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Influenza remains the predominant viral cause of community-acquired pneumonia (CAP) in adults [I][II]. The World Health Organization estimates that annual influenza epidemics result in about 3-5 million cases of severe illness and about 250,000 to 500,000 deaths worldwide. Patients aged 65 years or older are at particular risk of death from viral pneumonia, as well as from influenza not complicated by pneumonia, and the fatality rate in adults can reach up to 30 percent in the intensive care unit (ICU), with up to 45 percent of hospitalized patients admitted to the ICU [III].
Early identification of patients with H1N1 influenza pneumonia plays a critical role in the early administration of antiviral drugs, whereas delays in therapy have been associated with increased ICU admission and mortality [IV].
Biomarkers may enable early diagnosis and prognosis, as well as help determine response to treatment. One approach for identifying disease biomarkers is metabolomic profiling.
Metabolomics shows promise as a potential early diagnostic and prognostic tool for H1N1 pneumonia. Targeted and nontargeted metabolomic methods such as proton nuclear magnetic resonance (1H-NMR) spectroscopy, gas chromatography coupled with mass spectrometry (GC-MS), and liquid chromatography coupled mass spectrometry (LC-MS) allow for the identification of more than 4,000 metabolites in human biofluids [V].
Using Bruker's 1H-NMR, as well as GC-MS, Canadian researchers applied metabolomic profiling to diagnose patients with H1N1 pneumonia vs. patients with bacterial CAP and ventilated ICU control subjects. The study found that H1N1 pneumonia can create a quite different plasma metabolic profile from bacterial culture-positive pneumonia and ventilated control subjects in the ICU early in the course of disease[VI].
Orthogonal partial least-squares discriminant analysis (OPLS-DA) models showed a clear discrimination of metabolomic profiles of patients with H1N1 from profiles of patients with CAP with positive bacterial cultures (Fig. 1a and b) and ICU control subjects (Fig. 2a and b).
Additionally, the team analyzed the metabolomic profiling data using supervised OPLS-DA for modeling. Of the NMR data (Fig. 3), 27 different metabolites were used as potential variables to separate nonsurvivors from survivors, indicating very good separation between the two cohorts at the plasma metabolomic level for H1N1 mortality. Fig. 3b shows samples from the survivor and nonsurvivor cohorts were well separated based on 63 features.
Overall, H1N1 infections create a distinct metabolic signature compared to bacterial infection and ventilated ICU control subjects. Metabolomic profiling also revealed that the pathophysiologic pathways initiated or affected by H1N1 infection have a greater influence on the metabolic responses leading to mortality than other observed factors, such as clinical demographics and serious comorbidities.
As a result, metabolomic studies show promise for H1N1 diagnosis and prognosis. Using metabolomic studies as prediction tools for early antiviral therapy and other supportive treatments could result in better outcomes for patients.
[I] Ruuskanen O, Lahti E, Jennings LC, Murdoch DR. Viral pneumonia. Lancet. 2011;377(9773):1264-75
[II] Freed DH, Henzler D, White CW, Fowler R, Zarychanski R, Hutchison J, et al. Extracorporeal lung support for patients who had severe respiratory failure secondary to influenza A (H1N1) 2009 infection in Canada. Can J Anaesth. 2010;57(3):240-7.
[III] Sehgal N, Woodhead M. Predicting the unpredictable: is it possible clinically to separate H1N1 from non-H1N1 community-acquired pneumonia? Thorax. 2011;66(3):187-8.
[IV] Halasa NB. Update on the 2009 pandemic influenza A H1N1 in children. Curr Opin Pediatr. 2010;22(1):83-7.
[V] Psychogios N, Hau DD, Peng J, Guo AC, Mandal R, Bouatra S, et al. The human serum metabolome. PLoS One. 2011;6(2):e16957.
[VI ]Banoei et al. Plasma metabolomics for the diagnosis and prognosis of H1N1 influenza pneumonia. Critical Care (2017) 21:97.