Background/Objectives: In oncology patients, total parenteral nutrition (TPN) prescriptions are complex and depend on individual nutritional and clinical status. Prescriptions for TPN solutions often result in over- or under-dosing of specific nutrients, due to the large number of ingredients and formulation-related constraints. Clinical support decision systems (CDSSs) may assist clinicians in complex decision-making processes. The aim of this study was to quantify discrepancies between CDSS TPN prescriptions and ready-to-use PN formulation compositions administered in routine clinical practice. Methods: In this cross-sectional study, 40 hospitalized adult oncology patients who were prescribed TPN were recruited. CDSS data was used to calculate individual nutritional needs (i.e., fluids, micro-/macronutrients, and electrolytes) and utilized to identify the closest available standardized ready-to-use TPN formula corresponding to those needs. The algorithm created by the use of the CDSS was based on evidence-based equations from ASPEN. We compared the CDSS-calculated nutritional needs with the ready-to-use TPN formula and identified nutrients that had to be added to the TPN solution bag. Results: The daily needs of all macronutrients were fully covered by the ready-to-use TPN, while actual intake of micronutrients, except for phosphorus (P), was insufficient and had to be supplemented in the TPN bag (amino acids: +21.1%, p < 0.001; lipids: +8.4%, p = 0.023; P: +32.5% p = 0.001; Na: -30.5%, p < 0.001; K: -50.6% (p < 0.001); Ca: -51.7%, p < 0.001). Conclusions: The use of the CDSS tool could facilitate PN prescriptions by indicating the most suitable standardized commercial PN solutions to support patients' nutritional needs and help physicians assess the patient's additional needs.

Diabetic kidney disease (DKD) is a severe microvascular complication traditionally attributed to general metabolic derangement and genetic susceptibility. However, this classic pathophysiological approach overlooks the role of red blood cells in the development and the progression of the disease. Prolonged exposure to high blood glucose and oxidative stress compromises the cell’s membrane architecture and ionic homeostasis, resulting in altered rheological properties. By synthesizing these molecular-to-rheological pathways, this review establishes a novel pathophysiological framework for understanding DKD, repositioning erythrocytes to a primary catalyst of renal injury and a highly sensitive target for early diagnostic intervention.

Coronary heart disease (CHD) is the leading cause of morbidity and mortality worldwide despite significant improvements in diagnostic modalities. Emerging evidence suggests that erythrocytes, or red blood cells (RBCs), are one of the most important contributors to the events implicated in atherosclerosis, although the molecular mechanisms behind it are under investigation. We used NMR-based lipidomic technology to investigate the RBC lipidome in patients with CHD compared to those with normal coronary arteries (NCAs), all angiographically documented, and its correlation with coronary artery stenosis. Targeted and untargeted lipidomic analysis revealed that CHD patients presented significant lipid alterations in the RBC membrane, characterized by higher cholesterol, sphingolipids, saturated and monounsaturated fatty acids, lower phospholipids (glycerophospholipids and ether glycerolipids), and unsaturated and polyunsaturated fatty acids. These aberrations gradually distinguish the three subgroups of patients with mild, moderate, and severe coronary stenosis, potentially indicating their non-negligible involvement in the onset and progression of atherosclerosis. The comprehensive analysis of RBC-membrane-derived lipids with omics approaches could unravel specific lipid abnormalities taking place at the silent subclinical stage of atherosclerosis and could have the potential to identify patients with subtle, but still proatherogenic, abnormalities that may confer a higher risk for the development of CHD.

Introduction Lipoprotein(a) [Lp(a)] is a strong, genetically determined, pathogenetic factor of atherosclerotic cardiovascular disease (ASCVD). The aim of this post-hoc analysis was to compare the effect of hypolipidemic treatment on Lp(a) levels of patients with mixed hyperlipidemia. Material and methods We previously randomized patients with mixed hyperlipidemia (low-density lipoprotein [LDL-C] > 160 mg/dl and triglycerides > 200 mg/dl) to rosuvastatin monotherapy 40 mg/day (R group, n = 30) or rosuvastatin 10 mg/day combined with fenofibrate 200 mg/day (RF group, n = 30) or omega-3 fatty acids 2 g/day (RΩ group, n = 30). In the present post-hoc analysis, we included only the patients whose Lp(a) levels were assessed (16, 16 and 15 in the R, RF and RΩ groups, respectively). Lipid profile and Lp(a) were measured at baseline and after 3 months of treatment. Results Significant reductions in total cholesterol, LDL-C, non-high-density lipoprotein-cholesterol (non-HDL-C) and triglyceride levels were observed in all groups. A significant increase in Lp(a) levels was noted in the R (p = 0.017) and RF (p = 0.029) groups, while no significant difference was seen in the RΩ group (p = NS). Regarding Lp(a) elevations, no differences were found between groups. In the R group, a strong negative correlation between the changes in Lp(a) and LDL-C (r = –0.500, p = 0.049) was observed, while a significant negative correlation between the changes in Lp(a) and triglycerides (r = –0.531, p = 0.034) was noted in the RF group. Conclusions Rosuvastatin and/or fenofibrate treatment increases Lp(a) levels in patients with mixed hyperlipidemia. Novel therapies should target Lp(a) level reduction to decrease the residual ASCVD risk in patients with mixed hyperlipidemia.

