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IntroductionAccurate post-mortem interval (PMI) estimation is essential in forensic investigations. Although various methods for PMI determination have been developed, only an approximate estimation is still achievable, and an accurate PMI indication is still challenging. Therefore, in this study, we employed gas chromatography-mass spectrometry (GC-MS)-based metabolomics to assess post-mortem changes in porcine blood samples collected with and without the addition of anticoagulant (EDTA). Our study aimed to identify metabolites dependent on the EDTA addition and time (taking into account the biodiversity of the studied organism) and those that are time−dependent but resistant to the addition of an anticoagulant.MethodsThe experiment was performed on blood samples collected from 16 animals (domestic pig, breed: Polish Large White), 8 with and 8 without EDTA addition. The moment of death (time 0) and 15 additional time points (from 3 to 168 h after death) were selected to examine changes in metabolites’ levels in specific time intervals. We employed linear mixed models to study the relationship between metabolite intensities, time and presence of EDTA while accounting for the effect of individual pigs.Results and DiscussionWe confirmed that the intensity of 16 metabolites (mainly amino acids) significantly depends on PMI and the presence of EDTA. However, the intensity of the ideal biomarker(s) for PMI estimation should be determined only by the time after death and not by external factors such as the presence of the anticoagulant agent. Thus, we identified 41 metabolites with time−dependent intensities that were not susceptible to EDTA presence. Finally, we assessed the performance of these metabolites in a PMI predictive model. Citraconic acid yielded one of the lowest errors in general PMI estimation (32.82 h). Moreover, similar errors were observed for samples with and without EDTA (33.32 h and 32.34 h, respectively). Although the small sample size and information leak in predictive modelling prevent drawing definite conclusions, citraconic acid shows potential as a robust PMI estimator.

Abstract Metabolomics combined with machine learning methods (MLMs), is a powerful tool for searching novel diagnostic panels. This study was intended to use targeted plasma metabolomics and advanced MLMs to develop strategies for diagnosing brain tumors. Measurement of 188 metabolites was performed on plasma samples collected from 95 patients with gliomas (grade I–IV), 70 with meningioma, and 71 healthy individuals as a control group. Four predictive models to diagnose glioma were prepared using 10 MLMs and a conventional approach. Based on the cross-validation results of the created models, the F1-scores were calculated, then obtained values were compared. Subsequently, the best algorithm was applied to perform five comparisons involving gliomas, meningiomas, and controls. The best results were obtained using the newly developed hybrid evolutionary heterogeneous decision tree (EvoHDTree) algorithm, which was validated using Leave-One-Out Cross-Validation, resulting in an F1-score for all comparisons in the range of 0.476–0.948 and the area under the ROC curves ranging from 0.660 to 0.873. Brain tumor diagnostic panels were constructed with unique metabolites, which reduces the likelihood of misdiagnosis. This study proposes a novel interdisciplinary method for brain tumor diagnosis based on metabolomics and EvoHDTree, exhibiting significant predictive coefficients.

Obesity rates among children are growing rapidly worldwide, placing massive pressure on healthcare systems. Untargeted metabolomics can expand our understanding of the pathogenesis of obesity and elucidate mechanisms related to its symptoms. However, the metabolic signatures of obesity in children have not been thoroughly investigated. Herein, we explored metabolites associated with obesity development in childhood. Untargeted metabolomic profiling was performed on fasting serum samples from 27 obese Caucasian children and adolescents and 15 sex- and age-matched normal-weight children. Three metabolomic assays were combined and yielded 726 unique identified metabolites: gas chromatography-mass spectrometry (GC-MS), hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC LC-MS/MS), and lipidomics. Univariate and multivariate analyses showed clear discrimination between the untargeted metabolomes of obese and normal-weight children, with 162 significantly differentially expressed metabolites between groups. Children with obesity had higher concentrations of branch-chained amino acids and various lipid metabolites, including phosphatidylcholines, cholesteryl esters, triglycerides. Thus, an early manifestation of obesity pathogenesis and its metabolic consequences in the serum metabolome are correlated with altered lipid metabolism. Obesity metabolite patterns in the adult population were very similar to the metabolic signature of childhood obesity. Identified metabolites could be potential biomarkers and used to study obesity pathomechanisms.

