Dataset Information

Metabolomic and proteomic analysis of serum from preterm infants with necrotising entercolitis and late-onset sepsis.

ABSTRACT:

Background

Necrotising enterocolitis (NEC) and late-onset sepsis (LOS) are the leading causes of death among preterm infants in the developed world. This study aimed to explore the serum proteome and metabolome longitudinally in preterm infants with NEC or LOS, matched to controls.

Methods

Nineteen patients (10 cases, 9 controls) were included. A sample 14 d prior to and following, as well as at disease diagnosis, was included for cases. Controls had serum matched at diagnosis for corresponding case. All samples (n = 39) underwent shotgun proteomic analysis, and 37 samples also underwent metabolomics analysis using ultra performance liquid chromatography-tandem mass spectrometry.

Results

The proteomic and metabolomic profiles of serum were comparable between all infants. Eight proteins were associated with NEC and four proteins were associated with LOS. C-reactive protein was increased in all NEC patients at diagnosis.

Conclusion

No single protein or metabolite was detected in all NEC or LOS cases which was absent from controls; however, several proteins were identified which were associated with disease status. The differing expression of these proteins between diseased infants potentially relates to differing pathophysiology of disease. Thus, it is unlikely a single biomarker exists for NEC and/or LOS.

SUBMITTER: Stewart CJ

PROVIDER: S-EPMC4823643 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Publications

Metabolomic and proteomic analysis of serum from preterm infants with necrotising entercolitis and late-onset sepsis.

Stewart Christopher J CJ Nelson Andrew A Treumann Achim A Skeath Tom T Cummings Stephen P SP Embleton Nicholas D ND Berrington Janet E JE

Pediatric research 20151116 3

<h4>Background</h4>Necrotising enterocolitis (NEC) and late-onset sepsis (LOS) are the leading causes of death among preterm infants in the developed world. This study aimed to explore the serum proteome and metabolome longitudinally in preterm infants with NEC or LOS, matched to controls.<h4>Methods</h4>Nineteen patients (10 cases, 9 controls) were included. A sample 14 d prior to and following, as well as at disease diagnosis, was included for cases. Controls had serum matched at diagnosis for ...[more]

PMID: 26571220

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Project description:BACKGROUND:Host immune responses during late-onset sepsis (LOS) in very preterm infants are poorly characterised due to a complex and dynamic pathophysiology and challenges in working with small available blood volumes. We present here an unbiased transcriptomic analysis of whole peripheral blood from very preterm infants at the time of LOS. METHODS:RNA-Seq was performed on peripheral blood samples (6-29 days postnatal age) taken at the time of suspected LOS from very preterm infants <30 weeks gestational age. Infants were classified based on blood culture positivity and elevated C-reactive protein concentrations as having confirmed LOS (n = 5), possible LOS (n = 4) or no LOS (n = 9). Bioinformatics and statistical analyses performed included pathway over-representation and protein-protein interaction network analyses. Plasma cytokine immunoassays were performed to validate differentially expressed cytokine pathways. RESULTS:The blood leukocyte transcriptional responses of infants with confirmed LOS differed significantly from infants without LOS (1,317 differentially expressed genes). However, infants with possible LOS could not be distinguished from infants with no LOS or confirmed LOS. Transcriptional alterations associated with LOS included genes involved in pathogen recognition (mainly TLR pathways), cytokine signalling (both pro-inflammatory and inhibitory responses), immune and haematological regulation (including cell death pathways), and metabolism (altered cholesterol biosynthesis). At the transcriptional-level cytokine responses during LOS were characterised by over-representation of IFN-?/?, IFN-?, IL-1 and IL-6 signalling pathways and up-regulation of genes for inflammatory responses. Infants with confirmed LOS had significantly higher levels of IL-1? and IL-6 in their plasma. CONCLUSIONS:Blood responses in very preterm infants with LOS are characterised by altered host immune responses that appear to reflect unbalanced immuno-metabolic homeostasis.

Project description:ObjectivesPrediction of late-onset sepsis (onset beyond day 3 of life) in preterm infants, based on multiple patient monitoring signals 24 hours before onset.DesignContinuous high-resolution electrocardiogram and respiration (chest impedance) data from the monitoring signals were extracted and used to create time-interval features representing heart rate variability, respiration, and body motion. For each infant with a blood culture-proven late-onset sepsis, a Cultures, Resuscitation, and Antibiotics Started Here moment was defined. The Cultures, Resuscitation, and Antibiotics Started Here moment served as an anchor point for the prediction analysis. In the group with controls (C), an "equivalent crash moment" was calculated as anchor point, based on comparable gestational and postnatal age. Three common machine learning approaches (logistic regressor, naive Bayes, and nearest mean classifier) were used to binary classify samples of late-onset sepsis from C. For training and evaluation of the three classifiers, a leave-k-subjects-out cross-validation was used.SettingLevel III neonatal ICU.PatientsThe patient population consisted of 32 premature infants with sepsis and 32 age-matched control patients.InterventionsNo interventions were performed.Measurements and main resultsFor the interval features representing heart rate variability, respiration, and body motion, differences between late-onset sepsis and C were visible up to 5 hours preceding the Cultures, Resuscitation, and Antibiotics Started Here moment. Using a combination of all features, classification of late-onset sepsis and C showed a mean accuracy of 0.79 ± 0.12 and mean precision rate of 0.82 ± 0.18 3 hours before the onset of sepsis.ConclusionsInformation from routine patient monitoring can be used to predict sepsis. Specifically, this study shows that a combination of electrocardiogram-based, respiration-based, and motion-based features enables the prediction of late-onset sepsis hours before the clinical crash moment.

Dataset Information

Metabolomic and proteomic analysis of serum from preterm infants with necrotising entercolitis and late-onset sepsis.

Background

Methods

Results

Conclusion

Publications

Metabolomic and proteomic analysis of serum from preterm infants with necrotising entercolitis and late-onset sepsis.

Similar Datasets

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