The oxylipin and endocannabidome responses in acute phase Plasmodium falciparum malaria in children

Abstract

BackgroundOxylipins and endocannabinoids are low molecular weight bioactive lipids that are crucial for initiation and resolution of inflammation during microbial infections. Metabolic complications in malaria are recognized contributors to severe and fatal malaria, but the impact of malaria infection on the production of small lipid derived signalling molecules is unknown. Knowledge of immunoregulatory patterns of these molecules in malaria is of great value for better understanding of the disease and improvement of treatment regimes, since the action of these classes of molecules is directly connected to the inflammatory response of the organism.MethodsDetection of oxylipins and endocannabinoids from plasma samples from forty children with uncomplicated and severe malaria as well as twenty controls was done after solid phase extraction followed by chromatography mass spectrometry analysis. The stable isotope dilution method was used for compound quantification. Data analysis was done with multivariate (principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA®) and univariate approaches (receiver operating characteristic (ROC) curves, t tests, correlation analysis).ResultsForty different oxylipin and thirteen endocannabinoid metabolites were detected in the studied samples, with one oxylipin (thromboxane B2, TXB2) in significantly lower levels and four endocannabinoids (OEA, PEA, DEA and EPEA) at significantly higher levels in infected individuals as compared to controls according to t test analysis with Bonferroni correction. Three oxylipins (13-HODE, 9-HODE and 13-oxo-ODE) were higher in severe compared to uncomplicated malaria cases according to the results from multivariate analysis. Observed changes in oxylipin levels can be connected to activation of cytochrome P450 (CYP) and 5-lipoxygenase (5-LOX) metabolic pathways in malaria infected individuals compared to controls, and related to increased levels of all linoleic acid oxylipins in severe patients compared to uncomplicated ones. The endocannabinoids were extremely responsive to malaria infection with majority of this class of molecules found at higher levels in infected individuals compared to controls.ConclusionsIt was possible to detect oxylipin and endocannabinoid molecules that can be potential biomarkers for differentiation between malaria infected individuals and controls and between different classes of malaria. Metabolic pathways that could be targeted towards an adjunctive therapy in the treatment of malaria were also pinpointed.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-017-2001-y) contains supplementary material, which is available to authorized users.

L-arginine supplementation and thromboxane synthase inhibition increases cerebral blood flow in experimental cerebral malaria

“…Little is known about any role of TxA2 in ECM pathogenesis, although an early hypothesis proposed that TxA2 would exert deleterious effects in malaria through its vasoconstrictor and platelet aggregation properties whereas prostacyclin, with the opposite profile, would be protective 41 . A recent study with a limited number of plasma samples from uncomplicated and severe malaria patients indicated that TxA2 plasma levels were lower in malaria than in uninfected healthy controls 42 . However, plasma levels of TxA2 may be more representative of systemic production by platelets, whereas the local astrocyte source may be more relevant for the brain levels as measured here.…”

Distinct amino acid and lipid perturbations characterize acute versus chronic malaria

“…Liquid chromatography-mass spectrometry (LC-MS) is a powerful tool for analyzing the large repertoire of metabolites present in biological samples, and for distinguishing healthy and disease states (13). Striking changes in the plasma levels of amines, fatty acids, glycerophospholipids, endocannabinoids, and hemoglobin-related metabolites have been associated with severe P. falciparum malaria in humans (14)(15)(16)(17). Specific metabolic profiles have also characterized chloroquine-resistant and high-parasite-density Plasmodium vivax malaria in humans (18,19).…”

Joint and unique multiblock analysis of biological data – multiomics malaria study

“…Samples were extracted and analyzed with the GCMS metabolomics proling method, 29 with LCMS metabolomics and lipidomics proling methods 27 and with oxylipin targeted LCMS proling. 28 For easy interpretation, and due to the large overlap between detected compounds and the fact that they were extracted in the same sample preparation step, metabolomics GCMS and LCMS data (from both ionization modes) were combined into one metabolomic data set. For compounds that were common between platforms or between LCMS ionization modes, the ones with lower relative standard deviations in the pooled samples were kept in the table.…”

“…These results are consistent with the ones obtained from the OPLS-DA analysis of differences between patients and controls performed for separate data sets. 27,28 This conrms that JUMBA can be used for the fast, successful integration and extraction of relevant information from the multiblock data. While nding correlations between different data sets corresponding to the known sample groups by studying data sets separately and then combining the results is possible to some extent, analysis of any trends in common between blocks that are not known a priori can only be carried out using an integrated approach.…”

“…26 The study was later expanded to the analysis of another set of samples and application of an additional two platforms: LCMS lipid 27 and oxylipin proling. 28 In these studies, we showed that the malaria infection altered the lipid and oxylipin patterns and that these changes could be connected to energy turnover and immune regulation. In the present study we wanted to see if we can conrm the ndings from the analysis of separate data sets by application of a faster, integrative approach and to investigate if such an approach can provide more information about unknown trends/structures in the data that can be used for enhanced interpretation of the studied data sets.…”