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Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections.
Respir Res 2015; 16:125RR

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.

Authors+Show Affiliations

Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. Manuela.Nickler@ksa.ch.Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. Manuel.Ottiger@ksa.ch.Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland. Christian.Steuer@ksa.ch.Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland. Andreas.Huber@ksa.ch.Principal, Medical Linguistics Consulting, North Olmsted, OH, USA. medlinguistics@sbcglobal.net.Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. happy.mueller@unibas.ch.Medical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. schuetzph@gmail.com. University Department of Medicine, Kantonsspital Aarau, Tellstrasse, CH-5001, Aarau, Switzerland. schuetzph@gmail.com.

Pub Type(s)

Journal Article
Review
Systematic Review

Language

eng

PubMed ID

26471192

Citation

Nickler, Manuela, et al. "Systematic Review Regarding Metabolic Profiling for Improved Pathophysiological Understanding of Disease and Outcome Prediction in Respiratory Infections." Respiratory Research, vol. 16, 2015, p. 125.
Nickler M, Ottiger M, Steuer C, et al. Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections. Respir Res. 2015;16:125.
Nickler, M., Ottiger, M., Steuer, C., Huber, A., Anderson, J. B., Müller, B., & Schuetz, P. (2015). Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections. Respiratory Research, 16, p. 125. doi:10.1186/s12931-015-0283-6.
Nickler M, et al. Systematic Review Regarding Metabolic Profiling for Improved Pathophysiological Understanding of Disease and Outcome Prediction in Respiratory Infections. Respir Res. 2015 Oct 15;16:125. PubMed PMID: 26471192.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections. AU - Nickler,Manuela, AU - Ottiger,Manuel, AU - Steuer,Christian, AU - Huber,Andreas, AU - Anderson,Janet Byron, AU - Müller,Beat, AU - Schuetz,Philipp, Y1 - 2015/10/15/ PY - 2015/08/05/received PY - 2015/09/29/accepted PY - 2015/10/17/entrez PY - 2015/10/17/pubmed PY - 2016/7/13/medline SP - 125 EP - 125 JF - Respiratory research JO - Respir. Res. VL - 16 N2 - 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. SN - 1465-993X UR - https://www.unboundmedicine.com/medline/citation/26471192/Systematic_review_regarding_metabolic_profiling_for_improved_pathophysiological_understanding_of_disease_and_outcome_prediction_in_respiratory_infections L2 - https://respiratory-research.biomedcentral.com/articles/10.1186/s12931-015-0283-6 DB - PRIME DP - Unbound Medicine ER -