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

Isabel M Vincent, Rónán Daly, Bertrand Courtioux, Amy M Cattanach, Sylvain Biéler, Joseph M Ndung'u, Sylvie Bisser, Michael P Barrett, Isabel M Vincent, Rónán Daly, Bertrand Courtioux, Amy M Cattanach, Sylvain Biéler, Joseph M Ndung'u, Sylvie Bisser, Michael P Barrett

Abstract

Treatment for human African trypanosomiasis is dependent on the species of trypanosome causing the disease and the stage of the disease (stage 1 defined by parasites being present in blood and lymphatics whilst for stage 2, parasites are found beyond the blood-brain barrier in the cerebrospinal fluid (CSF)). Currently, staging relies upon detecting the very low number of parasites or elevated white blood cell numbers in CSF. Improved staging is desirable, as is the elimination of the need for lumbar puncture. Here we use metabolomics to probe samples of CSF, plasma and urine from 40 Angolan patients infected with Trypanosoma brucei gambiense, at different disease stages. Urine samples provided no robust markers indicative of infection or stage of infection due to inherent variability in urine concentrations. Biomarkers in CSF were able to distinguish patients at stage 1 or advanced stage 2 with absolute specificity. Eleven metabolites clearly distinguished the stage in most patients and two of these (neopterin and 5-hydroxytryptophan) showed 100% specificity and sensitivity between our stage 1 and advanced stage 2 samples. Neopterin is an inflammatory biomarker previously shown in CSF of stage 2 but not stage 1 patients. 5-hydroxytryptophan is an important metabolite in the serotonin synthetic pathway, the key pathway in determining somnolence, thus offering a possible link to the eponymous symptoms of "sleeping sickness". Plasma also yielded several biomarkers clearly indicative of the presence (87% sensitivity and 95% specificity) and stage of disease (92% sensitivity and 81% specificity). A logistic regression model including these metabolites showed clear separation of patients being either at stage 1 or advanced stage 2 or indeed diseased (both stages) versus control.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. Current diagnosis of HAT.
Fig 1. Current diagnosis of HAT.
CATT: card agglutination test for trypanosomiasis. CSF: cerebrospinal fluid. RDT: Rapid Diagnostic Test.
Fig 2. Variation in metabolic coverage of…
Fig 2. Variation in metabolic coverage of each biofluid.
The percentage shows the number of metabolites detected in each metabolic class (based on matches to the IDEOM database) as a percentage of the total number of metabolites detected in all three groups. Unannotated peaks: masses with no IDEOM database match, no annotated pathway: metabolites that did not match databases for known metabolic pathways. Medium components are those that are commonly found in trypanosome growth medium.
Fig 3. Variability across urine samples.
Fig 3. Variability across urine samples.
(A) Total ion chromatograms (TICs) show the range in concentration of the ions between samples. Ions are analysed in positive (top) and negative (bottom) ionisation modes. The control group is shown as an example. (B) Principal components analysis shows a lack of separation of the sample groups in raw data.
Fig 4. Separation between the metabolite patterns…
Fig 4. Separation between the metabolite patterns of stage 1 and advanced stage 2 CSF samples.
(A) Principal components analysis plot. (B) Histograms for metabolites showing significant differences between control (C), stage 1 (S1) and advanced stage 2 (S2) infected patients. * indicates p

Fig 5. Patients can be classified into…

Fig 5. Patients can be classified into stage 1 and advanced stage 2 groups using…

Fig 5. Patients can be classified into stage 1 and advanced stage 2 groups using eleven biomarkers in CSF.
O-acetylcarnitine and tryptophan match to authentic standards. Some masses did not match to metabolites in the IDEOM [32] database and are identified by the mass only. Red shading indicates peak area intensities above/below the cut-off for advanced stage 2 disease. More information on the cut-offs are shown in S4 Table.

Fig 6. Sleep-inducing metabolites linoleamide and oleamide…

Fig 6. Sleep-inducing metabolites linoleamide and oleamide were increased in both stage 1 and advanced…

Fig 6. Sleep-inducing metabolites linoleamide and oleamide were increased in both stage 1 and advanced stage 2 patients.
Bars show the mean and the standard error of the mean. Metabolite annotations are by mass only. Relative intensities measure peak areas. * indicates p

Fig 7. Metabolite differences in plasma are…

Fig 7. Metabolite differences in plasma are small, but significant.

