Aromatase inhibitors (AIs) are the standard adjuvant endocrine therapy for postmenopausal women with hormone receptor-positive breast cancer; however, their effects on lipid metabolism remain incompletely characterized. In this study, we investigated AI-associated alterations in the plasma lipidome using mass spectrometry-based lipidomics. Plasma samples were collected from 30 patients prior to AI initiation and 29 patients receiving non-steroidal AI therapy for at least 24 months. Ultra-high-performance liquid chromatography-tandem mass spectrometry identified and relatively quantified 649 lipid species across 23 lipid classes and subclasses. Lipidomic analysis revealed significant differences in specific lipid species. Several phosphatidylcholine, sphingomyelin, and lysophosphatidylethanolamine species were significantly more abundant in patient plasma prior to AI therapy, whereas higher levels of selected ceramides, hexosylceramides, phosphatidylinositol (PI 16:0_16:0), and a polyunsaturated diacylglycerol species were observed in patients receiving AI therapy. Multivariate analyses revealed patient group separation, and a Naive Bayes classification model based on lipid-class levels achieved an area under the curve of 0.79. Additionally, lipid network and hierarchical clustering analyses identified systematic lipid-class trends. Protein-protein interaction network analysis based on lipidomic profiles highlighted enzymes associated with sphingolipid metabolism pathways. These findings demonstrate that long-term AI therapy is associated with specific alterations in the plasma lipidome, consistent with estrogen-deprivation-related metabolic differences. Targeted lipidomic profiling may provide mechanistic insights into therapy-associated metabolic effects and support future efforts to optimize long-term management of breast cancer survivors.

Inflammatory bowel diseases (IBD), including Crohn’s disease and ulcerative colitis, are chronic immune-mediated diseases that are increasingly recognized as systemic diseases with significant cardiovascular consequences. Growing epidemiological evidence suggests that patients with IBD face an increased risk of atherosclerotic cardiovascular disease (ASCVD) that cannot be fully explained by traditional cardiovascular risk factors. This excess risk is most pronounced in younger patients and during periods of active intestinal inflammation. This review summarizes current knowledge on common pathogenic mechanisms linking IBD and ASCVD. Chronic systemic inflammation plays a central role, promoting endothelial dysfunction, hypercoagulability, immune cell activation, and accelerated atherogenesis. Other factors include intestinal barrier disruption with microbial translocation, dysbiosis of the gut microbiome, dysfunctional visceral adipose tissue, and adverse metabolic effects of some IBD therapies. Particular emphasis is placed on lipid abnormalities observed in IBD, including the “lipid paradox”, a phenomenon in which reduced circulating lipid levels paradoxically coexist with increased cardiovascular risk due to inflammation-mediated changes in lipid metabolism leading to lipoprotein dysfunction, and emerging lipidomic biomarkers that suggest causal relationships between specific lipid species, inflammatory mediators, and cardiovascular risk. Attention is also given to current strategies for the assessment and prevention of cardiovascular risk in IBD, emphasizing the importance of controlling disease activity, minimizing corticosteroid exposure, and aggressive treatment of modifiable cardiovascular risk factors. Traditional risk calculators may underestimate risk in this population, highlighting the need for tools that integrate inflammatory burden and imaging of subclinical atherosclerosis. Optimization of anti-inflammatory therapy along with individualized cardiovascular prevention strategies may improve long-term outcomes in patients with IBD.

