Research, which included the participation of BRAINN, analyzed data from over 2,500 individuals with Parkinson’s and developed metrics for each clinical stage of the disease.

Originally published by Agência FAPESP

 

By establishing a new metric, researchers envision advancements in diagnosing and treating a disease that is estimated to affect around 4 million people worldwide.

Maria Fernanda Ziegler | Agência FAPESP – In a study that analyzed brain images from more than 2,500 individuals with Parkinson’s disease across 20 countries, scientists identified neurodegeneration patterns and created metrics for each of the disease’s five clinical stages.

The work, published in NPJ Parkinson’s Disease, represents a breakthrough in understanding Parkinson’s. The analyses and the vast data obtained could lead to significant developments, not only in diagnostic advancements but also in enabling new treatments to be tested and monitored like never before.

 

Read the article:
Laansma, M.A., Zhao, Y., van Heese, E.M., et al. A worldwide study of subcortical shape as a marker for clinical staging in Parkinson’s disease. npj Parkinson’s Dis. 10, 223 (2024). https://doi.org/10.1038/s41531-024-00825-9

 

Approximately 4 million people worldwide are estimated to have Parkinson’s disease, a progressive neurological condition affecting brain structures linked to movement. The disease progresses variably among patients, potentially taking up to 20 years to transition through all stages.

In its early stages, initial signs include tremors, muscle stiffness, and slowed movements on one side of the body. Later, symptoms become bilateral. In the final stage, patients may rely on wheelchairs as leg stiffness prevents walking.

“For many years, clinical diagnosis, supported by complementary exams, has been well established. However, for the first time, it was possible to correlate the disease’s progression scale—the five stages of clinical symptoms—with quantitative changes in brain images,” explains Fernando Cendes, lead researcher at the Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), a FAPESP Research, Innovation, and Dissemination Center (CEPID) based at the State University of Campinas (Unicamp).

BRAINN is part of the ENIGMA Consortium, an international network of scientists in imaging genomics, neurology, and psychiatry. The group leverages high-resolution MRI, genetic data, and other information to study conditions like epilepsy, Parkinson’s, Alzheimer’s, autism, and schizophrenia.

Cendes explains that Parkinson’s disease involves changes in the brain’s basal ganglia—regions associated with automatic movements. However, the study revealed progressive alterations in other cortical areas, previously thought to be less involved in the disease.

“We observed that as each disease stage advanced, there was increased atrophy or hypertrophy not only in movement-related structures but also in other cortical areas. These combinations of atrophy and hypertrophy correlate with the disease’s stage,” he says.

Additionally, researchers found shape differences in various brain structures. Some thalamic regions, responsible for relaying sensory information to the cortex, thickened, while others, such as the amygdala, responsible for social behavior and emotion regulation, atrophied.

“These changes are not visible to the naked eye,” Cendes explains. “They are submillimetric measurements. However, with programs and AI, it is possible to identify patterns and monitor these changes in the future.”

 

Driving New Treatments

By establishing a metric to quantify brain changes related to Parkinson’s stages, the study could have several implications, beginning with improving diagnosis.

“The morphometric data we obtained are sensitive and reproducible, supporting clinical diagnosis. With the vast amount of data from this study, AI-assisted programs could aid clinicians,” Cendes says.

Further implications lie in treatments. Currently, Parkinson’s is incurable, and treatments only address dopamine deficiency—the neurotransmitter lost in patients, which triggers brain changes and symptoms.

Over time, the disease affects other brain areas, causing non-motor symptoms like depression, anxiety, sleep disorders, cognitive decline, and, eventually, dementia.

“These findings allow new ways to monitor treatments developed in the future. The ultimate goal is to find a treatment that halts neurodegeneration or at least slows its progression. The metrics we identified are essential to evaluating future therapies, ensuring they work comprehensively—not just on movement-related areas but also on others affected by the disease,” he emphasizes.

Another significant impact of the study is in data science. The large dataset includes diverse countries, study groups, disease stages, and data types.

“The innovation lies not only in identifying metrics related to Parkinson’s stages but also in the data analysis methods. These advances pave the way for future AI-driven studies on other diseases,” Cendes concludes.

The article A worldwide study of subcortical shape as a marker for clinical staging in Parkinson’s disease can be read at: https://www.nature.com/articles/s41531-024-00825-9.

Also available on UOL.com.br and Veja.com.br.