(A) Principal components analysis. (B)…

Fig 7. Metabolite differences in plasma are small, but significant.
(A) Principal components analysis. (B) Extracted peaks for m/z 133 (ornithine) and m/z 216 (aminododecanoic acid). Stage 1: green, advanced stage 2: blue. (C) Histograms for m/z 133 and m/z 216 (relative intensities measure peak areas). ** indicates a p-value of
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References
    1. Buguet A. Is sleeping sickness a circadian disorder? The serotonergic hypothesis. Chronobiol Int.1999;16: 477–89. Available: http://www.ncbi.nlm.nih.gov/pubmed/10442241 - PubMed
    1. Giordani F, Mwenechanya R, Barrett M. Advances in understanding and treatment of human African trypanosomiasis: divergent diseases caused by distinct parasites In: Padmanabhan S, editor. Handbook of pharmacogenomics and stratified medicine. Academic Press; 2014. pp. 901–916. <10.1016/B978-0-12-386882-4.00039-6>) - DOI
    1. Horn D. Antigenic variation in African trypanosomes. Mol Biochem Parasitol. 2014;195: 123–129. 10.1016/j.molbiopara.2014.05.001 - DOI - PMC - PubMed
    1. Barrett MP, Boykin DW, Brun R, Tidwell RR. Human African trypanosomiasis: pharmacological re-engagement with a neglected disease. Br J Pharmacol. 2007;152: 1155–71. 10.1038/sj.bjp.0707354 - DOI - PMC - PubMed
    1. Steinmann P, Stone CM, Sutherland CS, Tanner M, Tediosi F. Contemporary and emerging strategies for eliminating human African trypanosomiasis due to Trypanosoma brucei gambiense: review. Trop Med Int Heal. 2015;20: 717–18. - PubMed
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Fig 5. Patients can be classified into…
Fig 5. Patients can be classified into stage 1 and advanced stage 2 groups using eleven biomarkers in CSF.
O-acetylcarnitine and tryptophan match to authentic standards. Some masses did not match to metabolites in the IDEOM [32] database and are identified by the mass only. Red shading indicates peak area intensities above/below the cut-off for advanced stage 2 disease. More information on the cut-offs are shown in S4 Table.
Fig 6. Sleep-inducing metabolites linoleamide and oleamide…
Fig 6. Sleep-inducing metabolites linoleamide and oleamide were increased in both stage 1 and advanced stage 2 patients.
Bars show the mean and the standard error of the mean. Metabolite annotations are by mass only. Relative intensities measure peak areas. * indicates p

Fig 7. Metabolite differences in plasma are…

Fig 7. Metabolite differences in plasma are small, but significant.

(A) Principal components analysis. (B)…

Fig 7. Metabolite differences in plasma are small, but significant.
(A) Principal components analysis. (B) Extracted peaks for m/z 133 (ornithine) and m/z 216 (aminododecanoic acid). Stage 1: green, advanced stage 2: blue. (C) Histograms for m/z 133 and m/z 216 (relative intensities measure peak areas). ** indicates a p-value of
All figures (7)
Similar articles
Cited by
References
    1. Buguet A. Is sleeping sickness a circadian disorder? The serotonergic hypothesis. Chronobiol Int.1999;16: 477–89. Available: http://www.ncbi.nlm.nih.gov/pubmed/10442241 - PubMed
    1. Giordani F, Mwenechanya R, Barrett M. Advances in understanding and treatment of human African trypanosomiasis: divergent diseases caused by distinct parasites In: Padmanabhan S, editor. Handbook of pharmacogenomics and stratified medicine. Academic Press; 2014. pp. 901–916. <10.1016/B978-0-12-386882-4.00039-6>) - DOI
    1. Horn D. Antigenic variation in African trypanosomes. Mol Biochem Parasitol. 2014;195: 123–129. 10.1016/j.molbiopara.2014.05.001 - DOI - PMC - PubMed
    1. Barrett MP, Boykin DW, Brun R, Tidwell RR. Human African trypanosomiasis: pharmacological re-engagement with a neglected disease. Br J Pharmacol. 2007;152: 1155–71. 10.1038/sj.bjp.0707354 - DOI - PMC - PubMed
    1. Steinmann P, Stone CM, Sutherland CS, Tanner M, Tediosi F. Contemporary and emerging strategies for eliminating human African trypanosomiasis due to Trypanosoma brucei gambiense: review. Trop Med Int Heal. 2015;20: 717–18. - PubMed
Show all 63 references
Publication types
MeSH terms
[x]
Cite
Copy Download .nbib
Format: AMA APA MLA NLM
Fig 7. Metabolite differences in plasma are…
Fig 7. Metabolite differences in plasma are small, but significant.
(A) Principal components analysis. (B) Extracted peaks for m/z 133 (ornithine) and m/z 216 (aminododecanoic acid). Stage 1: green, advanced stage 2: blue. (C) Histograms for m/z 133 and m/z 216 (relative intensities measure peak areas). ** indicates a p-value of
All figures (7)

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