Onchocerca volvulus-neurotransmitter tyramine is a biomarker for river blindness.

Onchocerciasis, also known as "river blindness", is a neglected tropical disease infecting millions of people mainly in Africa and the Middle East but also in South America and Central America. Disease infectivity initiates from the filarial parasitic nematode Onchocerca volvulus, which is transmitted by the blackfly vector Simulium sp. carrying infectious third-stage larvae. Ivermectin has controlled transmission of microfilariae, with an African Program elimination target date of 2025. However, there is currently no point-of-care diagnostic that can distinguish the burden of infection--including active and/or past infection--and enable the elimination program to be effectively monitored. Here, we describe how liquid chromatography-MS-based urine metabolome analysis can be exploited for the identification of a unique biomarker, N-acetyltyramine-O,ß-glucuronide (NATOG), a neurotransmitter-derived secretion metabolite from O. volvulus. The regulation of this tyramine neurotransmitter was found to be linked to patient disease infection, including the controversial antibiotic doxycycline treatment that has been shown to both sterilize and kill adult female worms. Further clues to its regulation have been elucidated through biosynthetic pathway determination within the nematode and its human host. Our results demonstrate that NATOG tracks O. volvulus metabolism in both worms and humans, and thus can be considered a host-specific biomarker for onchocerciasis progression. Liquid chromatography-MS-based urine metabolome analysis discovery of NATOG not only has broad implications for a noninvasive host-specific onchocerciasis diagnostic but provides a basis for the metabolome mining of other neglected tropical diseases for the discovery of distinct biomarkers and monitoring of disease progression.

Dynamic vaccine blocks relapse to compulsive intake of heroin.

Heroin addiction, a chronic relapsing disorder characterized by excessive drug taking and seeking, requires constant psychotherapeutic and pharmacotherapeutic interventions to minimize the potential for further abuse. Vaccine strategies against many drugs of abuse are being developed that generate antibodies that bind drug in the bloodstream, preventing entry into the brain and nullifying psychoactivity. However, this strategy is complicated by heroin's rapid metabolism to 6-acetylmorphine and morphine. We recently developed a "dynamic" vaccine that creates antibodies against heroin and its psychoactive metabolites by presenting multihaptenic structures to the immune system that match heroin's metabolism. The current study presents evidence of effective and continuous sequestration of brain-permeable constituents of heroin in the bloodstream following vaccination. The result is efficient blockade of heroin activity in treated rats, preventing various features of drugs of abuse: heroin reward, drug-induced reinstatement of drug seeking, and reescalation of compulsive heroin self-administration following abstinence in dependent rats. The dynamic vaccine shows the capability to significantly devalue the reinforcing and motivating properties of heroin, even in subjects with a history of dependence. In addition, targeting a less brain-permeable downstream metabolite, morphine, is insufficient to prevent heroin-induced activity in these models, suggesting that heroin and 6-acetylmorphine are critical players in heroin's psychoactivity. Because the heroin vaccine does not target opioid receptors or common opioid pharmacotherapeutics, it can be used in conjunction with available treatment options. Thus, our vaccine represents a promising adjunct therapy for heroin addiction, providing continuous heroin antagonism, requiring minimal medical monitoring and patient compliance.

Characterization of differences between blood sample matrices in untargeted metabolomics.

Large-scale proteomic and metabolomic technologies are increasingly gaining attention for their use in the diagnosis of human disease. In order to ensure the statistical power of relevant markers, such analyses must incorporate a large number of representative samples. While in a best-case scenario these samples are collected through a study design that is specifically tailored for the desired analysis, often studies must rely upon the analysis of large numbers of previously banked samples that may or may not have complete and accurate documentation of their associated collection and storage methods. In this study, several human blood matrices were analyzed and compared for the quality of metabolomic output. The sample types that were tested include plasma prepared with a variety of anticoagulants and serum collected by venipuncture and capillary blood collection protocols. Analysis with liquid chromatography-mass spectrometry (LC-MS) revealed only subtle differences between the various plasma preparation methods. Differences between the serum and plasma samples appear to be largely peptide/protein-based and are consistent with the biological distinction of the two matrices. Interestingly, the small molecule lysophosphatidylinositol was found to be in higher abundance in plasma, as a possible consequence of the effect of the intrinsic clotting cascade on adjacent metabolic pathways. Comparison of the small-molecule profiles of the capillary- and venipuncture-collected samples revealed 23 statistically significant compound differences between these sample types. Most of these features can be attributed to surfactants and detergents used to pretreat the skin in order to maintain the sterility of sample collection. However, several have identical mass and molecular formulas as endogenous human metabolites and could be erroneously attributed to actual metabolic perturbations. Understanding the extent of these matrix effects is important for control of systematic bias and ensuring the quality of metabolomic analysis.

Metabolomics-based discovery of diagnostic biomarkers for onchocerciasis.

BACKGROUND: Development of robust, sensitive, and reproducible diagnostic tests for understanding the epidemiology of neglected tropical diseases is an integral aspect of the success of worldwide control and elimination programs. In the treatment of onchocerciasis, clinical diagnostics that can function in an elimination scenario are non-existent and desperately needed. Due to its sensitivity and quantitative reproducibility, liquid chromatography-mass spectrometry (LC-MS) based metabolomics is a powerful approach to this problem. METHODOLOGY/PRINCIPAL FINDINGS: Analysis of an African sample set comprised of 73 serum and plasma samples revealed a set of 14 biomarkers that showed excellent discrimination between Onchocerca volvulus-positive and negative individuals by multivariate statistical analysis. Application of this biomarker set to an additional sample set from onchocerciasis endemic areas where long-term ivermectin treatment has been successful revealed that the biomarker set may also distinguish individuals with worms of compromised viability from those with active infection. Machine learning extended the utility of the biomarker set from a complex multivariate analysis to a binary format applicable for adaptation to a field-based diagnostic, validating the use of complex data mining tools applied to infectious disease biomarker discovery and diagnostic development. CONCLUSIONS/SIGNIFICANCE: An LC-MS metabolomics-based diagnostic has the potential to monitor the progression of onchocerciasis in both endemic and non-endemic geographic areas, as well as provide an essential tool to multinational programs in the ongoing fight against this neglected tropical disease. Ultimately this technology can be expanded for the diagnosis of other filarial and/or neglected tropical diseases.