Risky behaviors and Parkinson’s disease: A Mendelian randomization study in up to 1 million study participants

Abstract

Objective: Dopaminergic neurotransmission is known to be a potential modulator of risky behaviors including substance abuse, promiscuity, and gambling. Furthermore, observational studies have shown associations between risky behaviors and Parkinson's disease; however, the causal nature of these associations remains unclear. Thus, in this study, we examine causal associations between risky behavior phenotypes on Parkinson's disease using a Mendelian Randomization approach.Methods: We used two-sample Mendelian randomization to generate unconfounded estimates using summary statistics from two independent, large meta-analyses of genome-wide association studies on risk taking behaviors (n=370,771-939,908) and Parkinson's disease (cases: n=4127, controls: n = 62,037). We used inverse variance weighted as the main method for judging causality. Results:Our results support a strong protective association between the tendency to smoke and Parkinson's disease (OR=0.714 per log odds of ever smoking; 95% CI=0.568-0.897; p-value=0.0041;Cochran Q test; p-value=0.238; I 2 index=6.3%). Furthermore, we observed risk association trends between automobile speed propensity as well as the number of sexual partners and Parkinson's disease after removal of overlapping loci with other risky traits (OR=1.986 for each standard deviation increase in normalized automobile speed propensity; 95% CI=1.215-3.243; p-value=0.0066, OR=1.635 for each standard deviation increase in number of sexual partners; 95% CI=1.165-2.293; p-value=0.0049).Interpretation: These findings provide support for a causal relationship between general risk tolerance and Parkinson's disease and may provide new insights in the pathogenic mechanisms leading to the development of Parkinson's disease.

Genetic evidence for protective effects of smoking and drinking behavior on Parkinson’s disease: A Mendelian Randomization study

“…Previously, Grover et al . 40 reported a strong protective effect of ever being a regular smoker against PD, using data from the largest GWAS on risky behaviors (Linnér et al . 41 ) as the exposure dataset and the PD GWAS summary statistics available from the PDGene database (Lill et al .…”

A Mendelian randomization study of glycemic and anthropometric traits and Parkinson’s disease

“…0.05/15). We used Cochrane Q-statistics and I 2 for the IVW method as well as Rucker’s Q-statistics and the Intercept deviation test with MR-Egger’s method 36-39 .…”

“…We employed MR-Egger, WME, and MBE methods to check the reliability of estimates with varying proportions of pleiotropic variants, as previously explained 37,39-42 . We further compared the results with genetic instruments from studies that reported discovery, replication, and pooled cohorts.…”

“…We used the Phenoscanner database to identify potential pleiotropic genetic instruments that are known to be associated with potential confounders 44 . To avoid the overlapping of samples from UK Biobank, which has been included in recently published GWAS, we computed casual effect estimates by using PD datasets without UK biobank samples, as used in the previous study (9,581 PD cases and 33,245 controls) 32,45,46 .…”

Role of educational attainment, cognitive performance and intelligence in neurodegeneration: a bidirectional Mendelian randomization study

“…I used F-statistic to judge the strength of the genetic instruments, and power calculation was done using the online tool available at http://cnsgenomics.com/shiny/mRnd/). I used inverse variance weighted (IVW) fixed effect method as primary method to do causal estimate analysis and heterogeneity analysis including use of additional MR methods was conducted as described elsewhere 13 .…”