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Resequencing analysis of five Mendelian genes and the top genes from genome-wide association studies in Parkinson’s Disease

Molecular Neurodegeneration volume 11, Article number: 29 (2016) Cite this article

Abstract

Background

Most sequencing studies in Parkinson’s disease (PD) have focused on either a particular gene, primarily in familial and early onset PD samples, or on screening single variants in sporadic PD cases. To date, there is no systematic study that sequences the most common PD causing genes with Mendelian inheritance [α-synuclein (SNCA), leucine-rich repeat kinase 2 (LRRK2), PARKIN, PTEN-induced putative kinase 1 (PINK1) and DJ-1 (Daisuke-Junko-1)] and susceptibility genes [glucocerebrosidase beta acid (GBA) and microtubule-associated protein tau (MAPT)] identified through genome-wide association studies (GWAS) in a European-American case-control sample (n=815).

Results

Disease-causing variants in the SNCA, LRRK2 and PARK2 genes were found in 2 % of PD patients. The LRRK2, p.G2019S mutation was found in 0.6 % of sporadic PD and 4.8 % of familial PD cases. Gene-based analysis suggests that additional variants in the LRRK2 gene also contribute to PD risk. The SNCA duplication was found in 0.8 % of familial PD patients. Novel variants were found in 0.8 % of PD cases and 0.6 % of controls. Heterozygous Gaucher disease-causing mutations in the GBA gene were found in 7.1 % of PD patients. Here, we established that the GBA variant (p.T408M) is associated with PD risk and age at onset. Additionally, gene-based and single-variant analyses demostrated that GBA gene variants (p.L483P, p.R83C, p.N409S, p.H294Q and p.E365K) increase PD risk.

Conclusions

Our data suggest that the impact of additional untested coding variants in the GBA and LRRK2 genes is higher than previously estimated. Our data also provide compelling evidence of the existence of additional untested variants in the primary Mendelian and PD GWAS genes that contribute to the genetic etiology of sporadic PD.

Background

PD is the second most common neurodegenerative disorder after Alzheimer’s disease (AD) [1]. By the year 2030, the prevalence of PD is projected to be between 8.7 and 9.3 million [1]. Genetic studies in PD have provided valuable insights into the underlying pathogenic mechanisms [2], leading to the development of animal models for investigation of disease mechanisms and identification of novel therapeutic targets [3]. Initial studies of multiplex families with PD found concordance rates of 75 % in monozygotic twins, 22 % in dizygotic twins [5], and an increased relative risk of PD of 2.9 (95 % CI 2.2–3.8) for those with an affected first-degree relative [6]. These findings indicate that the genetic etiology of PD does not fit a simple genetic model [5]. GWAS of PD have identified variants at 20 loci influencing PD risk [2, 4, 7–9], with population-specific differences [10, 11]. The currently identified genetic factors explain only 6–7 % of the phenotypic variability associated with PD [12], and the most prevalent GWA signals account for only 3–5 % of PD genetic variance in individuals of European ancestry [12]. These results provide unequivocal, compelling evidence for the existence of undiscovered genetic factors that contribute to the etiology of PD. Both candidate gene association studies and GWAS repeatedly validate that the most statistically significant signals associated with PD are common variants located close to SNCA, LRRK2, MAPT genes and low frequency coding variants in the GBA gene [2, 4, 7, 10, 13–16].

Non-coding variants are the most significant single nucleotide polymorphisms (SNPs) identified near the MAPT and SNCA genes by GWAS [4]. To date, the functional variants driving such associations are unknown. We hypothesize that low frequency or rare coding variants can be identified by re-sequencing the MAPT and SNCA genes. In addition, deep-sequencing LRRK2 and GBA genes can not only identify additional untested coding risk variants but also protective alleles, as previously reported in these genes [17].

Highly penetrant mutations in the SNCA and LRRK2 genes are found in families with autosomal dominant inheritance, whereas autosomal recessive families with a typical PD phenotype carry mutations in the PARK2/PARKIN, PARK6/PINK1 and PARK7/DJ-1 genes [18]. Most genetic studies in PD have focused on sequencing a particular Mendelian gene in familial or early onset PD, or have directly screened few variants in sporadic PD cases in small samples [18]. A systematic study that sequences all of these genes (SNCA, LRRK2, PARK2, PINK1 and PARK7) in a large PD dataset has not been reported in European Americans [19, 20]. Thus, we used next-generation sequencing technology to re-sequence five Mendelian and the top GWAS susceptibility PD genes in a well-characterized case–control European American dataset (478 cases and 337 healthy controls) to identify both risk and protective low frequency or rare variants for PD.

Results

We performed pooled DNA-targeted deep-sequencing of the protein-coding regions of 7 genes, including 5 genes previously reported to most frequently cause familial forms of PD (SNCA, LRRK2, DJ-1, PARK2 and PINK1) and 2 genes that have significant associations in GWAS with sporadic PD (GBA and MAPT genes) in 478 PD patients and 337 healthy individuals of European-American descent from the Washington University in Saint Louis Movement Disorder Clinic (Table 1) [15, 21]. This cohort contains 83 % late-onset PD (LOPD) and 74 % sporadic PD cases.

Table 1 Summary of the sample demographics
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Rare variants in a European American case-control sample

We validated missense and splice-affecting variants with a predicted minor allele frequency (MAF) <5 %. In this European-American descent sample, a total of 47 low-frequency (0.5–5 %) and rare (<0.5 %) non-synonymous coding variants were validated. 36.2 % (17/47) of the variants are found in LRRK2, 21.2 % (10/47) in GBA, 17 % (8/47) in PARK2, 14.9 % (7/47) in PINK-1, 8.5 % (4/47) in MAPT and 2.1 % (1/47) in DJ-1 (Table 2). 70 % of these variants are either singletons (24/47) or doubletons (9/47).

Table 2 Summary of the variants found in the European-American case-control sample
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Novel variants

8.5 % (4/47) of the total variants are novel and not present in public databases (accessed on June 11th, 2015). All of the novel singleton variants located on LRRK2, p.D1887N and p.S885C, and GBA, p.T336S genes are present exclusively in LOPD patients (Table 3). The PINK1 p.R147C, variant was found in one control individual but was not present in public datasets.

