Next Generation Sequencing Data Analysis Evaluation in Patients with Parkinsonism from a Genetically Isolated Population

Vodička, Radek; Vrtěl, Radek; Menšíková, Kateřina; Kaňovský, Petr; Dolinová, Iva; Kolaříková, Kristýna; Procházka, Martin

doi:10.18547/gcb.2017.vol3.iss3.e44

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…Additionally, NGS data is frequently combined with other sources to derive more powerful conclusions. For instance, the manuscript presented in this special issue by Vodicka et al compares two NGS data analyses and epidemiological data in order to investigate prevalence of Parkinson' disease in Czech Republic [4]. After integration, authors were able to highlight three statistically significant missense mutations associated to the disease.…”

Section: Highlightsmentioning

confidence: 99%

Highlights from the International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO) – 2015 and 2016 Editions

Guzman

Rojas

2018

Genomics Comput Biol

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Section: Highlightsmentioning

confidence: 99%

Highlights from the International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO) – 2015 and 2016 Editions

Guzman

Rojas

2018

Genomics Comput Biol

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Evaluating Basic Next-Generation Sequencing Parameters in Relation to True/False Positivity Findings of Rare Variants in an Isolated Population from the Czech Republic South-Eastern Moravia Region with a High Incidence of Parkinsonism

Vodička

Kolaříková

Vrtěl

et al. 2020

Bioinformatics and Biomedical Engineering

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High-Throughput Sequencing Haplotype Analysis Indicates in LRRK2 Gene a Potential Risk Factor for Endemic Parkinsonism in Southeastern Moravia, Czech Republic

Kolaříková

Vodička

Vrtěl

et al. 2022

Life

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Parkinson’s disease and parkinsonism are relatively common neurodegenerative disorders. This study aimed to assess potential genetic risk factors of haplotypes in genes associated with parkinsonism in a population in which endemic parkinsonism and atypical parkinsonism have recently been found. The genes ADH1C, EIF4G1, FBXO7, GBA, GIGYF2, HTRA2, LRRK2, MAPT, PARK2, PARK7, PINK1 PLA2G6, SNCA, UCHL1, and VPS35 were analyzed in 62 patients (P) and 69 age-matched controls from the researched area (C1). Variants were acquired by high-throughput sequencing using Ion Torrent workflow. As another set of controls, the whole genome sequencing data from 100 healthy non-related individuals from the Czech population were used (C2); the results were also compared with the Genome Project data (C3). We observed shared findings of four intron (rs11564187, rs36220738, rs200829235, and rs3789329) and one exon variant (rs33995883) in the LRRK2 gene in six patients. A comparison of the C1–C3 groups revealed significant differences in haplotype frequencies between ratio of 2.09 for C1, 1.65 for C2, and 6.3 for C3, and odds ratios of 13.15 for C1, 2.58 for C2, and 7.6 for C3 were estimated. The co-occurrence of five variants in the LRRK2 gene (very probably in haplotype) could be an important potential risk factor for the development of parkinsonism, even outside the recently described pedigrees in the researched area where endemic parkinsonism is present.

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Next Generation Sequencing Data Analysis Evaluation in Patients with Parkinsonism from a Genetically Isolated Population

Cited by 3 publications

References 38 publications

Highlights from the International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO) – 2015 and 2016 Editions

Highlights from the International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO) – 2015 and 2016 Editions

Evaluating Basic Next-Generation Sequencing Parameters in Relation to True/False Positivity Findings of Rare Variants in an Isolated Population from the Czech Republic South-Eastern Moravia Region with a High Incidence of Parkinsonism

High-Throughput Sequencing Haplotype Analysis Indicates in LRRK2 Gene a Potential Risk Factor for Endemic Parkinsonism in Southeastern Moravia, Czech Republic

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