Atypical myopathy (AM) is a frequently fatal, toxin-induced disease in horses, characterised by acute progression and mortality rates exceeding 70

Objectives G protein-coupled receptor 180 (GPR180) has been implicated in systemic energy metabolism, primarily in adipose tissue and the liver. Given impaired whole-body glucose tolerance following GPR180 dysfunction, we aimed to determine whether GPR180 regulates pancreatic β-cell function. We investigated whether GPR180 contributes to β-cell insulin secretion by modulating metabolic processes that couple glucose sensing to mitochondrial energy production. Methods Phenotyping of whole-body (Gpr180 −/−) and β cell-specific Gpr180 (bGpr180-KO) knockout mice was combined with gain- and loss-of-function studies in MIN6 cells. Glucose-stimulated insulin secretion, pancreatic endocrine architecture and identity, transcriptomic and metabolic profiles, as well as mitochondrial function were assessed using in vivo and in vitro approaches, including metabolic challenge tests, histology, RNA sequencing, targeted metabolomics, respirometry, and transmission electron microscopy. Results Loss of GPR180 impaired first-phase insulin secretion and glucose tolerance without affecting insulin sensitivity. These defects were β-cell-autonomous, as confirmed in the bGpr180-KO mice and in MIN6 cells. Functional studies revealed that GPR180 regulates mitochondrial substrate utilization, anaplerotic support of the TCA cycle, and ATP generation without affecting glucose uptake or mitochondrial biogenesis. In particular, Gpr180-deficient β cells showed mitochondrial membrane depolarization, reduced oxygen consumption, and endoplasmic reticulum remodeling, altering the local mitochondrial microenvironment. In vivo, Gpr180 deletion in β cells led to downregulation of mitochondrial gene programs in islets, along with altered endocrine cell identity. Conclusions GPR180 is a previously unrecognized regulator of pancreatic β-cell metabolic competence and identity, linking defects in insulin secretion with alterations in mitochondrial function and endocrine cell identity.

We developed a robust, hybrid RNA-based reporter assay for the quantification of cytidine deaminase (CDA) activity, overcoming limitations of current methods often compromised by interferences in crude biological samples. Our two-step method physically separates the enzymatic reaction in cell lysates from a highly specific detection step in a selected and validated CDA-deficient reporter cell line (143B cell line). This design confers exceptional robustness, eliminating the need for sample purification. In the first step, a cell lysate converts 5-fluorocytidine to 5-fluorouridine. After heat inactivation of lysate proteins, 5-fluorouridine is quantified by its incorporation into reporter cell RNA, yielding a highly specific fluorescent signal. The detection limit of a formed product in the assay achieves 2.7 µM. The assay shows good correlation with LC-MS data, and its adaptability to a multi-well plate format makes it an ideal and cost-effective tool for high-throughput screening. We further applied this assay to reveal that CDA-positive cells actively secrete 5-fluorouridine, providing quantitative evidence for a potential therapeutic bystander effect.

A549 cells are widely used as an in vitro model of alveolar type II (ATII) epithelial cells; however, their phenotype and metabolic state are highly sensitive to culture conditions, cell density, and the duration of static, non-passaged cultivation. Here, we examined how prolonged static culture affects lipid metabolism, mitochondrial bioenergetics, and viability in A549 cells. A549 cultures were maintained without passaging for up to 25 days in DMEM or Ham's F-12 and analyzed using lipid secretion assays, targeted lipidomics, [14C]-acetate incorporation, Seahorse bioenergetic profiling, and transcriptional analysis of stress-associated markers. Several surfactant-associated readouts were highest during early culture, peaking on day 7, as evidenced by elevated expression of ABCA3 and SP-A and maximal secretion of surfactant-associated phospholipids. With prolonged cultivation and increasing culture density, cellular phosphatidylglycerol levels declined progressively and became nearly undetectable by day 25, accompanied by reduced anabolic lipid metabolism, lower oxygen consumption, and impaired glycolytic activity. These changes coincided with increased reactive oxygen species, elevated intracellular Ca2+ levels, and increased expression of stress-associated transcripts, including CASP1, IL1B, and C3. Later stages were also associated with reduced mitochondrial respiration and decreased viability. Collectively, our findings show that prolonged static culture is associated with metabolic remodeling and reduced bioenergetic capacity in A549 cells.

