Parkinson’s disease (PD) is a complex disorder underpinned by both environmental and genetic factors. The latter only began to be understood around two decades ago, but since then great inroads have rapidly been made into deconvoluting the genetic component of PD. In particular, recent large-scale projects such as genome-wide association (GWA) studies have provided insight into the genetic risk factors associated with genetically ‘’complex’’ PD (PD that cannot readily be attributed to single deleterious mutations). Here, we discuss the plethora of genetic information provided by PD GWA studies and how this may be utilized to generate polygenic risk scores (PRS), which may be used in the prediction of risk and trajectory of PD. We also comment on how pathway-specific genetic profiling can be used to gain insight into PD-related biological pathways, and how this may be further utilized to nominate causal PD genes and potentially druggable therapeutic targets. Finally, we outline the current limits of our understanding of PD genetics and the potential contribution of variation currently uncaptured in genetic studies, focusing here on uncatalogued structural variants.

The hominid SINE-VNTR-Alu (SVA) retrotransposons represent a repertoire of genomic variation which could have significant effects on genome function. A human-specific SVA in the promoter region of the gene leucine-rich repeats and immunoglobulin-like domains 2 (LRIG2), which we termed SVA_LRIG2, is a common retrotransposon insertion polymorphism (RIP), defined as an element which is polymorphic for its presence or absence in the genome. We hypothesised that this RIP might be associated with differential levels of expression of LRIG2. The RIP genotype of SVA_LRIG2 was determined in a subset of frontal cortex DNA samples from the North American Brain Expression Consortium (NABEC) cohort and was imputed for a larger set of that cohort. Utilising available frontal cortex total RNA-seq and CpG methylation data for this cohort, we observed that increased allele dosage of SVA_LRIG2 was non-significantly associated with a decrease in transcription from the region and significantly associated with increased methylation of the CpG probe nearest to SVA_LRIG2, i.e., SVA_LRIG2 is a significant methylation quantitative trait loci (mQTL) at the LRIG2 locus. These data are consistent with SVA_LRIG2 being a transcriptional regulator, which in part may involve epigenetic modulation.

SINE-VNTR-Alu (SVA) retrotransposons represent mobile regulatory elements that have the potential to influence the surrounding genome when they insert into a locus. Evolutionarily recent mobilisation has resulted in loci in the human genome where a given retrotransposon might be observed to be present or absent, termed a retrotransposon insertion polymorphism (RIP). We previously observed that an SVA RIP ~ 2 kb upstream of LRIG2 on chromosome 1, the ‘LRIG2 SVA’, was associated with differences in local gene expression and methylation, and that the two were correlated. Here, we have used CRISPR-mediated deletion of the LRIG2 SVA in a cell line model to validate that presence of the retrotransposon is directly affecting local expression and provide evidence that is suggestive of a modest role for the SVA in modulating nearby methylation. Additionally, in leveraging an available Hi-C dataset we observed that the LRIG2 SVA was also involved in long-range chromatin interactions with a cluster of genes ~ 300 kb away, and that expression of these genes was to varying degrees associated with dosage of the SVA in both CRISPR cell line and population models. Altogether, these data support a regulatory role for SVAs in the modulation of gene expression, with the latter potentially involving chromatin looping, consistent with the model that RIPs may contribute to interpersonal differences in transcriptional networks.

Parkinson’s disease (PD) is a neurodegenerative disease with an often complex genetic component identifiable by genome-wide association studies (GWAS). The most recent large scale PD GWASes have identified more than 90 independent risk variants for PD risk and progression across 80 loci. One major challenge in current genomics is identifying the causal gene(s) and variant(s) from each GWAS locus. Here we present a GWAS locus browser application that combines data from multiple databases to aid in the prioritization of genes associated with PD GWAS loci. We included 92 independent genome-wide significant signals from multiple recent PD GWAS studies including the PD risk GWAS, age-at-onset GWAS and progression GWAS. We gathered data for all 2336 genes within 1Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Our aim is that the information contained in this browser ( https://pdgenetics.shinyapps.io/GWASBrowser/ ) will assist the PD research community with the prioritization of genes for follow-up functional studies and as potential therapeutic targets.