Distinct clinical phenotypes in gastric pathologies: a cluster analysis of demographic and biomarker profiles in a diverse patient population

BACKGROUND

Understanding the heterogeneity of a population at risk is an important step in the early detection of gastric cancer. This study aimed to cluster demographic, hematologic, and biochemical markers of gastric cancer in a heterogeneous sample of patients.

METHODS

Data of 695 adult patients (50.0% women) who were diagnosed with histologically confirmed gastric cancer or benign gastric disease or identified as healthy individuals (December 2018 to August 2019; Hangzhou, China) were analyzed. A hierarchical clustering was performed using a factorial analysis of mixed data. To assess the clustering scheme, a machine-learning classification model was developed using the Extreme Gradient Boosting algorithm and subsequently ranked the variables for differentiating patient phenotypes.

RESULTS

Of note, 3 clusters were identified using patient characteristics. The classification model demonstrated high performance (multiclass area under the curve = 0.921) in recognizing the clusters. The top 5 important variables in differentiating the clusters were sex (male/female), hemoglobin, albumin, creatinine, and high-density lipoprotein (all analysis of variance P <.001) in decreasing order of importance. The prevalence rates of gastric cancer in clusters I, II, and III were 95.8%, 53.8%, and 34%, respectively (χ2(2) = 164.050; P <.001). Cluster I (n = 167) predominantly had an inflammatory profile, cluster II (n = 240) had metabolic disturbances, and cluster III (n = 288) had a relatively favorable metabolic and inflammatory profile.

CONCLUSION

There were distinct clinical phenotypes in the population, each with varying prevalence of gastric cancer. A combination of routine clinical data outperformed carbohydrate or carcinoembryonic antigens in capturing the heterogeneity of the population regarding gastric pathologies.

Untargeted metabolomics analysis as a potential screening tool for 3-methylglutaconic aciduria syndromes

The 3-methylglutaconic aciduria (3-MGA-uria) syndromes comprise a heterogeneous group of inborn errors of metabolism defined biochemically by detectable elevation of 3-methylglutaconic acid (3-MGA) in the urine. In type 1 (or primary) 3-MGA-uria, distal defects in the leucine catabolism pathway directly cause this elevation. Secondary 3-MGA-uria syndromes, however, are unrelated to leucine metabolism-specific defects but share a common biochemical phenotype of elevated 3-MGA. It is currently thought that this accumulation is due to an underlying buildup of acetyl-CoA in the mitochondria from impaired function of the TCA cycle with ensuing formation of trans-3-methylglutaconyl CoA and its subsequent byproducts, including 3-MGA. In these disorders, urine 3-MGA levels are known to be fluctuant and at times undetectable by standard urine organic acid analysis (UOA), thereby reducing the utility of this biochemical screening method. Here, we retrospectively evaluated a cohort of nine patients with confirmed 3-MGA-uria syndromes. It was observed that UOA analysis obtained from three separate patients did not identify detectable 3-MGA levels. This inherent limitation highlights the need for a more sensitive clinical modality. Untargeted metabolomics profiling is a rapidly emerging technology that is being used to detect and characterize biochemical abnormalities in many inborn errors of metabolism. Untargeted metabolomics profiling performed on plasma samples in this cohort identified significant elevations of 3-MGA in all nine individuals. This high degree of clinical sensitivity demonstrates the promising potential for untargeted metabolomics analysis as both an effective biochemical screening tool for 3-MGA-uria syndromes and a functional method to assist with validation of genomic variants of uncertain significance in these disorders.

α-tocopherol deficiency in follicular ovarian cyst (FOCs) follicular fluid (FF) elevates oxidative stress and impairs oocyte maturation

Follicular ovarian cysts (FOCs) are prevalent reproductive disorders in both humans and animals, especially in livestock, where they cause economic losses by reducing fertility and productivity. FOCs are marked by a dominant follicle that fails to ovulate, disrupting the estrous cycle and reproductive efficiency. Previous studies indicate that the follicular fluid (FF) in cystic ovaries shows oxidative imbalance, affecting oocyte quality by altering glutathione peroxidase (GPX1) and selenium pathways. However, the metabolic profile of FF in cystic ovaries needs further exploration. This study examined oxidative stress and metabolic changes in FOC pathogenesis. Using untargeted metabolomics of goat FF, we found significant differences in 12,741 metabolites between cystic and control FF. Cystic FF had reduced levels of α-tocopherol and 8'-apocaroten-8'-ol, key for oxidative stress management, and increased levels of mycotoxins (e.g., Deoxynivalenol-3-glucoside) and long-chain fatty acids. Adding 200 μM α-tocopherol to FOC FF oocyte cultures doubled oocyte maturation rates and decreased reactive oxygen species (ROS). Metabolomic analysis linked low α-tocopherol to high lipid peroxyl radicals and low glutathione oxidation, emphasizing oxidative stress regulation's importance in the follicular microenvironment. Our findings suggest that α-tocopherol may serve as a biomarker and therapeutic agent to enhance oocyte maturation in FOCs.

Metabolic Fingerprint of Dual Body Fluids Deciphers Diabetic Retinopathy

Diabetic retinopathy (DR) is a microvascular complication of diabetes, affecting 34.6% of diabetes patients worldwide. Early detection and timely treatment can effectively improve the prognosis of DR. Metabolomic analysis provides a powerful tool for studying pathophysiological processes. Conducting metabolomic analyses on DR-related biofluids helps identify differential metabolic expressions during disease progression, thereby discovering potential biomarkers to support clinical diagnosis and treatment. Here, an innovative workflow for vitreous liquid analysis is established, and a machine learning-based DR analysis platform integrating vitreous liquid metabolic fingerprint (VL-MF) and plasma metabolic fingerprint (P-MF) derived via nanoparticle enhanced laser desorption/ionization mass spectrometry is developed. Direct VL-MF and P-MF are obtained with desirable reproducibility (coefficient of variation, CV <5%) and remarkable speed (3 s per sample), and DR patients are distinguished from healthy controls applying dual biofluid-MF with an area under the curve (AUC) of 0.957. Moreover, a biomarker candidate panel from vitreous liquid and plasma with an AUC of 0.945 is constructed and the related metabolic pathways are identified by metabolomics pathway analysis (MetPA). This work offers a powerful multi-biofluid platform that can not only contribute to DR but also provide solid references for other clinical applications.

Non-invasive diagnosis of papillary thyroid microcarcinoma using a novel metabolomics analysis of urine

BACKGROUND

The severity of thyroid cancer is judged on the basis of histologic and clinical features. A limited number of studies have considered urinary metabolite signatures for its diagnosis, and no reliable urinary metabolite biomarkers have been proposed. This diagnostic method would be particularly valuable because of its non-invasive nature.

METHOD

A nuclear magnetic resonance (NMR)-based metabolomics approach was used as the analytical platform to study the urine samples of patients with PTMC. Urine samples collected from 41 PTMC patients, 52 healthy subjects, and 13 patients with benign tumors were analyzed using 1H-NMR spectroscopy to identify metabolic changes. PLS-DA, or partial least squares discriminant analysis, was used to analyze the NMR spectra. A double cross-validation method and randomization tests were used to validate PLS-DA models.

RESULTS

Clear discriminations between PTMC patients and healthy controls, as well as between PTMC patients and patients with benign tumors were obtained. Collectively, pi-methyhistidine, trimethylamine, myo-inositol, acetate, suberate, azelate, mannitol, tau-methylhistine, ascorbate, 3-aminoisobutyric acid, 2-oxoglutarate, and methanol contributed to the discrimination. Apart from myo-inositol and methanol, all of these metabolites exhibited increased levels in the urine samples of PTMC patients as compared to that of patients with benign tumors.

CONCLUSIONS

The application of this NMR-based metabolomics approach allowed the detection of anomalous metabolic traits directly connected PTMC, potentially yielding a more sensitive and comprehensive diagnostic results for PTMC.

Elevated isoleucine may be a protective factor for primary hypertension: A pooled causal effect study

Hypertension continues to pose a huge burden to global public health. Abnormal metabolism not only serves as a risk factor for hypertension but also acts as a driving force in its aggravation. However, there remains a lack of large-scale causal demonstration based on extensive samples. Our study aims to investigate the causal relationship between metabolism and primary hypertension (PH) using Mendelian randomization analysis. We used genome-wide association studies instrumental variables for Mendelian randomization association analysis integrating the diagnosis results of PH in 3 populations from East Asia, the Middle East, and Africa with serum metabolites and metabolite ratios. This allowed us to identify predictive metabolites and metabolic pathways for diagnosing or treating PH. Inverse-variance weighting was the main model for establishing causal associations. In addition horizontal pleiotropy test, linkage disequilibrium test, and sensitivity analysis were employed to test the explanatory power of instrumental variables. A total of 10,922 cases of PH and 8299 cases of metabolomics detection cohorts were included in the study. In East Asian, Middle Eastern, and African populations, we found 36, 57, and 40 known metabolites respectively strongly associated with PH (P < .05). Cross-section and meta-analysis of these strongly correlated metabolites across the 3 ethnic groups revealed 7 common metabolites. Notably, elevated isoleucine (odds ratio = 0.74, 95% confidence interval: 0.56-0.96) was demonstrated as a potential protective factor against PH across 3 ethnic groups. The metabolites associated with PH have certain polymorphisms in different populations. Isoleucine may be a promising biomarker for PH diagnosis or treatment, but more clinical validation is needed.

