Chronic kidney disease is associated with attenuated plasma metabolome response to oral glucose tolerance testing

Chronic kidney disease (CKD), a major public health problem, is associated with decreased anabolic response to insulin contributing to protein-energy wasting. Targeted metabolic profiling of the response to oral glucose tolerance testing (OGTT) may help identify metabolic pathways contributing to disruptions to insulin response in CKD. Using targeted metabolic profiling, we examined plasma metabolome in 41 moderate-to-severe non-diabetic CKD patients with estimated glomerular filtration rate (eGFR)<60ml/min per 1.73m2 (38.9+-12.7) and 20 healthy controls with normal eGFR (87.2+-17.7) before and after 2h of 75g oral glucose load. Compared to controls, CKD participants had higher lactate: pyruvate (L:P) ratio both at fasting and after oral glucose challenge. Total energy production estimated through GTP:GDP ratio was impaired during OGTT despite similar fasting GTP:GDP ratio. CKD group had sustained elevation of vitamin B family members, TCA cycle metabolites, and purine nucleotides in response to glucose challenge. Metabolic profiling in response to OGTT suggests a broad disruption of mitochondrial energy metabolism in CKD patients. These findings motivate further investigation into insulin sensitizers in patients with non-diabetic CKD and their impact on energy metabolism.

Deep metabolic profiling assessment of tissue extraction protocols for three model organisms

Metabolic profiling harbors the potential to better understand various disease entities such as cancer, diabetes, Alzheimer's, Parkinson's disease or COVID-19. Deciphering these intricate pathways in human studies requires large sample sizes as a means of reducing variability. While such broad human studies have discovered new associations between a given disease and certain affected metabolites, i.e. biomarkers, they often provide limited functional insights. To design more standardized experiments, reduce variability in the measurements and better resolve the functional component of such dynamic metabolic profiles, model organisms are frequently used. Standardized rearing conditions and uniform sampling strategies are prerequisites towards a successful metabolomic study. However, further aspects such as the choice of extraction protocol and analytical technique can influence the outcome drastically. Here, we employed a highly standardized metabolic profiling assay analyzing 630 metabolites across three commonly used model organisms (Drosophila, mouse and Zebrafish) to find the optimal extraction protocols for various matrices. Focusing on parameters such as metabolite coverage, metabolite yield and variance between replicates we compared seven extraction protocols. We found that the application of a combination of 75% ethanol and methyl tertiary-butyl ether (MTBE), while not producing the broadest coverage and highest yields, was the most reproducible extraction protocol. We were able to determine up to 530 metabolites in mouse kidney samples, 509 in mouse liver, 422 in Zebrafish and 388 in Drosophila and discovered a core overlap of 261 metabolites in these four matrices. To enable other scientists to search for the most suitable extraction protocol in their experimental context and interact with this comprehensive data, we have integrated our data set in the open-source shiny app MetaboExtract. This will enable scientists to search for their metabolite or metabolite class of interest, compare it across the different tested extraction protocols and sample types as well as find reference concentrations.

1H Nuclear Magnetic Resonance: A Future Approach to the Metabolic Profiling of Psychedelics in Human Biofluids?

While psychedelics may have therapeutic potential for treating mental health disorders such as depression, further research is needed to better understand their biological effects and mechanisms of action when considering the development of future novel therapy approaches. Psychedelic research could potentially benefit from the integration of metabonomics by proton nuclear magnetic resonance (1H NMR) spectroscopy which is an analytical chemistry-based approach that can measure the breakdown of drugs into their metabolites and their metabolic consequences from various biofluids. We have performed a systematic review with the primary aim of exploring published literature where 1H NMR analysed psychedelic substances including psilocin, lysergic acid diethylamide (LSD), LSD derivatives, N,N-dimethyltryptamine (DMT), 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) and bufotenin. The second aim was to assess the benefits and limitations of 1H NMR spectroscopy-based metabolomics as a tool in psychedelic research and the final aim was to explore potential future directions. We found that the most current use of 1H NMR in psychedelic research has been for the structural elucidation and analytical characterisation of psychedelic molecules and that no papers used 1H NMR in the metabolic profiling of biofluids, thus exposing a current research gap and the underuse of 1H NMR. The efficacy of 1H NMR spectroscopy was also compared to mass spectrometry, where both metabonomics techniques have previously shown to be appropriate for biofluid analysis in other applications. Additionally, potential future directions for psychedelic research were identified as real-time NMR, in vivo1H nuclear magnetic resonance spectroscopy (MRS) and 1H NMR studies of the gut microbiome. Further psychedelic studies need to be conducted that incorporate the use of 1H NMR spectroscopy in the analysis of metabolites both in the peripheral biofluids and in vivo to determine whether it will be an effective future approach for clinical and naturalistic research.