Bilateral Remote Ischemic Conditioning in Children:a two-center, double-blind, randomized controlled trial in young children undergoing cardiac surgery

Objective: The study objective was to determine whether adequately delivered bilateral remote ischemic preconditioning is cardioprotective in young children undergoing surgery for 2 common congenital heart defects with or without cyanosis.Methods: We performed a prospective, double-blind, randomized controlled trial at 2 centers in the United Kingdom. Children aged 3 to 36 months undergoing tetralogy of Fallot repair or ventricular septal defect closure were randomized 1:1 to receive bilateral preconditioning or sham intervention. Participants were followed up until hospital discharge or 30 days. The primary outcome was area under the curve for high-sensitivity troponin-T in the first 24 hours after surgery, analyzed by intention-to-treat. Right atrial biopsies were obtained in selected participants.Results: Between October 2016 and December 2020, 120 eligible children were randomized to receive bilateral preconditioning (n = 60) or sham intervention (n = 60). The primary outcome, area under the curve for high-sensitivity troponin-T, was higher in the preconditioning group (mean: 70.0 ± 50.9 μg/L/h, n = 56) than in controls (mean: 55.6 ± 30.1 μg/L/h, n = 58) (mean difference, 13.2 μg/L/h; 95% CI, 0.5-25.8; P = .04). Subgroup analyses did not show a differential treatment effect by oxygen saturations (pinteraction = .25), but there was evidence of a differential effect by underlying defect (pinteraction = .04). Secondary outcomes and myocardial metabolism, quantified in atrial biopsies, were not different between randomized groups.Conclusions: Bilateral remote ischemic preconditioning does not attenuate myocardial injury in children undergoing surgical repair for congenital heart defects, and there was evidence of potential harm in unstented tetralogy of Fallot. The routine use of remote ischemic preconditioning cannot be recommended for myocardial protection during pediatric cardiac surgery

Optimisation of Biofluid and Tissue Metabolite and Lipid Extraction for Clinical Metabolic Phenotyping

Introduction Clinical metabolic phenotyping aims to detect and measure 1000s of metabolites and lipids within clinical samples (e.g. biofluids and tissues) to identify changes between metabolic phenotypes (e.g. disease status) and to understand biochemical mechanisms driving the phenotype. Sample extraction is a critical step in clinical metabolic phenotyping: it must be reproducible and give a high extraction yield of metabolites and lipids. Technological and methodological innovation We tested multiple monophasic and biphasic metabolite/lipid extraction methods for biofluids (urine/plasma) and tissue (heart/kidney/liver). We also tested solvent-biofluid incubation time/temperature. Extracts were analysed by UHPLC-MS assays: HILIC (urine, plasma, tissue polar extracts); C18 aqueous reversed phase [RP] (urine polar extracts); C18 reversed phase (plasma & tissue lipid extracts). Each method was assessed for yield, reproducibility and class of extracted metabolites. Results and impact Based on yield and reproducibility the best methods were: plasma/urine HILIC\u2013 monophasic 50:50 methanol (MeOH):acetonitrile (ACN); urine RP \u2013 any tested monophasic method except 100% ACN; plasma lipids \u2013 monophasic 100% isopropanol (IPA). Altering solvent-biofluid incubation time/temperature had little effect on yield. For tissue, MeOH/CHCl3/H2O was the best all-round method; however, for some specific compounds other methods performed better, e.g. cardiolipins were better extracted by 100% IPA

Oxidized phosphatidylcholines suggest oxidative stress in patients with medium-chain acyl-CoA dehydrogenase deficiency