Gut Metabolome in Companion Animal Nutrition-Linking Diets to Health

Tailoring diet to support a healthy gut microbiome is key for animal well-being. The gut metabolome, including all small molecules in the gut, is central to diet-microbiome-health interactions. While comprehension of the gut metabolome in companion animal nutrition is emerging, a substantial number of studies have been undertaken to elucidate the metabolomic shifts and identify specific marker metabolites influenced by diverse dietary interventions. By employing various metabolomic approaches, researchers have extensively documented the effects of different diet types, nutrient compositions, and dietary supplements on the gut metabolome in dogs and cats. Despite these advancements, there remains several notable limitations, including a lack of integrated microbiome analysis, incomplete understanding of specific marker metabolites, and an over-reliance on extrapolating findings from human studies. Therefore, this review aims to summarize the current understanding of the canine and feline gut metabolome, while exploring future possibilities and challenges for the field.

The relationship between serum uric acid level and non-alcoholic fatty liver disease in northern China: a retrospective cohort study

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent chronic liver disease among adults. High uric acid (UA) increases the incidence of NAFLD in the general population. However, further exploration is warranted to determine the relationship between UA levels and NAFLD in various populations. We conducted a historical cohort study to investigate the causality between UA and NAFLD across different weight categories.

METHODS

A historical cohort was established from the Jidong community cohort. All participants were enrolled and followed up from July 1st, 2013 to August 1st, 2018. The study participants were retrospectively assigned to four groups according to their UA levels (Q1, 69-210 μmol/L; Q2, 211-255 μmol/L; Q3, 256-310 μmol/L; Q4, 311-593 μmol/L). The NAFLD incidence was investigated in each group. We used the UA level determined by an automatic analyzer. NAFLD was diagnosed with abdominal ultrasonography examination. Demographic information, lifestyle history, clinical anthropometric data, and blood samples of participants were collected. Univariate analysis and multivariable Cox regression were applied to analyze the relationship between UA and NAFLD by stratification of participants' body mass index (BMI) categories (underweight, normal weight, overweight, and obese).

RESULTS

Two thousand nine hundred eighty four participants were enrolled. 740 (24.8%) were assigned to UA Q1 group, 755 (25.3%) to UA Q2, 743 (24.9%) to UA Q3, and 746 (25.0%) to UA Q4. The global incidence of NAFLD was 26.0% (777/2984). The risk of NAFLD significantly increased with elevated UA levels in underweight and normal-weight participants (HR = 3.498, 95% CI: 2.413-5.072, P < 0.05). In multivariable analysis, UA showed a positive association with NAFLD, independent of other risk factors in underweight and normal-weight participants (UA Q2: 1.152 (0.761-1.743), UA Q3: 2.168 (1.489-3.157), UA Q4: 3.075 (2.103-4.196), P < 0.05). In the absence of other risk factors, high UA levels independently explained 17% of NAFLD risk in underweight and normal-weight participants.

CONCLUSIONS

High UA levels serve as an independent risk factor for NAFLD in underweight and normal-weight individuals, highlighting the necessity of early NAFLD screening through monitoring liver function and UA levels, and personalized treatment plans for NAFLD patients with higher UA levels, which may include uric acid-lowering therapy and lifestyle modifications. However, the relationship between UA levels and NAFLD in overweight and obese individuals remains inconclusive.

Decoding Sugars: Mass Spectrometric Advances in the Analysis of the Sugar Alphabet

Monosaccharides play a central role in metabolic networks and in the biosynthesis of glycomolecules, which perform essential functions across all domains of life. Thus, identifying and quantifying these building blocks is crucial in both research and industry. Routine methods have been established to facilitate the analysis of common monosaccharides. However, despite the presence of common metabolites, most organisms utilize distinct sets of monosaccharides and derivatives. These molecules therefore display a large diversity, potentially numbering in the hundreds or thousands, with many still unknown. This complexity presents significant challenges in the study of glycomolecules, particularly in microbes, including pathogens and those with the potential to serve as novel model organisms. This review discusses mass spectrometric techniques for the isomer-sensitive analysis of monosaccharides, their derivatives, and activated forms. Although mass spectrometry allows for untargeted analysis and sensitive detection in complex matrices, the presence of stereoisomers and extensive modifications necessitates the integration of advanced chromatographic, electrophoretic, ion mobility, or ion spectroscopic methods. Furthermore, stable-isotope incorporation studies are critical in elucidating biosynthetic routes in novel organisms.

Refined highland barley ameliorates obesity-associated insulin resistance in high-fat diet-fed mice by targeting the gut microbiota and liver transcriptomics

PURPOSE

It is generally believed that refined grains lack nutritional value compared to whole grains. The objective of this study was to investigate whether refined highland barley (RHB) holds the potential to combat obesity-associated insulin resistance.

METHODS

Thirty-two male 6-week-old C57BL/6J mice were randomly divided into four groups fed with a normal chow diet, a high-fat diet (HFD), a 30% RHB supplemented HFD diet, and a 30% whole-grain highland barley (WGHB) supplemented HFD diet. We examined the anti-obesity and anti-insulin resistance effects of RHB and compared them with WGHB in mice.

RESULTS

RHB intervention effectively improved obesity and insulin resistance, enhanced the intestinal mucosal barrier, and reduced inflammation. Moreover, it promoted the abundance of beneficial gut bacteria such as Akkermansia, Bifidobacterium, Lachnospiraceae_NK4A136_group, Lachnospiraceae_UCG-001, Alloprevotella, and increased the production of short-chain fatty acids (SCFAs) in faeces. Additionally, RHB intervention modulated liver gene transcription, downregulating inflammatory genes like IRF3/7, STAT1/2, NLRP3, and TLR2.

CONCLUSIONS

RHB could effectively alleviate obesity-related insulin resistance by targeting gut microbiota and liver transcriptomics, and its beneficial impacts are comparable to those of WGHB.

Microbiota-Gut-Brain Axis: Mass-Spectrometry-Based Metabolomics in the Study of Microbiome Mediators-Stress Relationship

The microbiota-gut-brain axis is a complex bidirectional communication system that involves multiple interactions between intestinal functions and the emotional and cognitive centers of the brain. These interactions are mediated by molecules (metabolites) produced in both areas, which are considered mediators. To shed light on this complex mechanism, which is still largely unknown, a reliable characterization of the mediators is essential. Here, we review the most studied metabolites in the microbiota-gut-brain axis, the metabolic pathways in which they are involved, and their functions. This review focuses mainly on the use of mass spectrometry for their determination, reporting on the latest analytical methods, their limitations, and future perspectives. The analytical strategy for the qualitative-quantitative characterization of mediators must be reliable in order to elucidate the molecular mechanisms underlying the influence of the above-mentioned axis on stress resilience or vulnerability.

Impact of Olive Oil Components on the Expression of Genes Related to Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is a multifactorial metabolic disorder characterized by insulin resistance and beta cell dysfunction, resulting in hyperglycemia. Olive oil, a cornerstone of the Mediterranean diet, has attracted considerable attention due to its potential health benefits, including reducing the risk of developing T2DM. This literature review aims to critically examine and synthesize existing research regarding the impact of olive oil on the expression of genes relevant to T2DM. This paper also seeks to provide an immunological and genetic perspective on the signaling pathways of the main components of extra virgin olive oil. Key bioactive components of olive oil, such as oleic acid and phenolic compounds, were identified as modulators of insulin signaling. These compounds enhanced the insulin signaling pathway, improved lipid metabolism, and reduced oxidative stress by decreasing reactive oxygen species (ROS) production. Additionally, they were shown to alleviate inflammation by inhibiting the NF-κB pathway and downregulating pro-inflammatory cytokines and enzymes. Furthermore, these bioactive compounds were observed to mitigate endoplasmic reticulum (ER) stress by downregulating stress markers, thereby protecting beta cells from apoptosis and preserving their function. In summary, olive oil, particularly its bioactive constituents, has been demonstrated to enhance insulin sensitivity, protect beta cell function, and reduce inflammation and oxidative stress by modulating key genes involved in these processes. These findings underscore olive oil's therapeutic potential in managing T2DM. However, further research, including well-designed human clinical trials, is required to fully elucidate the role of olive oil in personalized nutrition strategies for the prevention and treatment of T2DM.

Natural products targeting AMPK signaling pathway therapy, diabetes mellitus and its complications

Diabetes mellitus (DM) ranks among the most prevalent chronic metabolic diseases, characterized primarily by a persistent elevation in blood glucose levels. This condition typically stems from either insufficient insulin secretion or a functional defect in the insulin itself. Clinically, diabetes is primarily classified into type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), with T2DM comprising nearly 90% of all diagnosed cases. Notably, the global incidence of T2DM has surged dramatically over recent decades. The adenylate-activated protein kinase (AMPK) signaling pathway is crucial in regulating cellular energy metabolism, marking it as a significant therapeutic target for diabetes and related complications. Natural products, characterized by their diverse origins, multifaceted bioactivities, and relative safety, hold considerable promise in modulating the AMPK pathway. This review article explores the advances in research on natural products that target the AMPK signaling pathway, aiming to inform the development of innovative antidiabetic therapies.

