Using genomic technology to transform how genetics is used to diagnose and treat disease

Abstract

Interpreting the clinical significance of rare genetic sequence variants is challenging due limited evidence, and as a result, most newly identified missense variants are interpreted as variants of uncertain significance (VUS). Multiplexed assays of variant effet (MAVEs), where hundreds to thousands of variant effects are measured in a single experiment have significantly accelerated the rate at which functional data are generated. Since functional data can be applied when interpreting variants, MAVEs have the potential to revolutionize clinical genetics by providing functional data at scale to resolve VUS. We systematically evaluated the clinical utility of MAVEs by integrating published MAVE data with clinical interpretations and resolved 49% of VUS for BRCA1, 69% for TP53, and 15% for PTEN. Although we demonstrated the potential for MAVEs to resolve uncertainty in genetic testing, MAVE technologies were limited to genes with phenotypes in utilitarian cancer derived cell lines. We addressed this limitation by developing iPSC-SGE, where variants are edited into iPSCs, enabling phenotyping in differentiated cells. We introduced 498 SNVs into POLG and 496 variants into MYBPC3. POLG variant effects were measured with a growth assay in iPSCs in the context of different background alleles and MYBPC3 variant effects were measured by variant abundance in cardiomyocytes. iPSC-SGE data was validated with known pathogenic and benign variants and is poised to generate functional data for genes previously inaccessible with MAVEs. Finally, we explored the use of variant effect predictors for variant interpretation, a major factor contributing to the VUS problem. We found that current calibration methods lead to inappropriate evidence for up to 75% of variants and offer a new solution for calibration via clustering VEP data for protein domains on similarity of score distributions. This method enables more accurate evidence strength thresholding while maintaining robust sets of calibration varants. Taken together, cell context specific functional data and variant specific VEP calibration will result in significant reduction to VUS while providing rich phenotypic insight for advancing precision medicine.