SGLT-2 inhibitors have been shown to exert cardio- and renoprotective actions. We aimed to investigate the underlying mechanisms using 1H-NMR based metabolomics in patients with type-2 diabetes mellitus who received dapagliflozin. 50 patients with type 2 diabetes mellitus, inadequately controlled on metformin monotherapy (HbA1c > 7

BACKGROUND AND AIMS:Metabolomics is used to predict, diagnose, and monitor metabolic disorders but altered metabolomic signatures have also been reported in diverse diseases, including autoimmune disorders. However, the metabolomic profile in autoimmune hepatitis (AIH) has not been investigated in depth. Therefore, we investigated the metabolomic signature of AIH and its significance as a diagnostic and pathogenetic tool. APPROACH AND RESULTS:Metabolites in plasma samples from 50 patients with AIH at diagnosis, 43 healthy controls, 72 patients with primary biliary cholangitis (PBC), 26 patients with metabolic dysfunction-associated liver disease, and 101 patients with chronic viral hepatitis were determined by 1 H NMR (nuclear magnetic resonance) spectroscopy. Fifty-two metabolites were quantified, and metabolic pathway analysis was performed. Multivariate analysis revealed that AIH could be differentiated from healthy controls and each of the disease controls ( p <0.001). Fifteen metabolites differentiated AIH from disease controls (PBC+chronic viral hepatitis+metabolic dysfunction-associated liver disease) (95% sensitivity and 92% specificity). Ten distinct metabolic pathways were altered in AIH compared to disease controls. The metabolic pathway of branched-chain amino acids (lower valine, leucine, and isoleucine levels and their catabolic intermediates in PBC), methionine (lower methionine, 2-aminobutyrate, and 2-hydroxybutyrate levels in PBC), alanine-aspartate-glutamate (lower metabolites in PBC), and that of metabolites associated with gut microbiota (lower choline, betaine, and dimethylamine levels in PBC) were significantly different between AIH and PBC ( p <0.01). CONCLUSIONS:1 H NMR spectroscopy could be a promising novel tool to diagnose and study AIH pathogenesis as there is no need for much sample handling, is highly reproducible with high sensitivity and specificity, and low cost.

In recent years, remarkable advancements in elucidating the intricate molecular underpinnings of type 2 diabetes mellitus (T2D) have been achieved. Insulin resistance (IR) has been unequivocally acknowledged as the driving pathogenetic mechanism of T2D, preceding disease onset by several years. Nonetheless, diagnostic tools for ascertaining IR are lacking in current clinical practice, representing a critical unmet need; use of the hyperinsulinemic-euglycemic glucose clamp, widely accepted as the gold standard method for evaluating IR at present, is cumbersome in a clinical setting. Thus, the development of well-validated, reliable, and affordable biomarkers of IR has attracted considerable attention from the research community. The biomarkers under investigation can be divided into two major categories: (1) indices or ratios, comprising parameters obtained from a basic or comprehensive metabolic panel and/or derived from anthropometric measurements, and (2) circulating molecules implicated in pathophysiological processes associated with IR. Furthermore, numerous novel biomarkers, including markers of β-cell dysfunction, radiographic quantification of excess visceral adipose tissue, T2D prediction models, certain microRNAs and metabolomic biomarkers, have also provided promising preliminary results. This narrative review aims to present current evidence pertaining to the most notable and exciting biomarkers of IR that are under rigorous evaluation.

Background and Aims: To compare the effect of hypolipidemic treatment on Lipoprotein(a) [Lp(a)] levels of patients with mixed hyperlipidemia. Methods: We previously randomised patients with mixed hyperlipidemia [low density lipoprotein (LDL-C) >160 mg/dl and triglycerides >200 mg/dl) to rosuvastatin monotherapy 40 mg/day (R group, n = 30) or rosuvastatin 10 mg/day combined with fenofibrate 200 mg/day (RF group, n = 30) or omega-3 fatty acids 2 g/day (RΩ group, n = 30). In the present retrospective study, we included only the patients whose Lp(a) levels were assessed (16, 16 and 15 in the R, RF and RΩ groups, respectively). Lipid profile and Lp(a) were measured at baseline and after 3 months of treatment. Results: A significant increase in Lp(a) levels was noted in the R (p = 0.017) and RF (p = 0.029) groups, while a slight increase was seen in RΩ group (p = NS). Regarding Lp(a) elevations, no differences were found between groups. In the R group, a strong negative correlation between the changes in Lp(a) and LDL-C (r = -0.500, p = 0.049) was observed, while a significant negative correlation between the changes in Lp(a) and triglycerides (r = -0.531, p = 0.034) was noted in the RF group. Conclusions: Hypolipidemic treatment increases Lp(a) levels in patients with mixed hyperlipidemia. Novel therapies should target on Lp(a) levels reduction to decrease the residual atherosclerotic cardiovascular disease risk.

