According to the World Health Organization, ischemic stroke is the second leading cause of death in the world. Frequently, it is caused by brachiocephalic artery (BCA) atherosclerosis. Timely detection of atherosclerosis and its unstable course can allow for a timely response to potentially dangerous changes and reduce the risk of vascular complications. Omics technologies allow us to identify new biomarkers that we can use in diagnosing diseases. This research included 90 blood plasma samples. The study group comprised 52 patients with severe atherosclerotic lesions BCA, and the control group comprised 38 patients with no BCA atherosclerosis. Targeted and panoramic lipidomic profiling of their blood plasma was carried out. There was a statistically significant difference (p < 0.05) in the values of the indices saturated fatty acids (FAs), unsaturated FAs, monounsaturated FAs, omega-3, and omega-6. Based on the results on the blood plasma lipidome, we formed models that have a fairly good ability to determine atherosclerotic lesions of the brachiocephalic arteries, as well as a model for identifying unstable atherosclerotic plaques. According only to the panoramic lipidome data, divided into groups according to stable and unstable atherosclerotic plaques, a significant difference was taken into account: p value < 0.05 and abs (fold change) > 2. Unfortunately, we did not observe significant differences according to the established plasma panoramic lipidome criteria between patients with stable and unstable plaques. Omics technologies allow us to obtain data about any changes in the body. According to our data, statistically significant differences in lipidomic profiling were obtained when comparing groups with or without BCA atherosclerosis.

According to the World Health Organisation ischemic stroke is the second leading cause of death in the world. More frequent it is caused by brachiocephalic arteries (BCA) atherosclerosis. Timely detection of the atherosclerosis and it`s unstable course can allow a timely response to potentially dangerous changes and reduce the risk of vascular complications. Omics technologies allow us to identify new biomarkers that we can use in diagnosing diseases. The research included 90 blood plasma samples. The first group - 52 patients with severe atherosclerotic lesions, second group - 38 patients with no BCA atherosclerosis. Targeted and panoramic lipidomic profiling of blood plasma was carried out. There is a statistically significant difference (р

Background: Atherosclerosis and its associated chronic inflammation of the arterial wall disrupt fatty acid metabolism, leading to changes in plasma fatty acid composition. These alterations can be used to improve disease diagnosis and risk stratification by the development and application of specific lipidomic indices. Objectives: The objectives of this study are to evaluate the performance of conventional fatty acid indices and enhance diagnostic efficiency in atherosclerosis by introducing novel index based on plasma PUFA n-6 and n-3 content (Omega-6/3 Balance Index, O6/3-BI), as well as the perspective SFA/MUFA ratio (stearic/oleic acid ratio, C18:0/C18:1n-9) and a logit function combining PUFA and SFA/MUFA biomarkers. Methods: Plasma fatty acids were quantified by LC-MS/MS in healthy controls (n = 50) and patients with carotid atherosclerosis (n = 52), stratified by atorvastatin, rosuvastatin, or no statin therapy. The conventional indices (the Omega-3 Status (EPA + DHA), AA/EPA, and the omega-6/omega-3 ratio), and pathway ratios (C18:0/C18:1n-9; and C20:4n-6/C22:4n-6), as well as the newly introduced PUFA index and combined PUFA-SFA/MUFA logit function, were calculated. Their diagnostic performance for distinguishing atherosclerosis was assessed by a receiver operating characteristic (ROC) analysis with the cross-validation and calculation of Cliff’s Δ effect size. Results: The conventional parameters demonstrated a poor to low discrimination ability of the atherosclerosis patients’ groups from healthy controls (area under the ROC curve, AUC 0.548–0.711). In statin-treated patients, these conventional markers lost significance. The newly introduced PUFA index and SFA/MUFA ratio demonstrated improved patients’ discrimination with AUC 0.734–0.780 for the former and strong predictive power with AUC 0.831–0.858 for the latter marker and maintained their diagnostic value under statin therapy. The most significant positive effect size was observed for the SFA/MUFA ratio with Cliff’s Δ = 0.67–0.71. The combined PUFA-SFA/MUFA logit function also demonstrated a strong predictive power with AUC = 0.880 (Cliff’s Δ = −0.76), outperforming any single index. Conclusions: The newly introduced lipidomic index based on the PUFA content, SFA/MUFA ratio, and a logit function combining PUFA-SFA/MUFA biomarkers demonstrated a substantially better discrimination of atherosclerosis-related fatty acid metabolic disturbances than conventional fatty acid biomarkers.

Ischemic cardiovascular events (ischemic stroke, myocardial infarction) are the most common complications of cardiovascular diseases. One of the leading mechanisms of these complications is atherosclerosis. Lipids play an important role in plaque development. Recently, the lipidome has been of greatest interest, since it may have a prognostic value in atherosclerosis development. With an increase in the circulation of proatherogenic lipidomic biomarkers, the risk of atheroscle­rosis destabilization and ischemic complications increases.The conducted studies made it possible to create additional risk stratification scales, for example, Cardiovascular Event Risk Test (CERT) 1 and 2. They make it possible to estimate the residual risk in patients taking statins. The lipidome examination in extracranial artery atherosclerosis can identify those plaques that have signs of instability, and therefore are dangerous for ischemic stroke development.The review describes the features of plasma lipidome in various cardiovascular diseases associated with atherosclerosis.

Background/Objectives: Omega-3 highly unsaturated fatty acids (HUFAs), particularly EPA and DHA, have anti-inflammatory and lipid-modulating properties for treating atherosclerosis. However, the relationship between plasma fatty acid profiles, omega-3 status, and statin efficacy in carotid atherosclerosis remains poorly defined. Objectives: This study evaluates plasma and plaque fatty acid (FA) composition, explores their associations with plaque stability, and examines the relationship of omega-3 levels, lipid biomarkers (VLDL-C, LDL-C, HDL-C, total cholesterol, and triglycerides) with statin and β-blocker treatment. A mathematical model was developed to predict the erythrocyte omega-3 index from plasma. Methods: In this case–control study, plasma and carotid plaques of 52 patients undergoing carotid endarterectomy were analyzed. Plasma was compared with that of 50 healthy controls. FAs were quantified by LC-MS/MS. Plaques were histologically classified as stable or unstable. Results: Atherosclerotic patients showed disturbed FA metabolism, including decreased plasma omega-3 EPA + DHA, SFAs and HUFAs, increased MUFAs, and impaired desaturase and elongase activity. Unstable plaques had higher MUFA and lower HUFA content compared with stable plaques. Significant correlations between plasma EPA + DHA and HDL-C and triglycerides were observed in statin-naïve patients, whereas statins appeared to attenuate these associations. Co-treatment with β-blockers had no significant effect. A validated logit-based model accurately predicted the erythrocyte omega-3 index from plasma (R² = 0.782). Conclusions: Altered plasma and plaque FA profiles correlate with atherosclerosis’s plaque instability and inflammatory lipid profiles. Statins significantly influence these associations, suggesting their complex interaction with lipid metabolism. Plasma measurements of omega-3 fatty acids in combination with predictive modelling may be beneficial for diagnostic and therapeutic monitoring in carotid atherosclerosis.