Subject-to-subject variability in response to drugs and environmental agents creates a significant challenge for the safe and effective treatment of many human diseases. Pharmacogenomics seeks to address this challenge by linking drug response to patient genotypes at important loci, termed pharmacogenes, in order to better customize patient treatments. Cytochrome P450 (CYP) gene variation is a major contributor to adverse drug reactions resulting from alterations in a subject's ability to metabolize therapeutic agents and environmental toxins, relative to the population at large. Genetic variation in CYPs is extensive. For example, amongst 12 of the most important cytochrome P450 (CYP) genes, 10% of people carry at least one rare, potentially deleterious variant. Further complexity is introduced via complex alleles consisting of common variation plus linked rare variants, and by extensive copy number variation and gene fusions at these loci. Unfortunately, only a small number of variants have been unambiguously linked to alterations in drug/xenobiotic response. Clearly, new approaches are needed to annotate the consequences of the huge pool of variants of unknown significance, including those already identified by existing large-scale sequencing programs, and those that will be discovered as clinical sequencing becomes routine. We have developed a suite of methods to test all possible single substitutions at all amino acid residues in several CYP genes. In order to accomplish this, we use deep mutational scanning, a method we have developed that allows parallelized, quantitative measurements to be performed on libraries of genetic variants. We are in the midst of applying this approach to single site variants of CYP2C9 and CYP2D6. We propose to extend our work to include CYP2C19, the third prototypic CYP pharmacogene, CYP3A4, quantitatively the most important human liver drug metabolizing enzyme, CYP2A6, which metabolizes nicotine and modulates smoking behaviors and lung cancer risk, and CYP1A1, which bioactivates polycyclic heteroaromatic carcinogens. These efforts, which span the major xenobiotic metabolizing CYP families (CYP1-3), constitute Aim 1.
In Aim 2, we will evaluate more complex alleles, including novel chimeras, and in Aim 3 we will dissect the substrate-dependency of genetic variation, both efforts focusing on the drug-metabolizing CYP2 family. The result of this project will be a comprehensive, context aware, functional analysis of CYP variants that will lead to a deeper understanding of the consequences of genetic variation in these key pharmacogenes. We will also develop new, generalizable methods for generating complex variant libraries and for directly assessing the effects of enzyme variants in a multiplex fashion.
Pharmacogenomics seeks to identify genetic sources of inter-individual variability in drug response, with the goal of personalizing drug selection and dose to improve patient outcomes. A key barrier to using pharmacogenomic information is lack of clarity about the functional impact of variants, which hampers the provision of clear, unambiguous guidance to health care providers. We propose to connect pharmacogenomic variant discovery with novel high-throughput experimental approaches to guide the use of individual pharmacogenomic information in personalizing drug treatment.