Rapid exometabolome footprinting combined with multivariate statistics: A powerful tool for bioprocess optimization

Corynebacterium glutamicum is used as an industrial platform organism for amino acid production. Previously, the organism was utilized to produce l-histidine with research focusing on metabolic engineering approaches to increase titer and yield. Only a few studies have been published that provide information on bioprocess development, with media optimization and fed-batch cultivation procedure being particularly promising areas. In this work, we show how experimental setups such as miniature cultivation technology, dynamic and time-optimized LC-MS/MS metabolic footprinting tools, and automated workflows for the detection of local and global metabolic patterns can significantly accelerate bioprocess development. Potential media bottlenecks in form of phosphate and magnesium availability were identified by sensitivity analysis in parallelized microscale cultivation assisted by lab automation. A rapid dilute-and-shoot flow-injection-analysis tandem mass spectrometry approach was used to cope with the resulting cultivation throughput and allowed to quantify amino acids with 1 min per sample. We were able to increase the l-histidine titer of a C. glutamicum random mutagenesis mutant by a factor of 5.8 through process optimization while also identifying both known and previously unknown targets for additional strain improvements. The presented methodology can be seen as a supplement to traditional approaches in the field of bioprocess development.

Development of a Catalyst-Free Ultrasound-Assisted Derivatization Method for Detection of Valproic Acid in Epilepsy Patient's Serum Using High-Performance Liquid Chromatography: A Comparison With Chemiluminescence Immunoassay

The aim of this research was the therapeutic drug monitoring for valproic acid in epilepsy patient's serum samples by the common, sensitive, and accessible HPLC-UV method. Because of the absence of a suitable chromophore in the valproic acid structure, a facile, selective, and cost-effective pre-column derivatization was designed. This catalyst-free ultrasound-assisted derivatization assay can accomplish the derivatization very quickly only in 5.0 min and at a mild temperature of 60°C. 2,4'-Dibromoacetophenone and nonanoic acid was used as derivatizing agent and internal standard, respectively. The effect of sample pH, buffer concentration, ultrasound exposure time, reaction temperature, and derivatizing agent amount were optimized. The proposed method exhibited a good linear range of 5.0-300.0 µg/mL with acceptable correlation coefficients of 0.9981. The limit of detection was as low as 0.4 µg/mL. Also, the limit of quantification was reported as 1.3 µg/mL. Interday and intraday relative standard deviations (n = 10) were 1.1% and 0.3%-7.0%, respectively. In addition, the relative recovery ranged from 100.3% to 107.7%. The measurement of valproic acid was performed in the presence of several epilepsy and non-epilepsy drugs by the developed protocol. This confirmed the specific and accurate determination of valproic acid in the patient's serum. A comparative evaluation was employed against the precise chemiluminescence immunoassay approach. The correlation coefficient between the two methods was 0.9992, which demonstrated the results were statistically the same.

Serum metabolic profiling analysis of chronic gastritis and gastric cancer by untargeted metabolomics

Chronic gastritis (CG), particularly when associated with Helicobacter pylori (H. pylori) infection, is a significant precursor to gastric cancer (GC), a leading cause of cancer-related deaths worldwide. The persistent inflammation in CG, driven by factors such as H. pylori, induces oxidative stress and DNA damage in gastric epithelial cells, which can lead to malignant transformation. Atrophic gastritis, a form of CG, can be categorized into autoimmune and H. pylori-associated types, both of which increase the risk of GC development, particularly when compounded by external factors like smoking and dietary habits. This manuscript explores the pathophysiological mechanisms underlying CG and its progression to GC, highlighting the critical role of metabolomics in advancing our understanding of these processes. Metabolomics, the comprehensive study of metabolites, offers a novel approach to identifying biomarkers that could facilitate early detection and improve the accuracy of GC diagnosis and prognosis. The analysis of metabolic alterations, particularly in glucose, lipid, and amino acid metabolism, reveals distinct biochemical pathways associated with the progression from benign gastritis to malignancy. Integrating metabolomic profiling with traditional diagnostic methods can revolutionize GC management, enabling more personalized treatment strategies and improving clinical outcomes. However, significant challenges remain, including the need to validate biomarkers across diverse populations and standardize metabolomic techniques. Future research should address these challenges to fully realize the potential of metabolomics in early GC detection and treatment, ultimately aiming to reduce the global burden of this deadly disease.

Temporal transcriptome profiling in the response to Salmonella enterica serovar enteritidis infection in chicken cecum

Salmonella enterica serovar Enteritidis (S. Enteritidis) is a common zoonotic pathogen that not only causes gastroenteritis or death of livestock and poultry but also poses a serious threat to human health, causing severe economic losses to the poultry industry and society. Herein, RNA-sequencing (RNA-seq) was used to analyze the transcriptome variation of chicken cecum at four different time points (1, 3, 7, and 14 days) following S. Enteritidis infection. There were 529, 1477, 476, and 432 differentially expressed genes (DEGs) in the cecum at four different days post-infection (dpi), respectively. The DEGs were significantly enriched in various immune-related pathways on 3 dpi and 7 dpi, such as cytokine-cytokine-receptor interaction and Toll-like receptor signaling pathway. DEGs were significantly enriched in several metabolic pathways on 14 dpi. Gene ontology (GO) enrichment of DEGs showed that up-regulated genes were significantly enriched in immune-related terms on 3 and 7 dpi. On 14 dpi, up-regulated genes were mainly enriched in the signaling-related terms, while the down-regulated genes were primarily enriched in the metabolic-related terms. Based on weighted gene co-expression network analysis (WGCNA), the key modules related to energy, non-coding processes, immunity, and development-related functions were identified at 1, 3, 7, and 14 dpi, respectively, and 5, 8, 6, and 5 hub genes were screened out, respectively. This study demonstrated that the chicken cecal transcriptome regulation responding to S. Enteritidis infection is time-dependent. The regulation of S. Enteritidis infection in chickens is coordinated by multiple systems, mainly involving immunity, metabolism, and signal transduction. Both 3 and 7 dpi are key time points for immune response. As the infection progresses, metabolism-related pathways were increasingly identified. This change reflects the dynamic adjustment between immune response and metabolism in Jining Bairi chickens following S. Enteritidis infection. These results suggested that starting from 3 dpi, the chickens gradually transition from an immune response triggered by S. Enteritidis infection to a state where they adapt to the infection by modulating their metabolism.

The modulatory effect of oat on brain-derived neurotrophic factor, orexigenic neuropeptides, and dopaminergic signaling in obesity-induced rat model: a comparative study to orlistat

BACKGROUND

Obesity is a non-communicable complex disease that is the fifth leading cause of death worldwide. According to a novel viewpoint, the brain plays a significant role in the central regulation of satiety and energy homeostasis. Because of its rich nutritional profile and versatile uses, oat (Avena sativa) is one of the most popular functional foods recommended by many nutritionists. The anti-obesity effect of oat was hypothesized, focusing on the brain as the target organ. In the current study, the interplay between brain biomarkers, obesity, and its related complications was evaluated in diet-induced obese rats for 25 weeks, in which 60 adult male white albino Wistar rats were divided into three control and seven treatment groups given oat extracts in a dose-dependent manner.

RESULTS

Oat significantly improved obesity-related metabolic complications. In terms of brain function, oat significantly increased dopaminergic signaling, brain-derived neurotrophic factor levels, vaspin, irisin, and uncoupling protein-1 brain levels, while decreasing the expression of agouti-related peptide and neuropeptide Y (P-value < 0.05).

CONCLUSION

The current study proposes oat supplementation as a new conceptual framework with numerous implications for hedonic and homeostatic mechanisms that control satiety. © 2024 Society of Chemical Industry.

Promising mass spectrometry imaging: exploring microscale insights in food

This review focused on mass spectrometry imaging (MSI), a powerful tool in food analysis, covering its ion source schemes and procedures and their applications in food quality, safety, and nutrition to provide detailed insights into these aspects. The review presented a detailed introduction to both commonly used and emerging ionization sources, including nanoparticle laser desorption/ionization (NPs-LDI), air flow-assisted ionization (AFAI), desorption ionization with through-hole alumina membrane (DIUTHAME), plasma-assisted laser desorption ionization (PALDI), and low-temperature plasma (LTP). In the MSI process, particular emphasis was placed on quantitative MSI (QMSI) and super-resolution algorithms. These two aspects synergistically enhanced MSI's analytical capabilities: QMSI enabled accurate relative and absolute quantification, providing reliable data for composition analysis, while super-resolution algorithms improved molecular spatial imaging resolution, facilitating biomarker and trace substance detection. MSI outperformed conventional methods in comprehensively exploring food functional factors, biomarker discovery, and monitoring processing/storage effects by discerning molecular species and their spatial distributions. However, challenges such as immature techniques, complex data processing, non-standardized instruments, and high costs existed. Future trends in instrument enhancement, multispectral integration, and data analysis improvement were expected to deepen our understanding of food chemistry and safety, highlighting MSI's revolutionary potential in food analysis and research.

