New endemic familial parkinsonism in south Moravia, Czech Republic and its genetical background

Endemic parkinsonism: clusters, biology and clinical features

The term 'endemic parkinsonism' refers to diseases that manifest with a dominant parkinsonian syndrome, which can be typical or atypical, and are present only in a particular geographically defined location or population. Ten phenotypes of endemic parkinsonism are currently known: three in the Western Pacific region; two in the Asian-Oceanic region; one in the Caribbean islands of Guadeloupe and Martinique; and four in Europe. Some of these disease entities seem to be disappearing over time and therefore are probably triggered by unique environmental factors. By contrast, other types persist because they are exclusively genetically determined. Given the geographical clustering and potential overlap in biological and clinical features of these exceptionally interesting diseases, this Review provides a historical reference text and offers current perspectives on each of the 10 phenotypes of endemic parkinsonism. Knowledge obtained from the study of these disease entities supports the hypothesis that both genetic and environmental factors contribute to the development of neurodegenerative diseases, not only in endemic parkinsonism but also in general. At the same time, this understanding suggests useful directions for further research in this area.

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

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.

Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.

Association study of DNAJC13, UCHL1, HTRA2, GIGYF2, and EIF4G1 with Parkinson's disease

Rare mutations in genes originally discovered in multigenerational families have been associated with increased risk of Parkinson's disease (PD). The involvement of rare variants in DNAJC13, UCHL1, HTRA2, GIGYF2, and EIF4G1 loci has been poorly studied or has produced conflicting results across cohorts. However, they are still being often referred to as "PD genes" and used in different models. To further elucidate the role of these 5 genes in PD, we fully sequenced them using molecular inversion probes in 2408 patients with PD and 3444 controls from 3 different cohorts. A total of 788 rare variants were identified across the 5 genes and 3 cohorts. Burden analyses and optimized sequence Kernel association tests revealed no significant association between any of the genes and PD after correction for multiple comparisons. Our results do not support an association of the 5 tested genes with PD. Combined with previous studies, it is unlikely that any of these genes plays an important role in PD. Their designation as "PARK" genes should be reconsidered.