Statistical integration of multi-omics data identifies potential therapeutic targets for synucleinopathies

Parkinson’s disease and multiple system atrophy are characterized by aggregation of the α -synuclein protein in the brain. The causes and consequences of this aggregation are currently unclear, hampering the development of an effective therapy against these synucleinopathies. To gain understanding in the neurobiological events underlying α -synuclein aggregation, LUHMES cell lines have been utilized to measure transcriptomics and proteomics data and perform differential regulation analyses. The LUHMES cells have also been used to screen 1600 FDA-approved drugs for their ability to reduce α -synuclein-induced toxicity. We implemented a probabilistic data integration method, POPLS-DA, to model α -synuclein overexpression in terms of the transcriptomics and proteomics data jointly. Using POPLS-DA, we selected 200 relevant genes and proteins and integrated this gene list with the FDA drugs that were validated to be protective against α -synuclein-induced toxicity. Using interactome and functional enrichment analyses, we identified clusters of synaptic and lysosome-related genes and proteins that were targeted by the protective drugs. We found that HSPA5 , a member of the heat shock protein 70 family, was one of the most targeted genes by the validated drugs. Our integrative approach results provide new directions for therapeutic targets for synucleinopathies. ### Competing Interest Statement The authors have declared no competing interest.