Redox State of Pentraxin 3 as a Novel Biomarker for Resolution of Inflammation and Survival in Sepsis |
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Authors: | Friederike Cuello Manu Shankar-Hari Ursula Mayr Xiaoke Yin Melanie Marshall Gonca Suna Peter Willeit Sarah R. Langley Tamani Jayawardhana Tanja Zeller Marius Terblanche Ajay M. Shah Manuel Mayr |
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Affiliation: | 3. From the King''s British Heart Foundation Centre, King''s College London, SE5 9NU London, UK;;4. Department of Experimental Pharmacology and Toxicology, Cardiovascular Research Centre, University Medical Center Hamburg-Eppendorf, Hamburg, 20246 Germany;;5. DZHK (German Center for Cardiovascular Research), partner site Hamburg/Kiel/Lübeck, Germany;;6. Critical Care Medicine, Guy''s and St Thomas'' NHS Foundation Trust, London, SE1 7EH UK;;12. Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK;;8. Department of Neurology, Innsbruck Medical University, Innsbruck, 6020 Austria;;9. Clinic for General and Interventional Cardiology, University Heart Centre Hamburg, Hamburg 20246, Germany |
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Abstract: | In an endotoxaemic mouse model of sepsis, a tissue-based proteomics approach for biomarker discovery identified long pentraxin 3 (PTX3) as the lead candidate for inflamed myocardium. When the redox-sensitive oligomerization state of PTX3 was further investigated, PTX3 accumulated as an octamer as a result of disulfide-bond formation in heart, kidney, and lung—common organ dysfunctions seen in patients with sepsis. Oligomeric moieties of PTX3 were also detectable in circulation. The oligomerization state of PTX3 was quantified over the first 11 days in critically ill adult patients with sepsis. On admission day, there was no difference in the oligomerization state of PTX3 between survivors and non-survivors. From day 2 onward, the conversion of octameric to monomeric PTX3 was consistently associated with a greater survival after 28 days of follow-up. For example, by day 2 post-admission, octameric PTX3 was barely detectable in survivors, but it still constituted more than half of the total PTX3 in non-survivors (p < 0.001). Monomeric PTX3 was inversely associated with cardiac damage markers NT-proBNP and high-sensitivity troponin I and T. Relative to the conventional measurements of total PTX3 or NT-proBNP, the oligomerization of PTX3 was a superior predictor of disease outcome.Severe sepsis is a common acute illness in intensive care units (ICUs)1 and is associated with high mortality rates and chronic morbidity. When it is associated with hypotension (termed septic shock), the mortality rate is very high (50% to 80%). Cardiovascular dysfunction during sepsis is multifactorial and often associated with minimal loss of myocardial tissue, but with the release of myocardial-specific markers such as troponins. A key unmet clinical need is the availability of a biomarker that predicts myocardial dysfunction early, monitors response to treatment, and thus identifies a cohort of patients at higher risk of septic shock to aid in targeted interventions and improve outcome (1).In the present study, we used proteomics for biomarker discovery. Over the past decade, the field of proteomics has made impressive progress. Plasma and serum, however, are the most complex proteomes of the human body (2), and less abundant proteins tend to be missed in untargeted proteomics analyses of body fluids (3). Thus, we pursued an alternative strategy: the application of proteomics to diseased tissue (4), in which the potential biomarkers are less dilute and have a less uncertain cellular origin (5–7). We employed a solubility-based protein-subfractionation methodology to analyze inflammatory proteins that are retained with sepsis tissue. This innovative proteomics approach shall reveal inflammatory molecules that reside and persist within inflamed tissue. We hypothesized that proteins that accumulate in the susceptible tissues are more likely to be biomarker candidates for organ dysfunction than proteins that just circulate in plasma or serum. We then validated our proteomics findings in the preclinical model using samples from sepsis patients admitted to ICUs. |
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