Researchers Propose New Way to Classify Parkinson�

Researchers Propose New Way to Classify Parkinson’s Disease

A multinational team of researchers has proposed a new way of classifying Parkinson’s disease (PD) that accounts for all the underlying complex biological processes involved in the progressive disorder. Led by Dr. Antony Lang, a neurologist, a senior scientist at Krembil Brain Institute and a professor at the University of Toronto Department of Medicine, the research team developed the new classification model to account for the biological determinants of Parkinson’s Disease.

Although researchers have spent several decades developing more and more advanced means of testing for and diagnosing PD, most diagnostics methods rely on the presence of motor symptoms such as tremors. Lang, who also serves as the Jack Clark Chair for Parkinson’s disease and Lily Safra Chair in Movement Disorders at the University Health Network, says current research efforts should focus on the biological processes associated with Parkinson’s disease rather than rely on limited descriptions of a patient’s symptoms.

His research team recently published a paper in the “Lancet Neurology” journal proposing a biologically based model called SynNeurGe for classifying Parkinson’s disease. The proposed model places particular emphasis on critical interactions between three biological factors that contribute to PD development. Those factors include the presence of pathologic α-synuclein (S), neurodegeneration (N) and gene variants that increase a person’s likelihood of developing Parkinson’s disease (G). The resulting “S-N-G” classification system seems to be more effective at accounting for PD’s biological heterogeneity and the different ways it presents itself in patients.

Researchers could also use the system to differentiate between different subgroups of Parkinson’s disease patients who developed the condition in distinct ways and develop more effective treatments. Lang explained that researchers should recognize that the progressive condition can differ significantly between patients and requires a broader and more holistic approach to treatment.

UHN’s Krembil Brain Institute codirector Dr. Jaideep Bains says that with the new model, Lang is spearheading international efforts to redefine Parkinson’s disease by understanding its biological complexity. Ultimately, Lang and his team’s efforts could contribute to more streamlined and advanced studies on improving Parkinson’s Disease diagnostics methods and lead to the development of precision medicine for PD patients, Dr. Bains says.

The research team believes the new classification system will help scientists study Parkinson’s disease’s molecular basis, distinguish it from similar neurodegenerative disorders with common biological features and find targets for new PD therapies. Even so, Lang noted that the model wasn’t ready for clinical use and was still meant for research purposes only.

These new insights into how to classify Parkinson’s disease more accurately could provide added impetus to the numerous companies such as Clene Inc. (NASDAQ: CLNN) and others engaged in developing the next generation of treatments for a variety of neurodegenerative illnesses.

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