NEW YORK (GenomeWeb) — The National Institute of Neurological Disorders and Stroke has awarded $5.9 million to support a consortium focused on better understanding the biological and genetic etiology of sudden unexpected death in epilepsy, or SUDEP.
The funding for this new Center for SUDEP Research will support nine projects in total, including several genetic projects, as well as an informatics core that will support the other consortium groups.
Walter Koroshetz, acting director of NINDS, said in a statement that the institute hopes that "by encouraging scientists with expertise in a variety of areas to join forces … we may learn how to prevent the tragic death of as many as 3,000 children and adults each year in the United States."
One of the genetics-focused efforts in the new program, led by John William Belmont and Alica Goldman from Baylor College of Medicine, will conduct genomic analyses on samples from individuals who have died or are at a high risk of SUDEP. Called the Center for SUDEP Research: Molecular Diagnostics Core, this team will try to identify genes that cause SUDEP in order to support the development of genetic tests or other tools to predict which epilepsy sufferers are at a higher risk of dying.
According to the grant abstract for the group, the Molecular Diagnostics Core will also perform genetic analyses and annotate samples from other projects in the consortium, including a group from the University of Michigan focused on neuron function and heart rhythms in individuals with Dravet syndrome, a severe form of pediatric epilepsy associated with higher risk of sudden death.
Another genomic project, also at Baylor, and led by the college's Jeffrey Noebels, will focus specifically on cardiac genes. This group, the Center for SUDEP Research: Cardiac Gene and Circuit Mechanisms, will investigate how changes in these genes may increase the risk of SUDEP by causing abnormalities in patients' cardiovascular functions, such as heart rate and breathing.
Other projects in the consortium will simultaneously investigate other non-genetic biomarkers, such as brain size and structure, as well as perform other analyses of biological pathways associated with SUDEP in mouse models, and human data.