Lipid metabolites as potential diagnostic and prognostic biomarkers for acute community acquired pneumonia

Abstract

Early diagnosis of acute community-acquired pneumonia (CAP) is important in patient triage and treatment decisions. To identify biomarkers that distinguish patients with CAP from non-CAP controls, we conducted an untargeted global metabolome analysis for plasma samples from 142 patients with CAP (CAP cases) and 97 without CAP (non-CAP controls). Thirteen lipid metabolites could discriminate between CAP cases and non-CAP controls with area-under-the-receiver-operating-characteristic curve of >0.8 (P ≤ 10(-9)). The levels of glycosphingolipids, sphingomyelins, lysophosphatidylcholines and L-palmitoylcarnitine were higher, while the levels of lysophosphatidylethanolamines were lower in the CAP cases than those in non-CAP controls. All 13 metabolites could distinguish CAP cases from the non-infection, extrapulmonary infection and non-CAP respiratory tract infection subgroups. The levels of trihexosylceramide (d18:1/16:0) were higher, while the levels of lysophosphatidylethanolamines were lower, in the fatal than those of non-fatal CAP cases. Our findings suggest that lipid metabolites are potential diagnostic and prognostic biomarkers for CAP.

Additional molecular testing of saliva specimens improves the detection of respiratory viruses

“…30 Pneumonia was defined by radiological evidence of new or increased pulmonary infiltrate in a chest radiograph and at least one of the following symptoms (cough with or without sputum production, dyspnea, tachypnea, or pleuritic chest pain) plus one auscultatory finding or one sign of infection (core body temperature 438°C, shivers, leukocyte count 410 000 cells/μL or o4000 cells/μL) as described previously. 31 Routine respiratory virus testing in the clinical microbiology laboratory NPA samples were collected in viral transport medium (VTM) as described previously. 32 Routine testing for respiratory viruses was performed using antigen detection by DFA (D 3 Ultra 8 DFA Respiratory Virus Screening and Identification Kit, Diagnostic Hybrids, Inc., Quidel, San Diego, CA, USA), which included influenza A virus, and influenza B virus, parainfluenza viruses 1-3, respiratory syncytial virus (RSV), human metapneumovirus (hMPV) and adenovirus.…”

Molecular Diagnostics in Pulmonary Infections

“…Groups have found metabolic patterns specific to sepsis, some metabolites that potentially can identify severe versus less severe pneumonia, and certain metabolites that may predict poorer outcomes. For instance, To's group found that 13 lipid metabolites could discriminate between CAP and non-CAP cases with an AUC of >0.8, and that trihexosylceramide levels were higher in fatal cases [103]. A separate group used 1D 1H nuclear magnetic resonance (NMR) spectra to generate metabolic profiles from 15 patients with pneumonia; comparing the metabolic profiles using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) they were able to differentiate cases of VAP from those without [104].…”

Predicting human health from biofluid-based metabolomics using machine learning

“…Cancer represented the largest category, with 14 studies 11,12,25,29,[31][32][33][34][35][36][37][38][39] ; cardiovascular 28 , rheumatologic 26 , ‡ , renal ‡ , and respiratory 16 diseases were represented by only one or two studies. Other health states with a small to medium number of studies included neuro/neuropsychiatric 18,19 , endocrine 21,24,40,41 , and infectious disease 14,15,27,30,42,43 , as well as a general 'other' category 17,[44][45][46] .…”