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Am J Hum Genet. Nov 2005; 77(5): 685–693.
Published online Sep 9, 2005. doi:  10.1086/496902
PMCID: PMC1271381

High-Resolution Whole-Genome Association Study of Parkinson Disease


We performed a two-tiered, whole-genome association study of Parkinson disease (PD). For tier 1, we individually genotyped 198,345 uniformly spaced and informative single-nucleotide polymorphisms (SNPs) in 443 sibling pairs discordant for PD. For tier 2a, we individually genotyped 1,793 PD-associated SNPs (P<.01 in tier 1) and 300 genomic control SNPs in 332 matched case–unrelated control pairs. We identified 11 SNPs that were associated with PD (P<.01) in both tier 1 and tier 2 samples and had the same direction of effect. For these SNPs, we combined data from the case–unaffected sibling pair (tier 1) and case–unrelated control pair (tier 2) samples and employed a liberalization of the sibling transmission/disequilibrium test to calculate odds ratios, 95% confidence intervals, and P values. A SNP within the semaphorin 5A gene (SEMA5A) had the lowest combined P value (P=7.62×10-6). The protein encoded by this gene plays an important role in neurogenesis and in neuronal apoptosis, which is consistent with existing hypotheses regarding PD pathogenesis. A second SNP tagged the PARK11 late-onset PD susceptibility locus (P=1.70×10-5). In tier 2b, we also selected for genotyping additional SNPs that were borderline significant (P<.05) in tier 1 but that tested a priori biological and genetic hypotheses regarding susceptibility to PD (n=941 SNPs). In analysis of the combined tier 1 and tier 2b data, the two SNPs with the lowest P values (P=9.07×10-6; P=2.96×10-5) tagged the PARK10 late-onset PD susceptibility locus. Independent replication across populations will clarify the role of the genomic loci tagged by these SNPs in conferring PD susceptibility.


Association-based genome scans provide localizing information that is much more precise (often extending over a few thousand base pairs) than the corresponding information from linkage-based studies (which often extend over many millions of base pairs). To date, there has been only one published high-resolution genome scan for association for any human disease (Klein et al. 2005). Here, we report the results of a high-resolution, whole-genome association study of Parkinson disease (PD [MIM 168600]). Our findings contribute to the creation of a genomic predisposition map for PD, and we illustrate a tiered genotyping approach that can be applied to the study of other complex diseases.

Material and Methods

We performed a high-resolution, whole-genome association study of PD, using a two-tiered genotyping approach (tier 1 and tiers 2a and 2b). All methods of the study were approved by the investigational review board of the Mayo Clinic.

Tier 1

For tier 1, we included sibling pairs that were discordant for PD. Cases were enrolled prospectively from the clinical practice of the Department of Neurology of the Mayo Clinic in Rochester, MN, from June 1996 through May 2004. They all resided within Minnesota or one of the surrounding four states (Wisconsin, Iowa, South Dakota, or North Dakota). All cases underwent a standardized clinical assessment performed by a neurologist subspecialized in movement disorders. Cases had at least two of four cardinal signs of parkinsonism (rest tremor, rigidity, bradykinesia, and/or postural instability) and no features atypical for PD (such as unexplained upper motor neuron signs or cerebellar signs). When nonmotor manifestations such as dysautonomia or dementia were present, they were mild and occurred late in the disease course. Subjects with secondary causes of parkinsonism (e.g., history of neuroleptic exposure, encephalitis, or multiple strokes) were excluded. All patients treated with a daily dosage total of [gt-or-equal, slanted]1 g of levodopa (in combination with carbidopa) had a more than minimal improvement in parkinsonism symptoms and signs. We obtained a genealogical history from all cases, and, when permitted, we contacted available siblings for a telephone interview, to exclude parkinsonism via a validated screening instrument (Rocca et al. 1998). For cases, we obtained blood after a clinical assessment performed either at the Mayo Clinic or in the subjects’ homes. For siblings who screened negative for PD (i.e., who had none of the following: prior diagnosis of PD, prior treatment with levodopa, or three or more of nine symptoms), we obtained blood via mail-in kits (we did no clinical assessment). All subjects provided written informed consent; their whole blood was obtained, via venipuncture, for DNA extraction (via the Puregene method [Gentra Sciences]) and storage. Cases were matched to a single participating sibling, without PD or parkinsonism, first by sex (when possible) and then by closest age.

