Sequencing of the human genome allowed for large-scale whole-genome population studies to identify the genetic underpinning of common diseases. While thousands of genome-wide association studies (GWAS) have now been published, a systematic functional validation of these efforts is lacking. Our goal in this study was to test if GWAS approaches do indeed identify genes/loci that modify disease severity. We focused on Parkinson’s disease (PD), a complex neurodegenerative disease that severely impairs motor function with age. In Drosophila melanogaster, PD can be modeled by pan-neuronal (elav-gal4) ectopic expression of human alpha-synuclein (UAS-αsyn). Meta-analysis of GWAS data from ~25,000 PD patients and >100,000 age-matched controls identified SNPs of varying p values (<10-4) which corresponded to 845 fly orthologs. Here we have systematically tested each candidate for PD-modifying effects by monitoring locomotor function throughout lifespan. Assessment of this initial dataset has allowed us to assess the validity of using GWAS to predict disease modifying genes. We have been able to show that probability of a disease-modifying phenotype inversely correlates with GWAS p-value and the distance between gene and SNP. Thus we conclude that at least for large studies, GWAS will pinpoint disease-modifying loci and has allowed us to identify multiple new conserved PD genes, which can inform on basic disease mechanisms or be considered as novel drug targets for this devastating illness.