Table 3 Summary of the individuals with novel variants in PD genes
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Copy number analysis

We observed a single structural genomic variant in a 70-year-old man with a family history of PD (1/126; 0.8 %; Fig. 1). B allele frequency and log R ratio indicate that this variant is an intra-chromosomal duplication at the SNCA locus. We did not identify this duplication, or any duplication at this locus, in control individuals. No other exonic rearrangements were observed in any PD patient in the PARK2, DJ-1 or PINK-1 loci.

Fig. 1
figure 1

SNCA duplication. The lower panel shows genotyping data from PD patient, generated using NeuroXchip. Shown is B Allele frequency for each single-nucleotide polymorphism (SNP) assayed, in which a value of 0 indicates a homozygous A/A genotype, a value of 1 indicates a homozygous B/B genotype, and a value of 0.5 represents a heterozygous A/B genotype. The highlighted region (pink) delimits the duplicated segment; within this region are a lack of heterozygous calls and clusters of points at a B allele frequency of ∼ 0.33 and ∼ 0.66, which, coupled with an increased log R ratio (upper panel), are indicative of A/A/B and A/B/B genotype calls, respectively. Figure plotted using R

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Known pathogenic variants

91.5 % (43/47) of the validated variants are reported in the PD mutation database [22]. Among the previously known variants, 7 % (3/43) are considered Mendelian pathogenic mutations for PD (LRRK2 p.G2019S, PINK1 p.R492X and PARK2 p.D53X) (Table 4). Six out of eight LRRK2 p.G2019S carriers reported PD family history. Thus, in this sample, 0.6 % (2/352) of the sporadic PD patients and a 4.8 % (6/126) of the familial PD subjects carry the LRRK2 p.G2019S mutation. The PARK2 p.D53X mutation heterozygous carrier is an EOPD patient with a positive family history. The PINK1 p.R492X heterozygous carrier is an asymptomatic 68-year old individual with no family history of PD (Table 4).

Table 4 Summary of the individuals with pathogenic mutations in PD genes
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Of all the previously known variants in all sequenced genes, 11.6 % (5/43) are located in the GBA gene (p.H294Q, p.D448H, p.N409S, p.L483P and p.A495P) and cause Gaucher disease (Table 2). We found that these variants are overrepresented in the PD patient sample, but did not reach statistical significance (p = 0.08; OR = 1.76, 95 % CI = 0.93–3.34). Two GBA variants, p.T408M and p.E365K, previously described as non-pathogenic polymorphisms for Gaucher disease, are significantly enriched (p = 0.01; OR = 2.35, 95 % CI = 1.19–4.66) in PD patients (7.5 %; 36/478) compared with controls (3.2 %; 11/337).

Variants of unclear and unknown pathogenicity

34.9 % (15/43) of the variants located on LRRK2 (four variants), PARK2 (six variants), PINK1 (4 variants) and PARK7 (one variant) have been reported previously and their pathogenicity is unclear (Table 2). Although the cumulative frequency of these variants is higher in PD patients (4.4 %) compared to controls (3.8 %), this difference is not statistically significant (p = 0.7; OR = 1.14, 95 % CI = 0.56–2.32), suggesting that either most of these variants are very unlikely to be true risk factors for PD or our sample size is not large enough to detect such differences.

There are 10 variants (21.3 %) with an unknown role in PD. In this cohort, 1.2 % of PD patients and 1.8 % of controls were found to carry one of these variants (p = 0.5; OR = 0.70, 95 % CI = 0.22–2.19).

The non-pathogenic variants, constituting 16.3 % (7/43) of the variants, were found in a similar proportion of PD patients (10 %) and controls (9.2 %) (p = 0.68; OR = 1.10, 95 % CI = 0.68–1.77), supporting their role as non-pathogenic.

Single-variant analysis

The minor allele of GBA p.T408M (p = 4.9 × 10−4) is associated with increased PD risk after multiple-testing correction (Table 2). The GBA p.T408M variant is present in 3.5 % (17/478) of the total number of PD cases and in none of the control group (Table 2). In addition, we found a nominal association with LRRK2 p.G2019S (p = 0.02) (Table 2). Using publicly available data from the exome variant server (EVS, European American) and Exome Aggregation Consortium (ExAc, European non-Finish) as controls, the variants p.T408M (p = 9.0 × 10−4; p = 1.0 × 10−2), p.L483P (p < 1.0 × 10−4; not found in ExAc), p.R83C (p = 1.0 × 10−2; p = 1.0 × 10−4), p.N409S (p = 2.0 × 10−2; p = 6.0 × 10−2), p.H294Q (p = 4.0 × 10−2; p = 1.0 × 10−2) and p.E365K (p = 4.0 × 10−2; p = 2.0 × 10−2) in the GBA gene, p.G2019S (p < 1.0 × 10−4; p < 1.0 × 10−4) and p.M1646T (not found in EVS; p = 3.0 × 10−2) in the LRRK2 gene and PINK1 p.N367S (Not found in EVS; p = 1.0 × 10−4) all achieved statistical significance in at least one of the control populations studied (Table 5).

Table 5 Frequency of validated variants in public databases
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The MAPT p.A152T variant has been associated with other neurodegenerative diseases including AD and frontotemporal dementia (FTD) [23]. In our study, the MAPT p.A152T variant occurs in 0.8 % (4/478) of PD cases but in none of the controls (0/337, p = 0.09).

