Recently, scientists at the University of Sheffield and the Stanford University School of Medicine, have created a machine learning program to uncover the causes of a rare condition called Motor Neurone Disease (MND).



Motor neuron disease (MND) is a rare condition that affects the human brain and nervous system. MND causes nerve cells to stop functioning and eventually leads to complete paralysis. That means the patient will lose the ability to voluntarily move their muscles. CDC estimates that two in every 100,000 people in the UK are affected by MND. About 5,000 people are living with the condition in the UK at any one time. In the US, 5,000 new cases are diagnosed annually.



Currently, there’s no cure for MND. Of course, some treatments help in minimizing the impact of MND on a patient’s life. Although, some people are still living with the condition for many years.



Those scientists from the universities have created a machine learning tool called RefMap. RefMap has already discovered around 690 risk genes for MND. Before the development of this machine learning tool, scientists were only able to find 15 risk genes. The data published in Neuron has helped the team of scientists to decrypt more information on how much of the disease is caused by heritability and by other environmental factors.

“This new tool will help us to understand and profile the genetic basis of MND. Using this model we have already seen a dramatic increase in the number of risk genes for MND, from approximately 15 to 690,” said Dr Johnathan Cooper-Knock, a project worker.

“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,” he said.

The data provided by the scientists indicate that KANK1 is one of the genes highlighted as a new MND gene that produces neurotoxicity in human neurons. This is considered a new potential target for the design of future drugs.



“By doing machine learning for genome analysis, we are discovering more hidden genes for human complex diseases such as MND, which will eventually power personalized treatment and intervention,” said Michael Snyder, professor, and chair of the department of genetics at the Stanford School of Medicine.

Sai Zhang, instructor of genetics at the Stanford University School of Medicine said “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.”

Now the findings will allow us to discover new targeted therapeutics and genetic testing for the disease.

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