Abstract The heterogeneity of acute myeloid leukemia (AML), a complex hematological malignancy, is caused by mutations in myeloid cells affecting their differentiation and proliferation. Thus, various cytogenetic alterations in AML cells may be characterized by a unique metabolome and require different treatment approaches. In this study, we performed untargeted metabolomics to assess metabolomics differences between AML patients and healthy controls, AML patients with different treatment outcomes, AML patients in different risk groups based on the 2017 European LeukemiaNet (ELN) recommendations for the diagnosis and management of AML, AML patients with and without FLT3-ITD mutation, and a comparison between patients with FLT3-ITD, CBF-AML (Core binding factor acute myelogenous leukemia), and MLL AML (mixed-lineage leukemia gene) in comparison to control subjects. Analyses were performed in serum samples using liquid chromatography coupled with mass spectrometry (LC–MS). The obtained metabolomics profiles exhibited many alterations in glycerophospholipid and sphingolipid metabolism and allowed us to propose biomarkers based on each of the above assessments as an aid for diagnosis and eventual classification, allowing physicians to choose the best-suited treatment approach. These results highlight the application of LC–MS-based metabolomics of serum samples as an aid in diagnostics and a potential minimally invasive prognostic tool for identifying various cytogenetic and treatment outcomes of AML.

Abstract Epithelial ovarian cancer (EOC) is one of the leading cancers in women, with high-grade serous ovarian cancer (HGSOC) being the most common and lethal subtype of this disease. A vast majority of HGSOC are diagnosed at the late stage of the disease when the treatment and total recovery chances are low. Thus, there is an urgent need for novel, more sensitive and specific methods for early and routine HGSOC clinical diagnosis. In this study, we performed miRNA expression profiling using the NanoString miRNA assay in 34 serum samples from patients with HGSOC and 36 healthy women. We identified 13 miRNAs that were differentially expressed (DE). For additional exploration of expression patterns correlated with HGSOC, we performed weighted gene co-expression network analysis (WGCNA). As a result, we showed that the module most correlated with tumour size, nodule and metastasis contained 8 DE miRNAs. The panel including miR-1246 and miR-150-5p was identified as a signature that could discriminate HGSOC patients with AUCs of 0.98 and 1 for the training and test sets, respectively. Furthermore, the above two-miRNA panel had an AUC = 0.946 in the verification cohorts of RT-qPCR data and an AUC = 0.895 using external data from the GEO public database. Thus, the model we developed has the potential to markedly improve the diagnosis of ovarian cancer.

Introduction: Discrimination between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) subtypes in non-small cell lung cancer (NSCLC) patients is a significant challenge in oncology. Lipidomics analysis provides a promising approach for this differentiation.Methods: In an accompanying paper, we explored oxPCs levels in a cohort of 200 NSCLC patients. In this research, we utilized liquid chromatography coupled with mass spectrometry (LC-MS) to analyze the lipidomics profile of matching tissue and plasma samples from 25 NSCLC patients, comprising 11 ADC and 14 SCC cases. This study builds upon our previous findings, which highlighted the elevation of oxidised phosphatidylcholines (oxPCs) in NSCLC patients.Results: We identified eight lipid biomarkers that effectively differentiate between ADC and SCC subtypes using an untargeted approach. Notably, we observed a significant increase in plasma LPA 20:4, LPA 18:1, and LPA 18:2 levels in the ADC group compared to the SCC group. Conversely, tumour PC 16:0/18:2, PC 16:0/4:0; CHO, and plasma PC 16:0/18:2; OH, PC 18:0/20:4; OH, PC 16:0/20:4; OOH levels were significantly higher in the ADC group.Discussion: Our study is the first to report that plasma LPA levels can distinguish between ADC and SCC patients in NSCLC, suggesting a potential role for LPAs in NSCLC subtyping. This finding warrants further investigation into the mechanisms underlying these differences and their clinical implications.