Gene-burden analyses

To determine whether rare variants in the LRRK2, DJ1, PARK2, PINK1, GBA or MAPT genes contribute collectively to PD risk, we performed a gene-burden association test using the optimal SNP-set sequence kernel association test (SKAT-O) [24]. Gene-based association testing achieved significance for GBA (PSKAT-O = 7.0 × 10−4; OR = 2.28 (1.41–3.68). Importantly, the most commonly reported GBA risk variants (p.N409S and p.L483P) occur in 2.9 % (14/478) of the PD cases and in 0.9 % (3/337) of the controls (p = 0.05; OR = 3.35, 95 % CI = 0.95–11.8). When we exclude p.N409S and p.L483P from the analysis, the role of GBA in PD risk remains significant (p = 4.9 × 10−3; OR = 2.04, 95 % CI = 1.24–3.37), suggesting that additional variants in this gene also increase risk for PD. When we exclude p.T408M from the analysis, the risk of PD conferred by GBA variants is not significant (p = 0.39), which suggests that p.T408M may be the primary driver of the association with PD risk. These findings highlight the importance and necessity to sequence the entire GBA gene as opposed to genotyping only known risk variants for PD.

We also found a significant enrichment of coding variants in the LRRK2 gene in PD cases compared to controls (p = 0.01, OR = 1.86, 95 % CI = 1.14-3.02) (Table 6), which suggests that there are other risk variants in the LRRK2 gene in addition to the known pathogenic p.G2019S mutation.

Table 6 Gene-based analyses for Mendelian and GWAS PD genes
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No significance was found for the MATP2, PARKIN, PINK1 and DJ-1 genes

Effect on age at onset (AAO) of PD

GBA variant carriers tend to exhibit an earlier AAO than non-carriers [25]. Thus, we tested whether GBA variants affect AAO; we found that GBA variants carriers have a earlier AAO than non-carriers (54 years. vs. 62 years.; p < 0.0001) (Fig. 2a). Interestingly, when restricted to carriers and non-carriers of p.N408M using the same model, carriers had a 5.0-year-earlier onset than non-carriers (57 years. vs. 62 years.; p = 0.006) (Fig. 2b).

Fig. 2
figure 2

a. Cumulative incidence rates of PD among carriers and non-carriers of all GBA variants. b. Cumulative incidence rates of PD among carriers and non-carriers of the p.N408M variant. Survival fractions were calculated using the Kaplan-Meier method and significant differences were calculated by Log-rank test

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Discussion

Disease-causing variants in the SNCA, LRRK2, PARKIN, PINK1 and DJ-1 genes have been found in familial early onset forms of PD [18]. In this study, we systematically screened for rare variants and pathogenic mutations in the SNCA, LRRK2, PARK2, PINK1, PARK7, MAPT and GBA genes in a series of well-characterized PD case-control samples. A total of 47 low-frequency and rare non-synonymous coding variants were validated.

Most common pathogenic variants in this cohort

Nine individuals (1.9 %) of the total sample of PD patients carry a known pathogenic mutation in two Mendelian genes, LRRK2 p.G2019S and PARK2 p.D53X. Among patients with a family history of PD, 5.6 % (7/126) carry a known pathogenic mutation. In this cohort, we found that among the sequenced genes, the LRRK2 gene was enriched with multiple variants, accounting for 36.2 % of all the validated variants. The LRRK2 p.G2019S mutation is significantly associated with risk of PD and occurs in 1.7 % of PD patients. Interestingly, mutation carriers were clinically indistinguishable from idiopathic PD, which support the evidence for involvement of this gene in late-onset sporadic PD. A recent meta-analysis reported that the mean frequency of the LRRK2 p. G2019S mutation in sporadic PD patients among studies in the U.S. is 0.4 % [26]. Meanwhile, another international multi-center study reports only 49 of 8371 (0.6 %) PD patients of European and Asian origin carry the LRRK2 p. G2019S mutation [17]. Both frequencies are similar to the frequency reported here of 0.6 % (2/352) in sporadic PD patients. Our gene-based analysis found a significant association with the LRRK2 gene, which suggests that there are additional risk variants in LRRK2 affecting PD risk.

We also detected a SNCA locus duplication in a 70-year-old man with a family history of PD (1/126; 0.8 %; Fig. 1) and a 3-year history of parkinsonism. This PD patient exhibited clinical features indistinguishable from idiopathic PD. As expected, we found no coding mutations in the SNCA gene in this cohort. Point mutations in the SNCA gene are extremely rare and have been identified mostly in familial and EOPD [18]. The most common variation found in the SNCA gene are copy number variations (CNVs). SNCA duplications are not fully penetrant and are associated with variable clinical features, ranging from early-onset with dementia and psychiatric features to late-onset sporadic [27].

A recent report examining rare variants in the main Mendelian PD genes in a small case–control sample consisting of 249 cases and 145 controls of European origin (Spanish) found an enrichment of rare functional variants in PD cases [20]. They reported that up to 3.6 % of patients with sporadic PD are carriers of known pathogenic mutations in different Mendelian genes. The difference in the frequency of pathogenic mutations reported here (1.9 %) and that reported by Spataro (3.6 %) [20] is likely due to differences in methodology (exome sequencing data vs pooled-targeted sequencing) and to the different genetic background of the samples (Spanish vs North American).

