Luxembourg National Research Fund

An estimated 10% of Parkinson’s Diseases cases are due to genetic factors – in the search for answers as to what could cause the other 90%, research is increasingly finding evidence pointing to environmental factors. To paint a clearer picture of what role chemicals could play in the disease, researchers are for example looking for ‘fingerprints’ of chemicals in biological samples.

Parkinson’s Disease is the second most common neurodegenerative disease, affecting around 6.1 million people worldwide, with incidence is on the rise due to ageing populations. Research has found environmental factors could play a role in the development of up to 90 per cent of all cases, but many questions need answering to paint a clearer picture.

“Previous studies have found differential metabolites between PD patients and healthy controls, where the main perturbed pathways relate to the metabolism of lipids, energy, fatty acids, bile acids plus polyamine and amino acids, yet the role of chemical exposure remains unexplained,” says pharmacist Begoña Talavera Andújar.

Finding the best way to screen thousands of chemicals

Researchers have, for example, turned to non-target high resolution mass spectrometry (NT-HRMS). Coupling this approach with liquid chromatography (LC) allows for the broad screening of thousands of chemicals in complex samples such as blood or feces, capable of detecting very small amounts of analyte.

“My work explores the known and unknown chemicals in NT-HRMS-based exposomics of blood and feces of PD patients,” Begoña Talavera Andújar, who is in the second year of her PhD, explains.

“I am looking for chemicals in blood and faeces of patients with Parkinson’s disease that might be different compared to healthy patients. I use mass spectrometry to look for ‘fingerprints’ of different chemicals in the samples and compare these across the different patients and disease states. This could help us to better understand the disease and discover ‘new chemicals’ that could be used in the near future for an early diagnosis or for the improvement of the current treatment and therapies.”

Creating disease-specific databases

There are millions, if not billions, of chemicals in society. This, combined with limited spectra in databases and the large number of samples needed to generate data with sufficient statistical relevance, makes identifying and interpreting relevant chemicals in complicated substances like feces extremely challenging. Begoña’s work combines analytical and computational developments – cheminformatics tools – to tackle these challenges.

“Cheminformatics tools are essential to analyse high resolution mass spectrometry (HRMS) data, but still require development. Information in open databases is improving, but the interpretation of results remains complicated, because discovering a chemical in a biological sample does not reveal the origin, for example whether it is due the patient’s altered metabolism or an environmental exposure.”

In her research, Begoña combines non-target LC-HRMS with new open cheminformatics tools (such as patRoon or MS-DIAL,) which make it easier to identify chemicals in complicated matrices.

“I then apply analytical and computational developments on different case studies together with international collaborators, who provide cohort samples and new data interpretation strategies. Working together with PubChem, we help improve features for exposomics that are then available to millions of users a month. Thus, with my work, I both help understand PD and improve patient outcomes, while also improving tools used by many researchers across the world beyond my own project.”

Begoña’s research contributes to her research group’s work to develop new cheminformatics approaches to identify relevant chemicals to better understand Parkinson’s Disease (PD). The group has already been able to create several disease-specific databases:

“With PubChem, we created 8 disease-specific databases of over 20,000 chemicals for screening in PD patient samples for either PD, early-stage health states, or related disorders. This will enable faster recognition and diagnosis of PD.”

Pharmacist Begoña Talavera Andújar is a 2^nd year PhD candidate in the Environmental Cheminformatics research group of FNR ATTRACT Fellow Emma Schymanski at the Luxembourg Institute of Systems Biomedicine (LCSB) at the University of Luxembourg. Her research project is funded by the FNR in the framework of the PRIDE Doctoral Training Unit (DTU) MICROH DTU.

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