JPND consortium

In brief

The CONTROL-PD consortium has received 1.5M€ in funding (2022-2025) from the EU Joint Program for Neurodegenerative Disease. Our research project involves the construction of a large multi-centric and multi-modal dataset to test new hypotheses regarding the propagation of Parkinson's Disease. We are particularly interested in neurodegeneration trajectories (i.e. body-first vs brain-first, cortex-first vs brainstem first) and their functional counterparts (i.e., both motor and non-motor symptoms).

To do so, we collaborate with neurologists and cognitive neuroscientists around the globe to develop a compact battery of cognitive tasks to characterize cognitive phenotypes in several cohorts of individuals at risk for Parkinson's disease and early stage patients, in The Netherlands, France, Canada, Israel, Germany and Australia.

You can already take a look at to see the battery in action. We are currently finishing to pilot the battery and implement multi-lingual instructions.


The World Health Organisation has estimated that 1 in 6 of the world’s population suffer from a neurological condition. With a globally growing elderly population this number tends to increase and so it is not surprising that neurological disorders are now the second leading cause of death worldwide. Parkinson's disease (PD) is the second most common neurodegenerative disease in the world and it is estimated that more than 10 million people worldwide suffer from this condition. Despite being a multi-level pathology, Parkinson’s disease is often classified as a motor disorder since it affects predominately dopaminergic neurons in the substantia nigra and it is widely diagnosed based on the existence of motor symptoms (e.g.: tremors, rigidity, bradykinesia). However, it is estimated that motor features appear when approximately 50–60% of dopaminergic neurons have already been lost. Losing the ability to smell, having trouble sleeping and speaking, being depressed or suffering from cognitive impairments are all symptoms of the prodromal stage of PD that can occur more than 20 years before its diagnosis. Although they dramatically reduce the quality of life of patients and constitute the most prevalent avoidable deaths, these symptoms are generally overlooked in Parkinson’s disease.

The presence of these symptoms in otherwise healthy people, e.g. hyposmia, REM-sleep behavioural disorder (RBD), depression and anxiety, substantially increases the risk of developing PD. In addition, genetic risk factors such as mutations in the LRRK2 and GBA genes are associated with an increased likelihood of developing PD, which is estimated at 26-42% at age 80. Increasing evidence suggests that different prodromal symptoms are associated with different propagation routes of brain dysfunction, and that this clinical heterogeneity protrudes into the clinical phase of PD. Specifically, evidence for both bottom-up (brainstem-to-cortex) and top-down (cortex-to-brainstem) propagation routes has been found. It is crucial to understand how PD propagates through the brain, particularly how inter-individual differences in neuroanatomical involvement lead to different cognitive (and clinical) expressions of PD, and which etiological factors (e.g. genetics) contribute to propagation routes.

A multi-centre approach, where large and diverse cohorts are combined, is necessary for a study that focuses on explaining clinical and cerebral heterogeneity. It would be impossible to collect the dataset proposed here without a multi-site approach to achieve: (1) large sample sizes with diverse genetics and disease stages; (2) combine multiple areas of expertise. This also comes with challenges, because a common framework needs to be in place to integrate data from different centres. Here, we address this challenge by making use of available data in several existing international imaging cohorts, while developing a new cognitive phenotyping procedure that links all of these subjects together. These cognitive data is collected using newly developed procedures to collect detailed behavioural responses remotely at the patients’ home.