Funding for the eMERGE Network

NIH’s https://www.hhs.nih.gov $75 million in funding will be shared by a coordinating center and a network of 10 other top academic medical centers. The funding will be used to launch a five year effort to improve genomic risk assessments for diverse populations to then integrate the data into clinical care.

NIH awarded one award for $13.4 million to Vanderbilt University to serve as a data coordinating center. About $61 million more will be shared among four clinical and six enhanced diversity clinical sites.

This award funding will build on a massive ongoing medical data project called Electronic Medical Records and Genomics (eMERGE). Since 2007, participating medical centers have been working to gather, organize, and share an ocean of data supporting the early stages of providing highly targeted treatments for cancer and other diseases based on a person’s unique genetic code.

The idea is to perform deep genomic “risk” assessments that could help doctors manage a patient’s care. The information could help determine the people most likely to develop diseases, which medications stand the best chance of success, and which medications pose risks with serious side effects. Conditions to receive improved, more diverse risk assessments include cardiovascular disease, Alzheimer’s disease, and diabetes.

Cincinnati Children’s Hospital Medical Center https://www.cincinnatichildren’s.org as one of the participating sites will receive about $6.9 million over five years. According to John Harley, MD, PhD, leading Cincinnati Children’s portion of the project said, “Recent advances in targeted precision medicine offers great promise for improved treatments and preventive strategies.

While a condition such as heart disease may occur widely across population groups, the sets of genes involved and the factors driving their activity may vary widely among racial and ethnic groups.”

Cincinnati Children’s will recruit up to 2,500 African American mothers and infants to collect entire sets of genomic data. The information will be combined with other known environmental and social factors that can be found within many EMRs. This will help experts produce more accurate genomic risk assessments or polygenic risk scores for people from various population groups.

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