The institute wanted to identify diagnostic biomarkers for neurodegenerative diseases by analysing proteins in extracellular vesicles from cerebrospinal fluid. Shotgun proteomics data contained missing values and required rigorous processing.

Our Approach

We applied rigorous data processing, statistical analysis and biological context assessment to identify diagnostic biomarkers.

• Data processing & statistical analysis: Filtered and imputed timsTOF data, performed pairwise comparisons and produced a detailed report with differentially expressed proteins.
• Quality control: Conducted quality control to remove samples with missing values or unclear phenotypes.
• Biological relevance & knowledge transfer: Assessed biological relevance of candidates through literature searches, suggested follow‑up analyses and held a knowledge‑transfer meeting.

The Outcome

• Delivered an evidence‑based list of differentially expressed proteins and contextualised them biologically.
• Validated quality control and statistical approaches to maximise scientific value within a limited budget.
• Provided guidance for future experiments and ensured knowledge transfer.

Why It Matters

Reliable biomarker discovery pipelines accelerate translational research. This project shows how expert analysis of proteomics data can reveal diagnostic candidates and guide further research.