Parkinson’s disease (PD), Alzheimer’s disease (AD), Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal dementia (FTD) are complex neurodegenerative disorders with many genetic factors. Several genetic changes have been shown to cause or increase a person’s chance of getting the diseases, however many genetic factors are still unknown. Recent advances using next-generation sequencing data allow us to study rare (seen in very few people) genetic changes that are believed to play an important role in whether someone gets PD or not. Here, we propose to use the UKBiobank 200,000 whole-genome, 470,000 whole-exomes, alongside with metabolomics and proteomic datasets to expand our current research and confirm our identified links of candidate genes coming from studying (i) the role of having too many rare genetic variants that are known to be important in PD, AD, ALS, FTD, among others and (iii) how to build a prediction model that is able to distinguish between individuals with disease and without disease using genetic and protein datasets.