Increasing attention has been directed towards the perturbation of glutamate (Glu) and γ-aminobutyric acid (GABA) homeostasis during the pathogenesis of Alzheimer's disease (AD). The prevailing disequilibrium, stemming from hyperactivation of the glutamatergic system, culminates in progressive neuronal impairment and cognitive deterioration. This study aimed to elucidate the contributory role of the ATP-binding cassette transporter A7 (ABCA7), identified as the second most critical genetic determinant in AD, in glutamatergic-associated neurotoxicity. This endeavor sought to advance molecular comprehension of neurological disorders where Glu-GABA neurotransmission represents a pivotal pharmacotherapeutic target. Utilizing multi-omics approaches, we rigorously analyzed four distinct mouse models, both with and without APPtg and ABCA7 expression, to simulate varied pathological and ABCA7-deficient states. Our results revealed amyloid-beta (Aβ) deposition as a catalyst for surging glutamatergic transmission. Notably, ABCA7 ablation exacerbated glutamatergic-induced neurotoxicity, attributed to diminished enzymatic activity related to neurotransmitter degradation and amplified expression levels of specific neurotransmitter transport proteins and receptor subunits, notably NMDA, AMPA, and GABAA. These findings furnish the first comprehensive description elucidating ABCA7's amplification of neurotoxic effects through modulation of Glu-GABA neurotransmission systems in neurodegenerative contexts, primarily mediated by lipid interaction. The evidence underscores ABCA7's imperative role in shaping future pharmacological strategies aimed at counteracting neurodegeneration precipitated by Glu-mediated neurotoxicity. This research advances the frontier for therapeutic exploration to ameliorate the deleterious neural consequences characteristic of neurodegenerative pathologies.

This collective opinion paper, based on presentations delivered during the two-day European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Strategic Conference 2026, "Laboratory Medicine for Society" (Prague, Czech Republic, 24-25 April 2026) offers a forward-looking overview of the Federation's strategic priorities, ongoing initiatives, and future projects aimed at enhancing the value, visibility, and societal contribution of laboratory medicine, thereby ensuring a bright and sustainable future for the profession. By generating actionable information that supports clinical decision-making across the entire continuum of care, laboratory medicine contributes substantially to improving patient outcomes, enhancing healthcare efficiency, and promoting population health.

BACKGROUND AND OBJECTIVE:Metabolomic interaction networks provide critical insights into the dynamic relationships between metabolites and their regulatory mechanisms. This study introduces MInfer, a novel computational framework that integrates outputs from MetaboAnalyst, a widely used metabolomic analysis tool, with Jacobian analysis to enhance the derivation and interpretation of these networks. METHODS:MInfer combines the comprehensive data processing capabilities of MetaboAnalyst with the mathematical modeling power of Jacobian analysis. This framework was applied to various metabolomic datasets, employing advanced statistical tests to construct interaction networks and identify key metabolic pathways. RESULTS:The application of MInfer revealed significant metabolic pathways and potential regulatory mechanisms across multiple datasets. The framework demonstrated high precision, sensitivity, and specificity in identifying interactions, enabling robust network interpretations. CONCLUSIONS:MInfer enhances the interpretation of metabolomic data by providing detailed interaction networks and uncovering key regulatory insights. This tool holds significant potential for advancing the study of complex biological systems.

Gout and hyperuricemia increase cardiovascular disease risk, highlighting the need for improved risk stratification. In this pilot study, we evaluated the Coronary Event Risk Test (CERT) in 94 hyperuricemic and 196 gout patients, and 53 controls. Plasma ceramides were determined by liquid chromatography-mass spectrometry. Elevated CERT scores (≥7) occurred in 11.7 % (2-fold increase) of hyperuricemic and 31.12 % (5.5-fold increase) of gout patients compared to controls. Additionally, both hyperuricemic and gout patients with increased CERT also exhibited higher levels of inflammation and atherogenic index of plasma, both of which were significantly associated with CERT. Incorporating CERT into routine care may enhance risk stratification and guide targeted interventions in this patient population.