Natural α-glucosidase inhibitors from Aquilaria sinensis leaf-tea: Targeted bio-affinity screening, identification, and inhibition mechanism

Aquilaria sinensis leaves have long been consumed as a popular replacement tea for lowering postprandial blood glucose levels, but their specific functional components remain unclear. In this study, Aquilaria sinensis leaf-tea 70 % ethanol extract (ALTE) exhibited excellent anti-α-glucosidase activity (IC50 = 6.93 ± 1.91 μg/mL) and promoted glucose consumption ability in 3 T3-L1 preadipocyte cells. Subsequently phenolic compositions of ALTE were identified for the first time. After that, five potential α-glucosidase inhibitors (α-GIs) including cynaroside-3,5-diglucose, malvidin 3-glucose, epicatechin, epigallocatechin gallate, and dihydromyricetin in ALTE were screened using a targeted bio-affinity ultrafiltration-HPLC/MS method. Moreover, these five α-GIs all showed good anti-α-glucosidase effects and glucose consumption-promoting ability. Furthermore, the binding properties and inhibition mechanisms of five α-GIs to α-glucosidase were further analyzed via enzyme inhibition kinetics, molecular docking, and molecular dynamics simulation. This study confirms that Aquilaria sinensis leaf-tea is effective in preventing post-hyperglycemia in vitro models, suggesting potential for future research in human trials.

Investigation of the Molecular Mechanism of Asthma in Meishan Pigs Using Multi-Omics Analysis

Asthma has been extensively studied in humans and animals, but the molecular mechanisms underlying asthma in Meishan pigs, a breed with distinct genetic and physiological characteristics, remain elusive. Understanding these mechanisms could provide insights into veterinary medicine and human asthma research. We investigated asthma pathogenesis in Meishan pigs through transcriptomic and metabolomic analyses of blood samples taken during autumn and winter. Asthma in Meishan pigs is related to inflammation, mitochondrial oxidative phosphorylation, and tricarboxylic acid (TCA) cycle disorders. Related genes include CXCL10, CCL8, CCL22, CCL21, OLR1, and ACKR1, while metabolites include succinic acid, riboflavin-5-phosphate, and fumaric acid. Transcriptomic sequencing was performed on panting and normal Meishan pigs, and differentially expressed genes underwent functional enrichment screening. Metabolomic analysis revealed differential metabolites and pathways between groups. Combined analyses indicated that lung inflammation is influenced by genetic, allergenic, and environmental factors disrupting oxidative phosphorylation in lung mitochondria, affecting the TCA cycle. Mitochondrial reactive oxygen species, glutathione S-transferases, arginase 1 and RORC in immune regulation, the Notch pathway, YPEL4 in cell proliferation, and MARCKS in airway mucus secretion play roles in asthma pathogenesis. This study highlights that many cytokines and signaling pathways contribute to asthma. Further studies are needed to elucidate their complex interactions.

The relationship between dietary branched-chain and aromatic amino acids with the regulation of leptin and FTO genes in adipose tissue of patients undergoing abdominal surgery

Recent studies have suggested that the interaction between diet and an individual's genetic predisposition can determine the likelihood of obesity and various metabolic disorders. The current study aimed to examine the association of dietary branched-chain amino acids(BCAAs) and aromatic amino acids(AAAs) with the expression of the leptin and FTO genes in the visceral and subcutaneous adipose tissues of individuals undergoing surgery. This cross-sectional study was conducted on 136 Iranian adults, both men and women, aged ≥18 years. The samples were selected from patients admitted for abdominal surgeries. The dietary intake of BCAAs and AAAs was determined using a valid and reliable 168-item food frequency questionnaire. Using the quantitative PCR method, leptin and FTO mRNA expression was measured in both visceral and subcutaneous fat tissues. The mean age of the participants was 39.8 ± 12.7 years, and the mean intake of BCAAs and AAAs was 17.7 ± 0.9 and 9.3 ± 0.3% of protein per day, respectively. In overweight-obese patients(body mass index = 25-34.9 kg/m2), the intake of BCAAs(β:-0.75,95%CI:-1.47,-0.03), valine(β:-0.78,95%CI:-1.51,-0.05), and tyrosine(β:-0.81,95%CI:-1.55,-0.06) was inversely associated with FTO gene expression in subcutaneous fat tissue in adjusted model. In morbidly obese patients(body mass index ≥ 35 kg/m2), a higher intake of total BCAAs(β:1.10,95%CI:0.07-2.13), leucine(β:1.07,95%CI:0.03-2.13), and isoleucine(β:1.49,95%CI:0.46-2.52) was associated with an increase of leptin gene expression in subcutaneous fat tissue. Our findings suggest that dietary BCAA may associated with gene expression in adipose tissues, potentially influencing obesity-related metabolic pathways. Further prospective studies are warranted to validate results and elucidate the potential for dietary interventions targeting amino acids intake in obesity management.

Large-scale analysis to identify risk factors for ovarian cancer

OBJECTIVE

Ovarian cancer is characterized by late-stage diagnoses and poor prognosis. We aimed to identify factors that can inform prevention and early detection of ovarian cancer.

METHODS

We used a data-driven machine learning approach to identify predictors of epithelial ovarian cancer from 2920 input features measured 12.6 years (IQR 11.9 to 13.3 years) before diagnoses. Analyses included 221 732 female participants in the UK Biobank without a history of cancer. During the follow-up 1441 women developed ovarian cancer. For factors that contributed to model prediction, we used multivariate logistic regression to evaluate the association with ovarian cancer, with evidence for causality tested by Mendelian randomization (MR) analyses in the Ovarian Cancer Genetics Consortium (25 509 cases).

RESULTS

Greater parity and ever-use of oral contraception were associated with lower ovarian cancer risk (ever vs never OR 0.74, 95% CI 0.66 to 0.84). After adjustment for established risk factors, greater height, weight, and greater red blood cell distribution width were associated with increased ovarian cancer risk, while higher aspartate aminotransferase levels and mean corpuscular volume were associated with lower risk. MR analyses confirmed observational associations with anthropometric/adiposity traits (eg, body fat percentage per standard deviation (SD); OR inverse-variance weighted (ORIVW) 1.28, 95% CI 1.13 to 1.46) and aspartate aminotransferase (ORIVW 0.87, 95% CI 0.78 to 0.98). MR also provided genetic evidence for a protective association of higher total serum protein on ovarian cancer, higher lymphocyte count on serous and endometrioid ovarian cancer, and greater forced expiratory volume in 1 s on serous ovarian cancer among other findings.

CONCLUSIONS

This study shows that certain risk factors for ovarian cancer are modifiable, suggesting that weight reduction and interventions to reduce the number of ovulations may provide potential for future prevention. We also identified blood biomarkers associated with ovarian cancer years before diagnoses, warranting further investigation.

Association between the triglyceride-glucose index and liver fibrosis in adults with metabolism-related fatty liver disease in the United States: a cross-sectional study of NHANES 2017-2020

OBJECTIVE

This study aimed to examine the association between the triglyceride-glucose (TyG) index and liver fibrosis (LF) in U.S. adults with Metabolic Dysfunction-Associated Steatotic Liver Disease (MAFLD).

METHODS

Using data from the 2017 to 2020 National Health and Nutrition Examination Survey (NHANES) database, we conducted a population-based cross-sectional study with 1,324 participants. MAFLD was defined as a controlled attenuation parameter (CAP) score ≥ 248 dB/m accompanied by metabolic dysfunction. A median liver stiffness measurement ≥ 8.2 kPa was used to identify significant fibrosis (≥ F2). Multivariable logistic regression was employed to assess the impact of the TyG index on LF outcomes. A restricted cubic spline (RCS) model was used to explore nonlinear effects, and receiver operating characteristic (ROC) curves were applied to evaluate the effectiveness in predicting.

RESULTS

Among the participants, 716 were men and 608 were women, aged 20 to 80 years, representing various racial groups. Significant fibrosis was observed in 137 out of 1,324 participants. After adjusting for confounding factors, a higher TyG index was significantly associated with an increased incidence of MAFLD-related LF (OR = 2.18, 95% CI, 1.14-4.18; p < 0.05). Elevated TyG levels showed a positive correlation with significant fibrosis, with an odds ratio (OR) exceeding 1 when the TyG index was above 8.054. Subgroup analyses stratified by sex, age, and body mass index (BMI) revealed differences after adjusting for confounders. The association was stronger in women (OR = 2.53, 95% CI, 1.16-5.53) than in men (OR = 1.95, 95% CI, 0.81-4.72). A significant correlation was also found between TyG levels and obesity status (overweight: OR = 4.80, 95% CI, 1.27-18.2; obese: OR = 2.26, 95% CI, 1.20-5.53). In MAFLD patients aged 40-59, TyG was strongly associated with LF (OR = 2.85, 95% CI, 1.16-6.79). Furthermore, the area under the ROC curve (AUC) for the TyG index in predicting significant fibrosis in MAFLD patients was 0.73 (95% CI, 0.68-0.78), indicating moderate predictive ability.

CONCLUSIONS

In the general U.S. population, elevated TyG index levels were positively associated with an increased risk of LF in MAFLD patients.