For each subject (matched discordant sibling pairs), ~1 μg of DNA was shipped to Perlegen Sciences for laboratory study. Whole-genome amplification was performed as described elsewhere (Dean et al. 2002). For each subject, DNA was individually genotyped, for a set of 248,535 SNPs, with unique positions on National Center for Biotechnology Information (NCBI) build 34. These SNPs were selected to have relatively uniform spacing across the genome and to preferentially include haplotype-defining common SNPs from the Perlegen haplotype map (Patil et al. 2001). Details regarding the distribution of genomic gaps is provided in table 1. The genotyping platform employed high-density oligonucleotide, photolithographic microarrays (DNA chips), such that one hybridization yielded genotypes for 85,000 SNPs in a single individual.

Table 1
Distribution of Gap Sizes between Adjacent Informative Tier 1 SNPs, within Chromosomal Contigs from NCBI Build 34[Note]

We performed a liberalization of the sibling transmission/disequilibrium test (sTDT) (Schaid and Rowland 1998) to identify SNPs that had significant allele-frequency differences in cases versus unaffected siblings, adjusting the analyses for age and sex. For each SNP, we calculated odds ratios (ORs), 95% CIs, and P values (using a log-additive or “trend” model).

Tier 2

For tiers 2a and 2b, we individually genotyped case–unrelated control pairs. Cases were enrolled as for tier 1 but had no siblings available. Unrelated controls were identified via random digit dialing from the same five-state region as the cases and were screened negative for parkinsonism via the same validated telephone instrument as for siblings in tier 1. DNA was collected at the time of clinical assessment for cases and via mail-in kits for controls. Case–unrelated control pairs were matched for sex and age (±3 years). DNA was again shipped to Perlegen Sciences for whole-genome amplification and genotyping. The genotyping for tiers 2a and 2b was performed using customized oligonucleotide microarrays.

For tier 2a, a subset of SNPs that were associated with PD (P<.01 in tier 1) were genotyped. An additional predefined set of 311 SNPs was genotyped for genomic control (Hinds et al. 2004). Conditional logistic regression analyses were performed, to test for and model associations between the SNPs and PD. The analyses were adjusted for age and sex, as appropriate. We calculated ORs, 95% CIs, and P values (as for tier 1, using a log additive or “trend” model). We also checked for population structure, using the genomic-control method (Devlin and Roeder 1999; Bacanu et al. 2000; Devlin et al. 2004). This method treats the subjects as unmatched and does not include adjustments for covariates; however, it should still provide guidelines for assessing the degree of stratification in tier 2. For the SNPs associated with PD (P<.01) in both the tier 1 and 2a analyses, we pooled data for the case–unaffected sibling and case–unrelated control pairs and again analyzed the data, using a liberalization of the sTDT (Schaid and Rowland 1998). This allowed us to maximize statistical power for the analyses to obtain a more precise ranking of replicated SNPs by ascending P values and a more precise estimate of ORs and 95% CIs.

