Predicting the Significance of Genetic Variants in Parkinson’s Disease

Abstract

Different genetic variants in the human genome can give rise to distinct forms of Parkinson’s Disease. This study aims to determine the significance of all variants in the human genome linked to Parkinson’s Disease based on empirically validated pathogenicity data.

We condensed the list of variants in the dbNSFP/ClinVar database to only those variants associated with Parkinson’s Disease, used 2 interpretation criteria from the American College of Medical Genetics and Genomics/Association for Molecular Pathology’s clinical guidelines to pair each empirically validated variant, with a variant with unknown significance, and finally analyzed for pathogenicity. 

The analysis of variant pairs based on ACMG/AMP criteria revealed strong correlation (R-squared = 0.9943) between CADD scores for PS1 variants. However, for PM5 variants, the lower correlation (R-squared = 0.118) indicates poor predictive value. This indicates that the PS1 criteria is effective in predicting the significance of VUSs based on empirically validated data. Furthermore, we analyzed the COMT gene to predict how treatment of Parkinson’s Disease can be affected. 

The results indicate that, for >1000 SNVs exome wide, we can accurately predict the significance of VUSs based off empirically validated data. On this basis, patients with currently unvalidated mutations can gain information about their likelihood of developing Parkinson’s Disease. Further research is required to understand the clinical presentation of each variant.