1. 1. Calculating PRS can differentiate cases from controls on a population or group level: Cases are expected to have a significantly higher mean PRS than controls
2. 2. Can advise exploration on different pathways or biomarkers: We can expect that a true biomarker of genetic risk will be more likely be present in persons with a high PRS than with a low PRS
3. 3. We can stratify Parkinson’s disease patients with a higher scores: You can calculate linear PRS based on a limited number of GWAS SNPs enriched in given cellular pathways like mitochondrial pathways and identify patients with higher mitochondrial burden, and then treat using particular medications which have been shown to boost up the mitochondrial functions
4. 4. Don’t need a large sample size: You can generate a PRS for any individual and get meaningful results

The vast majority of whole genome sequence data currently available for use in calculating PRS comes mainly from European populations, leading to an overrepresentation in global studies and potentially limiting accuracy when applied to other ethnic populations.There has been a large effort to collect data from underrepresented populations, especially of those of Asian, African, and indigenous descent, sparking initiatives like Global Parkinson's Genetics Program (GP2), which aims to collect, sequence, and analyze data from around the world.