Plasma Metabolomics in Human Pulmonary Tuberculosis Disease: A Pilot Study

Frediani, Jennifer K.; Jones, Dean P.; Tukvadze, Nestan; Uppal, Karan; Sanikidze, Eka; Kipiani, Maia; Tran, ViLinh; Hebbar, Gautam; Walker, Douglas I.; Kempker, Russell R.; Kurani, Shaheen; Colas, Romain A.; Dalli, Jesmond; Tangpricha, Vin; Serhan, Charles N.; Blumberg, Henry M.; Ziegler, Thomas R.

doi:10.1371/journal.pone.0108854

Cited by 139 publications

(115 citation statements)

References 63 publications

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“…These metabolites could be classified in various groups probably related to specific diet, environmental chemicals, and household microbes. This study showed eight metabolites that were specifically up-regulated by the mycobacterial infection, such as glutamate, choline derivatives, M. tuberculosis cell wall glycolipids, and lipid mediators of inflammation (47).…”

Section: Metabolomics and Diagnostic Biomarkersmentioning

confidence: 83%

Metabolomics: Applications and Promise in Mycobacterial Disease

Mirsaeidi

Banoei²,

Winston

et al. 2015

Annals ATS

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Until recently, the study of mycobacterial diseases was trapped in culture-based technology that is more than a century old. The use of nucleic acid amplification is changing this, and powerful new technologies are on the horizon. Metabolomics, which is the study of sets of metabolites of both the bacteria and host, is being used to clarify mechanisms of disease, and can identify changes leading to better diagnosis, treatment, and prognostication of mycobacterial diseases. Metabolomic profiles are arrays of biochemical products of genes in their environment. These complex patterns are biomarkers that can allow a more complete understanding of cell function, dysfunction, and perturbation than genomics or proteomics. Metabolomics could herald sweeping advances in personalized medicine and clinical trial design, but the challenges in metabolomics are also great. Measured metabolite concentrations vary with the timing within a condition, the intrinsic biology, the instruments, and the sample preparation. Metabolism profoundly changes with age, sex, variations in gut microbial flora, and lifestyle. Validation of biomarkers is complicated by measurement accuracy, selectivity, linearity, reproducibility, robustness, and limits of detection. The statistical challenges include analysis, interpretation, and description of the vast amount of data generated. Despite these drawbacks, metabolomics provides great opportunity and the potential to understand and manage mycobacterial diseases.

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Section: Metabolomics and Diagnostic Biomarkersmentioning

confidence: 83%

Metabolomics: Applications and Promise in Mycobacterial Disease

Mirsaeidi

Banoei²,

Winston

et al. 2015

Annals ATS

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“…14,15,22,23 For analysis, samples were batch randomized into 20-sample batches, with each batch containing an equal number of cases and controls in random order. Pooled reference plasma was run prior to and after each batch for quality control and quality assurance.…”

Section: Metabolomic Analysismentioning

confidence: 99%

“…Plasma sample aliquots (65 lL) were treated with 130 lL acetonitrile (2:1 vol/vol) containing an internal isotopic standard mix (3.5 lL per sample) as previously described. 15,23 The internal standard mix for quality control (Supplementary Table S1) consisted of 14 stable isotopic chemicals covering a broad range of chemical properties represented in small molecules. 15 Samples were mixed and placed on ice for 30 minutes prior to centrifugation for 10 minutes (16,100g at 48C) to remove protein.…”

Section: Metabolomic Analysismentioning

confidence: 99%

Metabolome-Wide Association Study of Primary Open Angle Glaucoma

Burgess

Uppal

Walker

et al. 2015

Invest. Ophthalmol. Vis. Sci.

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PURPOSE.To determine if primary open-angle glaucoma (POAG) patients can be differentiated from controls based on metabolic characteristics. METHODS.We used ultra-high resolution mass spectrometry with C18 liquid chromatography for metabolomic analysis on frozen plasma samples from 72 POAG patients and 72 controls. Metabolome-wide Spearman correlation was performed to select differentially expressed metabolites (DEM) correlated with POAG. We corrected P values for multiple testing using Benjamini and Hochberg false discovery rate (FDR). Hierarchical cluster analysis (HCA) was used to depict the relationship between participants and DEM. Differentially expressed metabolites were matched to the METLIN metabolomics database; both DEM and metabolites significantly correlating with DEM were analyzed using MetaboAnalyst to identify metabolic pathways altered in POAG.RESULTS. Of the 2440 m/z (mass/charge) features recovered after filtering, 41 differed between POAG cases and controls at FDR ¼ 0.05. Hierarchical cluster analysis revealed these DEM to associate into eight clusters; three of these clusters contained the majority of the DEM and included palmitoylcarnitine, hydroxyergocalciferol, and high-resolution METLIN matches to sphingolipids, other vitamin D-related metabolites, and terpenes. MetaboAnalyst also indicated likely alteration in steroid biosynthesis pathways.CONCLUSIONS. Global ultrahigh resolution metabolomics emphasized the importance of altered lipid metabolism in POAG. The results suggest specific metabolic processes, such as those involving palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors, may contribute to POAG status and merit more detailed study with targeted methods.

