investigacion Sanitaria (FIS, PI070014), Spanish Ministry of Science and Technology, European Social Fund, and the Asociación Parkinson Asturias.

Footnotes

Potential conflict of interest: Nothing to report

Financial disclosure related to research covered in this article: This work was supported by funding from the Department of Veterans Affairs (1I01BX000531), National Institutes of Health (P50 NS062684 and R01 NS065070), Spanish Ministry of Education and Science (SAF2006-10126: 2006–2009), Fondo de Investigacion Sanitaria (FIS, PI070014), Spanish Ministry of Science and Technology, European Social Fund, and the Asociación Parkinson Asturias.

Author Roles: 1. Research project: A. Conception and design, B. Acquisition of data, C. Analysis and interpretation of data.

2. Manuscript: A. Writing of the first draft, B. Review and Critique.

3. Other: A. Statistical analysis, B. Obtaining funding, C. Technical support, D. Supervision of data collection Mata: 1A, 1B, 1C, 2A, 2B, 3A, 3D; Yearout: 1B, 2B, 3C; Alvarez: 1B, 2A, 3C; Coto: 1B, 2B 3C; De Mena: 1B, 2B,; Ribacoba: 1B, 2B, 3C; Lorenzo-Betancor: 1B, 2B; Samaranch: 1B, 2B; Pastor: 1B, 2B, 3B, 3C; Cervantes: 1B, 2B; Infante: 1B, 2B; Sierra: 1B, 2B; Garcia-Gorostiaga: 1B, 2B, 3C; Combarros: 1B, 2B; Snapinn: 1C, 2B, 3A, 3B; Edwards: 1C, 2B, 3B, 3D; Zabetian: 1A,1B,1C, 2A, 3B, 3C, 3D

.

Full Financial Disclosures of all Authors for the past year:

Dr Mata, Dr Yearout and Dr Zabetian are supported by grants from the Dept of Veterans Affairs, NIH, Parkinson’s Disease Foundation, American Parkinson Disease Foundation, Michael J. Fox Foundation, and Northwest Collaborative Care. Dr Alvarez and Dr Infante are supported by grants from Instituto Carlos III. Dr de Mena is supported by a fellowship from Fundacion para el fomento en Asturias de la Investigacion Cientifica aplicada y la Tecnología (FICYT). Dr Edwards and Dr Snapinn are supported by an NIH grant. Dr Samaranch is supported by a Torres Quevedo fellowship from the Spanish ministry of science and technology. Dr Pastor is supported by grants from the Spanish ministry of science and technology and Fundacion para la Investigacion Medica Aplicada (FIMA). Dr Coto, Dr Ribacoba, Dr Lorenzo-Betancor, Dr Cervantes, Dr Infante, Dr Garcia-Gorostiaga, Dr Sierra and Dr Combarros report no disclosures.

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