Association of tricarboxylic acid cycle related-metabolites with hypertension in older adults: a community-based cross-sectional study

Hypertension is still a common chronic disease worldwide and seriously affects human health. Aim of this study was to investigate the association between tricarboxylic acid (TCA) cycle-related metabolites and hypertension in older adults. A total of 1127 community-dwelling older adults were included in this cross-sectional analysis, of whom 609 were assigned to the hypertension group and 518 to the no-hypertension group. Plasma concentrations of 8 TCA cycle-related metabolites (citrate, cis-aconitate, isocitrate, 2-oxoglutarate, succinate, maleate, fumarate, and malate) were determined by gas chromatography-triple quadrupole mass spectrometry. Multivariate logistic regression was used to assess the association between these metabolites and hypertension risk. After adjustment for covariates, we found that the increased plasma concentrations of 2-oxoglutarate and malate were significantly associated with hypertension. These two associations remained unchanged after using the false discovery rate (FDR)-adjustment method (both FDR-adjusted P-trend <0.05). In stratified analysis, these two associations were not modified by overweight, physical activity, and current drinking (all P-interaction >0.05). In the multivariate diagnostic model, the inclusion of these two metabolites modestly and significantly improved the diagnosis of hypertension (AUC = 0.64, 95% CI: 0.60-0.67). These results indicated that plasma 2-oxoglutarate and malate might be the candidate metabolic markers of hypertension among older adults. However, further longitudinal and experimental studies are necessary to confirm this finding.

The Multifaceted Role of the Polyphenol Curcumin: A Focus on Type 2 Diabetes Mellitus

Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disorder characterized by chronic hyperglycemia, which often co-exists with other metabolic impairments. This condition can damage various tissues and organs, resulting in the development of severe complications, both microvascular, such as retinopathy, nephropathy, and neuropathy, and macrovascular, responsible for an increased risk of cardiovascular diseases. Curcumin is the main bioactive molecule found in the rhizomes of turmeric. Many studies have reported curcumin to exhibit antioxidant, anti-inflammatory, anti-infectious, and anti-cancer properties; thus, there is an increasing interest in exploiting these properties in order to prevent the rise or the progression of T2DM, as well as its possible associated conditions. In this review, we have presented the current state-ofart regarding the clinical trials that have involved curcumin administration and analyzed the possible mechanisms by which curcumin might exert the beneficial effects observed in literature.

Optimization of metabolomics pretreatment method of cholangiocarcinoma cells based on ultrahigh performance liquid chromatography coupled with mass spectrometry

Metabolomics intends to maximize the quantity of available metabolites for the global metabolome, which largely depends on sample pretreatment protocols. However, there are few studies that comprehensively examined the effects of extraction and reconstitution solvents on metabolome coverage of adherent mammalian cells. In this study, the human cholangiocarcinoma TFK-1 cells were chosen as a cell model, and eight extraction solvents and five reconstitution solvents were used for the pretreatment based on ultrahigh performance liquid chromatography coupled with mass spectrometry (UPLC/MS). The coverage, reproducibility, and stability of the data were norms to evaluate the effectiveness of different extraction solvents and reconstitution solvents. Based on the number of metabolites, the mean Euclidean distance (EDMEAN) in the principal component analysis (PCA) 3D score plots and the relative standard deviation (RSD) distribution of metabolites, it was demonstrated that MeOH-CHCl3-H2O (8:1:1, v/v/v) was the optimal extraction solvent and MeOH-H2O (1:1, v/v) or H2O was superior to other reconstitution solvents for RP column analysis, and the extraction solvent MeOH-ACN-H2O (2:2:1, v/v/v) and the reconstitution solvents ACN-H2O (4:1, v/v) or MeOH-H2O (1:1, v/v) provide the best performance for HILIC column analysis. The optimized pretreatment methods explored in this study expand the coverage of polar and non-polar metabolites and improve the reproducibility and stability of the metabolic data, which can be applied to UPLC/MS-based global metabolomics study on cholangiocarcinoma cells, potentially providing better extraction solvents and reconstitution solvents for other adherent mammalian cells with similar chemical and physical properties.

Serum metabolome profiling in patients with mild cognitive impairment reveals sex differences in lipid metabolism

Alzheimer's disease (AD) affects more women than men. Although women live longer than men, it is not longevity alone, but other factors, including metabolic changes, that contribute to the higher risk of AD in women. Metabolic pathways have been implicated in AD progression, but studies to date examined targeted pathways, leaving many metabolites unmeasured. Sex is often a neglected biological variable, and most metabolomic studies were not designed to investigate sex differences in metabolomic profiles. Here, we performed untargeted metabolomic profiling of sera from male and female patients with mild cognitive impairment (MCI), a common precursor to AD, and matched controls. We discovered significant metabolic changes in individuals with MCI, and found several pathways that were strongly associated with sex. Peptide energy metabolism demonstrated sexual dimorphism. Lipid pathways exhibited the strongest differences between female and male MCI patients, including specific phosphatidylcholine lipids, lysophospholipids, long-chain fatty acids, and monoacylglycerols. 1-palmitoleoyl glycerol and 1-arachidonoyl glycerol were higher in female MCI subjects than in male MCI subjects with no differences between control males and females. Conversely, specific dicarboxylic fatty acids were lower in female MCI subjects than male MCI subjects. In cultured astrocytes, 1-arachidonoyl glycerol promoted phosphorylation of the transcriptional regulator sphingosine kinase 2, which was inhibited by the transient receptor potential vanilloid 1 receptor antagonists, as well as chromatin remodelling. Overall, we identified novel sex-specific metabolites in MCI patients that could serve as biomarkers of MCI in both sexes, help further define AD etiology, and reveal new potential prevention strategies for AD.

Metabolic Derangement in Non-Alcoholic Fatty Liver Disease: Opportunities for Early Diagnostic and Prognostic Markers

Non-alcoholic fatty liver disease is a globally prevalent disorder that can rapidly progress if not detected early. Currently, no accepted markers exist for early diagnosis and prognosis of NAFLD. This review describes derangement in major metabolic pathways of lipid, carbohydrate, and amino acids in NAFLD. It suggests that measuring levels of thrombospondin, TyG index, asymmetric dimethylarginine, LAL-A, GLP-1, FGF-21, and GSG index are potential markers for early diagnosis of NAFLD. A single marker may not indicate early NAFLD, and further large-scale studies on correlating levels of Thrombospondin-2, triglyceride-glucose index, and FGF-21 with NAFLD are warranted.

Improved ion detection sensitivity in mass spectrometry imaging using tapping-mode scanning probe electrospray ionization to visualize localized lipids in mouse testes

Mass spectrometry imaging (MSI) is a promising analytical method to visualize the distribution of lipids in biological tissues. To clarify the relationship between cellular distribution and lipid types in a tissue, it is crucial to achieve both an improvement in ion detection sensitivity and a reduction in the ionization area. We report methods for improving the efficiency of ion transfer to a mass spectrometer and miniaturizing the extraction area of a sample for tapping-mode scanning probe electrospray ionization (t-SPESI), atmospheric pressure sampling, and ionization methods. To verify the efficacy of the new t-SPESI measurement system, MSI was performed on mouse testes with a pixel size of 5 µm. Lipid images of the testes from wild-type (WT) and lysophospholipid acyltransferase 3 (LPLAT3) knockout mice revealed the characteristic distribution of docosahexaenoic acid-containing phospholipids (DHA-PLs). A comparison of the ion images obtained by MSI and optical images of the same tissues stained with hematoxylin and eosin suggested that the distribution of DHA-PLs was significantly altered by spermatogenesis in the WT mouse testes.

Identification of serum biomarkers for cystic echinococcosis in sheep through untargeted metabolomic analysis using LC-MS/MS technology

BACKGROUND

Echinococcosis is a zoonotic disease caused by an Echinococcus tapeworm infection. While diagnostic methods for humans often rely on ultrasound imaging and immunodiagnostic techniques, diagnosis in intermediate hosts typically has no widely used diagnostic markers, hampering disease control efforts.

METHODS

The differences in serum metabolites of sheep infected with Echinococcus granulosus and a control group were analyzed using ultrahigh-performance liquid chromatography (UHPLC) separation with tandem mass spectrometry (MS/MS) detection. This provided a basis for the early diagnosis and pathogenetic study of cystic echinococcosis (CE) in intermediate hosts at the metabolomics level. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used to analyze different metabolites in the serum of the two groups. The differentially abundant metabolites were entered into the MetaboAnalyst 5.0 online analysis website for processing, and the top-15-ranked metabolic pathways were set to produce bubble plots and differential abundance score plots, with a significant difference of P < 0.05 and a false discovery rate (FDR) < 0.1 as the screening conditions.

