Community-Based and Genomics-Informed Precision Medicine Pilot Project

Project Description Narrative:

This project aims to make precision medicine more accessible and beneficial for individuals in southeast Wisconsin by studying how genetic information influences health. In collaboration with community members, the research team seeks to understand better how unique genetic variations impact drug metabolism and optimize communication with our community about these effects. Community representatives will be vital to this research process to ensure that it aligns with local needs and priorities and to identify gaps in community understanding of the future clinical role of pharmacogenomics (PGx) and barriers to research participation.

Advancements in genomics have introduced promising avenues for personalized medicine, particularly in the domains of PGx. PGx is an important and growing area in medicine that deals with how each person's unique genome modifies how drugs affect them and how their body metabolizes drugs. PGx genes are increasingly entering everyday medical practice. Since significant racial differences exist in the prevalence of many PGx variants, diverse community members must contribute to the conversation about how this should occur. The disparities in mental health outcomes suggest that PGx affecting the metabolism of many drugs commonly used to manage mental health conditions, providing an ideal focus to start this inevitably broad conversation.

By examining genetic data from southeast Wisconsin residents, the research team aims to discover if unique genetic factors in this region influence health outcomes differently compared to other parts of the United States. They have selected CYP2D6 and CYP2C19, which metabolize selective serotonin reuptake inhibitors (SSRIs) and opioids, which are used to address some mental health disorders pharmacologically. The team has a long history of research that goes beyond a gene's sequence and models the encoded gene product over time and in 3D space. A critical innovation is that their protein structure-based approach can precisely model unique one-of-a-kind variations, whereas statistical genetics cannot. They will use physics-based computer modeling to characterize PGx protein structure and dynamics changes for each of the genomic variations identified from Wisconsin. The result of this analyses will be to understand better which genetic variations are more likely to damage PGx protein functions, thereby changing drug metabolism for those individuals.