Lipidomic profiling of heart and plasma of mice following swim training versus pressure overload
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus Musculus
TISSUE(S): Heart, Blood
PROVIDER: ST001019 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
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Project description:BackgroundExercise-induced metabolic changes, especially lipidomic changes are generally associated with improvements in cardiovascular health. Despite numerous previous studies, the differences in lipidomic profile response to different types of exercise training remain unclear. This study aimed to investigate how two different exercise intensities affect aerobic capacity and serum lipidomic profiles in healthy adolescents.MethodsTwenty-four healthy untrained male adolescents (13.08 ± 0.88 years old) were recruited and randomly assigned to moderate-intensity continuous training (MICT) group or sprint interval training (SIT) group to complete a specific training on a cycle ergometer for 6 weeks. Peak oxygen uptake (VO2peak) and body composition were measured, and blood samples were collected for serum lipoproteins and lipidomic analysis. Anthropometric, VO2peak, and serum biochemical data were analyzed using two-way repeated analysis of variance, while targeted lipidomic analysis was performed by principal component analysis and paired-sample t-test.ResultsVO2peak significantly improved from 39.05 ± 8.17 to 47.52 ± 8.51 [F (1, 44) = 14.75, p < 0.05] for MICT and from 40.13 ± 6.37 to 48.42 ± 7.01 [F (1, 44) = 14.75, p < 0.05] for SIT. A total of 28 lipids in MICT and 5 lipids in SIT showed significant changes out of 276 identified lipids (FC > 1.5 or <1/1.5, FDR <0.05). In MICT, 21 lipids, including sphingolipid (SP) and phospholipid (PL), decreased, while 7 lipids increased. In SIT, all 5 lipids, which were free fatty acid (FFA), decreased.ConclusionAlthough both MICT and SIT induced similar and significant improvements in VO2peak, serum lipid adaptations to the training differed. The primary changes in serum lipidomic intermediates for both types of training were reductions; however, SIT affected FFA, while MICT predominantly influenced SPs and PLs.
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2012-11-01 | E-GEOD-36074 | biostudies-arrayexpress
Project description:Duchenne muscular dystrophy (DMD) is a rare genetic disorder affecting paediatric patients. The disease course is characterized by loss of muscle mass, which is rapidly substituted by fibrotic and adipose tissue. Clinical and preclinical models have clarified the processes leading to muscle damage and myofiber degeneration. Analysis of the fat component is however emerging as more evidence shows how muscle fat fraction is associated with patient performance and prognosis. In this article we aimed to study whether alterations exist in the composition of lipids in plasma samples obtained from mouse models. Analysis of plasma samples was performed in 4 mouse models of DMD and wild-type mice by LC-MS. Longitudinal samplings of individual mice covering an observational period of 7 months were obtained to cover the different phases of the disease. We report clear elevation of glycerolipids and glycerophospholipids families in dystrophic mice compared to healthy mice. Triacylglycerols were the strongest contributors to the signatures in mice. Annotation of individual lipids confirmed the elevation of lipids belonging to these families as strongest discriminants between healthy and dystrophic mice. A few sphingolipids (such as ganglioside GM2, sphingomyelin and ceramide), sterol lipids (such as cholesteryl oleate and cholesteryl arachidonate) and a fatty acyl (stearic acid) were also found to be affected in dystrophic mice. Analysis of serum and plasma samples show how several lipids are affected in dystrophic mice affected by muscular dystrophy. This study sets the basis to further investigations to understand how the lipid signature relates to the disease biology and muscle performance.
| S-EPMC8217252 | biostudies-literature
Project description:Radiation biodosimeters are required urgently for fast and accurate evaluation of absorbed dose for irradiated individuals. Lipidomics has appeared as a credible technique for identification and quantification of lipid for researching biomarker of diseases. We performed a lipidomic profile on mice serum at time points of 6, 24, and 72 hours after 0, 2, 5.5, 7, and 8 Gy irradiation to select radiation-responsive lipids and conducted Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis to recognize the pathways and network changes. Then, Pearson correlation analysis was performed to evaluate the feasibility of radiation-responsive lipids to estimate radiation dose. Seven radiation-responsive lipids including PC (18:2/18:2), PC (18:0/18:2), Lyso PC 18:1, PC (18:0/20:4), SM (D18:0/24:1), PC (16:0/18:1), and Lyso PC 18:2 were identified in which glycerophospholipid metabolism presented as the most significant pathway, and they all presented good linear correlation with the irradiated dose. This study identified 7 radiation-responsive lipids in mice serum and certificate their feasibility of dose estimation as biodosimeters.