RESULTS

Data analyses of serum samples from both groups identified a total of 1905 significantly different metabolites, where 841 metabolites were upregulated and 1064 metabolites were downregulated. Twelve metabolites were significantly upregulated and 21 metabolites were significantly downregulated in the experimental group. Then, the 1,7-dihydroxyxanthone, 2-methylbutyrylglycine, 3,3-dimethylglutaric acid, 5,12-dihydroxy-6,8,10,14,17-eicosapentaenoic acid, 9-hydroperoxy-10E,12Z,15Z-octadecatrienoic acid, and trimethylamine N-oxide 6 metabolites were selected as diagnostically valuable candidate biomarkers (area under the curve [AUC] > 0.7). These differential metabolites are involved in various metabolic pathways, including amino acid metabolites (arginine, L-isoleucine, L-valine) and fatty acid metabolism (fenugreek, arachidonic acid, linolenic acid). Compared with the control group, sheep in the CE group had increased serum levels of fenugreek acid, while all other metabolites such as glycine showed significantly reduced serum levels (P < 0.01).

CONCLUSIONS

Through non-targeted metabolomic analysis of the serum of CE-infected sheep, differential metabolites closely related to amino acid metabolism and the fatty acid metabolism pathway were identified. These differentially abundant metabolites can serve as biomarkers for diagnosing CE infection in intermediate sheep hosts.

Atmospheric Pressure Mass Spectrometry Imaging Using Electrospray-Assisted Laser Desorption/Ionization with Gas Transportation through a Heated Tube and Minimal Sample Preparation

Mass spectrometry (MS) is a valuable tool that enables label-free analysis and the ability to measure multiple molecules. The atmospheric pressure MS imaging (MSI) method usually requires tedious sample preparation. A simple ionization method with minimal sample preparation is needed for high-throughput analysis. We have developed an ion source that does not require sample preparation such as thinning, curing, planarization, or addition of matrix by the electrospray-assisted laser desorption/ionization with gas transportation (ELDI-GT). The sample is transported with nitrogen gas through a heated tube to the electrospray. The ion signal of protonated caffeine was measured under different transport conditions. The ion signal intensity was found to increase 11-fold by changing the flow rate and tube temperature from 2.8 cm3/s and 473 K to 25 cm3/s and 673 K. ELDI-GT was able to visualize the localization of caffeine crystals at a pixel size of 50 µm using MSI because of the effective GT using the heated tube. The dependence of the ion signal intensity was discussed on the amount of heat applied to the sample in the heated tube. ELDI-GT allowed accurate localization of caffeine at a pixel size of 50 µm without the need to apply thinning and matrix to a sample.

Metabolomics-Driven Biomarker Discovery for Breast Cancer Prognosis and Diagnosis

Breast cancer is a cancer with global prevalence and a surge in the number of cases with each passing year. With the advancement in science and technology, significant progress has been achieved in the prevention and treatment of breast cancer to make ends meet. The scientific intradisciplinary subject of "metabolomics" examines every metabolite found in a cell, tissue, system, or organism from different sources of samples. In the case of breast cancer, little is known about the regulatory pathways that could be resolved through metabolic reprogramming. Evidence related to the significant changes taking place during the onset and prognosis of breast cancer can be obtained using metabolomics. Innovative metabolomics approaches identify metabolites that lead to the discovery of biomarkers for breast cancer therapy, diagnosis, and early detection. The use of diverse analytical methods and instruments for metabolomics includes Magnetic Resonance Spectroscopy, LC/MS, UPLC/MS, etc., which, along with their high-throughput analysis, give insights into the metabolites and the molecular pathways involved. For instance, metabolome research has led to the discovery of the glutamate-to-glutamate ratio and aerobic glycolysis as biomarkers in breast cancer. The present review comprehends the updates in metabolomic research and its processes that contribute to breast cancer prognosis and metastasis. The metabolome holds a future, and this review is an attempt to amalgamate the present relevant literature that might yield crucial insights for creating innovative therapeutic strategies aimed at addressing metastatic breast cancer.

Mangiferin and EGCG Compounds Fight Against Hyperlipidemia by Promoting FFA Oxidation via AMPK/PPARα

Background: Hyperlipidemia is a critical risk factor for obesity, diabetes, cardiovascular diseases, and other chronic diseases. Our study was to determine the effects and mechanism of mangiferin (MF) and epigallocatechin gallate (EGCG) compounds on improving hyperlipidemia in HepG2 cells. Methods: HepG2 cells were treated with 0.25 mM palmitic acid (PA) and then incubated with MF (12.5, 25, and 50 μM) or EGCG (25, 50, and 100 μM) or MF:EGCG (0:0, 6.25:12.5, 25:50, and 50:100 μM:μM) for 24 h. The improvement of hyperlipidemia was verified by Oil Red O staining, changes in triglyceride (TG) and free fatty acid (FFA) levels, and the expression of lipid metabolizing proteins in western blotting. Results: MF (12.5, 25, and 50 μM) or EGCG (25, 50, and 100 μM) markedly lowered lipid accumulations by lipid index levels. Furthermore, we found that the optimum concentration of MF and EGCG compounds was 25:50 (μM:μM), which significantly reduced the FFA level, TG, and total cholesterol (TC) accumulations and increased FFA uptake in HepG2 cells, and the effect was better than that of single phytochemicals. The adenosine 5⁣'-monophosphate (AMP)-activated protein kinase (AMPK) protein and its downstream proteins sirtuin 1 (SIRT1), peroxisome proliferator-activated receptor α (PPARα), and those involved in fatty acid translocase (CD36) and carnitine palmitoyltransferase 1 (CPT1) were also markedly increased in HepG2 cells. The upregulation of protein expression was reversed when AMPK-specific inhibitor Compound C was added. Conclusions: MF and EGCG (25:50 μM) compounds protect against hyperlipidemia by promoting the FFA oxidation, alleviating TG and TC accumulations via the AMPK/PPARα pathway in PA-treated HepG2 cells.

Metabolomics at the cutting edge of risk prediction of MASLD

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major public health threat globally. Management of patients afflicted with MASLD and research in this domain are limited by the lack of robust well-established non-invasive biomarkers for diagnosis, prognostication, and monitoring. The circulating metabolome reflects both the systemic metabo-inflammatory milieu and changes in the liver in affected individuals. In this review we summarize the available literature on changes in the different components of the metabolome in MASLD with a focus on changes that are linked to the presence of underlying steatohepatitis, severity of disease activity, and fibrosis stage. We further summarize the existing literature around biomarker panels that are derived from interrogation of the metabolome. Their relevance to disease biology and utility in practice are also discussed. We further highlight potential direction for future studies particularly to ensure they are fit for purpose and suitable for widespread use.

Pentachlorophenol increases diabetes risk by damaging β-cell secretion and disrupting gut microbial-related amino acids and fatty acids biosynthesis

Pentachlorophenol (PCP), a ubiquitous environmental pollutant, has been reported as a possible contributor to diabetes. However, evidence for general population is scarce while related mechanisms are largely unknown. Using a representative population-based case-control study in Beijing (n = 1796), we found a positive association between PCP exposure and diabetes risk with the odds ratio reaching 1.68 (95 % confidence interval: 1.30 to 2.18). A further rat experiment revealed that low-dose PCP mimicking real-world human exposure can significantly impair glycemic homeostasis by inducing pancreatic β-cell dysfunction, with non-linear dose-response relationships. Subsequent multi-omics analysis suggested that low-dose PCP led to notable gut microbiota dysbiosis (especially the species from genus Prevotella, such as intermedia, dentalis, ruminicola, denticola, melaninogenica, and oris), decreased serum amino acids (L-phenylalanine, L-tyrosine, and L-tryptophan) and increased serum fatty acids (oleic and palmitic acid) in rats, while strong correlations were observed among alterations of gut microbes, serum metabolites and glycemic-related biomarkers (e.g., fasting blood glucose and insulin). Collectively, these results imply PCP may increase diabetes risk by disrupting gut microbial-related amino acids and fatty acids biosynthesis. This will help guide future in-depth studies on the roles of PCP in the development of human diabetes.

Landscapes of maternal and neonatal gut microbiome and plasma metabolome signatures and their interaction in gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is prevalent among pregnant individuals and is linked to increased risks for both mothers and fetuses. Although GDM is known to cause disruptions in gut microbiota and metabolites, their potential transmission to the fetus has not been fully explored. This study aimed to characterize the similarities in microbial and metabolic signatures between mothers with GDM and their neonates as well as the interactions between these signatures. This study included 89 maternal-neonate pairs (44 in the GDM group and 45 in the normoglycemic group). We utilized 16S rRNA gene sequencing and untargeted metabolomics to analyze the gut microbiota and plasma metabolomics of mothers and neonates. Integrative analyses were performed to elucidate the interactions between these omics. Distinct microbial and metabolic signatures were observed in GDM mothers and their neonates compared to those in the normoglycemic group. Fourteen genera showed similar alterations across both groups. Metabolites linked to glucose, lipid, and energy metabolism were differentially influenced in GDM, with similar trends observed in both mothers and neonates in the GDM group. Network analysis indicated significant associations between Qipengyuania and metabolites related to bile acid metabolism in mothers and newborns. Furthermore, we observed a significant correlation between several genera and metabolites and clinical phenotypes in normoglycemic mothers and newborns, but these correlations were disrupted in the GDM group. Our findings suggest that GDM consistently affects both the microbiota and metabolome in mothers and neonates, thus elucidating the mechanism underlying metabolic transmission across generations. These insights contribute to knowledge regarding the multiomics interactions in GDM and underscore the need to further investigate the prenatal environmental impacts on offspring metabolism.

