The metabolic profiles, or metabolomes, of different brain regions, have been successfully measured by researchers at the University of Luxembourg. The findings could help scientists better understand neurodegenerative diseases.

The metabolome represents all or at least a large part of the metabolites in a given tissue, and therfore gives a snapshot of its physiology.

Study leader Dr. Manuel Buttini of the university’s Luxembourg Centre for Systems Biomedicine (LCSB), said:

“Our results, obtained in the mouse, are promising. They open up new opportunities to better understand neurodegenerative diseases, such as Parkinson’s, and could offer new ways to intervene therapeutically. In addition, with the help of metabolic profiles, such as those we have measured, the efficacy of novel therapeutic interventions could be tested more efficiently than with more common approaches."

Pathological Metabolic Alterations

Neurodegenerative processes, such as those occurring in Parkinson’s disease, are characterized by pathological alterations of the brain cells. These cells lose their structure and function, a process that is accompanied by changes in their metabolism.

Until now, most scientists have always focused on just one or a few aspects of the disease to better describe and understand the underlying mechanisms.

By analysing the whole metabolome however, LCSB researchers have realized a more global approach:

They now can analyse hundreds of biomolecules, produced by nerve cells in upper, middle, and lower brain regions of the mouse. In the process, they not only look at healthy brains, but also at brains in which neurodegeneration occurs.

Explains Dr. Christian J├Ąger, one of the three main authors of the study:

“To study the metabolite signatures of the brain, we used gas-chromatography coupled to mass spectrometry. This approach is particularly suitable for the analysis of samples from complex tissues."

Using Machine Learning

With metabolic studies, an area in which the LCSB is one of the worldwide leading institutions, one can assess known and still unknown biomolecules in tissue samples. After the measurements, LCSB-researchers have used a bioinformatical approach known as Machine Learning to specifically derive the metabolic profile of each brain region.

These efforts were spearheaded by Dr. Enrico Glaab, the second main author of the study:

“We found that a multitude of different molecules together reflect a specific functional state of nerve cells in each brain region."

By comparing their observations with microscopic analysis of pathologic processes in nerve cells, the LCSB researchers could show which particular metabolic profile is associated with the degeneration of these cells.

Dr. Alessandro Michelucci, the third main author of the study, adds:

“It was clearly the joined efforts of experts from quite different fields, an interdisciplinary approach that is encouraged at LCSB, that made this study possible. In this case, experts in Neurobiology, Biochemistry, Molecular Biology, and Bioinformatics came together to enable the successful completion of the study."

Says Dr. Manuel Buttini:

“Our observations are important, on the one hand, for paving the way for the discovery of novel therapeutic opportunities to combat neurodegeneration, and, on the other hand, for the development of new drugs to fight diseases such as Parkinson’s or Alzheimer’s. Indeed, by analysing metabolite profiles rather than just microscopic cellular changes or individual biomolecules, a better understanding of the effect of novel therapeutics for brain diseases should be feasible."

Christian Jaeger, Enrico Glaab, Alessandro Michelucci, Tina M. Binz, Sandra Koeglsberger, Pierre Garcia, Jean-Pierre Trezzi, Jenny Ghelfi, Rudi Balling, Manuel Buttini The Mouse Brain Metabolome: Region-Specific Signatures and Response to Excitotoxic Neuronal Injury Am J Pathol 2015, 185: 1-14;

_Photo: Peter Artymiuk, Wellcome Images, Creative Commons by-nc-nd 4.0 _

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