Cytokine Concentrations in Plasma and Serum Samples

Plasma and serum specimens offer an efficient, non-invasive option suitable for many research purposes, including biomarker discovery. Since up to 80% of laboratory errors can be traced to preanalytical variables during collection, processing and storage, it is imperative that laboratories observe proper procedures when collecting whole blood and processing it into plasma and serum samples.^1-3 Recently, Lee et al. (2016) evaluated the impact of delayed separation of whole blood on cytokine concentrations in these specimen types.⁴

To do this, the research team measured the concentration of 16 cytokines after delaying whole-blood centrifugation at room temperature at three time points (4, 6 and 24 hours). They compared these with the values found for specimens separated within two hours of collection.

The team reports that some values were stable under all experimental conditions for serum concentrations (IL-17A and MCP-) and plasma concentrations (IL-5, IL-17A and MIP-1α). In serum samples, five cytokines (IL-1β, IL-6, IL-8, MIP-1α and MIP-1β) showed significant elevation (>/=5-fold) after a 24 hour delay, with a tendency to increase as the delay increased. In plasma specimens, three cytokines (IL-1β, GM-CSF and sCD40L) demonstrated significant elevation (>2-fold) after a 24 hour delay, and one (IL-7) showed slight (40%) but significant elevation.

The team re-evaluated cytokine concentration at a later time point (48 hours). In both sample types, one cytokine (IL-17A) showed no change. In serum samples, the researchers reported wide variations (>5-fold) for five cytokines (IL-1β, IL-6, IL-8, MIP-1α and MIP-1β). In plasma samples, they found significant elevation (>2-fold) for four cytokines (IL-1β, IL-7, MIP-1α and sCD40L).

These findings point to the critical nature of prompt processing of these sample types. Further, the authors indicate that six cytokines (IL-8, MIP- 1α and MIP-1β in serum; IL-1b, GM-CSF and sCD40L in plasma) demonstrated potential utility for diagnosing delayed separation of whole blood.

Lee et al. recommend researcher access to processing data for the samples they choose via markers or standardized coding of preanalytical variables. They offer the Biospecimen Science Working Group of the International Society for Biological and Environmental Repositories’ Standard PREanalytical Code (SPREC) as a model for this.⁵

 

References

1. Lippi, G., et al. (2006) “Preanalytical variability: The dark side of the moon in laboratory testing,” Clinical Chemistry and Laboratory Medicine, 44 (pp. 358–365).

2. Carraro, P. and Plebani, M. (2007) “Errors in a stat laboratory: Types and frequencies 10 years later,” Clinical Chemistry, 53 (pp. 1338–1342).

3 Carraro, P., et al. (2012) “Exploring the initial steps of the testing process: Frequency and nature of pre-preanalytic errors,” Clinical Chemistry, 58 (pp. 638–642).

4. Lee, J-E., et al. (2016) “Impact of whole-blood processing conditions on plasma and serum concentrations of cytokines,” Biopreservation and Biobanking, 14(1) (pp. 51–55). doi: 0.1089/bio.2015.0059.

5. Betsou, F., et al. (2010) “Standard preanalytical coding for biospecimens: Defining the sample PREanalytical code,” Cancer Epidemiological Biomarkers and Prevention, 19 (pp. 1004–1011).