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Project description:ObjectiveSpecific lipid molecular changes leading to type 2 diabetes (T2D) are largely unknown. We assessed lipidome factors associated with future occurrence of T2D in a population at high cardiovascular risk.Research design and methodsWe conducted a case-cohort study nested within the PREDIMED trial, with 250 incident T2D cases diagnosed during 3.8 years of median follow-up, and a random sample of 692 participants (639 noncases and 53 overlapping cases) without T2D at baseline. We repeatedly measured 207 plasma known lipid metabolites at baseline and after 1 year of follow-up. We built combined factors of lipid species using principal component analysis and assessed the association between these lipid factors (or their 1-year changes) and T2D incidence.ResultsBaseline lysophosphatidylcholines and lysophosphatidylethanolamines (lysophospholipids [LPs]), phosphatidylcholine-plasmalogens (PC-PLs), sphingomyelins (SMs), and cholesterol esters (CEs) were inversely associated with risk of T2D (multivariable-adjusted P for linear trend ≤0.001 for all). Baseline triacylglycerols (TAGs), diacylglycerols (DAGs), and phosphatidylethanolamines (PEs) were positively associated with T2D risk (multivariable-adjusted P for linear trend <0.001 for all). One-year changes in these lipids showed associations in similar directions but were not significant after adjustment for baseline levels. TAGs with odd-chain fatty acids showed inverse associations with T2D after adjusting for total TAGs.ConclusionsTwo plasma lipid profiles made up of different lipid classes were found to be associated with T2D in participants at high cardiovascular risk. A profile including LPs, PC-PLs, SMs, and CEs was associated with lower T2D risk. Another profile composed of TAGs, DAGs, and PEs was associated with higher T2D risk.
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Project description:Plasma lipidomic measures may enable improved prediction of cardiovascular outcomes in secondary prevention. The aim of this study is to determine the association of plasma lipidomic measurements with cardiovascular events and assess their potential to predict such events. Plasma lipids (n = 342) were measured in a retrospective subcohort (n = 5,991) of the LIPID study. Proportional hazards regression was used to identify lipids associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death) and cardiovascular death. Multivariable models adding lipid species to traditional risk factors were created using lipid ranking established from the Akaike information criterion within a 5-fold cross-validation framework. The results were tested on a diabetic case cohort from the ADVANCE study (n = 3,779). Specific ceramide species, sphingolipids, phospholipids, and neutral lipids containing omega-6 fatty acids or odd-chain fatty acids were associated with future cardiovascular events (106 species) and cardiovascular death (139 species). The addition of 7 lipid species to a base model (11 conventional risk factors) resulted in an increase in the C-statistics from 0.629 (95% CI, 0.628-0.630) to 0.654 (95% CI, 0.653-0.656) for prediction of cardiovascular events and from 0.673 (95% CI, 0.671-0.675) to 0.727 (95% CI, 0.725-0.728) for prediction of cardiovascular death. Categorical net reclassification improvements for cardiovascular events and cardiovascular death were 0.083 (95% CI, 0.081-0.086) and 0.166 (95% CI, 0.162-0.170), respectively. Evaluation on the ADVANCE case cohort demonstrated significant improvement on the base models. The improvement in the prediction of cardiovascular outcomes, above conventional risk factors, demonstrates the potential of plasma lipidomic profiles as biomarkers for cardiovascular risk stratification in secondary prevention. Bristol-Myers Squibb, the National Health and Medical Research Council of Australia (grants 211086, 358395, and 1029754), and the Operational Infrastructure Support Program of the Victorian government of Australia.
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Project description:IntroductionThe relationship between dyslipidemia and obesity has been widely reported, but the global lipid profiles associated with the development of obesity still need to be clarified. An investigation into the association between the lipidomic plasma profile and adolescent obesity may provide new insights into the development of obesity.MethodsMass spectrometry coupled with liquid chromatography was applied to detect the global lipidome in the fasting plasma from 90 Chinese adolescents, including 34 obese adolescents, 26 overweight adolescents, and 30 adolescents with a normal body mass index (BMI). All participants underwent anthropometric measurements by using InBody. Clinical biochemical indicators were measured by Cobas Elecsys.ResultsBoth qualitative and quantitative analyses revealed a gradual change in plasma lipid features among obese students, exhibiting characteristics close to overweight students, but differing significantly from normal students. Compared with normal and overweight students, levels of triglyceride (TG), 18-hydroxycortisol, isohumulinone A, and 11-dihydro-12-norneoquassin were up-regulated in the obese group, while phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysoPC (LPC), lysoPE (LPE), and phosphatidylinositol (PI) were significantly down-regulated in the obese group. Then, we conducted Venn diagrams and selected 8 significant metabolites from the 3 paired comparisons. Most of the selected features were significantly correlated with the anthropometric measurements.ConclusionsThis study demonstrated evidence for a relationship between the eight significant metabolites with obese adolescents. These lipid features may provide a basis for evaluating risk and monitoring the development of obesity.
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