While diagnostic criteria have been established and validated for most neurodegenerative diseases, the considerable overlap between individual nosological entities remains a significant diagnostic challenge. Increasing evidence suggests that neurodegeneration is often initiated by inflammation within the central nervous system. The identification of inflammation could serve as a first signal of the pathophysiological process. As such, validated biological markers ("biomarkers") of neuroinflammation are critically important. This study aimed to assess the presence and levels of inflammatory biomarkers in three neurodegenerative diseases: Lewy body diseases (LBD), multiple system atrophy (MSA), and 4-repeat tauopathies (4RT). A total of 83 LBD, 24 MSA, and 31 4RT patients were included, with 83 control subjects for comparison. Six immune-related proteins were analysed in cerebrospinal fluid (CSF) and blood serum (serum): C3 complement, C4 complement, haptoglobin, transferrin, orosomucoid, and β2 microglobulin (β2M). ANCOVA statistical analysis revealed significantly lower levels of several inflammatory biomarkers in LBD (CSF: transferrin, C3 complement, orosomucoid; Serum: orosomucoid, β2M) and MSA (CSF: transferrin, C3 complement, C4 complement, orosomucoid) compared to controls. Significant differences were also observed between the synucleinopathy patient groups (LBD and MSA) and 4RT in serum levels of C3 complement. Additionally, the CSF/serum quotients for transferrin (LBD and MSA) and C3 complement (LBD) were significantly lower in disease relative to controls. These findings suggest that inflammatory processes may play a role in the pathophysiology of neurodegenerative proteinopathies, warranting further research to confirm these associations. The identification of potential fluid biomarkers would then represent a promising step forward in the field.

Mass spectrometry-based lipidomics and metabolomics generate extensive data sets that, along with metadata such as clinical parameters, require specific data exploration skills to identify and visualize statistically significant trends and biologically relevant differences. Besides tailored methods developed by individual labs, a solid core of freely accessible tools exists for exploratory data analysis and visualization, which we have compiled here, including preparation of descriptive statistics, annotated box plots, hypothesis testing, volcano plots, lipid maps and fatty acyl chain plots, unsupervised and supervised dimensionality reduction, dendrograms, and heat maps. This review is intended for those who would like to develop their skills in data analysis and visualization using freely available R or Python solutions. Beginners are guided through a selection of R and Python libraries for producing publication-ready graphics without being overwhelmed by the code complexity. This manuscript, along with associated GitBook code repository containing step-by-step instructions, offers readers a comprehensive guide, encouraging the application of R and Python for robust and reproducible chemometric analysis of omics data.

Motivation:The increasing use of big data and optimized prediction methods in metabolomics requires techniques aligned with biological assumptions to improve early symptom diagnosis. One major challenge in predictive data analysis is handling confounding factors-variables influencing predictions but not directly included in the analysis. Results:Detecting and correcting confounding factors enhances prediction accuracy, reducing false negatives that contribute to diagnostic errors. This study reviews concept drift detection methods in metabolomic predictions and selects the most appropriate ones. We introduce a new implementation of concept drift analysis in predictive classifiers using metabolomics data. Known confounding factors were confirmed, validating our approach and aligning it with conventional methods. Additionally, we identified potential confounding factors that may influence biomarker analysis, which could introduce bias and impact model performance. Availability and implementation:Based on biological assumptions supported by detected concept drift, these confounding factors were incorporated into correction of prediction algorithms to enhance their accuracy. The proposed methodology has been implemented in Semi-Automated Pipeline using Concept Drift Analysis for improving Metabolomic Predictions (SAPCDAMP), an open-source workflow available at https://github.com/JanaSchwarzerova/SAPCDAMP.

