Treatment of lean and diet-induced obesity (DIO) mice with a novel stable obestatin analogue alters plasma metabolite levels as detected by untargeted LC–MS metabolomics

Introduction: Obestatin is a controversial gastrointestinal peptide purported to have metabolic actions.

Objectives: This study investigated whether treatment with a stable obestatin analogue (PEG-OB(Cys10, Cys13)) changed plasma metabolite levels firstly in lean and subsequently in diet-induced obesity (DIO) C57BL6/J mice.

Methods: Untargeted LC-HRMS metabolomics experiments were carried out in ESI + mode with plasma extracts from both groups of animals. Data were normalised, multivariate and univariate statistical analysis performed and metabolites of interest putatively identified.

Results: In lean mice, 39 metabolites were significantly changed by obestatin treatment and the majority of these were increased, including various C16 and C18 moieties of phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine and monoacylglycerol, along with vitamin A, vitamin D3, tyrosine, acetylcarnitine and 2α-(hydroxymethyl)-5α-androstane-3β,17β-diol. Decreased concentrations of glycolithocholic acid, 3-dehydroteasterone and various phospholipids were observed. In DIO mice, 25 metabolites were significantly affected and strikingly, the magnitudes of changes here were generally much greater in DIO mice than in lean mice, and in contrast, the majority of metabolite changes were decreases. Four metabolites affected in both groups included glycolithocholic acid, and three different long-chain (C18) phospholipid molecules (phosphatidylethanolamine, platelet activating factor (PAF), and monoacylglycerol). Metabolites exclusively affected in DIO mice included various phosphatidylcholines, lysophosphatidylcholines and fatty acyls, as well as creatine and oxidised glutathione.

Conclusion: This investigation demonstrates that obestatin treatment affects phospholipid turnover and influences lipid homeostasis, whilst providing convincing evidence that obestatin may be acting to ameliorate diet-induced impairments in lipid metabolism, and it may influence steroid, bile acid, PAF and glutathione metabolism.

Rare coding variants in the phospholipase D3 gene confer risk for Alzheimer's disease.

Genome-wide association studies (GWAS) have identified several risk variants for late-onset Alzheimer's disease (LOAD)1, 2. These common variants have replicable but small effects on LOAD risk and generally do not have obvious functional effects. Low-frequency coding variants, not detected by GWAS, are predicted to include functional variants with larger effects on risk. To identify low-frequency coding variants with large effects on LOAD risk, we carried out whole-exome sequencing (WES) in 14 large LOAD families and follow-up analyses of the candidate variants in several large LOAD case–control data sets. A rare variant in PLD3 (phospholipase D3; Val232Met) segregated with disease status in two independent families and doubled risk for Alzheimer’s disease in seven independent case–control series with a total of more than 11,000 cases and controls of European descent. Gene-based burden analyses in 4,387 cases and controls of European descent and 302 African American cases and controls, with complete sequence data for PLD3, reveal that several variants in this gene increase risk for Alzheimer’s disease in both populations. PLD3 is highly expressed in brain regions that are vulnerable to Alzheimer’s disease pathology, including hippocampus and cortex, and is expressed at significantly lower levels in neurons from Alzheimer’s disease brains compared to control brains. Overexpression of PLD3 leads to a significant decrease in intracellular amyloid-β precursor protein (APP) and extracellular Aβ42 and Aβ40 (the 42- and 40-residue isoforms of the amyloid-β peptide), and knockdown of PLD3 leads to a significant increase in extracellular Aβ42 and Aβ40. Together, our genetic and functional data indicate that carriers of PLD3 coding variants have a twofold increased risk for LOAD and that PLD3 influences APP processing. This study provides an example of how densely affected families may help to identify rare variants with large effects on risk for disease or other complex traits.