Inborn errors of metabolism encompass a large group of diseases caused by enzyme deficiencies and are therefore amenable to metabolomics investigations. Medium chain acyl-CoA dehydrogenase deficiency (MCADD) is a defect in β-oxidation of fatty acids, and is one of the most well understood disorders. We report here the use of liquid chromatography–mass spectrometry (LC–MS) based untargeted metabolomics and targeted flow injection analysis–tandem mass spectrometry (FIA–TMS) that lead to discovery of novel compounds of oxidative stress. Dry blood spots of controls (n=25) and patient samples (n=25) were extracted by methanol/water (1/1, v/v) and these supernatants were analyzed by LC–MS method with detection by an Orbitrap Elite MS. Data were processed by XCMS and CAMERA followed by dimension reduction methods. Patients were clearly distinguished from controls in PCA. S-plot derived from OPLS-DA indicated that medium-chain acylcarnitines (octanoyl, decenoyl and decanoyl carnitines) as well as three phosphatidylcholines (PC(16:0,9:0(COOH))), PC(18:0,5:0(COOH)) and PC(16:0,8:0(COOH)) were important metabolites for differentiation between patients and healthy controls. In order to biologically validate these discriminatory molecules as indicators for oxidative stress, a second cohort of individuals were analyzed, including MCADD (n=25) and control (n=250) samples. These were measured by a modified newborn screening method using FIA–TMS (API 4000) in MRM mode. Calculated p-values for PC(16:0,9:0(COOH)), PC(18:0,5:0(COOH)) and PC(16:0,8:0(COOH)) were 1.927×10−14, 2.391×10−15 and 3.354×10−15 respectively. These elevated oxidized phospholipids indeed show an increased presence of oxidative stress in MCADD patients as one of the pathophysiological mechanisms of the disease

Chorioamnionitis alters lung surfactant lipidome in newborns with respiratory distress syndrome

Background: Chorioamnionitis is associated with preterm delivery and morbidities; its role in lung disease is controversial. The aim of this study is to assess the effect of chorioamnionitis on metabolite and lipid profiles of epithelial lining fluid in preterm newborns with respiratory distress syndrome (RDS). Methods: The study involved 30 newborns with RDS, born from mothers with or without histological chorioamnionitis (HCA): HCA+, N = 10; HCA 12, N = 20. Patients had a gestational age 6430 weeks; the groups were matched for age and birth weights. Tracheal aspirates were collected within 24 h after birth and analyzed using liquid chromatography/mass spectrometry-based untargeted lipidomics. Results: According to Mann\u2013Whitney U tests, 570 metabolite features had statistically significantly higher or lower concentrations (p < 0.05) in tracheal aspirates of HCA+ compared to HCA 12, and 241 metabolite features were putatively annotated and classified. The most relevant changes involved higher levels of glycerophospholipids (fold change 2.42\u201317.69) and sphingolipids, with lower concentration of all annotated sphingomyelins in HCA+ (fold change 0.01\u20130.50). Conclusions: Untargeted lipidomics of tracheal aspirates suggested the production of lipid mediators in the context of an ongoing inflammatory status in HCA+ babies. However, the effect of chorioamnionitis on epithelial lining fluid composition deserves further investigations on a larger group of infants. Impact: Our lipidomics investigation on tracheal aspirates of preterm newborns at birth suggested that exposure to maternal histological chorioamnionitis may cause changes in epithelial lining fluid composition.This is the first description of epithelial lining fluid lipidomic profiles in preterm infants with and without exposition to chorioamnionitis.These results could provide novel link between placental membrane inflammation and newborns\u2019 respiratory outcome

Metabolomic and lipidomic changes triggered by lipopolysaccharide-induced systemic inflammation in transgenic APdE9 mice

