Plasma Biomarkers and Identification of Resilient Metabolic Disruptions in Patients With Venous Thromboembolism Using a Metabolic Systems Approach.

OBJECTIVE: Deep vein thrombosis and pulmonary embolism referred as venous thromboembolism (VTE) are a common cause of morbidity and mortality. Plasma from healthy controls or individuals who have experienced a VTE were analyzed using metabolomics to characterize biomarkers and metabolic systems of patients with VTE. Approach and Results: Polar metabolite and lipidomic profiles from plasma collected 3 months after an incident VTE were obtained using liquid chromatography mass spectrometry. Fasting-state plasma samples from 42 patients with VTE and 42 healthy controls were measured. Plasma metabolomic profiling identified 512 metabolites forming 62 biological clusters. Multivariate analysis revealed a panel of 21 metabolites altogether capable of predicting VTE status with an area under the curve of 0.92 (P=0.00174, selectivity=0.857, sensitivity=0.971). Multiblock systems analysis revealed 25 of the 62 functional biological groups as significantly affected in the VTE group (P<0.05 to control). Complementary correlation network analysis of the dysregulated functions highlighted a subset of the lipidome composed mainly of n-3 long-chain polyunsaturated fatty acids within the predominant triglycerides as a potential regulator of the post-VTE event biological response, possibly controlling oxidative and inflammatory defence systems, and metabolic disorder associated dysregulations. Of interest was microbiota metabolites including trimethylamine N-oxide that remained associated to post incident VTE patients, highlighting a possible involvement of gut microbiota on VTE risk and relapse. CONCLUSIONS: These findings show promise for the elucidation of underlying mechanisms and the design of a diagnostic test to assess the likely efficacy of clinical care in patients with VTE.

In situ isobaric lipid mapping by MALDI-ion mobility separation-mass spectrometry imaging.

The highly diverse chemical structures of lipids make their analysis directly from biological tissue sections extremely challenging. Here, we report the in situ mapping and identification of lipids in a freshwater crustacean Gammarus fossarum using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) in combination with an additional separation dimension using ion mobility spectrometry (IMS). The high-resolution trapped ion mobility spectrometry (TIMS) allowed efficient separation of isobaric/isomeric lipids showing distinct spatial distributions. The structures of the lipids were further characterized by MS/MS analysis. It is demonstrated that MALDI MSI with mobility separation is a powerful tool for distinguishing and localizing isobaric/isomeric lipids.

Can we trust untargeted metabolomics? Results of the metabo-ring initiative, a large-scale, multi-instrument inter-laboratory study.

The metabo-ring initiative brought together five nuclear magnetic resonance instruments (NMR) and 11 different mass spectrometers with the objective of assessing the reliability of untargeted metabolomics approaches in obtaining comparable metabolomics profiles. This was estimated by measuring the proportion of common spectral information extracted from the different LCMS and NMR platforms. Biological samples obtained from 2 different conditions were analysed by the partners using their own in-house protocols. Test #1 examined urine samples from adult volunteers either spiked or not spiked with 32 metabolite standards. Test #2 involved a low biological contrast situation comparing the plasma of rats fed a diet either supplemented or not with vitamin D. The spectral information from each instrument was assembled into separate statistical blocks. Correlations between blocks (e.g., instruments) were examined (RV coefficients) along with the structure of the common spectral information (common components and specific weights analysis). In addition, in Test #1, an outlier individual was blindly introduced, and its identification by the various platforms was evaluated. Despite large differences in the number of spectral features produced after post-processing and the heterogeneity of the analytical conditions and the data treatment, the spectral information both within (NMR and LCMS) and across methods (NMR vs. LCMS) was highly convergent (from 64 to 91 % on average). No effect of the LCMS instrumentation (TOF, QTOF, LTQ-Orbitrap) was noted. The outlier individual was best detected and characterised by LCMS instruments. In conclusion, untargeted metabolomics analyses report consistent information within and across instruments of various technologies, even without prior standardisation.