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. 2010 Jan;3(1):26-35.
doi: 10.4103/0974-2700.58666.

A biomarker panel to discriminate between systemic inflammatory response syndrome and sepsis and sepsis severity

Chamindie Punyadeera  1 , E Marion Schneider, Dave Schaffer, Hsin-Yun Hsu, Thomas O Joos, Fabian Kriebel, Manfred Weiss, Wim Fj Verhaegh
Affiliations

A biomarker panel to discriminate between systemic inflammatory response syndrome and sepsis and sepsis severity

Chamindie Punyadeera et al. J Emerg Trauma Shock. 2010 Jan.

Abstract

Introduction: In this study, we report on initial efforts to discover putative biomarkers for differential diagnosis of a systemic inflammatory response syndrome (SIRS) versus sepsis; and different stages of sepsis. In addition, we also investigated whether there are proteins that can discriminate between patients who survived sepsis from those who did not.

Materials and methods: Our study group consisted of 16 patients, of which 6 died and 10 survived. We daily measured 28 plasma proteins, for the whole stay of the patients in the ICU.

Results: We observed that metalloproteinases and sE-selectin play a role in the distinction between SIRS and sepsis, and that IL-1alpha, IP-10, sTNF-R2 and sFas appear to be indicative for the progression from sepsis to septic shock. A combined measurement of MMP-3, -10, IL-1alpha, IP-10, sIL-2R, sFas, sTNF-R1, sRAGE, GM-CSF, IL-1beta and Eotaxin allows for a good separation of patients that survived from those that died (mortality prediction with a sensitivity of 79% and specificity of 86%). Correlation analysis suggests a novel interaction between IL-1alpha and IP-10.

Conclusion: The marker panel is ready to be verified in a validation study with or without therapeutic intervention.

Keywords: Biomarker; SIRS; cellular mechanism; sepsis outcome; sepsis stage.

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Conflict of interest statement

Conflict of Interest: None declared.

Figures

Figure 1
Figure 1
SIRS vs. sepsis biomarkers. Box plots show the distributions of the log measurements of plasma concentrations across the sample groups of the biomarkers MMP-1, -2, -7, -13 and soluble E-selectin, identified by the ANOVA and correlation analysis for the distinction between SIRS and sepsis
Figure 2
Figure 2
Additional sepsis severity biomarkers. Box plots show the distributions of the log measurements of plasma concentrations across the sample groups of the additional biomarkers IL-1α, IP-10, sTNF-R2 and sFas, identified by the ANOVA and correlation analysis for the distinction SIRS versus sepsis, severe sepsis and septic shock
Figure 3
Figure 3
Best-separating biomarker pairs. Biplots are shown for the three pairs of biomolecules that occur most in the sets that performed well on classifying between SIRS and sepsis
Figure 4
Figure 4
ROC curves. The left figure shows an ROC curve for the distinction between SIRS and sepsis, for the five most-distinguishing biomarkers. The right figure shows an ROC curve for predicting mortality, using the SAPS II score, the SOFA score and the identified panel of 12 biomarkers (MMP-3, -10, IL-1α, IP-10, sIL-2R, sFas, sTNF-R1, sTNF-R2, sRAGE, GM-CSF, IL-1β and Eotaxin)
Figure 5
Figure 5
Correctness of predicting mortality. For each patient and each of the days during his/her ICU stay it is indicated whether mortality is correctly predicted, for a Bayesian classifier using the identified panel of 12 biomarkers (MMP-3, -10, IL-1α, IP-10, sIL-2R, sFas, sTNF-R1, sTNF-R2, sRAGE, GM-CSF, IL-1β and Eotaxin). The colors indicate the sepsis score (green: score 3 - SIRS or less; orange: score 4 - sepsis; red: score 5 - severe sepsis; dark red: score 6 - septic shock)
Figure 6
Figure 6
Correlation plot of the 28 measured biomolecules. Shown is the Pearson correlation between the log measurements of each pair of biomolecules. Dark red means a correlation of +1 (see e.g., the diagonal), and dark blue means a correlation of −1. Furthermore, black dots indicate correlations with an absolute value greater than 0.8
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