Researchers at Weill Cornell Medicine have utilized machine learning to define three subtypes of Parkinson’s disease based on the rate at which the disease progresses. These subtypes, named Inching Pace, Moderate Pace, and Rapid Pace, have distinct driver genes and potential implications for diagnostic and prognostic purposes. By analyzing patient genetic and transcriptomic profiles, the researchers were able to identify molecular mechanisms associated with each subtype, such as neuroinflammation and oxidative stress. They also identified potential drug candidates that could target these specific molecular changes. The study, published in npj Digital Medicine, suggests personalized treatment strategies based on a patient’s disease subtype for Parkinson’s disease.
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Weill Cornell researchers define three Parkinson’s subtypes with machine learning