The increasing global burden of cardiometabolic diseases highlights the urgent clinical need for better personalized prediction and intervention strategies. Early diagnosis and prevention could greatly reduce the enormous socio-economic burden posed by these states. Plasma lipids including total cholesterol, triglycerides, HDL-C, and LDL-C have been at the center stage of the prediction and prevention strategies for cardiovascular disease; however, the bulk of cardiovascular disease events cannot be explained sufficiently by these lipid parameters. The shift from traditional serum lipid measurements that are poorly descriptive of the total serum lipidomic profile to comprehensive lipid profiling is an urgent need, since a wealth of metabolic information is currently underutilized in the clinical setting. The tremendous advances in the field of lipidomics in the last two decades has facilitated the research efforts to unravel the lipid dysregulation in cardiometabolic diseases, enabling the understanding of the underlying pathophysiological mechanisms and identification of predictive biomarkers beyond traditional lipids. This review presents an overview of the application of lipidomics in the study of serum lipoproteins in cardiometabolic diseases. Integrating the emerging multiomics with lipidomics holds great potential in moving toward this goal.

The functional status of High-Density Lipoprotein (HDLs) is not dependent on the cholesterol content but is closely related to structural and compositional characteristics. We reported the analysis of HDL lipidome in the healthy population and the influence of serum lipids, age, gender and menopausal status on its composition. Our sample comprised 90 healthy subjects aged between 30 and 77 years. HDL lipidome was investigated by Nuclear Magnetic Resonance (NMR) spectroscopy. Among serum lipids, triglycerides, apoAI, apoB and the ratio HDL-C/apoAI had a significant influence on HDL lipid composition. Aging was associated with significant aberrations, including an increase in triglyceride content, lysophosphatidylcholine, free cholesterol, and a decrease in esterified cholesterol, phospholipids, and sphingomyelin that may contribute to increased cardiovascular risk. Aging was also associated with an atherogenic fatty acid pattern. Changes occurring in the HDL lipidome between the two genders were more pronounced in the decade from 30 to 39 years of age and over 60 years. The postmenopausal group displayed significant pro-atherogenic changes in HDLs compared to the premenopausal group. The influence of serum lipids and intrinsic factors on HDL lipidome could improve our understanding of the remodeling capacity of HDLs directly related to its functionality and antiatherogenic properties, and also in appropriate clinical research study protocol design. These data demonstrate that NMR analysis can easily follow the subtle alterations of lipoprotein composition due to serum lipid parameters.

Insulin resistance (IR) and cardiovascular disease (CVD) represent two universal public health hazards, especially in today’s Western societies. A causal-effect relationship has been established that links IR with CVD. The mediating mechanisms are perplexing, under ongoing, rigorous investigation and remain to be fully elucidated. IR is a condition encompassing hyperglycemia and compensatory hyperinsulinemia. It occurs when insulin is not capable of exerting its maximum effects on target tissues, including skeletal muscles, liver and adipose tissue. This alteration of insulin signaling pathways results in the development of cardiometabolic disorders, including obesity, dyslipidemia, low-grade inflammation, endothelial dysfunction and hypertension, all of which are predisposing factors for atherosclerosis and CVD. The management of IR can be achieved through dietary modifications, the inclusion of regular exercise routines in everyday life, pharmacological agents and other interventions tailored to each individual patient’s needs. It is important to underline though that, although various antidiabetic drugs that may improve IR are available, no medications are as yet specifically approved for the treatment of IR. This narrative review will focus on the current scientific and clinical evidence pertaining to IR, the mechanisms connecting IR with CVD, as well as plausible strategies for a holistic, personalized approach for IR management.