For tier 2b, we also selected for genotyping additional SNPs that in tier 1 were only borderline significant but that tested a priori biological or genetic hypotheses regarding genomic susceptibility to PD. These SNPs did not achieve a P value <.01 in the tier 1 sample overall. However, some of these SNPs (1) had P values <.001 in tier 1 strata defined by sex or by median age at study; (2) had P values <.05 and were positioned within 10 kb of the linkage-derived candidate genes α-synuclein (SNCA [MIM 163890]), parkin (MIM 602544), ubiquitin carboxy-terminal hydrolase L1 (UCHL1 [MIM 191342]), microtubule-associated protein τ (MAPT [MIM 157140]), oncogene DJ1 (DJ1 [MIM 602533]), and PTEN-induced kinase 1 (PINK1 [MIM 608309]); (3) had P values <.05 and were positioned within additional loci linked to PD (i.e., PARK3 [MIM 602404], PARK8 [MIM 607060], PARK9 [MIM 606693], PARK10 [MIM 606852], PARK11 [MIM 607688]); (4) had P values <.05 and were positioned within exons or within 10 kb 5′ of the transcript, genomewide; or (5) were redundant tags of European American linkage-disequilibrium bins (Hinds et al. 2005) highlighted by some of the above criteria. We note that the tier 2b SNP selection predated the discovery of mutations in the leucine-rich repeat kinase 2 gene (LRRK2 [MIM 609007]) as the cause of PARK8-linked parkinsonism (although SNPs within the gene were indeed selected and genotyped). We tested the association of these tier 2b SNPs with PD in the combined samples, using a liberalization of the sTDT (as above).


Tier 1

For tier 1, we genotyped 443 case–unaffected sibling pairs. Table 2 summarizes demographic and clinical characteristics of the sample. For the 248,535 SNPs selected, the genotyping call rate was >80% for each of 220,143 SNPs. Of these SNPs, 205,031 (93%) were polymorphic within the study sample. The Hardy-Weinberg equilibrium (HWE) P value was >.001 in controls for 198,345 SNPs (97% of polymorphic SNPs, with an average gap between adjacent SNPs of 12,363 bp). Ultimately, for these subjects and informative SNPs, 172,420,019 genotype calls (98.1% of possible genotypes) were made. We regenotyped, in triplicate, 96 SNPs for each subject, with 99.8% concordance of genotypes. The concordance of genotypes called by the oligonucleotide array platform, as compared with genotypes called by other platforms employed as part of the multicenter HapMap project, was 99.5% (Hinds et al. 2005).

Table 2
Demographic and Clinical Characteristics (Tiers 1 and 2)

As a sensitivity analysis and to assess the genomic coverage of the informative SNPs, we determined our statistical power to detect unassayed, disease-associated variants with this SNP collection. Specifically, we previously genotyped these same SNPs in a different sample of European Americans who were also sequenced across selected genes by the SeattleSNPs Program for Genomic Applications (PGA) (SeattleSNPs) (Hinds et al. 2005). Our metric of coverage was the mean r2 value for any common PGA SNP (minor-allele frequency >10%) with the most-correlated SNP in the same region from the 198,345 informative SNPs. The statistical power to detect an unassayed, disease-associated allele indirectly by use of a correlated allele of an assayed SNP is related to r2. Specifically, the power to detect an association indirectly in N samples is equivalent to the power to detect it directly in Nr2 samples (Pritchard and Przeworski 2001). Despite our assaying only 3.3% of all of the common SNPs in these intervals (and only 1% of the less common SNPs), the mean r2 for unassayed SNPs was 0.57.

There were 1,862 SNPs that were associated with PD in tier 1 (P<.01), after exclusion of SNPs with fewer than nine discordances between sibling pairs (SNPs for which ORs could not be reliably estimated). We provide details for all informative tier 1 SNPs (including their dbSNP reference sequence identification numbers, gene names, case and control allele frequencies, ORs, 95% CIs, and P values) in tab-delimited text file 1 (online only); the columns are described in table 3.

Table 3
Column Descriptions for Text Files 1 and 2

Tier 2

For tier 2a, we genotyped 332 case–unrelated control pairs. Table 2 summarizes demographic and clinical characteristics for these samples. Genotypes and analyses were attempted for the 1,862 SNPs selected in tier 1 and for 311 genomic control SNPs. Of these, genotyping call rates of >80% and HWE P values >.001 (in controls) were achieved for 1,793 SNPs. We were able to call successfully 1,176,772 (99% of possible) genotypes for these SNPs.

To assess the impact of population structure on tier 2 associations, trend tests were performed on the genomic control SNPs. The mean trend test statistic over the genomic control SNPs, λm, was 0.96, which is less than the expected value of 1 for no population structure (Devlin et al. 2004). Therefore, there was no indication of substantial confounding due to population structure bias.

