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Objective Alterations in lipids in muscle and plasma have been documented in insulin-resistant people with obesity. Whether these lipid alterations are a reflection of insulin resistance or obesity remains unclear. Methods Nondiabetic sedentary individuals not treated with lipid-lowering medications were studied (n = 51). Subjects with body mass index (BMI) > 25 kg/m2 (n = 28) were stratified based on median glucose infusion rate during a hyperinsulinemic-euglycemic clamp into insulin-sensitive and insulin-resistant groups (above and below median, obesity/insulin-sensitive and obesity/insulin-resistant, respectively). Lean individuals (n = 23) served as a reference group. Lipidomics was performed in muscle and plasma by liquid chromatography electrospray ionization-tandem mass spectrometry. Pathway analysis of gene array in muscle was performed in a subset (n = 35). Results In muscle, insulin resistance was characterized by higher levels of C18:0 sphingolipids, while in plasma, higher levels of diacylglycerol and cholesterol ester, and lower levels of lysophosphatidylcholine and lysoalkylphosphatidylcholine, indicated insulin resistance, irrespective of overweight/obesity. The sphingolipid metabolism gene pathway was upregulated in muscle in insulin resistance independent of obesity. An overweight/obesity lipidomic signature was only apparent in plasma, predominated by higher triacylglycerol and lower plasmalogen species. Conclusions Muscle C18:0 sphingolipids may play a role in insulin resistance independent of excess adiposity.

Objectives While chronic obesity is associated with alterations in circulating glycerolipids, sphingolipids and plasmalogens, the effects of short-term overfeeding in humans are unclear. Design and Methods Healthy individuals (n = 40) were overfed by 1,250 kcal day−1 for 28 days. Insulin sensitivity (hyperinsulinemic-euglycemic clamp), abdominal fat distribution and serum lipidomics (mass spectrometry) were assessed. Results Overfeeding increased liver fat, insulin resistance, serum C-reactive protein and urinary F2-isoprostanes. HDL increased (11% ± 2%, P < 0.001) while LDL, triglycerides and nonesterified fatty acids were unchanged. Three hundred and thirty three serum lipids were detected, of which 13% increased and 20% decreased with overfeeding. Total diacylglycerol and lysoalkylphosphatidylcholine (LPC(O)) concentrations decreased (P < 0.01), while total ceramide, Cer22:0 and Cer24:0 increased (P ≤ 0.01). The most notable increases were observed in the HDL-associated phosphatidylethanolamine-based plasmalogens and their precursors alkylhosphatidylethanolamine (18 ± 5% and 38 ± 8% respectively, P ≤ 0.01). Conclusions Overfeeding led to weight gain and changes in the serum lipid profile. Increases in ceramides were noted, which left unchecked may promote systemic insulin resistance. Uniform increases were observed in plasmalogens and their precursors. Because plasmalogens are powerful antioxidants, this may be an appropriate response against increased oxidative stress generated by over-nutrition. The metabolic consequences of changes in concentrations of many circulating lipid species with overfeeding require further study. Copyright © 2013 The Obesity Society

While chronic obesity is associated with alterations in circulating glycerolipids, sphingolipids and plasmalogens, the effects of short-term overfeeding in humans are unclear.Healthy individuals (n = 40) were overfed by 1,250 kcal day(-1) for 28 days. Insulin sensitivity (hyperinsulinemic-euglycemic clamp), abdominal fat distribution and serum lipidomics (mass spectrometry) were assessed.Overfeeding increased liver fat, insulin resistance, serum C-reactive protein and urinary F2-isoprostanes. HDL increased (11% ± 2%, P0.001) while LDL, triglycerides and nonesterified fatty acids were unchanged. Three hundred and thirty three serum lipids were detected, of which 13% increased and 20% decreased with overfeeding. Total diacylglycerol and lysoalkylphosphatidylcholine (LPC(O)) concentrations decreased (P0.01), while total ceramide, Cer22:0 and Cer24:0 increased (P ≤ 0.01). The most notable increases were observed in the HDL-associated phosphatidylethanolamine-based plasmalogens and their precursors alkylhosphatidylethanolamine (18 ± 5% and 38 ± 8% respectively, P ≤ 0.01).Overfeeding led to weight gain and changes in the serum lipid profile. Increases in ceramides were noted, which left unchecked may promote systemic insulin resistance. Uniform increases were observed in plasmalogens and their precursors. Because plasmalogens are powerful antioxidants, this may be an appropriate response against increased oxidative stress generated by over-nutrition. The metabolic consequences of changes in concentrations of many circulating lipid species with overfeeding require further study. Copyright © 2013 The Obesity Society.

Objective— Traditional risk factors for coronary artery disease (CAD) fail to adequately distinguish patients who have atherosclerotic plaques susceptible to instability from those who have more benign forms. Using plasma lipid profiling, this study aimed to provide insight into disease pathogenesis and evaluate the potential of lipid profiles to assess risk of future plaque instability. Methods and Results— Plasma lipid profiles containing 305 lipids were measured on 220 individuals (matched healthy controls, n=80; stable angina, n=60; unstable coronary syndrome, n=80) using electrospray-ionisation tandem mass spectrometry. ReliefF feature selection coupled with an L2-regularized logistic regression based classifier was used to create multivariate classification models which were verified via 3-fold cross-validation (1000 repeats). Models incorporating both lipids and traditional risk factors provided improved classification of unstable CAD from stable CAD (C-statistic=0.875, 95% CI 0.874–0.877) compared with models containing only traditional risk factors (C-statistic=0.796, 95% CI 0.795–0.798). Many of the lipids identified as discriminatory for unstable CAD displayed an association with disease acuity (severity), suggesting that they are antecedents to the onset of acute coronary syndrome. Conclusion— Plasma lipid profiling may contribute to a new approach to risk stratification for unstable CAD.

The metabolic syndrome incorporating obesity, hypertension, dyslipidaemia and elevated plasma glucose has reached epidemic proportions in many Western countries leading to a dramatic increase in insulin resistance, steatosis and type 2 diabetes. Lipidomics presents a new set of tools to unravel the relationship between hyper-caloric diets and other environmental and genetic factors with the metabolic syndrome and disease progression.Plasma lipidomic studies are providing detailed characterisation of the dyslipidaemia associated with obesity and the metabolic syndrome. Combined with lipoprotein fractionation and dynamic modelling we are gaining a new comprehension of lipoprotein composition structure and function. At the population level genome-wide association studies are identifying potential loci linking lipid metabolism with disease pathogenesis. Analysis of tissue, cell and even organelle lipidomes are unravelling the complex relationships between lipotoxicity, inflammation, oxidative stress and cellular function.The global view of lipid metabolism offered by lipidomics is accelerating our understanding of disease processes and identifying new avenues of research into metabolic syndrome and its sequelae. The ongoing identification and validation of lipid biomarkers will likely see their introduction into clinical practice for improved quantification of disease risk, earlier identification of disease and improved patient management in the near future.