A Clinical and Molecular Genetic Study of 50 Families with Autosomal Recessive Parkinsonism Revealed Known and Novel Gene Mutations

(2018) A Clinical and Molecular Genetic Study of 50 Families with Autosomal Recessive Parkinsonism Revealed Known and Novel Gene Mutations. Molecular Neurobiology. pp. 3477-3489. ISSN 1559-1182 (Electronic) 0893-7648 (Linking)

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Abstract

In this study, the role of known Parkinson's disease (PD) genes was examined in families with autosomal recessive (AR) parkinsonism to assist with the differential diagnosis of PD. Some families without mutations in known genes were also subject to whole genome sequencing with the objective to identify novel parkinsonism-related genes. Families were selected from 4000 clinical files of patients with PD or parkinsonism. AR inheritance pattern, consanguinity, and a minimum of two affected individuals per family were used as inclusion criteria. For disease gene/mutation identification, multiplex ligation-dependent probe amplification, quantitative PCR, linkage, and Sanger and whole genome sequencing assays were carried out. A total of 116 patients (50 families) were examined. Fifty-four patients (46.55; 22 families) were found to carry pathogenic mutations in known genes while a novel gene, not previously associated with parkinsonism, was found mutated in a single family (2 patients). Pathogenic mutations, including missense, nonsense, frameshift, and exon rearrangements, were found in Parkin, PINK1, DJ-1, SYNJ1, and VAC14 genes. In conclusion, variable phenotypic expressivity was seen across all families.

Item Type: Article
Keywords: Early-onset Genotype-phenotype correlations Parkinson's disease Pathogenic mutations
Divisions: Faculty of Medicine > Departments of Clinical Sciences > Department of Neurology
Page Range: pp. 3477-3489
Journal or Publication Title: Molecular Neurobiology
Journal Index: Pubmed, ISI
Volume: 55
Number: 4
Identification Number: https://doi.org/10.1007/s12035-017-0535-1
ISSN: 1559-1182 (Electronic) 0893-7648 (Linking)
Depositing User: مهندس مهدی شریفی
URI: http://eprints.mui.ac.ir/id/eprint/1569

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