There were 26 SNPs with P values <.01 in both tier 1 and tier 2a. Of these SNPs, 11 had nominal P values <.01 and the same direction of the effect in tier 1 and tier 2a (termed “replicated SNPs”). A SNP (rs7702187) within the semaphorin 5A gene (SEMA5A [MIM 609297]) had the lowest P value (OR 1.74; 95% CI 1.36–2.24; P=7.62×10-6). A second SNP (rs10200894) tagged the PARK11 late-onset PD susceptibility locus (OR 1.84; 95% CI 1.38–2.45; P=1.70×10-5). Table 4 lists the 11 replicated SNPs, including their dbSNP reference sequence identification numbers and, when applicable, the corresponding gene ontology annotation of nearby genes. The SNPs are ordered by ascending combined P values. We provide additional results for the tier 2a SNPs (including their dbSNP reference sequence identification numbers and gene names and, for the combined samples, the case and control allele frequencies, ORs, 95% CIs, and P values), in tab-delimited text file 2 (online only); the columns are described in table 3. The 11 replicated SNPs from tiers 1 and 2a (table 4) had 20 neighboring SNPs within a distance of 15 kb of the reported data. None of these 20 SNPs were significant enough to be selected for inclusion in tier 2a. However, 6 of the 20 SNPs had tier 1 P values <.1 (P=.011 on a binomial test), and 14 of these 20 had P values <.2 (P=1.8×10-6). Thus, there is evidence of correlations among neighboring SNPs.

Table 4
Genomic SNPs Associated with PD in Two Samples (Tiers 1 and 2)

Table 5 summarizes the rationale for inclusion of the tier 2b SNPs, primarily on the basis of a priori biological and genetic hypotheses regarding susceptibility to PD. We considered 975 tier 2b SNPs. Of these, genotyping call rates of >80% and HWE P values >.001 in controls were achieved for 941 SNPs. We were able to call successfully 617,257 (99% of maximum possible) genotypes for these SNPs. Of these, the two SNPs (rs682705 and rs7520966) with the lowest combined tier 1 and tier 2b P values (P=9.07×10-6, OR 0.66, 95% CI 0.54–0.79 and P=2.96×10-5 OR 0.67, 95% CI 0.55–0.81, respectively) tagged the PARK10 late-onset PD susceptibility locus. The r2 value between the two SNPs was 0.993 (highly correlated). We provide additional results for the tier 2b SNPs (including their dbSNP reference sequence identification numbers, gene names, case and control allele frequencies, ORs, 95% CIs, and P values) in tab-delimited text file 2 (online only).

Table 5
Criteria for SNPs Selected for Genotyping in Tier 2


Twin studies and familial aggregation studies have suggested that the genetic contribution to PD is small and limited to younger-onset cases (Rocca et al. 2004; Wirdefeldt et al. 2004). However, parametric linkage studies have assigned 11 loci to PD, and causal mutations have been identified in six genes (SNCA, parkin, UCHL1, DJ1, PINK1, and LRRK2) (Polymeropoulos et al. 1997; Kitada et al. 1998; Leroy et al. 1998; Bonifati et al. 2003; Valente et al. 2004; Zimprich et al. 2004). Nonparametric linkage studies have also assigned the locus containing the MAPT gene to PD (Martin et al. 2001). Whereas mutations in these genes only rarely cause PD, common variations in some of these genes may confer susceptibility with a more sizable population-attributable risk (Farrer et al. 2001; West et al. 2002; Maraganore et al. 2004; Mamah et al. 2005; Mueller et al. 2005). However, the search for PD susceptibility genes has been largely limited to the candidate-genes approach.

Our study is unique because we aimed to discover common PD susceptibility gene variants via a whole-genome association design. Despite the low heritability of PD, we have nominated several new susceptibility genes for PD (table 4). Findings for the SEMA5A gene are particularly noteworthy and highlight the apoptosis pathway (Tatton et al. 2003).

