Convergence of miRNA expression profiling, α-synuclein interacton and GWAS in Parkinson's disease

Abstract

miRNAs were recently implicated in the pathogenesis of numerous diseases, including neurological disorders such as Parkinson's disease (PD). miRNAs are abundant in the nervous system, essential for efficient brain function and play important roles in neuronal patterning and cell specification. To further investigate their involvement in the etiology of PD, we conducted miRNA expression profiling in peripheral blood mononuclear cells (PBMCs) of 19 patients and 13 controls using microarrays. We found 18 miRNAs differentially expressed, and pathway analysis of 662 predicted target genes of 11 of these miRNAs revealed an over-representation in pathways previously linked to PD as well as novel pathways. To narrow down the genes for further investigations, we undertook a parallel approach using chromatin immunoprecipitation-sequencing (ChIP-seq) analysis to uncover genome-wide interactions of α-synuclein, a molecule with a central role in both monogenic and idiopathic PD. Convergence of ChIP-seq and miRNomics data highlighted the glycosphingolipid biosynthesis and the ubiquitin proteasome system as key players in PD. We then tested the association of target genes belonging to these pathways with PD risk, and identified nine SNPs in USP37 consistently associated with PD susceptibility in three genome-wide association studies (GWAS) datasets (0.46≤OR≤0.63) and highly significant in the meta-dataset (3.36×10⁻⁴<p <1.94×10⁻³). A SNP in ST8SIA4 was also highly associated with PD (p = 6.15×10⁻³) in the meta-dataset. These findings suggest that several miRNAs may act as regulators of both known and novel biological processes leading to idiopathic PD.

Figure 1. Unsupervised hierarchical clustering of the eighteen differentially expressed miRNAs (rows) for the 32 samples (columns).

The sample ID and a heat-map indicating the disease state of each subject in a color code (black for controls and red for cases) are shown at the bottom of the plot. The color scale at the bottom right illustrates the relative expression level of a miRNA across all samples: red represents an expression level above mean, and blue represents expression lower than the mean. The clustering is performed on log₂(sample/reference pool) ratios of the 18 differentially expressed miRNAs, using the Euclidean distance function and the average linkage clustering methods.