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Approved research

Multi-Omic Characterization of Common Disease States through Polygenic Modeling

Principal Investigator: Dr Sergey Kornilov
Approved Research ID: 48049
Approval date: July 31st 2019

Lay summary

Personalized medicine aims to improve health outcomes in patients by incorporating information about the genetic makeup of the individual into treatment planning and disease prevention. Recent advances in the fields of human genetics have led to the development of polygenic risk scores that combine the effects of multiple genetic variants to determine whether an individual is at an increased risk for a particular disease. The mechanisms through which these polygenic risk scores increase disease risk are poorly understood. Incorporation of this information into routine clinical care has the potential to reduce unnecessary interventions, enable early disease detection, and develop novel preventative care strategies. Throughout the course of 2019, Arivale's Research Team proposes to perform a set of studies using the UK BioBank data to build polygenic risk scores for a number of common diseases. We will then leverage the Arivale internal dataset that includes genetic, blood, stool, and health history data on more than 4,500 individuals to identify biological signatures of genetic risk for disease. The proposed research project has the potential to contribute to our understanding of the biological mechanisms that underlie genetic risk for common diseases by identifying the specific biological features characteristic of individuals with low and high estimated genetic risk. These biological signatures, in turn, may enable the discovery of early signs that a disease is developing, research on novel therapies, and the development of personalized strategies for disease prevention.