Bioanalysis Zone

Biomarkers of sepsis can predict death

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Using LC and GC with MS, researchers have identified biomarkers to predict death or survival from sepsis infection, which are not linked to the initial severity of sepsis.

A team of researchers led by Stephen Kingsmore (Center for Pediatric Genomic Medicine, Children’s Mercy Hospitals and Clinics, MO, USA) have uncovered biomarkers that could provide a prognosis for patients with sepsis. The team of researchers used two sets of blood plasma (taken at the time of admittance to hospital and 24 h after) from approximately 300 patients admitted to hospital with sepsis infection to study their metabolomes and proteomes using LC and GC with MS. Five biomarkers linked to fatty acid transport and β-oxidation, gluconeogenesis and the citric acid cycle were consistently related to patient outcome across these samples, independent of the initial severity of the infection.

It is hard to predict patient outcome and therefore prescribe a treatment plan for patients suffering from sepsis. Kingsmore kindly explains this further to the Bioanalysis Zone, “There are 11 million physician visits per year by patients with (sepsis) infections. Which of these patients will develop life-threatening sepsis is a mystery. Sepsis is a top ten killer in the US. The transition from infection to life threatening sepsis is highly variable in time. A test that would predict which patients with infection are likely to die from sepsis would allow physicians to admit them to hospital promptly for aggressive fluid resuscitation, antibiotics and organ support.”

The research found these biomarkers were consistent in patients who died from sepsis, and as symptoms and infection progressed, the difference in these biomarkers in patients who survived or died was more significant. As such, patients suffering from severe sepsis or septic shock showed no significant difference in these biomarkers when compared with patients suffering from mild sepsis. This research creates a foundation for the possibility to obtain a prognosis of patient outcome and prescribe medication accordingly.

Using LC and GC with MS, the team of researchers conducted novel research to deduce biomarkers of death by sepsis. Kingsmore explains the significance of this research in terms of bioanalysis, “This work had novel bioanalytical methods. In particular we integrated the metabolome and proteome to impute novel biochemical relationships, both novel class memberships for unannotated biochemicals and novel, potential regulators of metabolic pathways. These methods will be extended in a future study as we add the blood transcriptome to the metabolome and proteome”.

Kingsmore details how he and the vast team of researchers are planning to further this research, “This is one of three manuscripts looking at ‘omic data in this cohort. Our next manuscript will look at the transcriptome, which will strengthen several of the findings of the current data (the manuscript is in preparation). Our next manuscript will study the same data but looking at the biochemistry of acute and chronic renal failure, where we believe we have made some remarkable findings.”

Source: Langley R, Tsalik E, van Velkinburgh J et al. An Integrated Clinico-Metabolomic Model Improves Prediction of Death in Sepsis. Sci. Transl. Med. 5(195) 195ra95 (2013).

 

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