To derive knowledge on PD onset and progression and linking chemical exposure to perturbed molecular pathways, the FRANKIE project included 7 work packages and multiple interdisciplinary activities. Work performed so far and main results per work package:
- WP 1 – Planning and management
WP1 covered finances, budgeting, and task scheduling. A career development plan was prepared in collaboration with supervisors, addressing training needs, transferable skills, teaching, publication planning, and conference participation.
- WP 2 – Training
Technical training included operation of LC-HRMS instruments, hands-on QA/QC procedures, data analysis, health and safety training, ethics and data protection training and science-to-policy training. Complementary and transferrable skills training included grant writing training, project management training and communication & dissemination training.
- WP 3 – Data acquisition and processing
Analytical method used for data acquisition was firstly thoroughly characterized by analysing 602 chemically diverse standards consisting of native metabolites and chemical exposure agents. Analytical separation was run using two alternative column chemistries, using silica hydride in aqueous normal phase and pentabromobenzyl column in reverse phase. Based on retention properties of standards on both columns, retention mechanisms were estimated and retention prediction models built using support vector regression. Mass spectral data was used to construct spectral libraries, which are used in metabolite annotation.
Plasma samples were analysed using this method and strict quality control protocols. Acquired data was processing using open-source software MzMine 4.
- WP 4 – Data analysis
Data was checked for compliance for strict quality control parameters. Statistical models and machine learning models were constructed and robustly cross validated and candidates for biomarkers proposed. Exposures were annotated using suspect screening approach and associated with neurocognitive outcome.
- WP 5 – Biomarker identification and ssPA
Candidates for biomarkers were annotated against in-house and publicly available mass spectral libraries and experimental or predicted retention times. Structural and correlation networks were constructed and used for annotation propagation. Pathway analysis on differential features was completed using Mummichog algorithm.
- WP 6 – Data interpretation
Biomarker candidates were associated with clinical variables. Features sharing same biological pathway were put in biological context and biological relevance crosschecked with other published scientific results.
-WP 7 – Dissemination, communication and exploitation
Dissemination of the project progression, insights and achievements to the scientific public achieved by publishing scientific paper, preparation of the second paper and two oral presentations on conferences. Communication to general public achieved by presenting on seminars, social media and websites.
