According to the CDC, 5,000 new cases of Motor Neurone Disease (MND) are diagnosed annually in the United States. This disease causes nerve cells to stop functioning and die, resulting in sufferers losing the ability to voluntarily move their muscles and eventually becoming paralyzed.
Scientists, from the University of Sheffield and the Stanford University School of Medicine, have developed an AI program to dive deeper into understanding the genetic risk factors associated with the complex disease.
RefMap
The machine learning tool, named RefMap, has uncovered 690 risk genes for MND. Previously, only 15 genes were able to be linked to the illness so most of the markers identified, such as KANK1, are new discoveries!
This data, published in Neuron, has helped the team decipher more information on how much of the disease is caused by heritability and how much is other factors, such as the environment.
What are the applications of the program?
“Each new risk gene discovered is a potential target for the development of new treatments for MND and could also pave the way for genetic testing for families to work out their risk of disease,” stated Dr. Johnathan Cooper-Knock, who worked on the project.
The applications of this RefMap don’t just stop there, with the hope of applying the technology to many complex illnesses. “RefMap identifies risk genes by integrating genetic and epigenetic data. It is a generic tool and we are applying it to more diseases in the lab,” added Sai Zhang, Ph.D., a geneticist from Stanford.
Source study: Neuron – The impact of age on genetic risk for common diseases