Peripheral infections followed by systemic inflammation may contribute to the onset of Alzheimer`s disease (AD) and accelerate the disease progression later in life. Yet, the impact of systemic inflammation on the plasma and brain tissue metabolome and lipidome in AD has not been investigated. In this study, targeted metabolomic and untargeted lipidomic profiling experiments were performed on the plasma, cortices, and hippocampi of wild-type (WT) mice and transgenic APdE9 mice after chronic lipopolysaccharide (LPS) treatment, as well as saline-treated APdE9 mice. The lipidome and the metabolome of these mice were compared to saline-treated WT animals. In the brain tissue of all three models, the lipidome was more influenced than the metabolome. The LPS-treated APdE9 mice had the highest number of changes in brain metabolic pathways with significant alterations in levels of lysine, myo-inositol, spermine, phosphocreatine, acylcarnitines and diacylglycerols, which were not observed in the saline-treated APdE9 mice. In the WT mice, the effect of the LPS administration on metabolome and lipidome was negligible. The study provided exciting information about the biochemical perturbations due to LPS-induced inflammation in the transgenic AD model, which can significantly enhance our understanding of the role of systemic inflammation in AD pathogenesis.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Multi-Omics Analysis of Diabetic Heart Disease in the db/db Model Reveals Potential Targets for Treatment by a Longevity-Associated Gene

Characterisation of animal models of diabetic cardiomyopathy may help unravel new molecular targets for therapy. Long-living individuals are protected from the adverse influence of diabetes on the heart, and the transfer of a longevity-associated variant (LAV) of the human BPIFB4 gene protects cardiac function in the db/db mouse model. This study aimed to determine the effect of LAV-BPIFB4 therapy on the metabolic phenotype (ultra-high-performance liquid chromatography-mass spectrometry, UHPLC-MS) and cardiac transcriptome (next-generation RNAseq) in db/db mice. UHPLC-MS showed that 493 cardiac metabolites were differentially modulated in diabetic compared with non-diabetic mice, mainly related to lipid metabolism. Moreover, only 3 out of 63 metabolites influenced by LAV-BPIFB4 therapy in diabetic hearts showed a reversion from the diabetic towards the non-diabetic phenotype. RNAseq showed 60 genes were differentially expressed in hearts of diabetic and non-diabetic mice. The contrast between LAV-BPIFB4- and vehicle-treated diabetic hearts revealed eight genes differentially expressed, mainly associated with mitochondrial and metabolic function. Bioinformatic analysis indicated that LAV-BPIFB4 re-programmed the heart transcriptome and metabolome rather than reverting it to a non-diabetic phenotype. Beside illustrating global metabolic and expressional changes in diabetic heart, our findings pinpoint subtle changes in mitochondrial-related proteins and lipid metabolism that could contribute to LAV-BPIFB4-induced cardio-protection in a murine model of type-2 diabetes

Normalization techniques for PARAFAC modeling of urine metabolomic data

Introduction One of the body fluids often used in metabolomics studies is urine. The concentrations of metabolites in urine are affected by hydration status of an individual, resulting in dilution differences. This requires therefore normalization of the data to correct for such differences. Two normalization techniques are commonly applied to urine samples prior to their further statistical analysis. First, AUC normalization aims to normalize a group of signals with peaks by standardizing the area under the curve (AUC) within a sample to the median, mean or any other proper representation of the amount of dilution. The second approach uses specific end-product metabolites such as creatinine and all intensities within a sample are expressed relative to the creatinine intensity. Objectives Another way of looking at urine metabolomics data is by realizing that the ratios between peak intensities are the information-carrying features. This opens up possibilities to use another class of data analysis techniques designed to deal with such ratios: compositional data analysis. The aim of this paper is to develop PARAFAC modeling of three-way urine metabolomics data in the context of compositional data analysis and compare this with standard normalization techniques. Methods In the compositional data analysis approach, special coordinate systems are defined to deal with the ratio problem. In essence, it comes down to using other distance measures than the Euclidian Distance that is used in the conventional analysis of metabolomic data. Results We illustrate using this type of approach in combination with three-way methods (i.e. PARAFAC) of a longitudinal urine metabolomics study and two simulations. In both cases, the advantage of the compositional approach is established in terms of improved interpretability of the scores and loadings of the PARAFAC model. Conclusion For urine metabolomics studies, we advocate the use of compositional data analysis approaches. They are easy to use, well established and proof to give reliable results