Background: Recent advances in genetics have provided insights into important inherited causes of Parkinson’s disease (PD), but the underlying biological mechanisms are still incompletely understood. Gene expression studies have pointed toward the dysregulation of neuroinflammation, mitochondrial function, and protein degradation pathways. Objective: We aimed to identify groups of dysregulated genes in PD. Methods: In order to increase statistical power and control for potential confounders, we re-analyzed transcriptomic data from PD patients and model systems, integrating additional genomic data using a systems biology approach. Using weighted gene co-expression network analysis, we partitioned genes into co-expressed modules. Results: One co-expression module, M13, had an expression trajectory that was highly correlated with PD, was not characterized by any specific cell type markers, and was enriched in PD genes identified by genome-wide association studies. Genes within M13 seemed to be related to global microRNA biogenesis, and DICER1 and AGO3 were highly connected within the module. The NUCKS1 gene, previously identified as part of the PARK16 locus, was also a hub gene within M13. Conclusion: These results suggest that microRNA processing and function may play a role in the pathogenesis of PD, and thus may represent a useful target for future drug development.
Gene co-expression network analysis for identifying genetic markers in Parkinson's disease - a three-way comparative approach