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Monday, October 16, 2017

Genetic and Other Markers Seen to Predict Parkinson’s Progression in Computer Modeling Study

OCTOBER 16, 2017  BY CATARINA SILVA



Genetic and molecular markers of quicker motor decline in Parkinson’s disease (PD) patients were identified in a computer modeling study of disease progression.
Among already described demographic factors, like older age or male sex, the researchers specifically identified a novel and Parkinson’s-specific genetic interaction between the LINGO2 gene and a second genetic variant that might predict faster motor degeneration.
A better understanding of, and ability to predict, Parkinson’s disease progression could improve disease management and clinical trial design, they said of their work’s importance.
To develop predictive models, compare potential PD biological markers, and identify new predictors for motor progression in PD, the team at the University of Rochesterused longitudinal clinical, molecular, and genetic data from the Parkinson’s Progression Markers Initiative study (NCT01141023).
The researchers began by transforming genetic data and baseline molecular and clinical variables from 312 Parkinson’s patients and 117 healthy controls so as to construct computer models that might interpret motor progression rates. Data transformation was done using REFS, GNS Healthcare‘s casual machine learning and simulation platform.
The computer models allows researchers to simulate the effects of genetic and clinical variables on motor outcomes. Consequently, motor progression rate could be predicted for each patient in the study.
Results showed that the “machine” could distinguish between progression rates, reporting that women have a slower rate of decline. Older patients with higher baseline motor scores were also seen to be more likely to experience faster motor degeneration.
Importantly, patients who carried two genetic variations in two distinct genes had a substantially faster rate of motor decline. One of these genes, the LINGO2 gene, is exclusively expressed in the central nervous system. Interestingly, neither of the genetic variations were among the PD-related genetic alteration identified in genome-wide association studies.
“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,” Colin Hill, Chairman, CEO, and co-founder of GNS Healthcare, said in a press release. “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.”
https://parkinsonsnewstoday.com/2017/10/16/parkinsons-disease-progression-tied-to-genetic-other-markers-in-computer-modeling-study/

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