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Considerations for Soluble Protein Biomarker Blood Sample Matrix Selection.

Joel A Mathews1, Yan G Ni2, Connie Wang3

  • 1Ionis Pharmaceuticals, 2855 Gazelle Rd., Carlsbad, California, 92010, USA. jmathews@ionisph.com.

The AAPS Journal
|January 31, 2020
PubMed
Summary

Selecting the right blood sample matrix (serum vs. plasma) is crucial for accurate protein biomarker quantification in drug development. Differences in sample matrices can significantly alter analyte concentrations, impacting clinical interpretations.

Keywords:
anticoagulantsbiomarkersplasmaplateletsserum

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Area of Science:

  • Biomarker Discovery and Development
  • Clinical Chemistry and Laboratory Medicine

Background:

  • Blood-based soluble protein biomarkers are vital for diagnostics, prognostics, and pharmacodynamics in patient care and drug development.
  • Serum and plasma are the most common blood sample matrices, but their selection can impact biomarker quantification.
  • The choice of sample matrix is often based on convention rather than a thorough understanding of its effects on analyte levels.

Purpose of the Study:

  • To investigate the differences in soluble protein marker quantification between serum and plasma sample matrices.
  • To analyze how factors like platelet or immune cell activation influence analyte concentrations in different matrices.
  • To review the impact of anticoagulants on biomarker quantification and provide recommendations for optimal sample matrix selection.

Main Methods:

  • Analysis of a dataset comprising 32 different soluble protein markers measured in matched serum and plasma samples.
  • Examination of potential confounding factors, including platelet and immune cell activation.
  • Review of the literature concerning the effects of various anticoagulants on protein analyte quantification.

Main Results:

  • Significant differences in quantified concentrations of soluble protein markers were observed between serum and plasma samples.
  • Platelet and immune cell activation were identified as key contributors to matrix-dependent variations in analyte levels.
  • Anticoagulants can also influence the measured concentrations of specific protein biomarkers.

Conclusions:

  • Sample matrix selection critically impacts the reliability and accuracy of protein biomarker quantification.
  • A systematic, data-driven approach is recommended for choosing the appropriate sample matrix in biomarker studies.
  • Awareness of matrix effects is essential for robust biomarker assay development and reliable clinical interpretation.