Genetic analyses identify brain functional networks associated with the risk of Parkinson’s disease and drug-induced parkinsonism

Abstract Brain functional networks are associated with parkinsonism in observational studies. However, the causal effects between brain functional networks and parkinsonism remain unclear. We aimed to assess the potential bidirectional causal associations between 191 brain resting-state functional magnetic resonance imaging (rsfMRI) phenotypes and parkinsonism including Parkinson’s disease (PD) and drug-induced parkinsonism (DIP). We used Mendelian randomization (MR) to assess the bidirectional associations between brain rsfMRI phenotypes and parkinsonism, followed by several sensitivity analyses for robustness validation. In the forward MR analyses, we found that three rsfMRI phenotypes genetically determined the risk of parkinsonism. The connectivity in the visual network decreased the risk of PD (OR = 0.391, 95% CI = 0.235 ~ 0.649, P = 2.83 × 10−4, P_FDR = 0.039). The connectivity of salience and motor networks increased the risk of DIP (OR = 4.102, 95% CI = 1.903 ~ 8.845, P = 3.17 × 10−4, P_FDR = 0.044). The connectivity of limbic and default mode networks increased the risk of DIP (OR = 14.526, 95% CI = 3.130 ~ 67.408, P = 6.32 × 10−4, P_FDR = 0.0437). The reverse MR analysis indicated that PD and DIP had no effect on brain rsfMRI phenotypes. Our findings reveal causal relationships between brain functional networks and parkinsonism, providing important interventional and therapeutic targets for different parkinsonism.