Department of Medicine

Researchers propose biologically based classification system for Parkinson’s disease

rahul.kalvapalle — Tue, 20 Aug 2024 16:17:45 +0000

Researchers propose biologically based classification system for Parkinson’s disease

rahul.kalvapalle Tue, 08/20/2024 - 12:17

Cutline

The "SynNeurGe" classification system for Parkinson's disease, proposed by researchers led by Professor Anthony Lang of the University Health Network and ��ֱ��, is based on three key biomarkers (photo by FG Trade/Getty Images)

Eileen Hoftyzer

Topic

Breaking Research

Department of Medicine

Temerty Faculty of Medicine

Tanz Centre for Research in Neurodegenerative Diseases

Parkinson's

University Health Network

Subheadline

The classification system could enable advancements in the development of tailored treatments for Parkinson's disease

A team of researchers led by Anthony Lang of the University Health Network and the University of Toronto have proposed a novel classification system for Parkinson’s disease that considers biological features and not just clinical symptoms.

The "SynNeurGe" system, described by Lang and collaborators in a paper published in The Lancet Neurology, classifies Parkinson’s disease based on three biomarkers: presence or absence of misfolded alpha synuclein protein, which is believed to cause or contribute to the underlying neurodegeneration; evidence of neurodegeneration using imaging techniques; and presence of gene variants that increase disease risk.

The researchers argue that such a classification system is necessary to advance the development of tailored treatments for Parkinson’s disease.

Professor Anthony Lang (supplied image)

“This is a complex group of disorders that may cause similar symptoms, but biologically they're very different,” says Lang, a senior scientist and Lily Safra Chair in Movement Disorders at UHN and a professor in the department of medicine and the Tanz Centre for Research in Neurodegenerative Disease at ��ֱ��’s Temerty Faculty of Medicine, where he holds the Jack Clark Chair for Parkinson’s Disease Research

“If we cannot find ways to subdivide patients biologically, then applying a therapy designed to affect one biological pathway may not be effective in another group of patients that doesn't have that same pathway involved – and we won’t really have precision or personalized medicine for Parkinson’s disease.”

Currently, Parkinson’s disease is classified based on clinical presentation and symptoms, but the disease can affect the brain for years, possibly even decades, before symptoms appear. For future therapies to treat the underlying disease rather than just the symptoms, patients will need early intervention and treatments tailored to the biological features of the disease, researchers say.

Similar approaches are being used for other diseases – cancer treatments vary not only by the location of tumors but also their molecular features, and the development of drugs for Alzheimer’s disease is increasingly guided by the specific biological mechanisms involved in the disease.

The SynNeurGe classification system, while based on the three key biomarkers, also considers whether clinical features are present. The different combinations of biomarkers classify the disease into various sub-types.

Lang and co-authors note that such a classification should only be used for research at present, although it will almost certainly have clinical applications.

“Eventually we will see a biological approach influencing clinical care, particularly when we finally have effective disease-modifying therapies,” says Lang. “We currently don’t know how important these biomarkers actually are.

"We need large-scale prospective studies of biomarkers, imaging and clinical features to interpret the results, give patients accurate information about their diagnosis and provide appropriate treatment.”

Lang’s team plans to start conducting such studies of cerebrospinal fluid, skin and blood to look for biomarkers of different sub-types of Parkinson’s disease that will help inform the classification system and the development of tailored therapies.

“Now is the time to think about these diseases not solely based on their clinical manifestations, but to look at the biology and try to separate different biological subtypes so we can ultimately improve treatment for this disease,” Lang says.

Professor Graham Collingridge, director of the Tanz Centre, says Lang and his team’s “landmark paper” is poised to have a significant impact on clinical practice around Parkinson's. “I am delighted that our researchers have played such a key role in this important biological classification,” Collingridge says.

Lang says research by Tanz Centre scholars has contributed significantly to the body of knowledge used to develop the proposed biological classification.

For example, Professor Ekaterina Rogaeva’s research on the genetics and epigenetics of Parkinson’s disease has shown that multiple genes and environments can influence Parkinson’s risk, highlighting the need to tailor therapies based on a patient’s genetic makeup.

Other researchers – including Anurag Tandon, Joel Watts, Martin Ingelsson and Gabor Kovacs – have been studying the role of misfolded alpha synuclein in neurodegeneration as well as cases of Parkinson’s disease where alpha synuclein is absent – which informed how Lang’s team included the protein in the classification.

New cancer treatment slows aggressive neuroendocrine tumours: Study

rahul.kalvapalle — Tue, 02 Jul 2024 13:45:10 +0000

New cancer treatment slows aggressive neuroendocrine tumours: Study

rahul.kalvapalle Tue, 07/02/2024 - 09:45

Cutline

Simron Singh, a medical oncologist at Sunnybrook Health Sciences Centre and associate professor in the Temerty Faculty of Medicine, led a study that found that radioligand therapy reduces the risk of advanced neuroendocrine tumour progression and death (photo by Kevin Van Paassen, Sunnybrook)

Topic

Breaking Research

Department of Medicine

Sunnybrook Health Sciences Centre

Temerty Faculty of Medicine

Cancer

Subheadline

Research led by scientists at Sunnybrook Health Sciences Centre and ��ֱ�� showed radioligand therapy to be an effective first-line treatment for advanced uncurable cancers

A novel approach for early cancer treatment known as radioligand therapy (RLT) has been shown to significantly reduce the risk of advanced neuroendocrine tumour progression and death, according to research led by scientists at Sunnybrook Health Sciences Centre and the University of Toronto.