According to the fifth edition of the WHO Classification of Tumours of the Central Nervous System (CNS) published in 2021, grade 4 gliomas classification includes IDH-mutant astrocytomas and wild-type IDH glioblastomas. Unfortunately, despite precision oncology development, the prognosis for patients with grade 4 glioma remains poor, indicating an urgent need for better diagnostic and therapeutic strategies. Circulating miRNAs besides being important regulators of cancer development could serve as promising diagnostic biomarkers for patients with grade 4 glioma. Here, we propose a two-miRNA miR-362-3p and miR-6721-5p screening signature for serum for non-invasive classification of identified glioma cases into the highest-grade 4 and lower-grade gliomas. A total of 102 samples were included in this study, comprising 78 grade 4 glioma cases and 24 grade 2–3 glioma subjects. Using the NanoString platform, seven miRNAs were identified as differentially expressed (DE), which was subsequently confirmed via RT-qPCR analysis. Next, numerous combinations of DE miRNAs were employed to develop classification models. The dual panel of miR-362-3p and miR-6721-5p displayed the highest diagnostic value to differentiate grade 4 patients and lower grade cases with an AUC of 0.867. Additionally, this signature also had a high AUC = 0.854 in the verification cohorts by RT-qPCR and an AUC = 0.842 using external data from the GEO public database. The functional annotation analyses of predicted DE miRNA target genes showed their primary involvement in the STAT3 and HIF-1 signalling pathways and the signalling pathway of pluripotency of stem cells and glioblastoma-related pathways. For additional exploration of miRNA expression patterns correlated with glioma, we performed the Weighted Gene-Co Expression Network Analysis (WGCNA). We showed that the modules most associated with glioma grade contained as many as six DE miRNAs. In conclusion, this study presents the first evidence of serum miRNA expression profiling in adult-type diffuse glioma using a classification based on the WHO 2021 guidelines. We expect that the discovered dual miR-362-3p and miR-6721-5p signatures have the potential to be utilised for grading gliomas in clinical applications.

Introduction: Lung cancer is one of the most frequently studied types of cancer and represents the most common and lethal neoplasm. Our previous research on non-small cell lung cancer (NSCLC) has revealed deep lipid profile reprogramming and redox status disruption in cancer patients. Lung cell membranes are rich in phospholipids that are susceptible to oxidation, leading to the formation of bioactive oxidized phosphatidylcholines (oxPCs). Persistent and elevated levels of oxPCs have been shown to induce chronic inflammation, leading to detrimental effects. However, recent reports suggest that certain oxPCs possess anti-inflammatory, pro-survival, and endothelial barrier-protective properties. Thus, we aimed to measure the levels of oxPCs in NSCLC patients and investigate their potential role in lung cancer.Methods: To explore the oxPCs profiles in lung cancer, we performed in-depth, multi-level metabolomic analyses of nearly 350 plasma and lung tissue samples from 200 patients with NSCLC, including adenocarcinoma (ADC) and squamous cell carcinoma (SCC), the two most prevalent NSCLC subtypes and COPD patients as a control group. First, we performed oxPC profiling of plasma samples. Second, we analyzed tumor and non-cancerous lung tissues collected during the surgical removal of NSCLC tumors. Because of tumor tissue heterogeneity, subsequent analyses covered the surrounding healthy tissue and peripheral and central tumors. To assess whether the observed phenotypic changes in the patients were associated with measured oxPC levels, metabolomics data were augmented with data from medical records.Results: We observed a predominance of long-chain oxPCs in plasma samples and of short-chain oxPCs in tissue samples from patients with NSCLC. The highest concentration of oxPCs was observed in the central tumor region. ADC patients showed higher levels of oxPCs compared to the control group, than patients with SCC.Conclusion: The detrimental effects associated with the accumulation of short-chain oxPCs suggest that these molecules may have greater therapeutic utility than diagnostic value, especially given that elevated oxPC levels are a hallmark of multiple types of cancer.

