Autologous hematopoietic stem cell transplantation significantly alters circulating ceramides in peripheral blood of relapsing-remitting multiple sclerosis patients.

BACKGROUND: The common inflammatory disease multiple sclerosis (MS) is a disease of the central nervous system. For more than 25 years autologous hematopoietic stem cell transplantation (AHSCT) has been used to treat MS. It has been shown to be highly effective in suppressing inflammatory activity in relapsing-remitting MS (RRMS) patients. This treatment is thought to lead to an immune system reset, inducing a new, more tolerant system; however, the precise mechanism behind the treatment effect in MS patients is unknown. In this study, the effect of AHSCT on the metabolome and lipidome in peripheral blood from RRMS patients was investigated. METHODS: Peripheral blood samples were collected from 16 patients with RRMS at ten-time points over the five months course of AHSCT and 16 MS patients not treated with AHSCT. Metabolomics and lipidomics analysis were performed using liquid-chromatography high-resolution mass spectrometry. Mixed linear models, differential expression analysis, and cluster analysis were used to identify differentially expressed features and groups of features that could be of interest. Finally, in-house and in-silico libraries were used for feature identification, and enrichment analysis was performed. RESULTS: Differential expression analysis found 657 features in the lipidomics dataset and 34 in the metabolomics dataset to be differentially expressed throughout AHSCT. The administration of cyclophosphamide during mobilization and conditioning was associated with decreased concentrations in glycerophosphoinositol species. Thymoglobuline administration was associated with an increase in ceramide and glycerophosphoethanolamine species. After the conditioning regimen, a decrease in glycerosphingoidlipids concentration was observed, and following hematopoietic stem cell reinfusion glycerophosphocholine concentrations decreased for a short period of time. Ceramide concentrations were strongly associated with leukocyte levels during the procedure. The ceramides Cer(d19:1/14:0) and Cer(d20:1/12:0) were found to be increased (P < .05) in concentration at the three-month follow-up compared to baseline. C16 ceramide, Cer(D18:2/16:0), and CerPE(d16:2(4E,6E)/22:0) were found to be significantly increased in concentration after AHSCT compared to prior to treatment as well as compared to newly diagnosed RRMS patients. CONCLUSION: AHSCT had a larger impact on the lipids in peripheral blood compared to metabolites. The variation in lipid concentration reflects the transient changes in the peripheral blood milieu during the treatment, rather than the changes in the immune system that are assumed to be the cause of clinical improvement within RRMS patients treated with AHSCT. Ceramide concentrations were affected by AHSCT and associated with leukocyte counts and were altered three months after treatment, suggesting a long-lasting effect.

Evaluation of polarity switching for untargeted lipidomics using liquid chromatography coupled to high resolution mass spectrometry.

Untargeted lipidomics using liquid chromatography high-resolution mass spectrometry (LC-HRMS) was performed using polarity switching, and in positive and negative polarity separately on the same set of serum samples, and the performances of the methods were evaluated. Polarity switching causes an increase in the cycle time of the HRMS measurements (1.18 s/cycle vs 0.27 s/cycle), resulting in fewer data points across chromatographic peaks. The coefficient of variation (CV) was on average lower for the added isotopically labelled standards in pooled samples (QC) and patient samples using separate polarities (QC = 5.6%, samples = 12.5%) compared to polarity switching (QC = 8.5%, samples = 13.4%), but the difference was not statistically significant. For the endogenous features measured in the QCs polarity switching resulted in on average significantly higher CVs (3.80 (p = 4.25e-30) and 3.3 percentage points (p = 6.84e-40), for positive and negative modes, respectively) however still acceptable for an untargeted method (mean CVs of 17.9% and 12.2% in positive and negative modes respectively). A slightly larger number of endogenous features were detected using the separate polarities, but the large majority of features (>95%) were detected with both methodologies. The overlap of features detected in both positive and negative polarities was low (4.1%) demonstrating the importance of using both polarities for untargeted lipidomics. When investigating the effects of a treatment on multiple sclerosis patients it was found that both methodologies gave highly similar biological results, further confirming the applicability of polarity switching.