Lipidomic analysis of human plasma reveals ether-linked lipids that are elevated in morbidly obese humans compared to lean

Lipidomics reveals a link between CYP1B1 and SCD1 in promoting obesity

Cytochrome P450 1B1 (CYP1B1) is involved in the metabolism of xenobiotic compounds and endogenous metabolites. Disruption of Cyp1b1 in mice results in suppression of high-fat diet (HFD)-induced obesity and an extensive change in hepatic energy regulation despite minimal constitutive expression of CYP1B1 in hepatocytes. Lack of CYP1B1 is correlated with altered lipid metabolism, especially lysophosphatidylcholines, contributing to protection against obesity. Ultraperformance liquid chromatography coupled to electrospray ionization quadrupole mass spectrometry (UPLC-ESI-QTOFMS)-based metabolomics revealed lysophosphatidylcholine 18:0 (LPC 18:0) as a biomarker positively related to HFD-induced obesity. The increased serum LPC 18:0 in wild-type mice is reduced in Cyp1b1-null mice on a HFD, which is reversed in CYP1B1-humanized mice. CYP1B1-humanized mice show higher diet-induced obesity compared with Cyp1b1-null mice, suggesting that human CYP1B1 shows a similar response to HFD as mouse Cyp1b1. In addition, hepatic stearoyl-CoA desaturase 1 (SCD1) expression was decreased in Cyp1b1-null mice, and the attenuated diet-induced obesity and lower serum LPC 18:0 in the Cyp1b1-null mice is elevated after SCD1 overexpression, suggesting that SCD1 is correlated with CYP1B1-induced obesity. These studies establish a biochemical link between cytochromes P450, lipids, and metabolic disorders and suggest that inhibition of CYP1B1 could be target for antiobesity drugs.

Mass Spectrometry-based Lipidomics and Its Application to Biomedical Research

Lipidomics, a branch of metabolomics, is the large-scale study of pathways and networks of all cellular lipids in biological systems such as cells, tissues or organisms. The recent advance in mass spectrometry technologies have enabled more comprehensive lipid profiling in the biological samples. In this review, we compared four representative lipid profiling technoligies including GC-MS, LC-MS, direct infusion-MS and imaging-MS. We also summarized representative lipid database, and further discussed the applications of lipidomics to the diagnostics of various diseases such as diabetes, obesity, hypertension, and Alzheimer diseases.

Plasma lipidome is independently associated with variability in metabolic syndrome in Mexican American families

Plasma lipidome is now increasingly recognized as a potentially important marker of chronic diseases, but the exact extent of its contribution to the interindividual phenotypic variability in family studies is unknown. Here, we used the rich data from the ongoing San Antonio Family Heart Study (SAFHS) and developed a novel statistical approach to quantify the independent and additive value of the plasma lipidome in explaining metabolic syndrome (MS) variability in Mexican American families recruited in the SAFHS. Our analytical approach included two preprocessing steps: principal components analysis of the high-resolution plasma lipidomics data and construction of a subject-subject lipidomic similarity matrix. We then used the Sequential Oligogenic Linkage Analysis Routines software to model the complex family relationships, lipidomic similarities, and other important covariates in a variance components framework. Our results suggested that even after accounting for the shared genetic influences, indicators of lipemic status (total serum cholesterol, TGs, and HDL cholesterol), and obesity, the plasma lipidome independently explained 22% of variability in the homeostatic model of assessment-insulin resistance trait and 16% to 22% variability in glucose, insulin, and waist circumference. Our results demonstrate that plasma lipidomic studies can additively contribute to an understanding of the interindividual variability in MS.

A distinct fatty acid profile underlies the reduced inflammatory state of metabolically healthy obese individuals

BACKGROUND

Obesity is associated with numerous health complications; however, a subgroup of obese individuals (termed the metabolically healthy obese or MHO) appear to have lower risk for complications such as type 2 diabetes and cardiovascular disease. Emerging evidence suggests that MHO individuals have reduced inflammation compared to their metabolically unhealthy obese (MUO) counterparts. As it is recognized that fatty acids (FAs) have a strong relationship with inflammation, the current study aimed to uncover if the reduced inflammation observed in MHO individuals is mirrored by a more favourable FA profile.

METHODS

Fasted serum samples were collected from lean healthy (LH), MHO, and MUO participants (n = 10/group) recruited from the Diabetes Risk Assessment study. A panel of pro- and anti-inflammatory markers were measured by immunoassay. Total serum FA profiling, as well as the FA composition of circulating phospholipids (PL) and triglycerides (TG), was measured by gas chromatography. ANOVA and Mann-Whitney-Wilcoxon tests were used to assess statistical significance between the groups (P<0.05).

RESULTS

MHO and MUO individuals had similar BMI and body fat %; however, lipid parameters in MHO individuals more closely resembled that of LH individuals. MHO individuals had circulating levels of high sensitivity C-reactive protein (hsCRP) and interleukin-6 (IL-6) similar to LH individuals, while levels of platelet derived growth factor-ββ (PDGF-ββ) were intermediate to that of LH and MUO individuals. FA profiling analysis combined with discriminant analysis modelling highlighted a panel of nine FAs (consisting of three saturated, three monounsaturated, and three polyunsaturated FAs) in PL and TG fractions that distinguished the three groups. Specifically, saturated FA (myristic and stearic acids) levels in MHO individuals resembled that of LH individuals.

CONCLUSION

Our results suggest that the reduced inflammatory state of MHO individuals compared to MUO individuals may stem, in part, from a more favourable underlying FA profile.

Relationship between the lipidome, inflammatory markers and insulin resistance

The objectives of the present study were to (1) examine the effects of the phenotypic factors age, gender and BMI on the lipidomic profile and (2) investigate the relationship between the lipidome, inflammatory markers and insulin resistance.

Serum metabolic signatures induced by a three-day intensified exercise period persist after 14 h of recovery in runners

This study investigated changes in the human serum metabolome elicited by a 3-day period of intensified training. Runners (N = 15, mean ± SD age, 35.2 ± 8.7 years) ran for 2.5 h/day on treadmills at ∼70% VO2max for 3 days in a row, with blood samples collected pre-exercise, and immediately and 14 h post-exercise. Samples were analyzed using gas and liquid chromatography/mass spectrometry (GC-MS, LC-MS), with compounds identified based on comparison to more than 2800 purified standards. Repeated measures ANOVA was used to identify metabolites that differed significantly across time, with multiple testing corrected by the false discovery rate (FDR) (q-value). Immediately following the 3-day exercise period, significant 2-fold or higher increases in 75 metabolites were measured, with all but 22 of these metabolites related to lipid/carnitine metabolism, 13 to amino acid/peptide metabolism, 4 to hemoglobin/porphyrin metabolism, and 3 to Krebs cycle intermediates (q-values < 0.001). After a 14 h overnight recovery period, 50 of the 75 metabolites remained elevated, with 8 decreased (primarily amino acid-related metabolites) (q-values < 0.05). Among the top 20 metabolites, the mean fold changes were 12.4 ± 5.3 and 2.9 ± 1.3 immediately and 14-h post-exercise, respectively. Significant decreases (40-70%, q < 0.01) in 22 metabolites (primarily related to lysolipid and bile acid metabolism) were measured post-exercise, with all but 4 of these still decreased after 14 h rest recovery (q < 0.025). Runners experienced a profound systemic shift in blood metabolites related to energy production especially from the lipid super pathway following 3 days of heavy exertion that was not fully restored to pre-exercise levels after 14 h recovery.