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Parkinson’s Disease ‘Can Differ Dramatically Between Patients’ – and Now We Know How to Look For It

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Doctors still diagnose Parkinson’s Disease based on clinical features, such as the presence of tremors and other common motor symptoms but this disease exists in the brain for one to two decades, or longer, before tremors and other common motor symptoms appear.

In recent decades, scientists have identified various biochemical processes that contribute to Parkinson’s disease.

A buildup of the protein α-synuclein in the brain leads to neuron degeneration, and hereditary factors enhance the chance of getting the illness.

They have also started to develop viable ways for detecting these characteristics, known as biomarkers, in real patients.

Despite these advances, clinicians continue to identify the condition using clinical signs including tremors and other typical motor symptoms.

Dr. Lang, the Lily Safra Chair in Movement Disorders at the University Health Network (UHN), the Jack Clark Chair for Parkinson’s Disease Research, and a Professor in the Department of Medicine at the University of Toronto, believes that the traditional approach to diagnosing Parkinson’s disease fails to account for the complex biological processes at work.

“We know Parkinson’s exists in the brain for one to two decades, or longer, before the clinical manifestations present,” comments Dr. Lang. “So, we believe current research must be driven by biological determinants of the disease, rather than limited clinical descriptions of its signs and symptoms.”

“We need a radically different way of looking at this disease.”

In a recent Lancet Neurology release, Dr. Lang’s team suggested a novel, physiologically based methodology for defining Parkinson’s disease called SynNeurGe (pronounced “synergy”).

The model stresses the significant interplay between three biological components that lead to the disease:

  1. Pathologic α-synuclein levels in the brain (S).
  2. There is evidence of neurodegeneration as the illness advances (N); and
  3. The existence of gene variations that cause or significantly predispose a person to the illness (G).

According to the experts, the “S-N-G” categorization plan better accounts for PD’s biological heterogeneity and the many ways the disorder might manifest in individuals. As a result, the method could help researchers in identifying subgroups of patients with discrete disease processes and developing clinically relevant disease-modifying medicines.

“We need to recognize that Parkinson’s can differ dramatically between patients,” adds Dr. Lang.

“We are not dealing with a single disorder,” and “Our model provides a much broader, more holistic view of the disease and its causes.”

“With this new model, Dr. Lang is spearheading a truly pivotal international effort to redefine the biological complexity of Parkinson’s Disease, which will lead to more advanced and streamlined research in this area, and ultimately, to precision medicine for patients,” comments Dr. Jaideep Bains, co-Director of UHN’s Krembil Brain Institute.

The team believes that this new take on Parkinson’s disease can help researchers in studying its genetic foundation, distinguishing it from other neurodegenerative disorders with similar biological characteristics, and identifying targets for novel therapeutics.

Despite these possible uses, Dr. Lang emphasizes that the model is primarily for research reasons and is not yet suitable for urgent clinical use. However, it is already instilling optimism in patients and the medical community.

“The ability to tailor treatments improves when you can identify exactly what is going on in a specific patient like me,” points out Hugh Johnston, Founding Chair of The Movement Disorders Patient Advisory Board at UHN’s Krembil Brain Institute, who is currently living with PD. “This new way of thinking is what we have been waiting for. It’s a game changer.”

“Without looking at the biology, you can’t get answers. And without answers, we won’t have much-needed breakthroughs in Parkinson’s,” adds Dr. Lang. “This new classification system and the future research project it will inspire, is one of the most exciting things I have worked on in my career.”

Image Credit: iStock

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