Most common risk variants in this cohort

Heterozygous mutations in the GBA gene can be considered as low penetrance variants with autosomal dominant inheritance for PD [28]. In this study, fifty-three (11 %) of the PD patients and fifteen (4.5 %) controls carry heterozygous variants in the GBA gene (p = 1.0 × 10−3; OR = 2.17, 95 % CI = 1.36–3.46), which indicate that GBA coding variants increase risk for PD in this cohort. We also have demonstrated that those patients with PD carrying a GBA variant experience a disease onset 6 years earlier than patients without GBA variants. Interestingly, GBA variants mainly affect AAO of LOPD patients. Two GBA variants (p.N409S and p.L483P) have consistently been reported to be associated with increased PD risk in both, Ashkenazi Jewish and non-Ashkenazi populations [29]. Here, the p.N409S (MAF = 0.007) and p.L483P (MAF = 0.007) variants, are present in 2.9 % (14/478) of PD patients and 0.9 % (3/337) of controls. These allelic frequencies agree with previous reports [29]. We found that both variants are overrepresented in PD cases compared to controls, but they only reached statistical significance after including a larger control sample from publicly available databases. In addition, we report for the first time, an association between PD risk and the GBA variant p.T408M (MAF: 0.018). p.T408M is considered a polymorphism because it has been found in control populations [25, 30]. In this dataset, the GBA p.T408M variant drives the gene-based association with risk for PD. In the largest Non-Ashkenazi case–control sample studied to date, the GBA p.T408M variant was not significantly associated with PD [29]. This discrepancy could be explained by the heterogeneity of populations included in that study as it was enriched with individuals from populations in which the p.T408M variant is absent or very rare. The p.E365K allele is a hypomorphic variant (42.7 % of wild type activity) [31] often found in cis or trans with other Gaucher-causing non-synonymous mutations [32], exhibiting a frequency that is similar in controls and Gaucher patients [33]. We found that p.E365K achieves nominal significance (p = 0.02; OR = 1.69, 95 % CI = 1.06–2.67) after including controls from public databases. Interestingly, the OR found here is similar to those reported previously [33, 34]. Both p.T408M and p.E365K have been described as “mild” mutations or modifier alleles. In our study, we did not observe a “second” mutation that occurred with either p.T408M or p.E365K, which suggests a second hit may exist as an interacting factor, similar to those described in a traditionally considered non-pathogenic variant in AD [35]. Interestingly, we found seven PD patients carrying PD risk variants in two of all screened genes, further suggesting a double-hit mechanism impacting the risk for PD (Table 7), as reported by the presence of variants in the LRRK2 and GBA genes in PD patients [36].

Table 7 Individuals carrying two rare variants
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We also found that the MAPT p.A152T variant occurs in 0.8 % (4/478) of PD cases but in none of the controls (0/337, p = 0.09). It is possible that the MAPT p.A152T variant increases PD risk, but this association needs further confirmation in additional series.

Among the eight variants validated in PARK2, we found a stop-codon, p.D53X, in an EOPD (early onset PD) patient with a family history of PD. We also found one control individual carried the PINK1 (p.R492X) variant. We validated just a single variant DJ-1, p. A179T in a 56 year old PD patient with no family history of PD. All of these variants in recessive genes were found a heterozygous manner. Truly causative variants in PARK2, PINK1 or DJ-1 are present in a homozygous or heterozygous compound manner, but we cannot exclude the possible role of heterozygous variants on risk of sporadic PD. It is important to highlight that the most common pathogenic mutations in these genes are exon rearrangements or copy number variations. We did not detect exonic rearrangements in these genes in our cohort. The high proportion (83 %) of LOPD and sporadic cases (74 %) in our sample may explain the low number of validated variants found in the recessive genes.

Novel variants

We uncovered four novel variants (LRRK2, p.D1887N and p.S885C), (PINK1, p.R147C), and (GBA, p.T336S) in 0.8 % of PD cases. LRRK2, p.D1887N is located in the kinase domain and could play a functional role. The rareness of and the impossibility to expand the segregation studies with these variants to additional family members make its clinical interpretation challenging. However, finding novel variants in sporadic late onset PD suggests that it is possible to uncover such variants in genes linked to Mendelian PD or even in PD cases with an unclear pattern of inheritance. This is supported by our gene-based analysis, which demonstrates that additional untested variants in the GBA and LRRK2 genes contribute to the role of these genes in PD risk.

Conclusions

In summary, our results confirm the strong effect of GBA and LRRK2 on sporadic PD risk. However, our gene-based analyses demonstrates that non-synonymous GBA variants can have a greater impact on PD risk than LRRK2. In this cohort, the more common pathogenic mutations are located in the LRRK2 gene. Multiple GBA gene variants confer the highest risk for PD in our sample. We report novel interactions between variants in the GBA and LRRK2 genes as double hits affecting PD patients with no family history of PD. Our results also suggest that novel and untested variants in the GBA and LRRK2 genes influence PD risk. This has important implications on the genetic information provided to patients and families and potential new therapeutic approaches for PD patients. Our findings also strongly support the role of the lysosomal system as a pathogenic pathway in PD. Further work is necessary to clarify the role of specific and very rare variants in these genes on risk and PD phenotype.

Methods

Ethics statement

The Institutional Review Board (IRB) at the Washington University School of Medicine in Saint Louis approved the study. Prior to their participation, written informed consent was reviewed and obtained from family members. The Human Research Protection Office (HRPO) approval number for our ADRC Genetics Core family studies is 201104178.

Samples

Samples included 478 PD patients and 337 healthy individuals from the Washington University in Saint Louis Movement Disorder Clinic (MO, USA) [15, 21, 37]. All were examined by experienced movement disorder clinicians (J.S.P.). PD diagnosis was established according to the UK Brain Bank criteria.

Statistical and association analyses

For each variant, allele frequencies were calculated in cases and controls, and a χ2 test on allelic association was performed. A p-value of 0.05 was set as nominal significance threshold. The multiple-testing correction cutoff for the single-variant analysis using Bonferroni correction for 47 tests is 1.0 × 10−3 (0.05/47). We used Plink (http://pngu.mgh.harvard.edu/~purcell/plink/) to analyze associations [38]. The gene-based association was performed using SKAT-O, which utilizes the R package SKAT [24]. All variants were included in the model independent of their clinical interpretation. The influence of the genetic variants on AAO was carried out using the Kaplan-Meier method and tested for significant differences using a log-rank test.

