Metabolomics Identifies Multiple Candidate Biomarkers to Diagnose and Stage Human African Trypanosomiasis

Vincent, Isabel M.; Daly, Rónán; Castro, Bertrand; Cattanach, Amy M.; Biéler, Sylvain; Ndung’u, Joseph Mathu; Bisser, Sylvie; Barrett, Michael P.

doi:10.1371/journal.pntd.0005140

Cited by 36 publications

(33 citation statements)

References 59 publications

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“…4 Research Core Unit Metabolomics, Hannover Medical School, Hannover, Germany. 5 Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany. 6 Clinical Neuroimmunology and Neurochemistry, Dept.…”

Section: Acknowledgementsmentioning

confidence: 99%

“…Emerging evidence suggests that measuring concentrations of small molecules in CSF can help to identify CSF biomarkers for various aspects of central nervous system (CNS) infections such as differentiating between infectious and autoimmune etiologies [4], assessing CNS complications of chronic infections [5,6], or detecting CNS extension of infections with a presumed primary site outside of the CNS [7]. We have recently shown that major changes in CSF metabolite populations occur in viral CNS infections [4,7,8] and that certain membrane phospholipids, when measured in cell-free CSF, constitute highly accurate CSF biomarkers for meningoencephalitis during varicella zoster virus (VZV) reactivation [7] and for a diagnosis of enterovirus meningitis even in patients with normal CSF cell counts [8].…”

Section: Introductionmentioning

confidence: 99%

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Phosphatidylcholine PC ae C44:6 in cerebrospinal fluid is a sensitive biomarker for bacterial meningitis

et al. 2020

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Background: The timely diagnosis of bacterial meningitis is of utmost importance due to the need to institute antibiotic treatment as early as possible. Moreover, the differentiation from other causes of meningitis/encephalitis is critical because of differences in management such as the need for antiviral or immunosuppressive treatments. Considering our previously reported association between free membrane phospholipids in cerebrospinal fluid (CSF) and CNS involvement in neuroinfections we evaluated phosphatidylcholine PC ae C44:6, an integral constituent of cell membranes, as diagnostic biomarker for bacterial meningitis. Methods:We used tandem mass spectrometry to measure concentrations of PC ae C44:6 in cell-free CSF samples (n = 221) from patients with acute bacterial meningitis, neuroborreliosis, viral meningitis/encephalitis (herpes simplex virus, varicella zoster virus, enteroviruses), autoimmune neuroinflammation (anti-NMDA-receptor autoimmune encephalitis, multiple sclerosis), facial nerve and segmental herpes zoster (shingles), and noninflammatory CNS disorders (Bell's palsy, Tourette syndrome, normal pressure hydrocephalus).Results: PC ae C44:6 concentrations were significantly higher in bacterial meningitis than in all other diagnostic groups, and were higher in patients with a classic bacterial meningitis pathogen (e.g. Streptococcus pneumoniae, Neisseria meningitidis, Staphylococcus aureus) than in those with less virulent or opportunistic pathogens as causative agents (P = 0.026). PC ae C44:6 concentrations were only moderately associated with CSF cell count (Spearman's ρ = 0.45; P = 0.009), indicating that they do not merely reflect neuroinflammation. In receiver operating characteristic curve analysis, PC ae C44:6 equaled CSF cell count in the ability to distinguish bacterial meningitis from viral meningitis/encephalitis and autoimmune CNS disorders (AUC 0.93 both), but had higher sensitivity (91% vs. 41%) and negative predictive value (98% vs. 89%). A diagnostic algorithm comprising cell count, lactate and PC ae C44:6 had a sensitivity of 97% (specificity 87%) and negative predictive value of 99% (positive predictive value 61%) and correctly diagnosed three of four bacterial meningitis samples that were misclassified by cell count and lactate due to low values not suggestive of bacterial meningitis. © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article' s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article'

