How to Avoid Sample-Related Biases in Plasma Proteomics Studies?
Our aim is to prevent inter-batch variability in high throughput proteomics that may arise from sample-related factors.
Potential sample related factors include:
① Hemolysis
② Sample contamination
③ Duration of sample storage
④ Pre-treatment methods for plasma samples
Hemolysis:
The results, shown in Figure 1, indicate that the number of identified proteins increased with the severity of hemolysis, with the severe hemolysis group having almost twice as many identified proteins as the no hemolysis group.
Potential sample contamination:
Professor Matthias Mann from the Max Planck Institute has highlighted that platelets, red blood cells, and clotting factors are key contributors to plasma quality issues
Impact of sample storage duration:
On average, 2,932 PGs were identified in samples stored for 0.5 years (see Figure 5). This
number decreased to 1,237 PGs after 4 years and further dropped to 659 PGs after 12 years. This decline is likely due to protein structural changes and degradation over long
storage periods.
Plasma preprocessing methods:
Plasma is typically separated from blood using centrifugation. Research by Shen et al. [2] has shown that the delay before centrifugation can significantly affect plasma proteomics. They found that longer delays before centrifugation lead to higher levels of certain plasma proteins (see Figure 6).
Recommended Plasma Sample Processing Procedure:
Plasma: Centrifuge newly collected samples within 1 hour at room temperature or within 8 hours if kept at 4°C.
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Serum: Allow newly collected samples to clot at room
temperature for 30-60 minutes before centrifugation.
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Storage and Transport: Store samples at -80°C and use dry ice for shipping.
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Additional Guidelines:
- Record the procedures for sample collection and processing.
- Ensure uniform processing methods for all samples within a study. For example, keep centrifugation temperatures and speeds consistent, and use the