AI models spot potential risk genes for Parkinson’s disease

The research from a team at the Cleveland Clinic Genome Center is detailed in npj Parkinson’s Disease.

AI was used to integrate and analyse multiple different forms of information from genetic, proteomic, pharmaceutical and patient datasets to identify patterns that may not be obvious from analysing one form of data on its own.  

“Parkinson’s disease is the second most common neurodegenerative disorder, right after dementia, but we don’t have a way to stop or slow its progression in the millions of people who live with this condition worldwide; the best we can currently accomplish is managing symptoms as they appear,” said study first author Lijun Dou, PhD. “There is an urgent need to develop new disease-modifying therapies for Parkinson's disease.” 

Making compounds that halt or reverse the progression of Parkinson's disease is especially challenging because the field is still identifying which genes cause which Parkinson’s disease symptoms when mutated, said Dr Dou.