Abstract:
Parkinson's disease (PD) is a neurodegenerative disease, the incidence of which increases with age. The prevalence of PD is rapidly increasing in the global aging population. With the increasing number of PD patients, the social and economic costs rise exponentially, emphasizing the immediate need to understand PD's pathogenesis and effective disease-modifying treatments (Tolosa et al. 2021; Trist, Hare, and Double 2019).
From the time PD was described by James Parkinson in 1817 to the present, several significant milestones have been reached. In 1912, Frederick Lewy discovered intracytoplasmic inclusion bodies ("Lewy bodies"), which were identified years later as the pathological hallmark of PD (Holdorff 2006, 2002). In 1957, Arvid Carlsson and Oleh Hornykiewicz pioneered the link between dopamine deficiency and PD (Fahn 2018; Hargittai 2023). In 1967, George Cotzias revolutionized high-dose levodopa therapy, leading to a breakthrough in the treatment of PD (Lees, Tolosa, and Olanow 2015; Patten 1983). In 1997, Polymeropoulos and colleagues identified the first mutation causing autosomal dominant PD in a large family that originated in Greece and immigrated to Italy. This gene mutation is a missense mutation (A53T) in the SNCA gene encoding α-synuclein (normal state of α-synuclein, same as below) protein located on chromosome 4q21-q23 (Polymeropoulos et al. 1997). Later, Spillantini and her colleagues discovered that α-synuclein is present in the Lewy bodies, a significant discovery that cemented the importance of α-synuclein and its central role in the pathogenesis of PD (Spillantini et al. 1997). A year after discovering the first mutation in the PD-associated gene SNCA, mutations in Parkin (PRKN) were found to cause autosomal recessive PD (Matsumine et al. 1997).
The discovery of PD triggered by a single gene mutation made PD as a complex disease that both rare and common genetic variants can influence. The heritability of PD is estimated to be about 35%, which includes risk factors such as GBA and MAPT etc. However, the variants identified by GWAS have modest effect sizes and collectively fail to account for current estimates of PD heritability. Larger sample sizes are required to identify other risk factors (Nalls et al. 2019). However, it also seems likely that additional rare alleles with larger effect sizes contribute to PD risk in the population (Blauwendraat, Nalls, and Singleton 2020).
Nalls et al. and Fu et al. have identified 90 significant risk variants across 78 genomic regions associated with PD in the European population and 2 from Asia population (Nalls et al. 2019; Foo et al. 2020). However, the underlying genes need to be known to develop disease-modifying therapeutic strategies. A complete list of candidate genes was generated in our lab after determining the associated genomic region flanking the associated single nucleotide polymorphisms (SNPs) based on linkage disequilibrium calculations, followed by determining the genes located in these regions. Our mission is to determine which of these genes under each locus are affected by the causal variants and how changes in the function or regulation of the causal genes lead to altered disease risk. Since most SNPs regulate the expression of one or more neighboring genes, their effect can be mimicked by gene knockdown using RNA interference (RNAi) technology or gene activation using clustered regularly interspaced short palindromic repeats (CRISPR) technology. In this study, gene knockdowns were performed by using RNAi technology, the effect of candidate genes on the change of mitochondrial dynamics on PD was investigated by performing mitochondrial morphology assay and Parkin translocation assay, the effect of candidate genes on α-synuclein proteins level was investigated by performing α-synuclein enzyme-linked immunosorbent assay (ELISA). In addition, mRNA sequencing was performed to determine the knockdown efficiency and the effect of gene knockdown on molecular pathways to learn more about potential novel PD-relevant pathways.
The robust strictly standardized median difference (SSMD) was calculated for hit selection of mitochondrial morphology assay and Parkin translocation assay. Effects were considered significant when most of the shRNAs targeting one gene the SSMD ≥ 3 or ≤-3. The percentage of increased or decreased α-synuclein protein was calculated for hit selection of α-synuclein ELISA assay. Effects were considered significant when the percentage of increase of α-synuclein protein is ≥ 50% of negative control, or the decrease of α-synuclein protein is ≤ 50% of negative control for each treatment. Based on the result of functional assay and mRNA sequencing, a subset of priority genes per locus was selected from this study.
The data from this study helped us narrow down the list of risk genes for PD and suggested possible causative genes in each of the 78 known risk loci. Not only that, this study may also provide us with novel causative genes or novel roles of some genes in PD. Another critical point of this study is that our approach highlights a powerful experimental strategy that has broad applicability in future studies of diseases with complex genetic etiologies. The selection of priority genes from a large number of candidates has advanced the study of the PD genome, but there is still some way to go before we can identify the actual causative genes. To achieve this goal, targeted experiments need to be designed to validate these prioritized genes. The future of PD-targeted therapy is bright as our understanding and research continue to advance.
GWAS
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