A metabolomic analytical approach permits identification of urinary biomarkers for Plasmodium falciparum infection: a case-control study

Abstract

Background: Currently available diagnostic techniques of Plasmodium falciparum infection are not optimal for non-invasive, population-based screening for malaria. It was hypothesized that a mass spectrometry-based metabolomics approach could identify urinary biomarkers of falciparum malaria.

Methods: The study used a case-control design, with cases consisting of 21 adults in central Ethiopia with a diagnosis of P. falciparum infection confirmed with microscopy, and 25 controls of adults with negative blood smears for malaria matched on age and sex. Urinary samples were collected from these individuals during presentation at the clinic, and a second sample was collected from both cases and controls 4 weeks later, after the cases had received anti-malarial medication. The urine samples were screened for small molecule urinary biomarkers, using mass spectrometry-based metabolomics analyses followed by multivariate analysis using principal component analysis and orthogonal partial least square-discriminant analysis. The chemical identity of statistically significant malaria biomarkers was confirmed using tandem mass spectrometry.

Results: The urinary metabolic profiles of cases with P. falciparum infection were distinct from healthy controls. After treatment with anti-malarial medication, the metabolomic profile of cases resembled that of healthy controls. Significantly altered levels of 29 urinary metabolites were found. Elevated levels of urinary pipecolic acid, taurine, N-acetylspermidine, N-acetylputrescine and 1,3-diacetylpropane were identified as potential biomarkers of falciparum malaria.

Conclusion: The urinary biomarkers of malaria identified have potential for the development of non-invasive and rapid diagnostic test of P. falciparum infection.

Keywords: Biomarker; Falciparum; Malaria; Metabolomics; Urine.

Fig. 1

UHPLC-HRMS base peak chromatograms (BPC) obtained from malaria and control urine samples. BPC of a malaria patients (ESI+), b healthy controls (ESI+), c malaria patients (ESI−) and d healthy controls (ESI−) analysed using a HILIC column. Amino acids such as l-alanine, l-tryptophan, tyrosine and phenylalanine were eluted within the retention time range of 5–6.5 min, whereas, organic acids such as 4-aminohippuric acid, homovanillic acid, lactic acid, uric acid and 2-hydroxyisobutyric acid were detected within a wider retention time window (0.5–5 min). Some urinary pyrimidine nucleosides such as cytidine and uridine were eluted within 2.5 min

Fig. 2

OPLS-DA score plots obtained from urinary metabolomic analysis of malaria patients and controls. a OPLS-DA model was built using control samples (C1; baseline, green circles, n = 25), (C2; follow-up, yellow circles, n = 22), malaria samples: baseline (PF1; red circles, n = 21) and after antimalarial treatment (PF2; light brown circles, n = 20) and pooled QC (dark blue squares), b presents OPLS-DA model generated from C1 and PF1 samples