Cytidine deaminase (CDA) and deoxycytidine monophosphate deaminase (DCTD) play crucial roles in pyrimidine metabolism, affecting DNA synthesis, cell cycle progression, and the efficacy of numerous nucleoside analog-based chemotherapeutics. Given their significance, accurate and sensitive measurement of their enzymatic activity is paramount for both fundamental biochemical research and clinical applications. This review provides a comprehensive overview of the methodologies used to assess CDA and DCTD activity, both established and emerging. We systematically categorize and discuss various approaches, including spectrophotometric, fluorimetric, liquid chromatography-based (Ultraviolet-Visible, fluorescence, and mass spectrometry), radiometric, and cell-based assays. For each method, we present its underlying principles, advantages, and limitations. Furthermore, we draw comparisons across the techniques to highlight their suitability for specific research questions.

Objective: This study aims to characterize the metabolic alterations in patients with inherited mitochondrial enzymopathies. We focused on wide-coverage targeted metabolomic, organic acid and lipidomic analyses of patients with TMEM70 deficiency (TMEM70d), short-chain acyl-CoA dehydrogenase deficiency (SCADd), and individuals with both deficiencies (TMEM70d-SCADd). Methods: Serum and urine samples were collected from patients with TMEM70d (n = 13), SCADd (n = 11), TMEM70d-SCADd (n = 3), and controls (n = 38). Analyses were conducted using high-performance liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Univariate and multivariate statistical evaluation was performed to identify significant metabolic differences between patient groups and controls. Results: Distinct metabolic profiles were observed in urine and serum samples of patients with TMEM70d, SCADd, and TMEM70d-SCADd compared to controls. Urinary metabolomics revealed significant elevations in butyrylcarnitine and metabolites related to branched-chain amino acid degradation in SCADd and TMEM70d-SCADd patients. Serum metabolomic analysis indicated alterations in pyruvate metabolism, citric acid cycle intermediates, and acylcarnitine metabolism in TMEM70d and TMEM70d-SCADd patients. Lipidomic analysis showed decreased levels of glycerophospholipids and sphingolipids across all patient groups. Conclusion: Patients with TMEM70d, SCADd, and TMEM70d-SCADd exhibit distinct metabolic signatures characterized by disturbances in energy metabolism, amino acid degradation, and lipid homeostasis. The combination of TMEM70d and SCADd leads to synergistic metabolic effects, emphasizing the importance of comprehensive metabolic profiling in understanding complex mitochondrial disorders and identifying potential biomarkers for diagnosis and treatment monitoring.

Mismatched nucleobase uracil is commonly repaired through the base excision repair initiated by DNA uracil glycosylases. The data presented in this study strongly indicate that the nuclear uracil-N-glycosylase activity and nuclear protein content in human cell lines is highest in the S phase of the cell cycle and that its distribution kinetics partially reflect the DNA replication activity in replication foci. In this respect, the data demonstrate structural changes of the replication focus related to the uracil-N-glycosylase distribution several dozens of minutes before end of its replication. The analysis also showed that very popular synchronisation protocols based on the double thymidine block can result in changes in the UNG2 content and uracil excision rate. In response, we propose a new method for the description of the changes of the content and the activity of different cell components during cell cycle without the necessity to use synchronisation protocols.

Objective: The laboratory diagnosis of inherited metabolic disorders (IMD) has undergone significant development in recent decades, mainly due to the use of mass spectrometry, which allows rapid multicomponent analysis of a wide range of metabolites. Combined with advanced software tools, the diagnosis becomes more efficient as a benefit for both physicians and patients. Methods: A hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry assay for determination of urinary purines, pyrimidines, N-acylglycines, N-acetylated amino acids, sugars, sugar alcohols and other diagnostically important biomarkers was developed and validated. Evaluation of the results consisting of utilisation of robust scaling and advanced visualization tools is simple and even suitable for urgent requirements. Results: The developed method, covering 65 biomarkers, provides a comprehensive diagnostic platform for 51 IMD. For most analytes, linearity with R-2 > 0.99, intra and inter-day accuracy between 80 and 120 % and precision lower than 20 % were achieved. Diagnostic workflow was evaluated on 47 patients and External Quality Assurance samples involving a total of 24 different IMD. Over seven years, more than 2300 urine samples from patients suspected for IMD have been routinely analysed. Conclusions: This method offers the advantage of a broad coverage of intermediate metabolites of interest and therefore may be a potential alternative and simplification for clinical laboratories that use multiple methods for screening these markers.

