Bidirectional Mendelian randomization to explore the causal relationships between Sleep traits, Parkinson's disease and Amyotrophic lateral sclerosis

Objective: Sleep disturbances have been linked with Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS) in observational studies, and the comorbidity of PD and ALS has been reported in clinical case reports, but the causalities remain unclear. This study aims to examine bidirectional causal relationships between sleep traits, PD and ALS. Methods: Bidirectional two sample Mendelian randomisation (MR) analyses were conducted, with data from individuals of mainly European ancestry. Genetic instruments were obtained from the largest published genome-wide association studies (GWAS) concerning various sleep traits, PD and ALS. MR estimates from each genetic instrument were combined by inverse variance weighted method, with alternate methods (eg, weighted median, MR Egger, MR-PRESSO) and statistical graphs to assess horizontal pleiotropy and remove outliers. Results: MR analysis failed to observe any causal association between sleep disorders and PD, but found a possible causal effect of PD risk on ALS risk (odds ratio [OR] = 1.07; 95% CI: 1.01-1.14, P < 0.01), albeit with a horizontal pleiotropy. Furthermore, MR analyses indicated that excessive daytime sleepiness (EDS) (OR = 2.29; 95% CI: 1.04-5.03, P = 0.04) contributed to a modest increase in risk of ALS, but the reverse causalities were not significant. Higher risk of ALS may be associated with being a "morning person" (OR = 1.03, P = 0.02), a longer sleep duration (OR = 1.01, P < 0.01), and a mean of 9 h or more total sleep duration (beta = 0.02, P = 0.04). Conclusions: Aided by large-scale GWAS, a shortage of evidence supporting causal relationships of sleep traits and PD risk, while significant evidence supports that EDS, higher PD risk may causally influence ALS risk. Future researches are required to explore the underlying pathological mechanism as well as the clinically significance, and replicate our findings using independent samples when data become available. (C) 2022 Published by Elsevier B.V.