Serum or Plasma (and Which Plasma), That Is the Question

Area of Science:

• Clinical Chemistry
• Metabolomics
• Lipidomics

Background:

• Blood derivatives are crucial for clinical metabolomic studies due to their rich biological information and minimally invasive collection.
• However, the type of blood collection tube used can significantly alter plasma and serum metabolic profiles, posing challenges for data standardization.
• Standardization is essential for large-scale epidemiological studies utilizing multicenter cohorts.

Purpose of the Study:

• To compare the metabolomic and lipoprotein profiles of blood samples collected using different tube types: citrate plasma, EDTA plasma, and serum.
• To evaluate the impact of these collection tubes on metabolite levels, correlations, and lipoprotein profiles.
• To propose and validate a statistical method for mitigating collection tube-associated variations.

Main Methods:

• Blood samples from six healthy volunteers were collected simultaneously using citrate, EDTA, and serum tubes.
• Nuclear magnetic resonance (NMR) spectroscopy was employed for comprehensive metabolomic and lipoprotein analysis.
• A regression-based statistical approach was developed to correct for variations introduced by different collection tubes.

Main Results:

• Statistically significant alterations in several metabolites and their correlations were observed across the three blood matrices (citrate plasma, EDTA plasma, serum).
• Collection tubes also affected lipoprotein profiles, although to a lesser extent than metabolite profiles.
• The proposed regression method demonstrated efficiency in reducing the observed alterations in both metabolomic and lipoprotein profiles.

Conclusions:

• Blood collection tube selection critically influences metabolomic and lipoprotein profiles, necessitating careful consideration in study design.
• The developed statistical regression method offers a viable solution to harmonize data from different collection tubes.
• This approach facilitates the scalability of metabolomics and lipoprotein analysis for large-scale, multicenter epidemiological studies.