Genomics Collaborative Aims to Find New Precision Medicine Methods

Boston-based FDNA has launched a global initiative to promote medical research collaborations and to develop new precision approaches for diagnosing and treating disease, including Angelman syndrome.

The initiative, called Genomics Collaborative, uses computer analysis and artificial intelligence technologies to integrate genetic information with the physical and biological characteristics of a particular disease. This process is known as next-generation phenotyping, or NGP. It can be used to improve knowledge about disease genetics and to identify risk factors and potential therapeutic targets.

Multiple collaborators have already signed up for the challenge. Among other projects is an advocacy group in Cypress, Texas, called Bridge the Gap. The group is collaborating with FDNA, clinicians and patients to study SYNGAP1 gene variants related to Fragile X and other syndromes.

According to Bridge the Gap, SYNGAP1-related non-syndromic intellectual disability (NSID) in humans was first reported in 2009. SYNGAP1 was one of the first genes found to be associated with NSID.

Since initially described, an increasing number of children with SYNGAP1-related NSID have been identified, suggesting that it may represent one of the most common causes of intellectual disabilities. The recent use of genomic sequencing has dramatically increased the capacity of physicians to identify these mutations.

Researchers want to advance the use of facial analysis and other NGP approaches to help develop diagnostic methods and early personalized interventions.

Greenwood Genetic Center in Greenwood, South Carolina, plans to use NGP to identify and recognize potential correlations between specific biomarkers and patterns of facial features associated with various genetic syndromes.

“The patient is our greatest asset for the future of precision medicine,” Ilana Jacqueline, coordinator of the Genomics Collaborative, said in a press release. “The Genomics Collaborative is making it possible to look at patients in a safe, secure way to help understand how doctors can better diagnose and treat patients, based on their unique traits.”

“We’re interested in working with others to develop technologies that easily capture and analyze that data to help health care providers have all the facts when they are evaluating patients,” Jacqueline added. “When it comes to having the means to make a faster and more accurate diagnosis, physicians should have every advantage.”