An optimized prediction framework to assess the functional impact of pharmacogenetic variants

Abstract

Prediction of phenotypic consequences of mutations constitutes an important aspect of precision medicine. Current computational tools mostly rely on evolutionary conservation and have been calibrated on variants associated with disease, which poses conceptual problems for assessment of variants in poorly conserved pharmacogenes. Here, we evaluated the performance of 18 current functionality prediction methods leveraging experimental high-quality activity data from 337 variants in genes involved in drug metabolism and transport and found that these models only achieved probabilities of 0.1-50.6% to make informed conclusions. We therefore developed a functionality prediction framework optimized for pharmacogenetic assessments that significantly outperformed current algorithms. Our model achieved 93% for both sensitivity and specificity for both loss-of-function and functionally neutral variants, and we confirmed its superior performance using cross validation analyses. This novel model holds promise to improve the translation of personal genetic information into biological conclusions and pharmacogenetic recommendations, thereby facilitating the implementation of Next-Generation Sequencing data into clinical diagnostics.

Genetic insight into cytochrome P450 in Chinese from the Chinese Millionome Database

“…Therefore, computational prediction methods, such as PolyPhen-2 and SIFT, would be important to integrate these rare variants and common variants to phenotype the drug metabolism and disposition. [22][23][24] Importantly, previous studies on genetic variation of CYPs in the Chinese population might be inconsistent due to the limited number of recruited patients or the limitations of genotyping technology. For instance, one study that investigated genetic variation of CYP2D6 in 2127 Han Chinese healthy individuals (1127 southern Chinese and 1000 northern Chinese) found different allele frequencies for CYP2D6*10 in southern (0.529) and northern (0.474) Chinese populations, 10 but we found that these results did not meet Hardy-Weinberg equilibrium (P < .05).…”

Germline variant burden in multidrug resistance transporters is a therapy‐specific predictor of survival in breast cancer patients

“…The functional consequences of missense variants were analyzed using computational algorithms that assess sequence information as well as consequences of genetic variants on the respective protein structure. Specifically, we selected SIFT, Polyphen2, MutationAssessor, VEST3 and Eigen, as these tools were among the best performing models in four independent benchmarking data sets . Variants were categorized as deleterious when the majority of algorithms predicted functional consequences.…”

“…Specifically, we selected SIFT, Poly-phen2, MutationAssessor, VEST3 and Eigen, as these tools were among the best performing models in four independent benchmarking data sets. 22,23 Variants were categorized as deleterious when the majority of algorithms predicted functional consequences. In addition, we classified all variants as deleterious that resulted in frameshifts, inframe deletions or insertions, start-lost, stop-gained or that affected canonical splice sites.…”

Integrated evolutionary and structural analysis reveals xenobiotics and pathogens as the major drivers of mammalian adaptation

“…Enzymes involved in xenobiotic metabolism are of great disease relevance, as in humans they are responsible for metabolism of prescribed drugs. Traditional analyses of protein conservation are frequently not suitable for the analysis of genes involved in xenobiotic metabolism, as these tend to evolve rapidly and the analyses used do not explicitly distinguish between neutral evolution and positive selection 73 . Specific examples we have identified here could be investigated further, for example by detailed mutational studies that have been shown to augment statistical modelling of adaptive evolution 74 .…”