Objectives: Alström syndrome (ALMS) and Bardet-Biedl syndrome (BBS) are among the so-called ciliopathies and are associated with the development of multiple systemic abnormalities, including early childhood obesity and progressive neurodegeneration. Given the progressive deterioration of patients’ quality of life, in the absence of defined causal treatment, it seems reasonable to identify the metabolic background of these diseases and search for their progression markers. The aim of this study was to find metabolites characteristic to ALMS and BBS, correlating with clinical course parameters, and related to the diseases progression.Methods: Untargeted metabolomics of serum samples obtained from ALMS and BBS patients (study group; n = 21) and obese/healthy participants (control group; each of 35 participants; n = 70) was performed using LC-QTOF-MS method at the study onset and after 4 years of follow-up.Results: Significant differences in such metabolites as valine, acylcarnitines, sphingomyelins, phosphatidylethanolamines, phosphatidylcholines, as well as lysophosphatidylethanolamines and lysophosphatidylcholines were observed when the study group was compared to both control groups. After a follow-up of the study group, mainly changes in the levels of lysophospholipids and phospholipids (including oxidized phospholipids) were noted. In addition, in case of ALMS/BBS patients, correlations were observed between selected phospholipids and glucose metabolism parameters. We also found correlations of several LPEs with patients’ age (p < 0.05), but the level of only one of them (hexacosanoic acid) correlated negatively with age in the ALMS/BBS group, but positively in the other groups.Conclusion: Patients with ALMS/BBS have altered lipid metabolism compared to controls or obese subjects. As the disease progresses, they show elevated levels of lipid oxidation products, which may suggest increased oxidative stress. Selected lipid metabolites may be considered as potential markers of progression of ALMS and BBS syndromes.

Graves’ orbitopathy (GO) is a potentially sight-threatening and disfiguring, extrathyroidal manifestation of Graves’ disease. It often impairs patients’ qu ality of life, causing severe social and psychological sequelae. Intravenous glucocorticosteroids is currently the mainstay of therapy, but the efficacy is often underwhelming and recurrence rate is high. For many years, clinicians have been searching for new methods of treatment. Rituximab (RTX) is a chimeric monoclonal antibody targeted against CD20 w hich is a surface antigen present on B cells. It is frequently used to treat non-Hodgkin’ s lymphoma, chronic lymphocytic leukemia, rheumatoid arthritis, or various types of vasculitis. Numerous clinical trials employing RTX in the treatment of GO have shown promising results. RTX is currently considered to be a valid second-line treatment option in patients unresponsive to previous interventions or in disease reactivation. This revi ew summarizes the available literature on this topic, including two largest, randomized, co ntrolled studies. Potential benefits, as well as the limitations of RTX therapy, are discuss ed.

Introduction: Recent data suggest a possible role of endocannabinoids in the regulation of brown adipose tissue (BAT) activity. Those findings indicate potential treatment options for obesity. The aim of this study was to evaluate the relationship between plasma endocannabinoids concentrations and the presence of BAT in humans.Methods: The study group consisted of 25 subjects divided into two groups: BAT positive BAT(+), (n = 17, median age = 25 years) and BAT negative BAT(−), (n = 8, median age = 28 years). BAT was estimated using 18F-FDG PET/MR after 2 h of cold exposure. The level of plasma endocannabinoids was assessed at baseline, 60 min and 120 min of cold exposure.Results: In both groups, BAT(+) and BAT(−), during the cooling, we observed a decrease of the same endocannabinoids: arachidonoylethanolamide (AEA), eicosapentaenoyl ethanolamide (EPEA) and oleoyl ethanolamide (OEA) with a much more profound decline in BAT(+) subjects. Statistically significant fall of PEA (palmitoylethanolamide) and SEA (stearoylethanolamide) concentrations after 60 min (FC = 0.7, p = 0.007 and FC = 0.8, p = 0.03, respectively) and 120 min (FC = 0.81, p = 0.004, and FC = 0.9, p = 0.01, respectively) of cooling was observed only in individuals with BAT.Conclusion: We noticed the profound decline of endocannabinoids concentrations in subjects with increased 18F-FDG PET/MR uptake in BAT. Identification of a new molecules related to BAT activity may create a new target for obesity treatment.