The effect of curcumin supplementation on glycemic indices in adults: A meta-analysis of meta-analyses

Curcumin, an inherent polyphenolic compound, has the potential to influence glycemic indices. Nevertheless, the conclusions drawn from extant meta-analyses remain contentious. To determine the impact of curcumin supplementation on these indices, the current umbrella meta-analysis included existing systematic reviews and meta-analyses. A thorough systematic search was conducted using databases Embase, PubMed, WOS, Scopus, and the Cochrane Library to acquire peer-reviewed literature published before January 2024. The random-effects model was employed to conduct a meta-analysis. The present analysis incorporated a total of 22 meta-analytic studies. The findings of our study indicate that the administration of curcumin supplements leads to a significant decrease in fasting blood sugar levels (FBS) (ES: -1.63; 95 % CI: -2.36, -0.89, P<0.001; I2=88.4 %, P<0.001), homeostasis model assessment-estimated insulin resistance (HOMA-IR) (ES: -0.38; 95 % CI: -0.48, -0.28, P<0.001; I2=35.9 %, P=0.142), hemoglobin A1c (HbA1c) (ES: -0.44; 95 % CI: -0.67, -0.21, P<0.001; I2=65.0 %, P=0.014), and insulin (ES: -0.86; 95 % CI: -1.52, -0.21, P=0.010; I2=92.5 %, P<0.001). The results of this study suggest that the administration of curcumin supplements may be a beneficial intervention for enhancing glycemic indices.

Effects of carnosine and histidine-containing dipeptides on biomarkers of inflammation and oxidative stress: a systematic review and meta-analysis

CONTEXT

Carnosine and histidine-containing dipeptides (HCDs) are suggested to have anti-inflammatory and antioxidative benefits, but their effects on circulating adipokines and inflammatory and oxidative stress biomarkers remain unclear.

OBJECTIVES

The aim of the present systematic review and meta-analysis was to determine the impact of HCD supplementation on inflammatory and oxidative stress biomarkers.

DATA SOURCES

A systematic search was performed on Medline via Ovid, Scopus, Embase, ISI Web of Science, and the Cochrane Library databases from inception to 25 January 2023.

DATA EXTRACTION

Using relevant key words, trials investigating the effects of carnosine/HCD supplementation on markers of inflammation and oxidative stress, including C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), adiponectin, malondialdehyde (MDA), glutathione (GSH), superoxide dismutase (SOD), total antioxidant capacity (TAC), and catalase (CAT) were identified. Meta-analyses were conducted using random-effects models to calculate the weighted mean differences (WMDs) and 95% confidence intervals (CIs).

DATA ANALYSIS

A total of 9 trials comprising 350 participants were included in the present meta-analysis. Carnosine/HCD supplementation led to a significant reduction in CRP (WMD: -0.97 mg/L; 95% CI: -1.59, -0.36), TNF-α (WMD: -3.60 pg/mL; 95% CI: -7.03, -0.18), and MDA (WMD: -0.34 μmol/L; 95% CI: -0.56, -0.12) and an elevation in CAT (WMD: 4.48 U/mL; 95% CI: 2.43, 6.53) compared with placebo. In contrast, carnosine/HCD supplementation had no effect on IL-6, adiponectin, GSH, SOD, and TAC levels.

CONCLUSION

Carnosine/HCD supplementation may reduce inflammatory and oxidative stress biomarkers, and potentially modulate the cardiometabolic risks associated with chronic low-grade inflammation and lipid peroxidation.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration no. CRD42017075354.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Serum metabolic profile evidence for relationship between schizophrenia and depression: An untargeted metabolomics

Given the genetic and clinical overlap observed between schizophrenia and depression, the present study was to identify the similarities and differences in serum metabolic profiles between patients with schizophrenia and depression. Global metabolomics research methods based on UHPLC-QTOF-MS/MS were performed. A total of 113 and 118 differential metabolites were screened and identified in depression and schizophrenia groups, respectively, as compared to health control; among those, 94 differential metabolites were shared by both. Pathway analysis indicated arginine and proline metabolism, alanine, aspartate, and glutamate metabolism were two significant metabolic pathways both in depression and schizophrenia groups as compared with health control groups, respectively. Similarly, 77 differential metabolites were identified between depression and schizophrenia groups, in which, serum N-acetylglutamine and isovalerylglycine levels showed significant differences between patients with depression and schizophrenia with p values less than 0.001 and without significant outliers. Sphingolipid metabolism was identified as a significant metabolic pathway distinguishing between depression and schizophrenia groups based on pathway analysis. Conclusively, common alterations in arginine and proline metabolism, alanine, aspartate, and glutamate metabolism were observed in patients with schizophrenia and depression; whereas differences in serum N-acetylglutamine and isovalerylglycine levels as well as sphingolipid metabolism were discovered between the two categories of patients.

Identification of genes related to fatty acid metabolism in type 2 diabetes mellitus

Aim

Fatty acid metabolism is pivotal for lipid synthesis, cellular signaling, and maintaining cell membrane integrity. However, its diagnostic significance in type 2 diabetes mellitus (T2DM) remains unclear.

Materials and methods

Three datasets and fatty acid metabolism-related genes were retrieved. Differential expression analysis, WGCNA, machine learning algorithms, diagnostic analysis, and validation were employed to identify key feature genes. Functional analysis, ceRNA network construction, immune microenvironment assessment, and drug prediction were conducted to explore the underlying molecular mechanisms.

Results

Six feature genes were identified with strong diagnostic performance and were involved in processes such as ribosome function and fatty acid metabolism. Immune cells, including dendritic cells, eosinophils, and neutrophils, may play a role in the progression of T2DM. ceRNA and drug-target network analysis revealed potential interactions, such as RP11-miR-29a-YTHDF3 and BPA-MSANTD1. The expression patterns of the feature genes, except for YTHDF3, were consistently upregulated in T2DM, aligning with trends observed in the training set.

Conclusion

This study investigated the potential molecular mechanisms of six fatty acid metabolism-related genes in T2DM, offering valuable insights that may guide future research and therapeutic development.

Therapeutic Effects of Taurine and Histidine Supplementation in Retinal Diseases

Amino acids are basic building blocks of structural proteins and enzymes. They also act as signaling molecules and as fuel. They are characterized as essential if sufficient quantities must be supplied exogenously or as non-essential if they can be endogenously synthesized. Appropriate intake of amino acids not only prevents the development of metabolic diseases but also can reduce the progression of some disease states. Amino acids are strongly associated with retinal metabolism in physiology and pathology. Nonetheless, there is a lack of robust clinical studies supporting the benefits of amino acid supplementation in retinopathy. In this review, we summarize preclinical evidence concerning the potential of supplementing the amino acids taurine and histidine to provide protection against diabetic retinopathy, glaucoma, and age-related macular degeneration. We suggest further directions for studying amino acid-based therapeutic interventions for eye diseases.

Metabolomic Hallmarks of Obesity and Metabolic Dysfunction-Associated Steatotic Liver Disease

From a detailed review of 90 experimental and clinical metabolomic investigations of obesity and metabolic dysfunction-associated steatotic liver disease (MASLD), we have developed metabolomic hallmarks for both obesity and MASLD. Obesity studies were conducted in mice, rats, and humans, with consensus biomarker groups in plasma/serum being essential and nonessential amino acids, energy metabolites, gut microbiota metabolites, acylcarnitines and lysophosphatidylcholines (LPC), which formed the basis of the six metabolomic hallmarks of obesity. Additionally, mice and rats shared elevated cholesterol, humans and rats shared elevated fatty acids, and humans and mice shared elevated VLDL/LDL, bile acids and phosphatidylcholines (PC). MASLD metabolomic studies had been performed in mice, rats, hamsters, cows, geese, blunt snout breams, zebrafish, and humans, with the biomarker groups in agreement between experimental and clinical investigations being energy metabolites, essential and nonessential amino acids, fatty acids, and bile acids, which lay the foundation of the five metabolomic hallmarks of MASLD. Furthermore, the experimental group had higher LPC/PC and cholesteryl esters, and the clinical group had elevated acylcarnitines, lysophosphatidylethanolamines/phosphatidylethanolamines (LPE/PE), triglycerides/diglycerides, and gut microbiota metabolites. These metabolomic hallmarks aid in the understanding of the metabolic role played by obesity in MASLD development, inform mechanistic studies into underlying disease pathogenesis, and are critical for new metabolite-inspired therapies.

