Functional Genomics of Disease Response Heterogeneity
Starting in October 2018 the research team will be led by Emma Davenport from Harvard Medical Schools, Brigham and Women's Hospital and the Broad Institute. The group's research interests will lie in combining genomic analysis with clinical data to understand the underlying genetic reasons why some patients are able to overcome infections more quickly than others and why people respond differently to the same drug.
The team will focus on discovering the differences in our genomes that determine how active our genes are and how they affect how our bodies respond to particular drug treatments. The researchers will use both computational approaches and wet laboratory experiments to identify the areas of the genome that play a role in a disease by lowering or raising the activity of specific genes, discover which biological processes are involved, in which cells and when. This work will help to identify new drug targets and biomarkers that could be used in diagnostic tests.
The work will also show how a person’s genetic makeup interacts with drugs to enable or inhibit their effectiveness. Some drugs work better when certain genes are more or less active. While other drugs have their effect by working directly on the DNA regions that control a gene’s activity, either driving its activity up to supply unmet need, or reducing its activity to remove damaging excess.
About Emma Davenport
Emma's research interests lie in applying sophisticated analytical strategies to cohorts of patients to improve the treatment of disease. She focuses on integrating functional genomics and clinical data in order to understand how genetics contributes to the patient-to-patient heterogeneity in treatment response. Emma completed her PhD research in 2014 under the supervision of Professor Julian Knight at the University of Oxford. In 2015, she joined Professor Soumya Raychaudhuri's lab at Harvard Medical School as a postdoctoral research fellow. Her PhD and postdoctoral research have given her a strong foundation in computational methods, wet lab molecular biology and data acquisition.