BackgroundDDX39B (BAT1) encodes an RNA helicase known to regulate expression of TNF and IL-6. Elevated levels of these two cytokines are associated with increased severity of clinical malaria. The aim of this study was to investigate the relationship between single nucleotide polymorphisms (SNPs) in the DDX39B, TNF and IL6 genes and the clinical outcomes of patients with Plasmodium vivax malaria.MethodsCross-sectional investigations were carried out in two regions of the Brazilian Amazon where several studies on the pathogenesis of vivax malaria had been performed. Individuals were categorized according to infection status as well as clinical presentation into the following groups: uninfected, asymptomatic infection, mild infection, or complicated infection. Polymorphisms were identified using PCR restriction fragment-length polymorphism analysis and the restriction enzymes NlaIII or NcoI. The plasma levels of cytokines were determined using ELISA.ResultsThe G allele of DDX39B-22C > G was associated with absent or decreased manifestations of malaria and the C allele was a risk factor for disease complications. Study participants heterozygous for TNF-308 (GA) and DDX39B-348 (CT) had higher TNF levels than wild-type participants. Haplotypes that included DDX39B (-22C > G and -348C > T) and TNF polymorphisms were not directly associated with mild or complicated malaria infections; however, haplotypes AGC, ACC, GGT, AGT and ACT were associated with increased TNF levels. Participants with genotype combinations GC/CC/GG/GG and GG/CT/GG/GG (DDX39B-22/DDX39B-348/TNF-308/IL6-176) had decreased and increased risk of mild malaria, respectively, compared with asymptomatic and uninfected participants. GC/CC/GG/GG was linked to decreased TNF and IL-6 levels.ConclusionsThis is the first study to describe patients with DDX39B and IL6 SNPs who had vivax malaria. These findings support the postulation that a set of mutations in immune-related genes is associated with inflammatory mediators and the clinical outcomes of patients with malaria.
BackgroundHyperbilirubinaemia (bilirubin >51.3 μmol/L) alone is not indicative of severe malaria, and the immune response underlying hyperbilirubinaemia remains largely unexplored. Liver damage associated with hyperbilirubinaemia may alter the expression of hepcidin, which regulates systemic iron by degrading ferroportin. For this study, the association between hepcidin and the levels of cytokines and chemokines in the serum of individuals with mild and severe vivax malaria and subjects with malaria with isolated hyperbilirubinaemia was evaluated.MethodsCytokines/chemokines and hepcidin were measured in individuals with mild (n = 72) and severe (n = 17) vivax malaria, as well as in the serum of subjects with vivax malaria with isolated hyperbilirubinaemia (n = 14) from the Brazilian Amazon between 2009 and 2013 by multiplex assay and ELISA, respectively. The polymorphism 744 G > T in the ferroportin gene was identified by restriction fragment-length polymorphism analysis and the restriction enzyme PvuII.ResultsThe polymorphism at position 744 G > T in the ferroportin gene was typed and no differences in the distributions of genotypes or alleles were observed between the study groups. Subjects with severe malaria had higher levels of interleukin (IL)-2 and IL-13 than subjects with hyperbilirubinaemia. No differences in the expression of immune markers were observed between subjects with mild malaria and those with hyperbilirubinaemia. However, hepcidin levels were higher in individuals with severe malaria and hyperbilirubinaemia than those with mild malaria (p = 0.0002 and p = 0.0004, respectively) and cut-off values of hepcidin differentiated these groups from subjects with mild malaria. Hepcidin was positively associated with IL-6 and IL-10 levels and with parasitaemia in subjects with mild malaria and with IFN-γ in subjects with severe malaria.ConclusionsMalaria in the presence of hyperbilirubinaemia produces a less robust inflammatory response compared to severe cases of malaria. Hepcidin levels are positively associated with immune markers in vivax malaria outcomes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-015-0930-x) contains supplementary material, which is available to authorized users.
We describe the first application of the Near-infrared spectroscopy (NIRS) technique to detect Plasmodium falciparum and P. vivax malaria parasites through the skin of malaria positive and negative human subjects. NIRS is a rapid, non-invasive and reagent free technique which involves rapid interaction of a beam of light with a biological sample to produce diagnostic signatures in seconds. We used a handheld, miniaturized spectrometer to shine NIRS light on the ear, arm and finger of P. falciparum (n=7) and P. vivax (n=20) positive people and malaria negative individuals (n=33) in a malaria endemic setting in Brazil. Supervised machine learning algorithms for predicting the presence or absence of malaria were applied to predict malaria infection status in independent individuals (n=12). Separate machine learning algorithms for differentiating P. falciparum from P. vivax infected subjects were developed using spectra from the arm and ear of P. falciparum and P. vivax (n=108) and the resultant model predicted infection in spectra of their fingers (n=54). NIRS non-invasively detected malaria positive and negative individuals that were excluded from the model with 100% sensitivity, 83% specificity and 92% accuracy (n=12) with spectra collected from the arm. Moreover, NIRS also correctly differentiated P. vivax from P. falciparum positive individuals with a predictive accuracy of 93% (n=54). These findings are promising but further work on a larger scale is needed to address several gaps in knowledge and establish the full capacity of NIRS as a non-invasive diagnostic tool for malaria. It is recommended that the tool is further evaluated in multiple epidemiological and demographic settings where other factors such as age, mixed infection and skin colour can be incorporated into predictive algorithms to produce more robust models for universal diagnosis of malaria.
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