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Background: Mendelian randomization (MR) is a method for exploring observational associations to find evidence of causality. Objective: To apply MR between multiple risk factors/phenotypic traits (exposures) and Parkinson disease (PD) in a large, unbiased manner, and to create a public resource for research. Methods: We used two-sample MR in which the summary statistics relating to SNPs from genome wide association studies (GWASes) of 5,839 exposures curated on MR-Base were used to assess causal relationships with PD. We selected the highest quality exposure GWASes for this report (n=401). For the disease outcome, summary statistics from the largest published PD GWAS were used. For each exposure, the causal effect on PD was assessed using the inverse variance weighted (IVW) method, followed by a range of sensitivity analyses. We used a false discovery rate (FDR) corrected p-value of <0.05 from the IVW analysis to prioritise traits of interest. Results: We observed evidence for causal associations between twelve exposures and risk of PD. Of these, nine were inverse causal effects related to increasing adiposity and decreasing risk of PD. The remaining top exposures that affected PD risk were tea drinking, time spent watching television and forced vital capacity, but the latter two appeared to be biased by violation of underlying MR assumptions. Discussion: We present a new platform which offers MR analyses for a total of 5,839 GWASes versus the largest PD GWASes available (https://pdgenetics.shinyapps.io/pdgenetics/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD.

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