Ref. 2018Health8

On-line application form

Supervisor name and surname:
Consuelo Pizarro

Supervisor mail:

Description of the research project:

After Alzheimer's disease, Parkinson's disease (PD) is the second most widespread neurodegenerative disorder in the word. In the near future, its importance will increase due to changes in the age structure of the population. The diagnosis of PD continues to be clinical and post-mortem histological confirmation is necessary. Since other conditions can mimic the initial symptoms of PD, the problems associated with their diagnosis worse, delaying it. To date, there are no definitive biological markers for accurate differential diagnosis. Therefore, there is an urgent need to identify sensitive and specific biomarkers for the early detection of PD in order to assess its severity, predict its evolution and evaluate the effectiveness of treatments. In biomarkers research, several biological samples are candidates as indirect indicators of pathophysiological states, although blood-based biomarkers would be ideal due to their minimal invasiveness. Recent studies suggest that abnormal lipid metabolism contributes to the pathogenesis of various neurodegenerative diseases. In this regard, an untargeted lipidomic approach, focusing on the comprehensive analysis of lipid profiles in biological systems that can serve to differentiate between different clinical states represents a promising field of research.

In this context, the present research project fits with the overall objective of determining lipid profiles in serum and plasma samples of patients with PD, and investigates, throughout a Big Data approach, the existence of differential patterns (lipid signatures) versus the control group and the lipid profile of Alzheimer's patients, in order to use the knowledge obtained to develop a simple diagnostic test.

To achieve this objective, several specific objectives were proposed, in accordance with the steps employed in any lipidomic study:

  • Obtain a representative set of samples
  • Develop sample preparation methods for lipid extraction
  • Obtain unspecific metabolite/lipid profiles of serum and plasma samples using different instrumental analytical platforms
  • Develop and apply multivariate analysis methodologies for the processing and analysis of the unspecific profiles collected
  • Apply big data pattern recognition methods for non-specific metabolic/lipid profiles in order to detect clusters with clinical meaning. Association of differential metabolic/lipid patterns at different stages of Parkinson's disease and in different patient groups
  • Identify lipid biomarkers with high discriminant and/or modelling power between the different sub-populations of patients

The present project is framed within the “Health-Tech” Campus Iberus Action Plan focused on the field of health and new technologies and, more specifically, within the Research Line called “BIG DATA analytics as a tool for medical decision making”, which is based on monitoring, modelling, and characterizing the medical decision-making process to establish guidelines for future data collection, processing and interpretation. The proposed research represents a complex and ambitious challenge, which requires the implementation and integration of advanced instrumental, analytical and big data technologies with medical supervision and expert guidance, to appraise its results and guarantee its real applicability. The balanced composition and interdisciplinary team presenting the project, formed by experts in analytical chemistry, chemometrics and neurodegenerative diseases, undoubtedly enables it to address the scientific and technological challenges proposed and to advance, in the era of Big Data, analytical technologies and personalized medicine, in the research of PD

PHD Programme:
Chemistry (PLAN 781D)
University of La Rioja

Title of the research project:

Lipid biomarkers in parkinson’s disease: a lipidomic approach for identifying lipid signatures in serum and plasma associated with different clinical stages

Supervisor short biography:

Consuelo Pizarro is Full Professor of Analytical Chemistry and Head of the “Process Analysis and Chemometrics” research group at the University of La Rioja. Her multidisciplinary research group has always be driven to face real problems in industrial, agro-food and bioanalytical contexts thanks to the combination of powerful analytical technologies (both spectroscopic and chromatographic) and advanced chemometric tools. Specific research interests include food fingerprinting and authentication, optimization of industrial processes, and development and validation of analytical methods based on separation techniques. Over the last years her research group has focused towards bioanalytical chemistry and metabolomics, particularly towards exploratory analysis of complex biological systems and biomarker discovery

Gross annual salary:

22.000-26.000 €
The employment contract in each recruiting institution will apply internal rules so final retribution might slightly differ.

Working hours:
37,5 hours a week

Full time