Pooled-DNA sequencing experiment

Pooled-DNA sequencing was performed as described previously [35, 39, 40]. Briefly, equimolar amounts of individual DNA samples were pooled together after being measured using Quant-iT PicoGreen reagent. Two different pools with 100 ng of DNA from 114 and 98 individuals were made. The coding exons and flanking regions (a minimum of 50 bp each side) were individually PCR amplified using specific primers and Pfu Ultra high-fidelity polymerase (Stratagene). An average of 20 diploid genomes (approximately 0.14 ng DNA) per individual were used as input for a total of 62 PCR reactions that covered 46,319 bases from the 7 genes. PCR products were cleaned using QIAquick PCR purification kits, quantified using Quant-iT PicoGreen reagent and ligated in equimolar amounts using T4 Ligase and T4 Polynucleotide Kinase. After ligation, concatenated PCR products were randomly sheared by sonication and prepared for sequencing on an Illumina Genome Analyzer IIx (GAIIx) according to the manufacturer’s specifications. pCMV6-XL5 amplicon (1908 base pairs) was included as a negative control. As positive controls, ten different constructs (p53 gene) with synthetically engineered mutations at a relative frequency of one mutated copy per 250 normal copies were amplified and pooled with the PCR products. Six DNA samples heterozygous for previously known mutants in MAPT gene were also included. Single reads (36 bp) were aligned to the human genome reference assembly build 36.1 (hg18) using SPLINTER [41]. SPLINTER uses the positive control to estimate sensitivity and specificity for variant calling. The wild type: mutant ratio in the positive control is similar to the relative frequency expected for a single mutation in one pool (1 chromosome mutated in 125 samples = 1/250). SPLINTER uses the negative control (first 900 bp) to model the errors across the 36-bp Illumina reads and to create an error model from each sequencing run of the machine. Based on the error model, SPLINTER calculates a p-value for the probability that a predicted variant is a true positive. A p-value at which all mutants in the positive controls were identified was defined as the cut-off value for the best sensitivity and specificity. All mutants included as part of the amplified positive control vector were found upon achieving >30-fold coverage at mutated sites (sensitivity = 100 %) and only ∼ 80 sites in the 1908 bp negative control vector were predicted to be polymorphic (specificity = ∼95 %). The variants with a p-value below this cut-off value were considered for follow-up confirmation.

Genotyping

All rare missense or splice site variants identified by SPLINTER were validated by directly genotyping all sequenced individuals using Sequenom iPLEX or KASPar genotyping systems as described previously [42–44]. The validated SNPs were then genotyped in all members of the series. An average coverage of 30-fold per allele per pool is the minimum coverage necessary to obtain an optimal positive predictive value for the SNP-calling algorithm [41]. The necessary number of lanes to obtain a minimum of 30-fold coverage per base and sample were run.

Copy number variation analysis

The B Allele frequency and Log R Ratio were used to identify genomic deletions and duplications as previously described [45] using NeuroX chip data [46].

Bioinformatics

The PD mutation database [22] was used to identify sequence variants previously found in other studies of familial PD and to determine whether or not they are considered to be disease-causative variants. The EVS (http://evs.gs.washington.edu/EVS/), SeattleSeq Annotation (http://snp.gs.washington.edu/SeattleSeqAnnotation137/), The Exome Aggregation Consortium (ExAC) http://exac.broadinstitute.org/ (June 19, 2015) and the Ensembl Genome Database (http://useast.ensembl.org/index.html) were used to annotate the rare variants. Polyphen algorithms were used to predict the functional effect of the identified variants.

Population structure

A PCA was conducted to infer genetic structure of individuals who have GWAS data available using the EIGENSTRAT software as previously described [40]. Samples were excluded if not located within the EA cluster. Individuals who do not have GWAS data available were included in the study if the self-reported ethnicity was non-Hispanic European.

Abbreviations

AAO:

age at onset

AD:

Alzheimer’s disease

CI:

confidence interval

CNVs:

copy number variations

DJ-1:

Daisuke-Junko-1

EOPD:

early-onset Parkinson’s disease

EVS:

exome variant server

ExAc:

exome aggregation consortium

FTD:

frontotemporal dementia

GBA:

glucocerebrosidase beta acid

GWAS:

genome-wide association studies

LOPD:

late-onset Parkinson’s disease

LRRK2:

leucine-rich repeat kinase 2

MAF:

minor allele frequency

MAPT:

microtubule-associated protein tau

OR:

odd ratio

PD:

Parkinson’s disease

PINK1:

PTEN-induced putative kinase 1

SKAT-O:

SNP-set sequence kernel association test

SNCA:

α-synuclein

References

  1. Dorsey ER, Constantinescu R, Thompson JP, Biglan KM, Holloway RG, Kieburtz K, Marshall FJ, Ravina BM, Schifitto G, Siderowf A, Tanner CM. Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology. 2007;68:384–6.

    Article  CAS  PubMed  Google Scholar 

  2. Sharma M, Ioannidis JPA, Aasly JO, Annesi G, Brice A, Van Broeckhoven C, Bertram L, Bozi M, Crosiers D, Clarke C, Facheris M, Farrer M, Garraux G, Gispert S, Auburger G, Vilariño-Güell C, Hadjigeorgiou GM, Hicks AA, Hattori N, Jeon B, Lesage S, Lill CM, Lin JJ, Lynch T, Lichtner P, Lang AE, Mok V, Jasinska-Myga B, Mellick GD, Morrison KE, et al. Large-scale replication and heterogeneity in Parkinson disease genetic loci. Neurology. 2012;79:659–67.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Valadas JS, Vos M, Verstreken P. Therapeutic strategies in Parkinson’s disease: what we have learned from animal models. Ann N Y Acad Sci. 2015;1338:16–37.

    Article  CAS  PubMed  Google Scholar 

  4. Nalls MA, Pankratz N, Lill CM, Do CB, Hernandez DG, Saad M, DeStefano AL, Kara E, Bras J, Sharma M, Schulte C, Keller MF, Arepalli S, Letson C, Edsall C, Stefansson H, Liu X, Pliner H, Lee JH, Cheng R, International Parkinson’s Disease Genomics C, Parkinson’s Study Group Parkinson's Research: The Organized GenI, andMe, GenePd, NeuroGenetics Research C, Hussman Institute of Human G, Ashkenazi Jewish Dataset I, Cohorts for H, Aging Research in Genetic E, North American Brain Expression C, et al. Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease. Nat Genet. 2014;46:989–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Piccini P, Burn DJ, Ceravolo R, Maraganore D, Brooks DJ. The role of inheritance in sporadic Parkinson’s disease: evidence from a longitudinal study of dopaminergic function in twins. Ann Neurol. 1999;45:577–82.