Polarity Gradient Solvent Confinement Membrane Cartridge to Broaden Metabolite Coverage of Plasma Untargeted Analysis

Various polarity chemicals exist in complex samples, such as plasma; nontargeted comprehensive analysis naturally requires multiple polar-extracted solvents; consequently, the polarity of the solvent plays a crucial role in the extraction efficiency of analytes from complex samples. In the present study, based on the diffusion behavior and nanoconfinement effect of solvents in the nanoconfined space, the polarity gradient solvent confinement liquid-phase nanoextraction (PGSC-NLPNE) protocol aimed to perform a one-step nontargeted analysis of a wide range of metabolites in plasma was established. The continuously wide range of extracted solvent polarities on carbon nanofibers/carbon fiber (CNFs/CF) membranes was achieved using a mixture of hexane, dichloromethane, methanol, and water as nanoconfined solvents. The polarities (Log P) of gradient solvents ranged from -1.38 to 3.94. Correlational analyses indicated that metabolites with Log P values ranging from -1.90 to 3.84 were closely related according to similarity-intermiscibility theory. Coupled with a homemade modified guard column device, CNFs/CF membrane cartridge (CCMC), a PGSC-NLPNE-UHPLC-MS online protocol was established and applied in plasma untargeted analysis. By comparing metabolome coverage, reproducibility, and extraction recovery with protein precipitation and two-step liquid-liquid extraction commonly used in untargeted analysis, the PGSC-NLPNE-CCMC protocol demonstrated higher reproducibility and recovery. This protocol has shown great potential for ultrafast analysis of plasma untargeted metabolomics with broader metabolome coverage. It could be a potential tool to rapidly screen out valuable biomarkers related to diseases in the clinic.

Metabolic changes associated with PFAS exposure in firefighters: A pilot study

This pilot study investigated the association between occupational exposure to per- and polyfluoroalkyl substances (PFASs) and metabolic profiles among two groups of aviation firefighters (n = 37), with an average of 6 and 31 years of working experience (here referred as junior and senior firefighters) at airports across Australia, with samples collected in 2013. PFAS levels in serum were determined in a previous study to be >17 times higher in the senior firefighter group, reflecting the difference in their occupational exposure to fluorosurfactants among the groups. The aim was to examine metabolic patterns across a broad range of PFAS exposure by comparing metabolic differences and their associations with PFAS levels. In this cross-sectional study, the length of firefighting experience and PFAS levels in serum were both further associated with changes in several classes of metabolites, including free fatty acids, bile acids, amino acids, lipids and metabolites related to gut microbial metabolism. The metabolites associated with the length of firefighting experience showed similarities with the metabolites associated with PFAS levels. A non-monotonic response to PFAS concentrations, particularly in saturated fatty acids, was also observed. In the junior firefighter group, the PFAS concentrations were positively associated with saturated fatty acids, i.e., the saturated fatty acid levels increased with increased PFAS levels. In the senior firefighter group, the trend was opposite, with saturated fatty acids decreasing with increasing levels of PFAS. Accounting for potential confounding factors such as BMI and age could not explain the results. While the study population was small, our results plausibly indicate that PFAS exposure can lead to a metabolic compensation strategy that is disrupted at high, long-term exposures. Our study also suggests that serum metabolites serve as better effect-based markers of the impact of exposure than the traditional clinical measurements alone, such as total triglycerides or total cholesterol.

Effect of Barley on Postprandial Blood Glucose Response and Appetite in Healthy Individuals: A Randomized, Double-Blind, Placebo-Controlled Trial

Background/Objectives: Barley dietary fiber (BDF), particularly β-glucan, has shown potential in modulating postprandial glycemic responses and improving metabolic health. This study aimed to assess the effects of Saechalssalbori (Hordeum vulgare L.), a glutinous barley variety rich in β-glucan, on postprandial blood glucose, insulin, glucagon, triglycerides, and appetite-related hormones in healthy adults. Methods: In this randomized, double-blind, placebo-controlled, crossover trial, healthy adults (n = 67) with fasting blood glucose levels below 126 mg/dL were assigned to consume either BDF or placebo (rice flour). Fasting and postprandial blood samples were collected at 30, 60, 120, and 180 min after consumption. Blood glucose, insulin, glucagon, triglycerides, and appetite-related hormones (ghrelin, PYY) were measured, and appetite was assessed using the visual analog scale (VAS). The study was approved by the Institutional Review Board (CHAMC 2022-08-040-007) and registered (KCT0009166). Results: BDF consumption significantly delayed the postprandial increase in blood glucose compared with placebo, reduced insulin secretion, and slightly increased glucagon and triglycerides. BDF also lowered hunger and increased satiety, with associated increases in ghrelin and PYY levels. Conclusions: BDF consumption, particularly from β-glucan-rich barley, may improve postprandial glycemic control and suppress appetite, making it a promising dietary intervention for managing metabolic conditions such as diabetes. Further studies are needed to explore its long-term impact on glycemic variability.

Serum metabolome profiling in patients with mild cognitive impairment reveals sex differences in lipid metabolism

Alzheimer's disease (AD) affects more women than men. Although women live longer than men, it is not longevity alone, but other factors, including metabolic changes, that contribute to the higher risk of AD in women. Metabolic pathways have been implicated in AD progression, but studies to date examined targeted pathways, leaving many metabolites unmeasured. Sex is often a neglected biological variable, and most metabolomic studies were not designed to investigate sex differences in metabolomic profiles. Here, we performed untargeted metabolomic profiling of sera from male and female patients with mild cognitive impairment (MCI), a common precursor to AD, and matched controls. We discovered significant metabolic changes in individuals with MCI, and found several pathways that were strongly associated with sex. Peptide energy metabolism demonstrated sexual dimorphism. Lipid pathways exhibited the strongest differences between female and male MCI patients, including specific phosphatidylcholine lipids, lysophospholipids, long-chain fatty acids, and monoacylglycerols. 1-palmitoleoyl glycerol and 1-arachidonoyl glycerol were higher in female MCI subjects than in male MCI subjects with no differences between control males and females. Conversely, specific dicarboxylic fatty acids were lower in female MCI subjects than male MCI subjects. In cultured astrocytes, 1-arachidonoyl glycerol promoted phosphorylation of the transcriptional regulator sphingosine kinase 2, which was inhibited by the transient receptor potential vanilloid 1 receptor antagonists, as well as chromatin remodelling. Overall, we identified novel sex-specific metabolites in MCI patients that could serve as biomarkers of MCI in both sexes, help further define AD etiology, and reveal new potential prevention strategies for AD.

Mechanisms by which obesity regulates inflammation and anti-tumor immunity in cancer

Obesity is associated with an increased risk for 13 different cancers. The increased risk for cancer in obesity is mediated by obesity-associated changes in the immune system. Obesity has distinct effects on different types of inflammation that are tied to tumorigenesis. For example, obesity promotes chronic inflammation in adipose tissue that is tumor-promoting in peripheral tissues. Conversely, obesity inhibits acute inflammation that rejects tumors. Obesity therefore promotes cancer by differentially regulating chronic versus acute inflammation. Given that obesity is chronic, the initial inflammation in adipose tissue will lead to systemic inflammation that could induce compensatory anti-inflammatory reactions in peripheral tissues to suppress chronic inflammation. The overall effect of obesity in peripheral tissues is therefore dependent on the duration and severity of obesity. Adipose tissue is a complex tissue that is composed of many cell types in addition to adipocytes. Further, adipose tissue cellularity is different at different anatomical sites throughout the body. Consequently, the sensitivity of adipose tissue to obesity is dependent on the anatomical location of the adipose depot. For example, obesity induces more inflammation in visceral than subcutaneous adipose tissue. Based on these studies, the mechanisms by which obesity promotes tumorigenesis are multifactorial and immune cell type-specific. The objective of our paper is to discuss the cellular mechanisms by which obesity promotes tumorigenesis by regulating distinct types of inflammation in adipose tissue and the tumor microenvironment.

Forever chemicals don't make hero mutant ninja turtles: Elevated PFAS levels linked to unusual scute development in newly emerged freshwater turtle hatchlings (Emydura macquarii macquarii) and a reduction in turtle populations

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants known to pose significant risks to human and wildlife health. Freshwater turtles (Emydura macquarii macquarii), as long-lived species inhabiting aquatic ecosystems, are particularly vulnerable to PFAS bioaccumulation. This study investigated the multifaceted impact of PFAS contamination on these turtles, focusing on metabolic disruptions, reproductive success, hatchling health, and population impacts. Comprehensive analyses, including proteomics, lipidomics, metabolomics, and histopathology, were conducted on turtles from PFAS-impacted, control, and reference sites. The findings reveal significant metabolic disruptions in PFAS-exposed turtles, with alterations in amino acid and lipid metabolism, energy production, and oxidative stress responses. Proteomic analysis identified several health biomarkers indicative of early disease progression. Despite high levels of PFAS in tissues and organs, no gross or histopathological phenotypical abnormalities were directly linked to PFAS exposure. Gravid females from contaminated sites exhibited altered egg composition, particularly in magnesium to calcium ratios, potentially affecting eggshell strength. Biochemical profiles of egg albumin and yolk indicated significant differences in metabolites and lipids between contaminated and reference sites, suggesting potential impacts on embryo development. Hatchling deformities were notably higher and with increased frequency in terms of the types of deformities at the PFAS-impacted sites, with common defects including abnormal intergular scale shapes and marginal scale counts. Furthermore, the demographic profile of the turtle population showed a lack of juvenile turtles at contaminated sites, indicating reduced recruitment and potential long-term population declines. This indicates a field-based demonstration of an Adverse Outcome Pathway, from elevated levels of PFAS in the turtles, to biochemical perturbations within the animals, and finally population effects. These findings underscore the urgent need for regulatory measures to address PFAS contamination and its detrimental effects on wildlife.