AI-Driven Discovery of Novel Predictors of Parkinson’s

The discovery was powered by patient data from the Parkinson’s Progression Markers Initiative, sponsored by the Michael J. Fox Foundation for Parkinson’s Research.

GNS Healthcare (GNS), a leading precision medicine company, announced the discovery of genetic and molecular markers of faster motor progression of Parkinson’s Disease (PD) patients, the LINGO2 gene together with a second genetic variant, along with demographic factors.

The publication describing the discovery, titled “Large-scale identification of clinical and genetic predictors of Parkinson’s disease motor progression in newly-diagnosed patients: a longitudinal cohort study and validation,” appears in the journal The Lancet Neurology. This discovery may accelerate the development of new drugs and better match new drugs to individual patients.

“Being able to use these predictors in the clinical setting will lead to faster and significantly cheaper clinical trials and accelerate the availability of new Parkinson’s Disease drugs for patients in need,” said Colin Hill, Chairman, CEO, and co-founder of GNS Healthcare. “A major hurdle in Parkinson’s research is that rates of progression are extremely varied. Some patients progress very quickly while others do not. With accurate predictors of rates of progression, we will be able to remove uncertainties from drug development and patient response, reduce the number of clinical trial enrollees required by as much as twenty percent, and speed up the development of effective new drugs.”

REFS™, the GNS causal machine learning (ML) and simulation platform was used to transform the longitudinal genetic and clinical patient data from 429 individuals (312 PD patients and 117 controls) into computer models that connect the genetic and molecular variation of patients to motor progression rates. These computer models were used to simulate the future effects of the genetic and prognostic variables on motor outcomes, essentially predicting the motor progression rate for each patient. The models were validated in an independent longitudinal study, and clearly demonstrated the ability to prospectively differentiate between patient progression rates.

“There is still so much to understand about the progression of chronic, debilitating illnesses like Parkinson’s disease,” said Jeanne C. Latourelle, D.Sc., a co-author of the study and Director of Precision Medicine, GNS Healthcare. “The validation of our models in this study underscores the power of our REFS™ technology and its ability to accelerate the development of effective therapies for patients in need.”

Displayed with permission from PRNewswire; Image courtesy of Pixabay by qimono under CC0 License.

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