    Article  CAS  PubMed  Google Scholar 

  6. Thacker EL, Ascherio A. Familial aggregation of Parkinson’s disease: a meta-analysis. Mov Disord. 2008;23:1174–83.

    Article  PubMed  Google Scholar 

  7. Do CB, Tung JY, Dorfman E, Kiefer AK, Drabant EM, Francke U, Mountain JL, Goldman SM, Tanner CM, Langston JW, Wojcicki A, Eriksson N. Web-based genome-wide association study identifies two novel loci and a substantial genetic component for parkinson’s disease. PLoS Genet. 2011;7:e1002141.

  8. Nalls MA, Plagnol V, Hernandez DG, Sharma M, Sheerin U-M, Saad M, Simón-Sánchez J, Schulte C, Lesage S, Sveinbjörnsdóttir S, Stefánsson K, Martinez M, Hardy J, Heutink P, Brice A, Gasser T, Singleton AB, Wood NW. Imputation of sequence variants for identification of genetic risks for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet. 2011;377:641–9.

    Article  PubMed  Google Scholar 

  9. Pastor P, Ezquerra M, Muñoz E, Martí MJ, Blesa R, Tolosa E, Oliva R. Significant association between the tau gene A0/A0 genotype and Parkinson’s disease. Ann Neurol. 2000;47:242–5.

    Article  CAS  PubMed  Google Scholar 

  10. Lill CM, Roehr JT, McQueen MB, Kavvoura FK, Bagade S, Schjeide BMM, Schjeide LM, Meissner E, Zauft U, Allen NC, Liu T, Schilling M, Anderson KJ, Beecham G, Berg D, Biernacka JM, Brice A, DeStefano AL, Do CB, Eriksson N, Factor SA, Farrer MJ, Foroud T, Gasser T, Hamza T, Hardy JA, Heutink P, Hill-Burns EM, Klein C, Latourelle JC, et al. Comprehensive research synopsis and systematic meta-analyses in Parkinson’s disease genetics: the PDgene database. PLoS Genet. 2012;8:e1002548.

  11. Mata IF, Yearout D, Alvarez V, Coto E, de Mena L, Ribacoba R, Lorenzo-Betancor O, Samaranch L, Pastor P, Cervantes S, Infante J, Garcia-Gorostiaga I, Sierra M, Combarros O, Snapinn KW, Edwards KL, Zabetian CP. Replication of MAPT and SNCA, but not p ARK16–18, as susceptibility genes for Parkinson’s disease. Mov Disord. 2011;26:819–23.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Keller MF, Saad M, Bras J, Bettella F, Nicolaou N, Simón-Sánchez J, Mittag F, Büchel F, Sharma M, Gibbs JR, Schulte C, Moskvina V, Durr A, Holmans P, Kilarski LL, Guerreiro R, Hernandez DG, Brice A, Ylikotila P, Stefansson H, Majamaa K, Morris HR, Williams N, Gasser T, Heutink P, Wood NW, Hardy J, Martinez M, Singleton AB, Nalls MA. Using genome-wide complex trait analysis to quantify “missing heritability” in Parkinson’s disease. Hum Mol Genet. 2012;21:4996–5009.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Shannon B, Soto-Ortolaza A, Rayaprolu S, Cannon HD, Labbé C, Benitez BA, Choi J, Lynch T, Boczarska-Jedynak M, Opala G, Krygowska-Wajs A, Barcikowska M, Van Gerpen JA, Uitti RJ, Springer W, Cruchaga C, Wszolek ZK, Ross OA. Genetic variation of the retromer subunits VPS26A/B-VPS29 in Parkinson’s disease. Neurobiol Aging. 2014;35:1958.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Benitez BA, Forero DA, Arboleda GH, Granados LA. Exploration of genetic susceptibility factors for Parkinson’ s disease in a South American sample. J Genet. 2010;89:229–32.

    Article  PubMed  Google Scholar 

  15. Davis AA, Andruska KM, Benitez BA, Racette BA, Perlmutter JS, Cruchaga C. Variants in GBA, SNCA, and MAPT influence Parkinson disease risk, age at onset, and progression. Neurobiol Aging. 2016;37:209.e1-7.

  16. De A, Duque AF, Lopez JC, Benitez B, Hernandez H, Yunis JJ, Fernandez W, Arboleda H, Arboleda G. Analysis of the LRRK2 p.G2019S mutation in Colombian Parkinson’ s disease patients. Colombia Médica. 2015;46:117–21.

  17. Ross OA, Soto-ortolaza AI, Heckman MG, Jan O, Abahuni N, Annesi G, Bacon JA, Bozi M, Brice A, Brighina L. Association of LRRK2 exonic variants with susceptibility to Parkinson’s disease: a case–control study. Lancet Neurol. 2011;10:898–908.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Petrucci S, Consoli F, Valente EM. Parkinson disease genetics: a “continuum” from Mendelian to multifactorial inheritance. Curr Mol Med. 2014;14:1079–88.

    Article  CAS  Google Scholar 

  19. Foo JN, Tan LC, Liany H, Koh TH, Irwan ID, Ng YY, Ahmad-Annuar A, Au WL, Aung T, Chan AYY, Chong SA, Chung SJ, Jung Y, Khor CC, Kim J, Lee J, Lim SY, Mok V, Prakash KM, Song K, Tai ES, Vithana EN, Wong TY, Tan EK, Liu J. Analysis of non-synonymous-coding variants of parkinson’s disease-related pathogenic and susceptibility genes in East Asian populations. Hum Mol Genet. 2014;23:3891–7.

    Article  CAS  PubMed  Google Scholar 

  20. Spataro N, Calafell F, Cervera-Carles L, Casals F, Pagonabarraga J, Pascual-Sedano B, Campolongo A, Kulisevsky J, Lleó A, Navarro A, Clarimón J, Bosch E. Mendelian genes for Parkinson’s disease contribute to the sporadic forms of the disease? Hum Mol Genet. 2014;24:2023–34.

    Article  PubMed  Google Scholar 

  21. Harms MB, Neumann D, Benitez BA, Cooper B, Carrell D, Racette BA, Perlmutter JS, Goate A, Cruchaga C. Parkinson disease is not associated with C9ORF72 repeat expansions. Neurobiol Aging. 2013;34:1519.e1-2.

