Statistical omics data integration identifies potential therapeutic targets for synucleinopathies

Synucleinopathies, such as Parkinson’s disease and multiple system atrophy, are characterized by α-synuclein aggregation in the brain. There is no disease-modifying therapy against synucleinopathies yet. To understand the neurobiological events underlying α-synuclein aggregation, LUHMES cell lines have been utilized to measure transcriptomics and proteomics data and screen 1600 FDA-approved drugs for their toxicity-reducing ability. However, rather than an integrative approach, the statistical analyses were performed per dataset. We propose a novel statistical data integration method, POPLS-DA, to jointly model the transcriptomics and proteomics data and discriminate disease cells from controls. We also performed a dose-response test to validate screened FDA-approved drugs. We integrated the validated drugs with the selected genes/proteins using integrative bioinformatic analyses. We identified clusters of synaptic and lysosome-related genes targeted by the validated drugs. Furthermore, HSPA5, a member of the heat shock protein 70 family, was one of the most targeted genes. HSPA5 has been previously linked to α-synuclein pathology, showing the relevance of our findings. Our integrative approach results provide new directions for therapeutic targets for synucleinopathies.