Researchers at Weill Cornell Medicine have used machine learning to define three subtypes of Parkinson's disease based on the pace at which the disease progresses.
Weill Cornell Medicine Jul 16 2024 Research ers at Weill Cornell Medicine have used machine learning to define three subtypes of Parkinson's disease based on the pace at which the disease progresses. In addition to having the potential to become an important diagnostic and prognostic tool, these subtypes are marked by distinct driver genes. If validated, these markers could also suggest ways the subtypes can be targeted with new and existing drugs.
The investigators defined the subtypes based on their distinct patterns of disease progression. They named them the Inching Pace subtype for disease with a mild baseline severity and mild progression speed, the Moderate Pace subtype for cases that have mild baseline severity but advance at a moderate rate, and Rapid Pace subtype , for cases with the most rapid symptom progression rate.
Dr. Wang's lab has been studying Parkinson's since 2016, when the group participated in the Parkinson's Progression Markers Initiative data challenge sponsored by the Michael J. Fox Foundation. The team won the challenge on the topic of deriving subtypes, and since then has received funding from the foundation to continue this work.
Clinical Research Network, based in New York, and the OneFlorida+ Clinical Research Consortium, are both part of the National Patient-Centered Clinical Research Network . INSIGHT is led by Dr. Rainu Kaushal, senior associate dean for clinical research at Weill Cornell Medicine and chair of the Department of Population Health Sciences at Weill Cornell Medicine and NewYork-Presbyterian/Weill Cornell Medical Center.
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