Innate lymphoid cell recovery and occurrence of GvHD after hematopoietic stem cell transplantation.

Lymphocytes are essential for microbial immunity, tumor surveillance, and tissue homeostasis. However, the in vivo development and function of helper-like innate lymphoid cells (ILCs) in humans remain much less well understood than those of T, B, and NK cells. We monitored hematopoietic stem cell transplantation (HSCT) to determine the kinetics of ILC development in both children and adults. It was found that, unlike NK cells, helper-like ILCs recovered slowly, mirroring the pattern observed for T cells, with normalization achieved at 1 year. The type of graft and the proportion of CD34+ cells in the graft did not significantly affect ILC reconstitution. As HSCT is often complicated by acute or chronic graft-versus-host disease (GVHD), the potential role of ILC subsets in maintaining tissue integrity in these conditions was also analyzed. It was found that GVHD was associated with lower levels of activated and gut-homing NKp44+ ILCP, consistent with a non-redundant role of this ILC subset in preventing this life-threatening disorder in lymphopenic conditions.

Imbalance of Circulating Innate Lymphoid Cell Subpopulations in Patients With Septic Shock.

Background: Septic shock, a major cause of death in critical care, is the clinical translation of a cytokine storm in response to infection. It can be complicated by sepsis-induced immunosuppression, exemplified by blood lymphopenia, an excess of circulating Treg lymphocytes, and decreased HLA-DR expression on circulating monocytes. Such immunosuppression is associated with secondary infections, and higher mortality. The effect of these biological modifications on circulating innate lymphoid cells (ILCs) has been little studied. Methods: We prospectively enrolled patients with septic shock (Sepsis-3 definition) in the intensive care unit (ICU) of Timone CHU Hospital. ICU controls (trauma, cardiac arrest, neurological dysfunction) were recruited at the same time (NCT03297203). We performed immunophenotyping of adaptive lymphocytes (CD3+ T cells, CD19+ B cells, CD4+CD25+FoxP3+ Treg lymphocytes), ILCs (CD3-CD56+ NK cells and helper ILCs - ILC1, ILC2, and ILC3), and monocytes by flow cytometry on fresh blood samples collected between 24 and 72 h after admission. Results: We investigated adaptive and innate circulating lymphoid cells in the peripheral blood of 18 patients in septic shock, 15 ICU controls, and 30 healthy subjects. As expected, the peripheral blood lymphocytes of all ICU patients showed lymphopenia, which was not specific to sepsis, whereas those of the healthy volunteers did not. Circulating CD3+ T cells and CD3-CD56+ NK cells were mainly concerned. There was a tendency toward fewer Treg lymphocytes and lower HLA-DR expression on monocytes in ICU patients with sepsis. Although the ILC1 count was higher in septic patients than healthy subjects, ILC2, and ILC3 counts were lower in both ICU groups. However, ILC3s within the total ILCs were overrepresented in patients with septic shock. The depression of immune responses has been correlated with the occurrence of secondary infections. We did not find any differences in ILC distribution according to this criterion. Conclusion: All ICU patients exhibit lymphopenia, regardless of the nature (septic or sterile) of the initial medical condition. Specific distribution of circulating ILCs, with an excess of ILC1, and a lack of ILC3, may characterize septic shock during the first 3 days of the disease.

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.

Metabolomics identifies a biological response to chronic low-dose natural uranium contamination in urine samples.

Because uranium is a natural element present in the earth's crust, the population may be chronically exposed to low doses of it through drinking water. Additionally, the military and civil uses of uranium can also lead to environmental dispersion that can result in high or low doses of acute or chronic exposure. Recent experimental data suggest this might lead to relatively innocuous biological reactions. The aim of this study was to assess the biological changes in rats caused by ingestion of natural uranium in drinking water with a mean daily intake of 2.7 mg/kg for 9 months and to identify potential biomarkers related to such a contamination. Subsequently, we observed no pathology and standard clinical tests were unable to distinguish between treated and untreated animals. Conversely, LC-MS metabolomics identified urine as an appropriate biofluid for discriminating the experimental groups. Of the 1,376 features detected in urine, the most discriminant were metabolites involved in tryptophan, nicotinate, and nicotinamide metabolic pathways. In particular, N-methylnicotinamide, which was found at a level seven times higher in untreated than in contaminated rats, had the greatest discriminating power. These novel results establish a proof of principle for using metabolomics to address chronic low-dose uranium contamination. They open interesting perspectives for understanding the underlying biological mechanisms and designing a diagnostic test of exposure.

The metabolomic approach identifies a biological signature of low-dose chronic exposure to cesium 137.

Reports have described apparent biological effects of (137)Cs (the most persistent dispersed radionuclide) irradiation in people living in Chernobyl-contaminated territory. The sensitive analytical technology described here should now help assess the relation of this contamination to the observed effects. A rat model chronically exposed to (137)Cs through drinking water was developed to identify biomarkers of radiation-induced metabolic disorders, and the biological impact was evaluated by a metabolomic approach that allowed us to detect several hundred metabolites in biofluids and assess their association with disease states. After collection of plasma and urine from contaminated and non-contaminated rats at the end of the 9-months contamination period, analysis with a LC-MS system detected 742 features in urine and 1309 in plasma. Biostatistical discriminant analysis extracted a subset of 26 metabolite signals (2 urinary, 4 plasma non-polar, and 19 plasma polar metabolites) that in combination were able to predict from 68 up to 94% of the contaminated rats, depending on the prediction method used, with a misclassification rate as low as 5.3%. The difference in this metabolic score between the contaminated and non-contaminated rats was highly significant (P = 0.019 after ANOVA cross-validation). In conclusion, our proof-of-principle study demonstrated for the first time the usefulness of a metabolomic approach for addressing biological effects of chronic low-dose contamination. We can conclude that a metabolomic signature discriminated (137)Cs-contaminated from control animals in our model. Further validation is nevertheless required together with full annotation of the metabolic indicators.

Circulating endothelial cell count as a diagnostic marker for non-ST-elevation acute coronary syndromes.

BACKGROUND: Shedding of endothelial cells from damaged endothelium into the blood occurs in a variety of vascular disorders. The purpose of this study was to evaluate the utility of circulating endothelial cell (CEC) count as a diagnostic marker of non-ST-elevation acute coronary syndromes (ACSs). METHODS AND RESULTS: CEC counts were determined immediately (H0), 4 hours (H4), and 8 hours (H8) after admission in 60 patients with documented non-ST-elevation ACS and 40 control patients with no evidence of coronary artery disease. A total of 32 patients in the ACS group had elevated CEC counts (>3 cells/mL) in relation to early admission and single-episode chest pain. Patients from the control group had normal CEC counts. The interval between the chest pain episode and elevation was significantly shorter for CEC than troponin I. No correlation was found between the 2 markers. Interestingly, a subgroup of ACS patients with initially normal troponin I levels had high CEC counts, thus allowing early diagnosis in 30% more cases. At H0, the mean area under the receiver operating characteristic curve was significantly higher with the CEC count than with the troponin I level. At H4 and H8, the combined use of CEC and troponin was significantly better as a marker of ACS than CEC alone or troponin I alone. CONCLUSIONS: This study demonstrates that CEC count can be used as an early, specific, independent diagnostic marker for non-ST-elevation ACS. A combined strategy using CEC count and troponin I level could provide an effective diagnostic tool.