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Study on to unravel Parkinson's mimickerThe goal is for the AI to learn how to help doctors diagnose the specific type of atypical Parkinsonism sooner, tell the 'mimicker' diseases apart from true Parkinson’s disease and speed up the development of better drugs and clinical trials in the future.
Ashwin BM
Last Updated IST
<div class="paragraphs"><p>Representative image for&nbsp;Parkinson’s disease.</p></div>

Representative image for Parkinson’s disease.

Credit: iStock Photo

Bengaluru: The National Institute of Mental Health and Neuro Sciences (Nimhans) has launched a major new study to understand a group of brain diseases which mimics Parkinson’s.

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Known scientifically as atypical Parkinsonian syndromes (APS), these diseases act like Parkinson’s disease, but are much more aggressive and progress faster.

They are responsible for a rapidly worsening and paralysing set of symptoms, where individuals experience a range of psychological and behavioural disturbances, collectively referred to as neuropsychiatric symptoms. 

The study, named ‘ATPARK’, aims to build India’s very first large, detailed set of information on these diseases, which include serious illnesses like progressive supranuclear palsy (PSP) and multiple system atrophy (MSA).

According to researchers, APS are often accompanied by significant psychosocial challenges, including caregiver burden and family dysfunction.

Addressing these needs requires the involvement of a multidisciplinary team comprising occupational therapists, physiotherapists, social workers, psychologists and speech-language pathologists, among others.

Unfortunately, current treatments for atypical Parkinsonian syndromes are limited.

Unlike Parkinson’s, APS lead to a rapid decline, with shorter survival rates. And doctors still don’t fully understand what causes them.

Globally, there is very little research that tracks these patients over many years, known as a longitudinal study. Experts note there is “hardly any from Asia and none from India”.

Dr Ravi Yadav, the lead researcher and a professor at dept of neurology, told DH that by focusing on a population that hasn’t been studied before, the project aims to find unique clues, or biomarkers (warning signs in the body), that are specific to the Indian population.

The ATPARK study will follow 400 patients across various subtypes of the illness. They will be tracked and tested at least three times over a period of years.

The researchers will use a variety of advanced, state-of-the-art tests to look for these crucial warning signs

The deep-dive body check is one where the team will analyse blood and brain fluid (cerebrospinal fluid or CSF) samples to look at the patients’ DNA, proteins and signs of inflammation.

This is like searching for tiny, molecular clues about why the disease progresses.

The advanced scans are when the patients will undergo detailed MRI scans of the brain. They will also use an advanced eye scanning technique called optical coherence tomography (OCT) , a simple eye scan that researchers predict could be a valuable way to track the disease without a brain biopsy.

Finally, during the clinical assessments, doctors will conduct thorough checks on the patients’ balance, movement and thinking skills. They will also perform in-depth sleep studies (using polysomnography or PSG) to see how sleep patterns are affected, as this can often be an early sign of neurodegenerative disease.

AI to speed up diagnosis

A key element of the study is the use of artificial intelligence (AI), specifically machine learning (ML) tools. Since long-term tracking will generate a huge amount of data, researchers will feed it into the AI. The ATPARK study has secured funding from the Pratiksha Trust and started in February 2024, with data collection planned to run until the end of 2029. 

The goal is for the AI to learn how to help doctors diagnose the specific type of atypical Parkinsonism sooner, tell the “mimicker” diseases apart from true Parkinson’s disease and speed up the development of better drugs and clinical trials in the future.

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(Published 16 December 2025, 02:10 IST)