Analytical pitfalls and challenges in clinical metabolomics

Area of Science:

• Clinical research
• Biomedical sciences
• Analytical chemistry

Background:

• Metabolomics is crucial for understanding disease mechanisms and advancing precision medicine.
• It enables personalized prevention and tailored treatments.
• However, challenges in the metabolomics workflow can compromise data quality and biological interpretation.

Purpose of the Study:

• To review the challenges in metabolomics-based clinical research.
• To identify potential pitfalls throughout the entire analytical workflow.
• To provide practical solutions for generating high-quality metabolomics data.

Main Methods:

• Systematic review of potential pitfalls in metabolomics experiments.
• Step-by-step discussion of challenges in study design, sample handling, and analysis.
• Identification of strategies to overcome these challenges.

Main Results:

• Identified numerous challenges in clinical metabolomics, from study design to data analysis.
• Detailed potential pitfalls in sample collection, storage, preparation, separation, and detection.
• Proposed practical solutions to mitigate these issues.

Conclusions:

• Addressing challenges in clinical metabolomics is essential for reliable data generation.
• Implementing robust strategies ensures high-quality data for accurate biological interpretation.
• This facilitates the effective application of metabolomics in precision medicine and clinical diagnostics.