2015
DOI: 10.1038/ejhg.2015.228
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Identification of candidate genes for familial early-onset essential tremor

Abstract: Essential tremor (ET) is one of the most common causes of tremor in humans. Despite its high heritability and prevalence, few susceptibility genes for ET have been identified. To identify ET genes, whole-exome sequencing was performed in 37 early-onset ET families with an autosomal-dominant inheritance pattern. We identified candidate genes for follow-up functional studies in five ET families. In two independent families, we identified variants predicted to affect function in the nitric oxide (NO) synthase 3 g… Show more

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Cited by 37 publications
(38 citation statements)
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“…For example, early onset ET cases might differ in their rates of progression and their tremor-related brain oscillatory circuits when compared to late onset ET cases [13,14]. The presence of family history in ET might indicate an underlying genetic etiology [15,16] as well as possible differences in the ability to metabolize naturally-occurring tremorgenic compounds [17]. In addition, ET cases with head tremor might have different degrees of cerebellar involvement than ET cases without head tremor, based on neuroimaging findings [18].…”
Section: Introductionmentioning
confidence: 99%
“…For example, early onset ET cases might differ in their rates of progression and their tremor-related brain oscillatory circuits when compared to late onset ET cases [13,14]. The presence of family history in ET might indicate an underlying genetic etiology [15,16] as well as possible differences in the ability to metabolize naturally-occurring tremorgenic compounds [17]. In addition, ET cases with head tremor might have different degrees of cerebellar involvement than ET cases without head tremor, based on neuroimaging findings [18].…”
Section: Introductionmentioning
confidence: 99%
“…Phenolyzer includes multiple components, including a tool to map the user-supplied phenotype to related disease, a resource that integrates existing knowledge on disease genes, an algorithm to predict previously unknown disease genes, a machine learning model that integrates multiple features to score and prioritize candidate genes and a network visualization tool to examine gene-gene and gene-disease relationships [39]. Previously, we performed WES [15] on a subset of the families (Families A, B, E and F) included in the current WGS analysis. For these families, WES did not identify the candidate genes identified in the current WGS study.…”
Section: Discussionmentioning
confidence: 99%
“…WGS which forgoes capturing is less sensitive to GC content and is more likely than WES to provide complete coverage of the entire coding region. Other factors that can affect variant and candidate gene identification include the bioinformatics pipeline (GATK version and implementation options) used and statistical analysis methods (WES study pVAAST [15, 45] versus WGS in the current study: MM-KBAC [45]).…”
Section: Discussionmentioning
confidence: 99%
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“…In contrast to linkage analysis WES may also be applied in smaller families with fewer generations. So far this method has been applied in several ET families [58][59][60][61]. The genes are listed in Table 1.…”
Section: Geneticsmentioning
confidence: 99%