The soluble epoxide hydrolase inhibitor GSK2256294 decreases the proportion of adipose pro-inflammatory T cells.

Adipose tissue contains a complex immune environment and is a central contributor to heightened systemic inflammation in obese persons. Epoxyeicosatrienoic acids (EETs) are lipid signaling molecules that decrease inflammation in obese animals, but their effect on inflammation in humans is unknown. The enzyme soluble epoxide hydrolase (sEH) hydrolyzes EETs to less active diols, and we hypothesized that pharmacologic sEH inhibition would decrease adipose inflammation in obese individuals. We treated obese prediabetic adults with the sEH inhibitor GSK2256294 versus placebo in a crossover design, collected subcutaneous abdominal adipose tissue via lipoaspiration and characterized the tissue T cell profile. Treatment with GSK2256294 decreased the percentage of pro-inflammatory T cells producing interferon-gamma (IFNγ), but not interleukin (IL)-17A, and decreased the amount of secreted tumor necrosis factor-alpha (TNFα). Understanding the contribution of the EET/sEH pathway to inflammation in obesity could lead to new strategies to modulate adipose and systemic inflammation.

Human PAH is characterized by a pattern of lipid-related insulin resistance.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a deadly disease of the small pulmonary vasculature with an increased prevalence of insulin resistance (IR). Insulin regulates both glucose and lipid homeostasis. We sought to quantify glucose- and lipid-related IR in human PAH, testing the hypothesis that lipoprotein indices are more sensitive indices of IR in PAH. METHODS: Oral glucose tolerance testing in PAH patients and triglyceride-matched (TG-matched) controls and proteomic, metabolomics, and lipoprotein analyses were performed in PAH and controls. Results were validated in an external cohort and in explanted human PAH lungs. RESULTS: PAH patients were similarly glucose intolerant or IR by glucose homeostasis metrics compared with control patients when matched for the metabolic syndrome. Using the insulin-sensitive lipoprotein index, TG/HDL ratio, PAH patients were more commonly IR than controls. Proteomic and metabolomic analysis demonstrated separation between PAH and controls, driven by differences in lipid species. We observed a significant increase in long-chain acylcarnitines, phosphatidylcholines, insulin metabolism-related proteins, and in oxidized LDL receptor 1 (OLR1) in PAH plasma in both a discovery and validation cohort. PAH patients had higher lipoprotein axis-related IR and lipoprotein-based inflammation scores compared with controls. PAH patient lung tissue showed enhanced OLR1 immunostaining within plexiform lesions and oxidized LDL accumulation within macrophages. CONCLUSIONS: IR in PAH is characterized by alterations in lipid and lipoprotein homeostasis axes, manifest by elevated TG/HDL ratio, and elevated circulating medium- and long-chain acylcarnitines and lipoproteins. Oxidized LDL and its receptor OLR1 may play a role in a proinflammatory phenotype in PAH. FUNDING: NIH DK096994, HL060906, UL1 RR024975-01, UL1 TR000445-06, DK020593, P01 HL108800-01A1, and UL1 TR002243; American Heart Association 13FTF16070002.

Proteomics characterization of exosome cargo.

Characterization of exosomal cargo is of significant interest because this cargo can provide clues to exosome biogenesis, targeting, and cellular effects and may be a source of biomarkers for disease diagnosis, prognosis and response to treatment. With recent improvements in proteomics technologies, both qualitative and quantitative characterization of exosomal proteins is possible. Here we provide a brief review of exosome proteomics studies and provide detailed protocols for global qualitative, global quantitative, and targeted quantitative analysis of exosomal proteins. In addition, we provide an example application of a standard global quantitative analysis followed by validation via a targeted quantitative analysis of urine exosome samples from human patients. Advantages and limitations of each method are discussed as well as future directions for exosome proteomics analysis.