Results of the multi-centre clinical trial, which were published in The Lancet, provided evidence for the first time that RLT – when applied in the early stages after a patient’s diagnosis – slowed down the progression of aggressive grade 2 and 3 neuroendocrine tumours of the gastrointestinal tract.

The treatment was shown to extend the average time of “progression-free survival” from approximately 8.5 months to 22.8 months.

“This is the first study to show the effectiveness of RLT as the ‘first-line’ treatment with advanced uncurable cancer, or any cancer,” said the study’s global principal investigator Simron Singh, a medical oncologist at Sunnybrook and associate professor in the department of medicine at ��ֱ��’s Temerty Faculty of Medicine. “This trial is groundbreaking not only for patients with neuroendocrine cancers, but for all cancer patients as it has implications for the practice of cancer treatment broadly.”

Singh described RLT as a “game changer” in the treatment of cancer, which has traditionally been carried out by surgery, drugs or radiation. “While it’s technically radiation, it is given via a chemotherapy route through the blood until it reaches the precise location of the tumour,” said Singh, who is also an affiliate scientist at Sunnybrook Research Institute and co-founder of the Susan Leslie Clinic for Neuroendocrine Tumours at Sunnybrook’s Odette Cancer Centre.

RLT involves injecting radioactive isotopes – in this case, the drug Lutathera – through an IV. This method targets specific cancer cell receptors, delivering precise radiation to kill cancer cells while preserving healthy tissue.

The study evaluated the use of RLT earlier as a first-line (or “up front”) treatment for patients newly diagnosed with grade 2 or 3 advanced gastrointestinal neuroendocrine tumours. Although neuroendocrine cancer is uncommon, incidence is rising rapidly, and few treatments exist for patients. This cancer is resistant to most therapies, making it challenging to treat.

The results confirm the clinical benefit of earlier use of RLT for patients diagnosed with aggressive and life-threatening tumours, said Singh. “This is the next step in personalized targeted cancer therapy for patients, focused on more effectively killing cancer cells, while limiting the damage to surrounding healthy tissues.”

Further investigations of RLT as a therapeutic option are ongoing to evaluate overall survival and long-term safety, which will better define next steps for how this therapy will change cancer treatment world-wide.

The multi-site trial included investigators and participants from Canada, the United States, France, Germany, Italy, Netherlands, South Korea, Spain and the UK. An overview of the results was presented at the 2024 American Society of Clinical Oncology (ASCO) Gastrointestinal (GI) Cancers Symposium in January 2024.

Add new author/reporter

Nadia Radovini

Study by ��ֱ��, international researchers predicts worsening dengue spread in Mexico and Brazil

Christopher.Sorensen — Mon, 10 Jun 2024 15:11:55 +0000

Study by ��ֱ��, international researchers predicts worsening dengue spread in Mexico and Brazil

Christopher.Sorensen Mon, 06/10/2024 - 11:11

Cutline

Patients await treatment at an emergency medical care unit for dengue in Brasilia, Brazil (photo by Mateus Bonomi/Anadolu via Getty Images)

Gabrielle Giroday

Topic

Breaking Research

Department of Medicine

Temerty Faculty of Medicine

Global

Research & Innovation

Subheadline

Geospatial machine learning models projected “a more extensive and rapid expansion” of the viral infection than previously thought

Brazil and Mexico may be affected by a much greater spread of dengue in the years to come, according to a new study from the University of Toronto’s Temerty Faculty of Medicine.

The research, published in Nature Communications, used geospatial machine learning models to map out the future spread of dengue in the two countries until 2039 using data related to regional environmental factors as well as historical data on human population mobility.

The model predicted that the percentage of municipalities affected by dengue will rise from 76 to 97 per cent in Brazil and from 55 to 91 per cent in Mexico, which the study notes is “a more extensive and rapid expansion” than previously thought.

“COVID-19 has brought emerging infectious diseases to the forefront of public discussion. The pandemic is a reminder of the profound harm emerging infectious diseases have on health systems,” says the study’s first author Vinyas Harish, an MD/PhD student at Temerty, post-graduate affiliate at the Vector Institute for Artificial Intelligence and clinical clerk at Unity Health Toronto.

Dengue is a viral infection, spread to humans by mosquitoes, that affects 100 to 400 million people each year in tropical and subtropical climates.

While some people experience mild symptoms, for others, dengue can lead to much more serious outcomes like hospitalization or death. No specific treatment for dengue exists, says the World Health Organization, and there was a global spike in cases in 2023 which led to international concern about the surging numbers.

(L-R) Vinyas Harish, Kamran Khan and Isaac Bogoch (supplied images)

For the study, researchers – who included Professor Kamran Khan and Associate Professor Isaac Bogoch from Temerty’s department of medicine – developed and validated their models by looking at more than 8,000 municipalities in Brazil and Mexico over 25 years. They also integrated insights from historical outbreak records, climate change projections and evolutionary history of viral genetic sequences.

The researchers say they believe it’s the first time, to their knowledge, “that spatial models of disease spread have informed origins, pathways and future projections of an emerging infectious disease.”

The paper – led by Oliver Brady of the London School of Hygiene and Tropical Medicine – involved researchers from Canada, the United States, Australia, England, Brazil and Mexico.

Researchers say they hope the findings of the paper help with understanding other emerging infectious diseases, and the best ways of combatting spread of dengue in future.

Department of Medicine

Researchers propose biologically based classification system for Parkinson’s disease

New cancer treatment slows aggressive neuroendocrine tumours: Study

Study by ����ֱ��, international researchers predicts worsening dengue spread in Mexico and Brazil

Study by ��ֱ��, international researchers predicts worsening dengue spread in Mexico and Brazil