| Abstract: |
The interpretation of genetic variants in complex diseases remains a major challenge in contemporary precision medicine, with a substantial proportion of individuals remaining undiagnosed despite advances in next-generation sequencing (NGS). Variants of Uncertain Significance (VUS) continue to constitute nearly 50% of submitted variants in databases such as ClinVar, representing a persistent diagnostic gap. This study investigates the integrated application of the Tab-Separated Values (TSV) filter tool within bioinformatics pipelines and Polygenic Risk Scores (PRS) to reduce variant ambiguity and improve diagnostic outcomes in complex diseases. We hypothesize that combined deployment of TSV-based variant filtering with PRS risk stratification will significantly improve variant classification accuracy and decrease the proportion of unresolved VUS. Using a systematic analysis design with data drawn from multiple population cohorts including the UK Biobank, PRSKB, and ClinVar repositories, we evaluate diagnostic yields, AUC performance metrics, and reclassification rates. Results demonstrate that PRS-integrated pipelines improve AUC values across major complex diseases, and TSV filter application reduces false-positive variant calls. These findings support the clinical integration of PRS and structured variant filtration as complementary strategies to close the diagnostic gap in complex polygenic disorders. |