The SEMA5A gene (sema domain, seven thrombospondin repeats [type 1 and type 1–like], transmembrane domain [TM], and short cytoplasmic domain, [semaphorin] 5A) has not been previously implicated in PD. Although the effect size is small (OR 1.7; 95% CI 1.36–2.24), the disease-associated allele occurs with sufficient frequency to confer a sizable population-attributable risk (minor-allele frequency=19.6% for unrelated controls). This gene maps to the deletion candidate interval for cri du chat syndrome. This chromosomal deletion syndrome is associated with severe abnormalities in brain development, with resultant mental retardation (Simmons et al. 1998). The encoded semaphorin protein has receptor activity and contributes to neurogenesis and apoptotic processes. It elicits multiple functional responses through its receptor plexin-B3 (Artigiani et al. 2004). Specifically, semaphorins may play a role in the development of the mesencephalic dopamine neuron system (Kawano et al. 2003). They are also positive mediators of dopamine-induced apoptosis; antibodies directed against semaphorins inhibit dopamine-induced neuronal death (Shirvan et al. 1999, 2000; Barzilai et al. 2000). The expression of semaphorin genes is abnormal in Alzheimer disease, which shares clinical, pathological, and etiological features with PD (Hirsch et al. 1999). It has also been suggested in a rat model of PD that the neuroprotective effects of vascular endothelial growth factor may be mediated via semaphorin inhibition (Yasuhara et al. 2004). To date, there have been no clinical studies of semaphorin inhibitors as neuroprotective therapy for PD. Our genetic findings converge with cell biology and animal experiments to support the research and development of therapies targeting semaphorins as neuroprotection for PD.

Several additional findings of the whole-genome scan are consistent with our current understanding of PD (table 4). One of the replicated SNPs mapped the PARK11 locus, which showed significant linkage to PD in one study but not in another (Pankratz et al. 2003; Prestel et al. 2005). Another replicated SNP was within the cancer-related UDP-N-acetyl-α-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 3 gene (GALNT3 [MIM 601756]). This may be consistent with epidemiological studies that suggest that patients with PD have a higher risk of cancers after the diagnosis of PD (Elbaz et al. 2005). Another replicated SNP was within the PR domain–containing protein 2 gene (PRDM2 [MIM 601196]), which is also related to neuronal differentiation and cancer. That gene is also estrogen related. This may be consistent with epidemiological data suggesting that endogenous estrogen and estrogen treatment are protective against PD (Benedetti et al. 2001). Finally, a replicated SNP was within the chromosome X gene PASD1 (PAS domain–containing 1). X inactivation of a major susceptibility gene could explain the sex difference in lifetime risk of PD (men have a 1.5-times-greater risk than women) (Elbaz et al. 2002; Carrel and Willard 2005).

Our tier 2b, hypothesis-based SNP analyses were noteworthy for highlighting a chromosome 1p32 locus previously linked to late-onset PD susceptibility. The PARK10 locus was originally identified in Icelandic families via a genomewide scan with use of microsatellite markers (Hicks et al. 2002). This locus was subsequently shown to influence age at onset in a multicenter study of families with PD (Li et al. 2002). To date, a specific gene within the PARK10 locus has not been identified. Our disease-associated SNPs (rs682705 and rs7520966) are within a gene designated LOC200008, which encodes a hypothetical protein with inferred oxidoreductase activity and potential involvement in cholesterol biosynthesis and electron transport. The SNPs are also within 21 kb upstream of the mitochondrial ribosomal protein L37 gene (MRPL37). Mitochondrial mechanisms of PD pathogenesis have been described (Dauer and Przedborski 2003), and a role for mitochondrial ribosomal protein genes in human disorders has been postulated (Kenmochi et al. 2001).