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“…We also recently identified extracellular metabolites specific to M. tuberculosis (25), supporting the potential of metabolomics in exploring novel biomarkers to better understand its biology and pathogenesis. On the other hand, metabolomics applied on direct patient samples may reveal specific diagnostic markers or be used to monitor treatment response (26)(27)(28)(29). It has been shown that volatile organic compounds (VOCs) in the urine of TB patients can be distinguished from those of healthy subjects (26).…”

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confidence: 99%

“…A study using nuclear magnetic resonance spectroscopy-based metabolomics on serum samples from TB patients demonstrated discrimination between patients and healthy controls (27). In another metabolomics study, several abundant metabolites were identified, including two mycobacterium-derived cell wall glycolipids, in EDTA-plasma from TB patients that were not identified in household contacts (28). However, patients with other bacterial infections were not included as controls in these studies, and thus, the potential of such a metabolic profile for use in the diagnosis of TB remains to be determined.…”

mentioning

confidence: 99%

Metabolomic Profiling of Plasma from Patients with Tuberculosis by Use of Untargeted Mass Spectrometry Reveals Novel Biomarkers for Diagnosis

et al. 2015

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h Although tuberculosis (TB) is a reemerging disease that affects people in developing countries and immunocompromised populations in developed countries, the current diagnostic methods are far from optimal. Metabolomics is increasingly being used for studies on infectious diseases. We performed metabolome profiling of plasma samples to identify potential biomarkers for diagnosing TB. We compared the plasma metabolome profiles of TB patients (n ‫؍‬ 46) with those of community-acquired pneumonia (CAP) patients (n ‫؍‬ 30) and controls without active infection (n ‫؍‬ 30) using ultrahigh-performance liquid chromatographyelectrospray ionization-quadrupole time of flight mass spectrometry (UHPLC-ESI-QTOFMS). Using multivariate and univariate analyses, four metabolites, 12R-hydroxy-5Z,8Z,10E,14Z-eicosatetraenoic acid [12(R)-HETE], ceramide (d18:1/16:0), cholesterol sulfate, and 4␣-formyl-4␤-methyl-5␣-cholesta-8-en-3␤-ol, were identified and found to have significantly higher levels in TB patients than those in CAP patients and controls. In a comparison of TB patients and controls, the four metabolites demonstrated area under the receiver operating characteristic curve ( T uberculosis (TB) is a disease caused by the bacterium Mycobacterium tuberculosis. Although it is a well-known disease that has been around for much of human history, there are still millions of new TB cases occurring per year worldwide, and TB remains a leading cause of deaths worldwide, especially in developing countries. Since the 1980s, TB has reemerged as a result of the AIDS epidemic and increasing use of immunosuppressants. In recent years, a higher incidence of extrapulmonary disease in immunocompromised hosts and the emergence of multidrug-resistant strains have further complicated diagnosis and treatment (1-3). Despite the medical importance of TB, diagnosis is still associated with many unresolved problems. The traditional gold standard methods are smear and culture for acid-fast bacilli from clinical specimens. Although culture offers higher sensitivity and specificity than those of smears, it is not useful for culture-negative cases, especially in early, disseminated, or extrapulmonary disease (4, 5). Moreover, it often takes 2 to 6 weeks before culture is positive and even longer for definitive species identification. While newer diagnostic modalities, such as adenosine deaminase levels in pleural fluid, lipoarabinomannan levels in urine, PCR, and Xpert MTB/RIF assays, have been developed (6-12), there are still limitations in terms of their sensitivity and/or specificity.Metabolomics is an emerging platform for studies of infectious diseases or pathogens (13)(14)(15)(16)(17)(18)(19). For TB, the technique has been applied on cultured isolates for differentiation from other Mycobacterium species and studies on the biology and virulence of tuberculosis (14,15,(20)(21)(22). For example, lipidomics studies have revealed novel metabolites potentially associated with growth and virulence of M. tuberculosis (23,24). We also recently identified ...

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Plasma Metabolomics in Human Pulmonary Tuberculosis Disease: A Pilot Study

Cited by 139 publications

References 63 publications

Metabolomics: Applications and Promise in Mycobacterial Disease

Metabolomics: Applications and Promise in Mycobacterial Disease

Metabolome-Wide Association Study of Primary Open Angle Glaucoma

Metabolomic Profiling of Plasma from Patients with Tuberculosis by Use of Untargeted Mass Spectrometry Reveals Novel Biomarkers for Diagnosis

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