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Respiratory Research
Published in: Respiratory Research 1/2015

Open Access 01-12-2015 | Review

Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections

Authors: Manuela Nickler, Manuel Ottiger, Christian Steuer, Andreas Huber, Janet Byron Anderson, Beat Müller, Philipp Schuetz

Published in: Respiratory Research | Issue 1/2015

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Abstract

Metabolic profiling through targeted quantification of a predefined subset of metabolites, performed by mass spectrometric analytical techniques, allows detailed investigation of biological pathways and thus may provide information about the interaction of different organic systems, ultimately improving understanding of disease risk and prognosis in a variety of diseases. Early risk assessment, in turn, may improve patient management in regard to cite-of-care decisions and treatment modalities. Within this review, we focus on the potential of metabolic profiling to improve our pathophysiological understanding of disease and management of patients. We focus thereby on lower respiratory tract infections (LRTI) including community-acquired pneumonia (CAP) and chronic obstructive pulmonary disease (COPD), an important disease responsible for high mortality, morbidity and costs worldwide. Observational data from numerous clinical and experimental studies have provided convincing data linking metabolic blood biomarkers such as lactate, glucose or cortisol to patient outcomes. Also, identified through metabolomic studies, novel innovative metabolic markers such as steroid hormones, biogenic amines, members of the oxidative status, sphingo- and glycerophospholipids, and trimethylamine-N-oxide (TMAO) have shown promising results. Since many uncertainties remain in predicting mortality in these patients, further prospective and retrospective observational studies are needed to uncover metabolic pathways responsible for mortality associated with LRTI. Improved understanding of outcome-specific metabolite signatures in LRTIs may optimize patient management strategies, provide potential new targets for future individual therapy, and thereby improve patients’ chances for survival.
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Metadata
Title
Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections
Authors
Manuela Nickler
Manuel Ottiger
Christian Steuer
Andreas Huber
Janet Byron Anderson
Beat Müller
Philipp Schuetz
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Respiratory Research / Issue 1/2015
Electronic ISSN: 1465-993X
DOI
https://doi.org/10.1186/s12931-015-0283-6

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