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Approved research

Prioritizing drug targets through genetic analyses

Principal Investigator: Dr Jason Merkin
Approved Research ID: 44290
Approval date: April 12th 2019

Lay summary

Model organisms are powerful tools for learning about biology and human disease. However, many disease models often do not capture the full breadth of the disease in humans. Further, many drugs targeting disease genes in mouse ultimately fail late-stage clinical trials. One way to address this shortcoming is to incorporate additional analyses in humans when identifying what genes to drug to treat the human disease. Large databases of genetic and other data from humans (such as the UK Biobank) allow us to conduct powerful analyses that accomplish this goal. We can look in these databases to see whether variants of genes we are interested in are associated with the disease we are trying to treat or other phenotypes related to it. Such observations would provide strong support for the gene's role in the human disease. The same analyses can also help to identify potential side-effects from a potential treatment if a gene is associated with other diseases or negative outcomes. The diseases and patient populations we are focused on include those with few if any treatment options, so the impact of successfully identifying and drugging genes for these diseases on these large patient populations will potentially be monumental.