Background Accumulation of tau leads to neuroinflammation and neuronal cell death in tauopathies, including Alzheimer’s disease. As the disease progresses, there is a decline in brain energy metabolism. However, the role of tau protein in regulating lipid metabolism remains less characterized and poorly understood. Methods We used a transgenic rat model for tauopathy to reveal metabolic alterations induced by neurofibrillary pathology. Transgenic rats express a tau fragment truncated at the N- and C-terminals. For phenotypic profiling, we performed targeted metabolomic and lipidomic analysis of brain tissue, CSF, and plasma, based on the LC-MS platform. To monitor disease progression, we employed samples from transgenic and control rats aged 4, 6, 8, 10, 12, and 14 months. To study neuron-glia interplay in lipidome changes induced by pathological tau we used well well-established multicomponent cell model system. Univariate and multivariate statistical approaches were used for data evaluation. Results We showed that tau has an important role in the deregulation of lipid metabolism. In the lipidomic study, pathological tau was associated with higher production of lipids participating in protein fibrillization, membrane reorganization, and inflammation. Interestingly, significant changes have been found in the early stages of tauopathy before the formation of high-molecular-weight tau aggregates and neurofibrillary pathology. Increased secretion of pathological tau protein in vivo and in vitro induced upregulated production of phospholipids and sphingolipids and accumulation of lipid droplets in microglia. We also found that this process depended on the amount of extracellular tau. During the later stages of tauopathy, we found a connection between the transition of tau into an insoluble fraction and changes in brain metabolism. Conclusion Our results revealed that lipid metabolism is significantly affected during different stages of tau pathology. Thus, our results demonstrate that the dysregulation of lipid composition by pathological tau disrupts the microenvironment, further contributing to the propagation of pathology.

Objectives: Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. Methods: A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. Results: Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. Conclusions: Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.

Huntington's disease (HD) is a debilitating neurodegenerative disorder characterized by severe motor deficits, cognitive decline and psychiatric disturbances. An early and significant morphological hallmark of HD is the activation of astrocytes triggered by mutant huntingtin, leading to the release of inflammatory mediators. Fingolimod (FTY), an FDA-approved sphingosine-1-phosphate (S1P) receptor agonist is used to treat multiple sclerosis (MS), a neuroinflammatory disease, and has shown therapeutic promise in other neurological conditions. Our study aimed to investigate the therapeutic potential of FTY for treating HD by utilizing a well-characterized mouse model of HD (zQ175dn) and wild-type littermates. The study design included a crossover, long-term oral treatment with 1 mg/kg to 2 mg/kg FTY from the age of 15-46 weeks (n = 128). Different motor behavior and physiological parameters were assessed throughout the study. The findings revealed that FTY rescued disease-related body weight loss in a sex-dependent manner, indicating its potential to regulate metabolic disturbances and to counteract neurodegenerative processes in HD. FTY intervention also rescued testicular atrophy, restored testis tissue structure in male mice suggesting a broader impact on peripheral tissues affected by huntingtin pathology. Histological analyses of the brain revealed delayed accumulation of activated astrocytes contributing to the preservation of the neural microenvironment by reducing neuroinflammation. The extent of FTY-related disease improvement was sex-dependent. Motor functions and body weight improved mostly in female mice with sustained estrogen levels, whereas males had to compensate for the ongoing, disease-related testis atrophy and the loss of androgen production. Our study underscores the beneficial therapeutic effects of FTY on HD involving endogenous steroid hormones and their important anabolic effects. It positions FTY as a promising candidate for therapeutic interventions targeting various aspects of HD pathology. Further studies are needed to fully evaluate its therapeutic potential in patients.