  22. Cruts M, Theuns J, Van Broeckhoven C. Locus-specific mutation databases for neurodegenerative brain diseases. Hum Mutat. 2012;33:1340–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Coppola G, Chinnathambi S, Lee JJ, Dombroski BA, Baker MC, Soto-ortolaza AI, Lee SE, Klein E, Huang AY, Sears R, Lane JR, Karydas AM, Kenet RO, Biernat J, Wang LS, Cotman CW, Decarli CS, Levey AI, Ringman JM, Mendez MF, Chui HC, Leber I, Brice A, Lupton MK, Preza E, Lovestone S, Powell J, Graff-radford N, Petersen RC, Boeve BF, et al. Evidence for a role of the rare p.A152T variant in mapt in increasing the risk for FTD-spectrum and Alzheimer’s diseases. Hum Mol Genet. 2012;21:3500–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X. Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet. 2011;89:82–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Clark LN, Ross BM, Wang Y, Mejia-Santana H, Harris J, Louis ED, Cote LJ, Andrews H, Fahn S, Waters C, Ford B, Frucht S, Ottman R, Marder K. Mutations in the glucocerebrosidase gene are associated with early-onset Parkinson disease. Neurology. 2007;69:1270–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Correia Guedes L, Ferreira JJ, Rosa MM, Coelho M, Bonifati V, Sampaio C. Worldwide frequency of G2019S LRRK2 mutation in Parkinson’s disease: a systematic review. Parkinsonism Related Disord. 2010;16:237–42.

    Article  CAS  Google Scholar 

  27. Ahn TB, Kim SY, Kim JY, Park SS, Lee DS, Min HJ, Kim YK, Kim SE, Kim JM, Kim HJ, Cho J, Jeon BS. α-Synuclein gene duplication is present in sporadic Parkinson disease. Neurology. 2008;70:43–9.

    Article  CAS  PubMed  Google Scholar 

  28. Anheim M, Elbaz A, Lesage S, Durr A, Condroyer C, Viallet F, Pollak P, Bonaïti B, Bonaïti-Pellié C, Brice A. Penetrance of Parkinson disease in glucocerebrosidase gene mutation carriers. Neurology. 2012;78:417–20.

    Article  CAS  PubMed  Google Scholar 

  29. Sidransky E, Nalls MA, Aasly JO, Aharon-Peretz J, Annesi G, Barbosa ER, Bar-Shira A, Berg D, Bras J, Brice A, Chen C-M, Clark LN, Condroyer C, De Marco E V, Dürr A, Eblan MJ, Fahn S, Farrer MJ, Fung H-C, Gan-Or Z, Gasser T, Gershoni-Baruch R, Giladi N, Griffith A, Gurevich T, Januario C, Kropp P, Lang AE, Lee-Chen G-J, Lesage S, et al. Multicenter analysis of glucocerebrosidase mutations in Parkinson’s disease. N Engl J Med. 2009;361:1651–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lwin A, Orvisky E, Goker-Alpan O, LaMarca ME, Sidransky E. Glucocerebrosidase mutations in subjects with parkinsonism. Mol Genet Metab. 2004;81:70–3.

    Article  CAS  PubMed  Google Scholar 

  31. Chabás A, Gort L, Díaz-Font A, Montfort M, Santamaría R, Cidrás M, Grinberg D, Vilageliu L. Perinatal lethal phenotype with generalized ichthyosis in a type 2 gaucher disease patient with the [L444P;E326K]/P182L genotype: effect of the E326K change in neonatal and classic forms of the disease. Blood Cells Mol Dis. 2005;35:253–8.

    Article  PubMed  Google Scholar 

  32. Horowitz M, Pasmanik-Chor M, Ron I, Kolodny EH. The enigma of the E326K mutation in acid α-glucocerebrosidase. Mol Genet Metab. 2011;104:35–8.

    Article  CAS  PubMed  Google Scholar 

  33. Duran R, Mencacci NE, Angeli AV, Shoai M, Deas E, Houlden H, Mehta A, Hughes D, Cox TM, Deegan P, Schapira AH, Lees AJ, Limousin P, Jarman PR, Bhatia KP, Wood NW, Hardy J, Foltynie T. The glucocerobrosidase E326K variant predisposes to Parkinson’s disease, but does not cause Gaucher’s disease. Mov Disord. 2013;28:232–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Pankratz N, Beecham GW, Destefano AL, Dawson TM, Doheny KF, Factor SA, Hamza TH, Hung AY, Hyman BT, Ivinson AJ, Krainc D, Latourelle JC, Clark LN, Marder K, Martin ER, Mayeux R, Ross OA, Scherzer CR, Simon DK, Tanner C, Vance JM, Wszolek ZK, Zabetian CP, Myers RH, Payami H, Scott WK, Foroud T. Meta-analysis of Parkinson’s disease: identification of a novel locus, RIT2. Ann Neurol. 2012;71:370–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Benitez BA, Karch CM, Cai Y, Jin SC, Cooper B, Carrell D, Bertelsen S, Chibnik L, Schneider JA, Bennett DA, Fagan AM, Holtzman D, Morris JC, Goate AM, Cruchaga C. The PSEN1, p.E318G variant increases the risk of Alzheimer’s disease in APOE-ε4 carriers. PLoS Genet. 2013;9:e1003685.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Spitz M, Pereira JS, Nicareta DH, Abreu Gde M, Bastos EF, Seixas TL, Pimentel MMG. Association of LRRK2 and GBA mutations in a Brazilian family with Parkinson’s disease. Park Relat Disord. 2015;21:825–6.

    Article  Google Scholar 

  37. Benitez BA, Cruchaga C. United States–Spain Parkinson’s Disease Research Group. TREM2 and neurodegenerative disease. N Engl J Med. 2013;369:1567–8.

