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[Preprint]. 2024 Dec 14:2024.12.13.24318996.
doi: 10.1101/2024.12.13.24318996.

Prioritizing Parkinson's disease risk genes in genome-wide association loci

Affiliations

Prioritizing Parkinson's disease risk genes in genome-wide association loci

Lara M Lange et al. medRxiv. .

Update in

Abstract

Recent advancements in Parkinson's disease (PD) drug development have been significantly driven by genetic research. Importantly, drugs supported by genetic evidence are more likely to be approved. While genome-wide association studies (GWAS) are a powerful tool to nominate genomic regions associated with certain traits or diseases, pinpointing the causal biologically relevant gene is often challenging. Our aim was to prioritize genes underlying PD GWAS signals. The polygenic priority score (PoPS) is a similarity-based gene prioritization method that integrates genome-wide information from MAGMA gene-level association tests and more than 57,000 gene-level features, including gene expression, biological pathways, and protein-protein interactions. We applied PoPS to data from the largest published PD GWAS in East Asian- and European-ancestries. We identified 120 independent associations with P < 5×10-8 and prioritized 46 PD genes across these loci based on their PoPS scores, distance to the GWAS signal, and presence of non-synonymous variants in the credible set. Alongside well-established PD genes (e.g., TMEM175 and VPS13C), some of which are targeted in ongoing clinical trials (i.e., SNCA, LRRK2, and GBA1), we prioritized genes with a plausible mechanistic link to PD pathogenesis (e.g., RIT2, BAG3, and SCARB2). Many of these genes hold potential for drug repurposing or novel therapeutic developments for PD (i.e., FYN, DYRK1A, NOD2, CTSB, SV2C, and ITPKB). Additionally, we prioritized potentially druggable genes that are relatively unexplored in PD (XPO1, PIK3CA, EP300, MAP4K4, CAMK2D, NCOR1, and WDR43). We prioritized a high-confidence list of genes with strong links to PD pathogenesis that may represent our next-best candidates for disease-modifying therapeutics. We hope our findings stimulate further investigations and preclinical work to facilitate PD drug development programs.

Keywords: Parkinson’s disease; PoPS; gene prioritization; genome-wide association study; statistical genetics.

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Conflict of interest statement

Competing interests LML, CCC, JK, AB, SA, GP, MS, NB, DP, SR and CB have nothing to disclose. KH is a former employee of 23andMe, Inc. and a current employee of Bayer AG.

Figures

Figure 1.
Figure 1.. Heatmap of prioritized Parkinson’s disease genes.
An overview of the evidence supporting each prioritized gene. Distance: distance in kilobases between gene and credible set. PoPS: PoPS percentile where 0 represents the smallest genome-wide value and 1 represents the largest. MAGMA: # genes: number of genes in the locus. L2G: Probability of being the causal genes according to the L2G model. Yu2024: Probability of being the causal genes according to the Yu2024 model.
Figure 2.
Figure 2.. Small molecule target tractability assessment.
Predicted tractability of the 38 prioritized genes that are not already targets of approved or investigational drugs. Data was extracted from the Open Targets platform using GraphQL API queries (https://platform.opentargets.org/) (see Methods). Various forms of evidence that suggest that a target may be tractable are shown on the x-axis, sorted from highest quality to lowest. Structure with Ligand: a Protein Data Bank co-crystal structure exists for the target and a small molecule. High-Quality Ligand: the target is bound by a ligand that 1) has a property forecast index ≤ 7, 2) binds ≤ 2 distinct protein domains and motifs identified by SMART (Simple Modular Architecture Research Tool), and 3) is derived from ≥ 2 distinct chemical scaffolds. High-Quality Pocket: the target has a DrugEBIlity score ≥ 0.7. Med-Quality Pocket: the target has a DrugEBIlity score 0–0.7. Druggable Family: the target was reported to be a member of the druggable genome in Finan et al. 2017. Light green cells indicate that a given gene is supported by a given form of evidence, while dark green cells indicate an absence of such evidence. For more information on ongoing targeted drug trials for a selection of genes, see Supplementary Table 3.
Figure 3.
Figure 3.. Variant-level associations and PoPS results for selected loci.
The upper portion of each sub-plot is a LocusZoom plot. Each point represents a different genetic variant, the x-axis represents physical position on the listed chromosome, the left y-axis represents −log10-transformed P value, the right y-axis represents the recombination rate, colour represents linkage disequilibrium with the lead variant in the locus (as shown in the legend), and the horizontal dashed line represents the genome-wide significance P value threshold of 5×10−8. The lower portion of each figure is a PoPS plot. Genes are denoted as blue bars spanning from their transcription start site to their transcription stop site using the same x-axis as the LocusZoom plot, the y-axis represents the raw PoPS score, the dashed horizontal grey lines represent the top 10% and 1% of PoPS scores genome-wide, and the solid horizontal grey line represents a PoPS score of 0.

References

    1. GBD 2016 Parkinson’s Disease Collaborators. Global, regional, and national burden of Parkinson’s disease, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018;17(11):939–953. - PMC - PubMed
    1. Periñán MT, Brolin K, Bandres-Ciga S, et al. Effect Modification between Genes and Environment and Parkinson’s Disease Risk. Ann Neurol. 2022;92(5):715–724. - PMC - PubMed
    1. Neumann WJ, Horn A, Kühn AA. Insights and opportunities for deep brain stimulation as a brain circuit intervention. Trends Neurosci. 2023;46(6):472–487. - PubMed
    1. Davidson B, Milosevic L, Kondrataviciute L, Kalia LV, Kalia SK. Neuroscience fundamentals relevant to neuromodulation: Neurobiology of deep brain stimulation in Parkinson’s disease. Neurotherapeutics. 2024;21(3):e00348. - PMC - PubMed
    1. McFarthing K, Buff S, Rafaloff G, et al. Parkinson’s Disease Drug Therapies in the Clinical Trial Pipeline: 2023 Update. J Parkinsons Dis. 2023;13(4):427–439. - PMC - PubMed

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