Atherosclerosis is an immunoinflammatory pathological procedure in which lipid plaques are formed in the vessel walls, partially or completely occluding the lumen, and is accountable for atherosclerotic cardiovascular disease (ASCVD). ACSVD consists of three components: coronary artery disease (CAD), peripheral vascular disease (PAD) and cerebrovascular disease (CCVD). A disturbed lipid metabolism and the subsequent dyslipidemia significantly contribute to the formation of plaques, with low-density lipoprotein cholesterol (LDL-C) being the main responsible factor. Nonetheless, even when LDL-C is well regulated, mainly with statin therapy, a residual risk for CVD still occurs, and it is attributable to the disturbances of other lipid components, namely triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C). Increased plasma TG and decreased HDL-C levels have been associated with metabolic syndrome (MetS) and CVD, and their ratio, TG/HDL-C, has been proposed as a novel biomarker for predicting the risk of both clinical entities. Under these terms, this review will present and discuss the current scientific and clinical data linking the TG/HDL-C ratio with the presence of MetS and CVD, including CAD, PAD and CCVD, in an effort to prove the value of the TG/HDL-C ratio as a valuable predictor for each aspect of CVD.

Aims: Administration of insulin degludec and liraglutide (IDegLira) correlates to fasting lipid profile changes of diabetic patients, while data concerning apoB-containing lipoprotein subclasses and HDL lipidome are scarce. We evaluated its effect on fasting lipid parameters, apolipoproteins, apoB-containing lipoprotein subclasses and HDL lipidome in patients with type 2 diabetes. Methods: Sixty three patients with HbA1c > 7 % on oral glucose-lowering drugs received either IDegLira or insulin degludec for 3 months. Lipoprotein subfraction profile was determined through Lipoprint method, whereas HDL lipid composition via 1H NMR. Results: Compared to insulin degludec, IDegLira administration resulted in significantly greater reduction of total and LDL-cholesterol. On the other hand, the effect of the two drugs on apolipoprotein-B-containing lipoprotein subfractions concentration was minimal and did not differ between the 2 interventions. IDegLira, but not insulin degludec, induced an atheroprotective shift in HDL's fatty acid composition and particle core depletion in triglycerides. Conclusions: IDegLira administration is accompanied by total and LDL-cholesterol reduction, while sdLDL con-centration only reduced in patients experiencing triglyceride reduction. IDegLira induced compositional changes of HDL particles. These changes may contribute to the cardioprotective properties of liraglutide.

The emergence of drug resistance in cancer poses the greatest hurdle for successful therapeutic results and is associated with most cancer deaths. In triple negative breast cancer (TNBC), due to the lack of specific therapeutic targets, systemic chemotherapy is at the forefront of treatments, but it only benefits a fraction of patients because of the development of resistance. Cancer cells may possess an innate resistance to chemotherapeutic agents or develop new mechanisms of acquired resistance after long-term drug exposure. Such mechanisms involve an interplay between genetic, epigenetic and metabolic alterations that enable cancer cells to evade therapy. In this work, we generated and characterized a chemoresistant TNBC cell line to be used for the investigation of mechanisms that drive resistance to paclitaxel. Transcriptomic analysis highlighted the important role of metabolic-associated pathways in the resistant cells, prompting us to employ 1H-NMR to explore the metabolome and lipidome of these cells. We identified and described herein numerous metabolites and lipids that were significantly altered in the resistant cells. Integrated analysis of our omics data revealed MSMO1, an intermediate enzyme of cholesterol biosynthesis, as a novel mediator of chemoresistance in TNBC. Overall, our data provide a critical insight into the metabolic adaptations that accompany acquired resistance in TNBC and pinpoint potential new targets.

BACKGROUND:Currently, it has been recognized that High-Density Lipoprotein (HDL) functionality plays a much more essential role in protection from atherosclerosis than circulating HDLcholesterol (HDL-C) levels per se. Cholesterol efflux capacity (CEC) from macrophages to HDL has been shown to be a key metric of HDL functionality. Thus, quantitative assessment of CEC may be an important tool for the evaluation of HDL functionality, as improvement of HDL function may lead to a reduction of the risk for Cardiovascular disease (CVD).INTRODUCTION:Although the cardioprotective action of HDLs is exerted mainly through their involvement in the reverse cholesterol transport (RCT) pathway, HDLs have also important anti-inflammatory, antioxidant, antiaggregatory and anticoagulant properties that contribute to their favorable cardiovascular effects. Certain genetic, pathophysiologic, disease states and environmental conditions may influence the cardioprotective effects of HDL either by inducing modifications in lipidome and/or protein composition, or in the enzymes responsible for HDL metabolism. On the other hand, certain healthy habits or pharmacologic interventions may actually favorably affect HDL functionality.METHODS:The present review discusses the effects of environmental factors, including obesity, smoking, alcohol consumption, dietary habits, various pharmacologic interventions, as well as aerobic exercise, on HDL functionality.RESULTS:Experimental and clinical studies or pharmacological interventions support the impact of these environmental factors in the modification of HDL functionality, although the involved mechanisms are not fully understood.CONCLUSION:Further research should be conducted to identify the underlying mechanisms of these environmental factors and to identify new pharmacologic interventions capable of enhancing CEC, improving HDL functionality and potentially improving cardiovascular risk.