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Section: Acknowledgementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Phosphatidylcholine PC ae C44:6 in cerebrospinal fluid is a sensitive biomarker for bacterial meningitis

et al. 2020

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“…There have been several reports of new biological CSF biomarkers or combinations of biomarkers, which have been suggested as potential staging tools for HAT. 28,34,35,36,37,38,39,40 While certainly of considerable interest both biologically and clinically, they all suffer from the same drawback which is that they are compared in sensitivity and specificity with the WHO CSF criteria as well as in some cases neurological features, 36 which, as we have seen, are themselves considered to be problematic in the first place. This approach, while entirely understandable, constitutes a form of inevitable ''circular argument'' because of the lack of a gold standard for comparison.…”

Section: The Problem Of Disease Staging In Hatmentioning

confidence: 99%

The challenging problem of disease staging in human African trypanosomiasis (sleeping sickness): a new approach to a circular question

Njamnshi

Gettinby

Kennedy

2017

Transactions of the Royal Society of Tropical Medicine and Hygiene

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Human African trypanosomiasis (HAT), also known as sleeping sickness, puts millions of people at risk in sub-Saharan Africa and is a neglected parasitic disease that is almost always fatal if untreated or inadequately treated. HAT manifests itself in two stages that are difficult to distinguish clinically. The problem of staging in HAT is extremely important since treatment options, some of which are highly toxic, are directly linked to the disease stage. Several suggested investigations for disease staging have been problematic because of the lack of an existing gold standard with which to compare new clinical staging markers. The somewhat arbitrary current criteria based on the cerebrospinal fluid (CSF) white blood cell (WBC) count have been widely used, but the new potential biomarkers are generally compared with these, thereby making the problem somewhat circular in nature. We propose an alternative 'reverse' approach to address this problem, conceptualised as using appropriate statistical methods to test the performance of combinations of established laboratory variables as staging biomarkers to correlate with the CSF WBC/trypanosomes and clinical features of HAT. This approach could lead to the use of established laboratory staging markers, potentially leading to a gold standard for staging and clinical follow-up of HAT.

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“…To evaluate the performance of the proposed method on actual complex biological data, PALS was used to analyse metabolomics data obtained for a study on Human African Trypanosomiasis (HAT) introduced in [30]. The causative agent of HAT is the parasite Trypanosoma brucei, which is transmitted to a human/mammalian host by the bite of the tsetse fly.…”

Section: Real Data Experimentsmentioning

confidence: 99%

Decomposing metabolite set activity levels with PALS

McLuskey

Wandy

Vincent

et al. 2020

Preprint

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Motivation: Related metabolites can be grouped into metabolite sets in many ways. Examples of these include the grouping of metabolites through their participation in a series of chemical reactions (forming metabolic pathways); or based on fragmentation spectral similarities and shared chemical substructures. Understanding how such metabolite sets change across samples can be incredibly useful in the interpretation and understanding of complex metabolomics data. However many of the available tools suitable for the enrichment analysis of metabolite sets are based on simple methods that badly handle the missing features inherent in untargeted metabolomics measurements and can be difficult to integrate into existing applications. Results: We present PALS (Pathway Activity Level Scoring), a Python library, command-line tool and Web application that performs the ranking of significantly-changing metabolite sets over different experimental conditions. As example applications, PALS is used to analyse metabolites grouped as pathways and by common MS-MS fragmentation structures. A comparison of PALS with two other commonly used methods (ORA and GSEA) is also given, and reveals that PALS is more robust to missing peaks and noisy data than the alternatives. We report results from using PALS to analyse pathways from a study of Human African Trypanosomiasis. Finally, we also report how PALS used tandem MS fragmentation structures to reveal enriched metabolite sets between clades in Rhamnaceae plant data, and on American Gut Project data. Availability: PALS is freely available from our project Web site at https://pals.glasgowcompbio.org/. It can be imported as a Python library, run as a stand-alone tool or used as a web application.

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Metabolomics Identifies Multiple Candidate Biomarkers to Diagnose and Stage Human African Trypanosomiasis

Cited by 36 publications

References 59 publications

Phosphatidylcholine PC ae C44:6 in cerebrospinal fluid is a sensitive biomarker for bacterial meningitis

Phosphatidylcholine PC ae C44:6 in cerebrospinal fluid is a sensitive biomarker for bacterial meningitis

The challenging problem of disease staging in human African trypanosomiasis (sleeping sickness): a new approach to a circular question

Decomposing metabolite set activity levels with PALS

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