To our knowledge, our study is the first high-resolution, whole-genome association study published about PD. Recent review articles anticipated such studies (Hirschhorn and Daly 2005; Wang et al. 2005), but our present understanding of human genome variability and the available high-throughput genotyping technologies currently allow for whole-genome studies (Patil et al. 2001; Olivier et al. 2001; Hinds et al. 2005). Also, our two-tiered study design had several strengths. First, we performed a family-based case-control study (tier 1). This limited false-positive results due to population stratification bias (Maraganore 2005). However, the relatedness of cases and siblings may have reduced statistical power to detect genetic associations (false-negative results). Second, we performed a case–unrelated control study (tiers 2a and 2b). The use of unrelated controls (rather than unaffected siblings) optimized statistical power for the replication study (Maraganore 2005). It is noteworthy that, for tier 2, there was minimal population structure, despite the inclusion of unrelated cases and controls. This is fortunate, since we therefore did not need to stratify the analyses for the tier 2 sample. It is also a strength of our study that all subjects were individually genotyped (no pooling of DNA samples was involved). This allowed analyses adjusted or stratified for age and sex, factors that have been shown elsewhere to influence heritability in PD (Rocca et al. 2004; Mueller et al. 2005). Individual genotyping will also allow us to perform studies of complex gene-gene and gene-environment interactions and genotype-phenotype correlations within the available data set. It is intriguing that 7 of the 11 replicated SNPs are intergenic. This may suggest that intergenic sequences are important to health, perhaps via gene regulatory effects (Martens et al. 2004).

It is likely that the number of SNPs genotyped—or the specific ones selected—as well as the available sample size resulted in our missing disease-associated loci across the human genome (Carlson et al. 2003, 2004; Wang et al. 2005). However, we observed an association of SNPs neighboring the 11 replicated SNPs (“clustering”), which suggests that we achieved an appreciable map density. Also, with the available samples, we detected significant (P<.01) ORs [gt-or-equal, slanted]1.34 in tier 1, [gt-or-equal, slanted]1.33 in tier 2a, and [gt-or-equal, slanted]1.21 in the combined analysis. It is also likely that multiple statistical comparisons or other factors resulted in false-positive findings (Storey and Tibshirani 2003; Hirschhorn and Daly 2005). None of our results were significant with use of a strict Bonferroni correction for the number of tests (198,345 SNPs for tier 1 and the combined analyses, 1,466 SNPs for tier 2a, and 1,312 SNPs for tier 2b). However, this is a very conservative evaluation of significance; it assumes total independence of the tests, and properly correcting for the correlational structure among the SNPs is not straightforward. Eleven SNPs had P values <.01 and the same direction of the effect in both tiers 1 and 2a, and many of these SNPs have compelling potential biological relationships with PD or are in regions otherwise implicated in PD via linkage analysis (“convergence”).

The results of this study draw a first genomic map of PD, which awaits replication across populations (including collaborative-pooled analyses within global consortia). Our findings may ultimately identify biomarkers that contribute to early disease detection and primary prevention strategies. Also, they may nominate new molecular targets for disease-modifying therapies (secondary prevention). Correlation studies of genotypes to prognostic outcomes may predict the effect of treatments targeting these genes and their proteins (“virtual clinical trials”) and thus reduce research and developments costs and identify subgroups of patients most likely to benefit from treatment (personalized medicine).

Supplementary Material

Text File 1:
Text File 2:


This study was supported primarily by a Michael J. Fox Foundation Linked Efforts to Accelerate Parkinson's Solutions award. We also received support from National Institutes of Health grants ES10751, ES10751-S1, NS33978, and NS40256. We acknowledge the outstanding contributions of the many Perlegen Sciences and Mayo employees who provided technical and infrastructural support for this work. But mostly, we thank the patients and study subjects who made this work possible and who give it value.

Web Resources

The URLs for data presented herein are as follows:

Online Mendelian Inheritance in Man (OMIM), http://www.ncbi.nlm.nih.gov/Omim/ (for PD, SNCA, parkin, UCHL1, MAPT, DJ1, PINK1, PARK3, PARK8, PARK9, PARK10, PARK11, LRRK2, SEMA5A, GALNT3, and PRDM2)
SeattleSNPs, http://pga.gs.washington.edu/ (for PGA)


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