Deciphering the Data in Parkinson’s

Winter 2015

Parkinsons-imgBy the time symptoms arise in many neurodegenerative diseases, much of the damage has already been done.

If only researchers had a better idea of the timeline—ideally, of the trackable markers that arise before symptoms become obvious—doctors might be more successful in battling many of these conditions.

That’s where Bruno Jedynak comes in. An associate research professor in the Department of Applied Mathematics and Statistics at the Whiting School, Jedynak and his colleagues Zoltan Mari and Liana Rosenthal, MD ’10, of the School of Medicine, recently received a $75,000 grant from the Michael J. Fox Foundation to analyze data generated by a study that is tracking hundreds of Parkinson’s disease patients as their disease progresses over time.

Jedynak has already had success in a similar endeavor that involved a dataset of hundreds of Alzheimer’s patients—a vast repository of information with measures ranging from blood tests to brain scans to cognition quizzes. Using powerful analytical techniques, Jedynak and his colleagues were able to determine that a common cognition test might serve as an early warning of Alzheimer’s—long before patients’ memory loss became obvious to them and their doctors.

The team, which includes graduate students Fan Zhou and Qingfeng Hu, hopes that similar analytical techniques can help clarify the wealth of data already being generated by the Parkinson’s Progression Markers Initiative, launched in 2010, at 32 clinical sites around the world.

“There’s really just a huge amount of data being generated by this study, too much for the eye to see,” Jedynak says. “We’re bringing some mathematics in order to uncover some of the mysteries of Parkinson’s.”

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