Dataset Information

Common and rare GCH1 variants are associated with Parkinson's disease.

ABSTRACT: GCH1 encodes the enzyme guanosine triphospahte (GTP) cyclohydrolase 1, essential for dopamine synthesis in nigrostriatal cells, and rare mutations in GCH1 may lead to Dopa-responsive dystonia (DRD). While GCH1 is implicated in genomewide association studies in Parkinson's disease (PD), only a few studies examined the role of rare GCH1 variants in PD, with conflicting results. In the present study, GCH1 and its 5' and 3' untranslated regions were sequenced in 1113 patients with PD and 1111 controls. To examine the association of rare GCH1 variants with PD, burden analysis was performed. Three rare GCH1 variants, which were previously reported to be pathogenic in DRD, were found in five patients with PD and not in controls (sequence Kernel association test, p = 0.024). A common haplotype, tagged by rs841, was associated with a reduced risk for PD (OR = 0.71, 95% CI = 0.61-0.83, p = 1.24 × 10-4), and with increased GCH1 expression in brain regions relevant for PD (www.gtexportal.org). Our results support a role for rare, DRD-related variants, and common GCH1 variants in the pathogenesis of PD.

SUBMITTER: Rudakou U

PROVIDER: S-EPMC6251729 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Common and rare GCH1 variants are associated with Parkinson's disease.

Rudakou Uladzislau U Ouled Amar Bencheikh Bouchra B Ruskey Jennifer A JA Krohn Lynne L Laurent Sandra B SB Spiegelman Dan D Liong Christopher C Fahn Stanley S Waters Cheryl C Monchi Oury O Fon Edward A EA Dauvilliers Yves Y Alcalay Roy N RN Dupré Nicolas N Gan-Or Ziv Z

Neurobiology of aging 20180915

GCH1 encodes the enzyme guanosine triphospahte (GTP) cyclohydrolase 1, essential for dopamine synthesis in nigrostriatal cells, and rare mutations in GCH1 may lead to Dopa-responsive dystonia (DRD). While GCH1 is implicated in genomewide association studies in Parkinson's disease (PD), only a few studies examined the role of rare GCH1 variants in PD, with conflicting results. In the present study, GCH1 and its 5' and 3' untranslated regions were sequenced in 1113 patients with PD and 1111 contro ...[more]

PMID: 30314816

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Project description:BackgroundGenome-wide association studies have been successful in identifying common genetic variants for human diseases. However, much of the heritable variation associated with diseases such as Parkinson's disease remains unknown suggesting that many more risk loci are yet to be identified. Rare variants have become important in disease association studies for explaining missing heritability. Methods for detecting this type of association require prior knowledge on candidate genes and combining variants within the region. These methods may suffer from power loss in situations with many neutral variants or causal variants with opposite effects.ResultsWe propose a method capable of scanning genetic variants to identify the region most likely harbouring disease gene with rare and/or common causal variants. Our method assigns a score at each individual variant based on our scoring system. It uses aggregate scores to identify the region with disease association. We evaluate performance by simulation based on 1000 Genomes sequencing data and compare with three commonly used methods. We use a Parkinson's disease case-control dataset as a model to demonstrate the application of our method. Our method has better power than CMC and WSS and similar power to SKAT-O with well-controlled type I error under simulation based on 1000 Genomes sequencing data. In real data analysis, we confirm the association of α-synuclein gene (SNCA) with Parkinson's disease (p = 0.005). We further identify association with hyaluronan synthase 2 (HAS2, p = 0.028) and kringle containing transmembrane protein 1 (KREMEN1, p = 0.006). KREMEN1 is associated with Wnt signalling pathway which has been shown to play an important role for neurodegeneration in Parkinson's disease.ConclusionsOur method is time efficient and less sensitive to inclusion of neutral variants and direction effect of causal variants. It can narrow down a genomic region or a chromosome to a disease associated region. Using Parkinson's disease as a model, our method not only confirms association for a known gene but also identifies two genes previously found by other studies. In spite of many existing methods, we conclude that our method serves as an efficient alternative for exploring genomic data containing both rare and common variants.

Dataset Information

Common and rare GCH1 variants are associated with Parkinson's disease.

Publications

Common and rare GCH1 variants are associated with Parkinson's disease.

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