Pharmacometabolomics is a rapidly emerging omics science signaling the convergence of clinical pharmacology, metabolomics, precision medicine, and biomarker research. Tuberculosis (TB) treatment outcomes have complex biological, environmental, and social determinants and thus, represent a promising application of pharmacometabolomics. In samples of 23 patients undergoing intensive phase TB therapy for 4 weeks, we identified drug-induced host-metabolome variations before and at repeated time intervals post-treatment: (1) an overall reduction in the oxidative stress levels over the course of TB treatment; (2) a time-dependent induction and inhibition of several enzymes in response to the drugs (CYP2E1, CYP3A4, alcohol dehydrogenase, and aminocarboxymuconate-semialdehyde decarboxylase), and altered oxidative stress levels (aconitase, formylglycine-generating enzyme, α-ketoglutarate dehydrogenase, and succinate-semialdehyde dehydrogenase); (3) an upregulated urea cycle; and (4) altered insulin production. This is the first study of its kind to indicate changes to the host metabolome in response to intensive TB treatment, at different time intervals during the course of treatment. These results provide new insights into the mechanisms of TB drug metabolism, drug action, and drug-related side effects, thereby paving the way for the development of improved therapeutic approaches for the disease, and perhaps more importantly, also for monitoring treatment progression.

Background: Animal models are important for tuberculosis (TB) research, offering controlled settings to study disease mechanisms. However, their ability to replicate TB-induced metabolic responses in humans is uncertain. This systematic review evaluated the current use of animal models in metabolomics studies aimed at characterising active pulmonary TB.Methods: PubMed, Scopus, and Web of Science were systematically searched for metabolomics studies of pulmonary TB in humans and animal models, following PRISMA guidelines. Eligible studies were screened, and quality was assessed using QUDOMICS and STAIR tools. Data were synthesised by species, sample matrix, experimental design, and reported differential metabolites. Differential metabolite names were compared between species and subjected to pathway analysis in MetaboAnalyst 6.0.Results: Of the 80 eligible studies, nine involved animal models, predominantly mice. These models captured only 4.7% of human TB-associated differential metabolites, with the highest overlap (3.8%) in mouse lung tissue. Despite low concordance at metabolite level, conserved disruptions were observed in amino acid, glutathione, and one-carbon metabolism pathways. Interspecies variation was evident, influenced by host species, sample matrix, infection protocol, and analytical method.Conclusion: Animal models partially replicated key metabolic features of human TB, particularly at the pathway level. However, variability across studies hampers current translational interpretation. Broader model use, standardised protocols, and integrated multi-platform omics approaches are needed to improve the relevance and comparability of animal models in TB metabolomics research.

Oral hormonal contraceptive users carry the risk of venous thrombosis and increased mortality. This study aimed to comprehensively profile the serum metabolome of participants using a combination of drospirenone (DRSP) and ethinyl estradiol (EE) containing oral contraceptives (COCs). The MxP Quant 500 kit for liquid chromatography mass tandem spectrometry (LC-MS/MS) was used to analyse the 22 controls and 44 COC users (22 on a low EE dose (DRSP/20EE) and 22 on a higher EE dose (DRSP/30EE)). The kit’s results were compared to our internally developed untargeted and targeted metabolomics methods previously applied to this cohort. Of the 630 metabolites included in the method, 277 provided desirable results (consistently detected above their detection limits), and of these, 5 had p-values < 0.05, including betaine, glutamine, cortisol, glycine, and choline. Notably, these variations were observed between the control and COC groups, rather than among the two COC groups. Partial least squares-discriminant analysis revealed 49 compounds with VIP values ≥ 1, including amino acids and their derivatives, ceramides, phosphatidylcholines, and triglycerides, among others. Ten differential compounds were consistent with our previous studies, reinforcing the notion of COCs inducing a prothrombotic state and increased oxidative stress. Although only a limited number of compounds were deemed usable, these were quantified with high reliability and facilitated the identification of meaningful biological differences among the sample groups. In addition to substantiating known drug-induced variations, new hypotheses were also generated.