    PubMed  PubMed Central  Google Scholar 

  38. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Jin S, Pastor P, Cooper B, Cervantes S, Benitez BA, Razquin C, Goate A, Cruchaga C. Pooled-DNA sequencing identifies novel causative variants in PSEN1, GRN and MAPT in a clinical early-onset and familial Alzheimer’s disease Ibero-American cohort. Alzheimers Res Ther. 2012;4:34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Jin SC, Benitez B a, Karch CM, Cooper B, Skorupa T, Carrell D, Norton JB, Hsu S, Harari O, Cai Y, Bertelsen S, Goate AM, Cruchaga C. Coding variants in TREM2 increase risk for Alzheimer’s disease. Hum Mol Genet. 2014;23:5838-46.

  41. Vallania FLM, Druley TE, Ramos E, Wang J, Borecki I, Province M, Mitra RD. High-throughput discovery of rare insertions and deletions in large cohorts. Genome Res. 2010;20:1711–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Benitez BA, Cooper B, Pastor P, Jin S-C, Lorenzo E, Cervantes S, Cruchaga C. TREM2 is associated with the risk of Alzheimer’s disease in Spanish population. Neurobiol Aging. 2013;34:1711. e15-7.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Jin SC, Carrasquillo MM, Benitez BA, Skorupa T, Carrell D, Patel D, Lincoln S, Krishnan S, Kachadoorian M, Reitz C, Mayeux R, Wingo TS, Lah JJ, Levey AI, Murrell J, Hendrie H, Foroud T, Graff-Radford NR, Goate AM, Cruchaga C, Ertekin-Taner N. TREM2 is associated with increased risk for Alzheimer’s disease in African Americans. Mol Neurodegener. 2015;10:19.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Benitez BA, Cairns NJ, Schmidt RE, Morris JC, Norton JB, Cruchaga C, Sands MS. Clinically early-stage CSPα mutation carrier exhibits remarkable terminal stage neuronal pathology with minimal evidence of synaptic loss. Acta Neuropathol Commun. 2015;3:73.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Gibbs JR, Singleton A. Application of genome-wide single nucleotide polymorphism typing: simple association and beyond. PLoS Genet. 2006;2:1511–7.

    Article  CAS  Google Scholar 

  46. Nalls MA, Bras J, Hernandez DG, Keller MF, Majounie E, Renton AE, Saad M, Jansen I, Guerreiro R, Lubbe S, Plagnol V, Gibbs JR, Schulte C, Pankratz N, Sutherland M, Bertram L, Lill CM, DeStefano AL, Faroud T, Eriksson N, Tung JY, Edsall C, Nichols N, Brooks J, Arepalli S, Pliner H, Letson C, Heutink P, Martinez M, Gasser T, et al. NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases. Neurobiol Aging. 2015;36:1605. e7-e12.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

The authors thank the participants and their families, whose help and participation made this work possible. The authors wish to thank to Dr. Andrew B. Singleton for performing the copy number variation analysis reported in this manuscript. The authors wish to thank Susan Loftin and Karen Klumpp for their expert technical assistance. This work was supported by grants from NINDS (NS075321, NS041509, NS058714, and R01-AG035083); the Barnes Jewish Hospital Foundation (BJHF); the American Parkinson Disease Association (APDA) Advanced Research Center for Parkinson Disease at Washington University in St. Louis; the Greater St. Louis Chapter of the APDA; the Barnes Jewish Hospital Foundation (Elliot Stein Family Fund and Parkinson Disease Research Fund), The Michael J. Fox Foundation for Parkinson’s Research, Alzheimer’s Association and Weston Brain Institute (BAND-14-338165). This research was conducted while C.C. was a recipient of a New Investigator Award in Alzheimer’s disease from the American Federation for Aging Research. C.C. is a recipient of a BrightFocus Foundation Alzheimer’s Disease Research Grant (A2013359S). This study was supported by grants from the Spanish Ministry of Science and Innovation SAF2006-10126 (2006–2009), SAF2010-22329-C02-01 (2010–2012) and SAF2013-47939-R (2013–2016) to P.P. We thank Dr. Shonali Midha who provided editing of the manuscript.

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Authors and Affiliations

  1. Department of Internal Medicine, School of Medicine, Washington University, 8007, 660 South Euclid Avenue, St. Louis, MO, 63110, USA

    Bruno A. Benitez

  2. Department of Neurology, School of Medicine, Washington University, St. Louis, MO, USA

    Albert A. Davis & Joel S. Perlmutter

  3. Department of Psychiatry, School of Medicine, Washington University, St. Louis, MO, USA

    Sheng Chih Jin, Laura Ibanez, Jiyoon Choi, Breanna Cooper & Carlos Cruchaga

  4. Department of Neurology, Complejo Asistencial Universitario de Palencia, Palencia, Spain

    Sara Ortega-Cubero

  5. Center for Applied Medical Research (CIMA) University of Navarra School of Medicine, Pamplona, Spain and Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain

    Sara Ortega-Cubero & Pau Pastor

  6. Movement Disorders Unit, Department of Neurology, University Hospital Mutua de Terrassa, University of Barcelona, Terrassa, Barcelona, Spain

    Pau Pastor

  7. Department of Radiology, Anatomy & Neurobiology, Program in Occupational Therapy, Program in Physical Therapy, Washington University, St. Louis, MO, USA

    Joel S. Perlmutter

  8. Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University, St. Louis, MO, USA

    Joel S. Perlmutter & Carlos Cruchaga

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  1. Bruno A. Benitez
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  2. Albert A. Davis
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  10. Carlos Cruchaga
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Correspondence to Bruno A. Benitez.

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Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

BAB and CC conceived and designed the study. JSP, AAD, SOC, and PP acquired and analyzed the clinical data. BAB, JC, and BC acquired the genetic data. BAB, JSC, LI and CC performed the statistical analysis and interpreted the genetic data. BAB wrote the draft of the manuscript and JSP, AAD, SOC, PP, JC, BC, JSC, LI and CC provided critical comments on the draft of the manuscript. All authors read and approved the final version of the manuscript.

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Benitez, B.A., Davis, A.A., Jin, S.C. et al. Resequencing analysis of five Mendelian genes and the top genes from genome-wide association studies in Parkinson’s Disease. Mol Neurodegeneration 11, 29 (2016). https://doi.org/10.1186/s13024-016-0097-0

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Keywords

Molecular Neurodegeneration

ISSN: 1750-1326