Tissue Lipidomic Alterations Induced by Prolonged Dexamethasone Treatment.

Dexamethasone is a synthetic glucocorticoid medication vastly used to treat abnormal immune responses and inflammation. Although the medication is well-established in the medical community, the prolonged treatment with high dosages of dexamethasone may lead to severe adverse effects through mechanisms that are not yet well-known. Lipids are a large class of hydrophobic molecules involved in energy storage, signaling, modulation of gene expression, and membranes. Hence, untargeted lipidomics may help unravel the biochemical alterations following prolonged treatment with high dosages of dexamethasone. We performed comprehensive lipidomic analyses of brain, heart, kidney, liver, and muscle samples obtained from rats that were treated with intramuscular injections of dexamethasone for 14 weeks compared to healthy controls. The employed methodology and statistical analysis showed that phosphatidic acids, glycerophospholipids, plasmalogens, and fatty acids are deeply affected by prolonged use of the medication. Brain tissue was only mildly affected, but skeletal muscle showed a strong accumulation of lipids that may be correlated with alterations in the energy metabolism, myopathy, and oxidative processes. This work provides new insights into the mechanisms of action and adverse effects for one of the most commonly prescribed class of drugs in the world.

Assessment of nucleosides as putative tumor biomarkers in prostate cancer screening by CE-UV.

Cancer is responsible for millions of deaths worldwide, but most base diseases may be cured if detected early. Screening tests may be used to identify early-stage malignant neoplasms. However, the major screening tool for prostate cancer, the prostate-specific antigen test, has unsuitable sensitivity. Since cancer cells may affect the pattern of consumption and excretion of nucleosides, such biomolecules are putative biomarkers that can be used for diagnosis and treatment evaluation. Using a previously validated method for the analysis of nucleosides in blood serum by capillary electrophoresis with UV-vis spectroscopy detection, we investigated 60 samples from healthy individuals and 42 samples from prostate cancer patients. The concentrations of nucleosides in both groups were compared and a multivariate partial least squares-discriminant analysis classification model was optimized for prediction of prostate cancer. The validation of the model with an independent sample set resulted in the correct classification of 82.4% of the samples, with sensitivity of 90.5% and specificity of 76.7%. A significant downregulation of 5-methyluridine and inosine was observed, which can be indicative of the carcinogenic process. Therefore, such analytes are potential candidates for prostate cancer screening. Graphical Abstract Separation of the studied nucleosides and the internal standard 8-Bromoguanosine by CE-UV (a); classification of the external validation samples (30 from healthy volunteers and 21 from prostate cancer patients) by the developed Partial Least Square - Discriminant Analysis (PLS-DA) model with accuracy of 82.4% (b); Receiver Operating Characteristics (ROC) curve (c); and Variable Importance in the Projection (VIP) values for the studied nucleosides (d). A significant down-regulation of 5- methyluridine (5mU) and inosine (I) was observed, which can be indicative of the presence of prostate tumors.

Higher detectability method for the analysis of nucleosides, putative tumor biomarkers, in blood serum samples by CE-UV with reversed EOF.

The development and validation of methodologies for the analysis of biological samples is of outcome importance in order to obtain trustworthy results. This work reports a novel CE-UV method for the assessment of nucleosides, putative tumor biomarkers, in blood serum. The separation of seven nucleosides within c.a. 20 min has been achieved with: BGE 30 mmol/L borate at pH 9.90, 50 mmol/L CTAB, and 10% methanol; V = -10 kV; T = 20°C; and capillary dimensions of 56 cm × 50 µm. The sample plug was concentrated by a modified large volume sample stacking strategy that provided better detectability. Validation showed that the method is suitable for bioanalytical purposes and initial applications in serum samples from healthy subjects are also presented. Finally, statistical methods were applied to verify the effect of characteristics such as age, smoking habits, and alcohol consumption on nucleoside concentrations in blood serum. Univariate statistical analysis tests emphasized the need for age matching, which was confirmed by PCA-DA and PLS-DA. Cancer history in the nearby family may also interfere in nucleoside levels in blood serum, since adenosine concentrations were statistically higher for volunteers who declared having diseased relatives.

An Integrated Multi-OMICS Approach Highlights Elevated Non-Esterified Fatty Acids Impact BeWo Trophoblast Metabolism and Lipid Processing.

Maternal obesity and gestational diabetes mellitus (GDM) are linked with impaired placental function and early onset of non-communicable cardiometabolic diseases in offspring. Previous studies have highlighted that the dietary non-esterified fatty acids (NEFAs) palmitate (PA) and oleate (OA), key dietary metabolites associated with maternal obesity and GDM, are potential modulators of placental lipid processing. Using the BeWo cell line model, the current study integrated transcriptomic (mRNA microarray), metabolomic, and lipidomic readouts to characterize the underlying impacts of exogenous PA and OA on placental villous trophoblast cell metabolism. Targeted gas chromatography and thin-layer chromatography highlighted that saturated and monounsaturated NEFAs differentially impact BeWo cell lipid profiles. Furthermore, cellular lipid profiles differed when exposed to single and multiple NEFA species. Additional multi-omic analyses suggested that PA exposure is associated with enrichment in ß-oxidation pathways, while OA exposure is associated with enrichment in anti-inflammatory and antioxidant pathways. Overall, this study further demonstrated that dietary PA and OA are important regulators of placental lipid metabolism. Encouraging appropriate dietary advice and implementing dietary interventions to maintain appropriate placental function by limiting excessive exposure to saturated NEFAs remain crucial in managing at-risk obese and GDM pregnancies.

Lipidomics Profiling of Metformin-Induced Changes in Obesity and Type 2 Diabetes Mellitus: Insights and Biomarker Potential.

Metformin is the first-line oral medication for treating type 2 diabetes mellitus (T2DM). In the current study, an untargeted lipidomic analytical approach was used to investigate the alterations in the serum lipidome of a cohort of 89 participants, including healthy lean controls and obese diabetic patients, and to examine the alterations associated with metformin administration. A total of 115 lipid molecules were significantly dysregulated (64 up-regulated and 51 down-regulated) in the obese compared to lean controls. However, the levels of 224 lipid molecules were significantly dysregulated (125 up-regulated and 99 down-regulated) in obese diabetic patients compared to the obese group. Metformin administration in obese diabetic patients was associated with significant dysregulation of 54 lipid molecule levels (20 up-regulated and 34 down-regulated). Levels of six molecules belonging to five lipid subclasses were simultaneously dysregulated by the effects of obesity, T2DM, and metformin. These include two putatively annotated triacylglycerols (TGs), one plasmenyl phosphatidylcholine (PC), one phosphatidylglycerol (PGs), one sterol lipid (ST), and one Mannosyl-phosphoinositol ceramide (MIPC). This study provides new insights into our understanding of the lipidomics alterations associated with obesity, T2DM, and metformin and offers a new platform for potential biomarkers for the progression of diabetes and treatment response in obese patients.