Context Brain-derived neurotrophic factor (BDNF) concentrations may differ between BDNF genotype carriers. These changes occur in individuals with metabolic and mental disorders. Objective The aim of this study was to assess the associations of glucose homeostasis parameters and the frequency of food consumption with BDNF protein concentrations based on BDNF single nucleotide polymorphisms (SNPs). Methods Among the 439 participants, some common rs10835211 BDNF gene variants were analyzed. We evaluated BDNF concentrations, and measured glucose and insulin after fasting and during oral glucose tolerance tests. Anthropometric measurements, body composition, and body fat distribution were assessed, and a 3-day food intake diary and food frequency questionnaire were completed. Results We observed significant differences in BDNF concentration between AA and AG genotype rs10835211 carriers (P =.018). The group of AA genotype holders were older, and positive correlation was found between age and BDNF in the whole study population (P =.012) and in the GG genotype carriers (P =.023). Moreover, BDNF protein correlated with fasting insulin (P =.015), HOMA-IR (P =.031), HOMA-B (P =.010), and the visceral/subcutaneous adipose tissue (VAT/SAT) ratio (P =.026) in the GG genotype individuals. Presence of the GG genotype was negatively correlated with nut and seed (P =.047) and lean pork consumption (P =.015), and the BDNF protein. Moreover, we observed correlations between the frequency of chicken (P =.028), pasta (P =.033), and sweet food intake (P =.040) with BDNF concentration in the general population. Among carriers of the AA genotype, we observed a positive correlation between the consumption of rice (P =.048) and sweet food (P =.028) and the BDNF protein level. Conclusion Peripheral BDNF may be associated with VAT content and insulin concentrations in GG genotype carriers and may vary with particular food intake, which warrants further investigation. [ABSTRACT FROM AUTHOR]

Abstract An investigation of new ways to activate brown adipose tissue (BAT) is highly valuable, as it is a possible tool for obesity prevention and treatment. The aim of our study was to evaluate the relationships between dietary intake and BAT activity. The study group comprised 28 healthy non-smoking males aged 21–42 years. All volunteers underwent a physical examination and 75-g OGTT and completed 3-day food intake diaries to evaluate macronutrients and fatty acid intake. Body composition measurements were assessed using DXA scanning. An FDG-18 PET/MR was performed to visualize BAT activity. Brown adipose tissue was detected in 18 subjects (67% normal-weight individuals and 33% overweight/obese). The presence of BAT corresponded with a lower visceral adipose tissue (VAT) content (p = 0.04, after adjustment for age, daily kcal intake, and DXA Lean mass). We noted significantly lower omega-6 fatty acids (p = 0.03) and MUFA (p = 0.02) intake in subjects with detected BAT activity after adjustment for age, daily average kcal intake, and DXA Lean mass, whereas omega-3 fatty acids intake was comparable between the two groups. BAT presence was positively associated with the concentration of serum IL-6 (p = 0.01) during cold exposure. Our results show that BAT activity may be related to daily omega-6 fatty acids intake.

Aims: Interocular comparison of the metabolomic signature of aqueous humor (AH) was performed. The aim of the study was to quantitatively evaluate the symmetry in concentrations of various metabolites belonging to different categories.Methods: The study included AH samples from 23 patients, 74.17 ± 11.52 years old, undergoing simultaneous bilateral cataract surgery at the Ophthalmology Department of the Medical University of Bialystok, Poland. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted metabolomics and lipidomics analyses of AH samples were performed using the AbsoluteIDQ® p180 kit. Out of 188 metabolites available in the kit, 67 were measured in the majority (>70%) of the samples: 21/21 amino acids, 10/22 biogenic amines, 9/40 acylcarnitines, 0/14 lysophosphatidylcholines, 21/76 phosphatidylcholines, 5/15 sphingolipids, and 1/1sum of hexoses.Results: The comparison of both eyes revealed that the concentrations of metabolites did not differ significantly (p < 0.05) except for taurine (p = 0.037). There was moderate-to-strong positive interocular correlation (r > 0.5) between most metabolites regarding concentration. This was confirmed by the high intraclass correlation coefficient (ICC) values of different levels, which varied for the different metabolites. However, there were exceptions. Correlations were not significant for 2 acylcarnitines (tiglylcarnitine and decadienylcarnitine) and 3 glycerophospholipids (PC aa C32:3, PC aa C40:2, and PC aa C40:5).Conclusion: With a few exceptions, a single eye was found to be representative of the fellow eye in terms of the concentration of most of the analyzed metabolites. The degree of intraindividual variability in the AH of fellow eyes differs for particular metabolites/metabolite categories.

Macrophage inflammation promotes insulin resistance during diet-induced obesity. Here the authors show that macrophage NOC4L is decreased in humans and mice with obesity, that macrophage NOC4L deficiency aggravated high-fat diet induced inflammation and insulin resistance, and that NOC4L interacts with toll-like receptor 4, to inhibit endocytosis, and thus blocks TLF4/TRIF inflammatory signaling.