Prenatal EGCG consumption impacts hepatic glycogen synthesis and lipid metabolism in adult mice

In this study, the impact of prenatal exposure to Epigallocatechin gallate (EGCG) on the liver of adult offspring mice was investigated. While EGCG is known for its health benefits, its effects of prenatal exposure on the liver remain unclear. Pregnant C57BL/6 J mice were exposed to 1 mg/kg of EGCG for 16 days to assess hepatotoxicity effects of adult offspring. Transcriptomics and metabolomics were employed to elucidate the hepatotoxicity mechanisms. The findings revealed that prenatal EGCG exposure led to a decrease in liver somatic index, enhanced inflammatory responses and disrupted liver function through increased glycogen accumulation in adult mice. The integrated omics analysis revealed significant alterations in key pathways involved in liver glucose lipid metabolism, such as gluconeogenesis, dysregulation of insulin signaling, and induction of liver inflammation. Furthermore, the study found a negative correlation between the promoter methylation levels of Ppara and their mRNA levels, suggesting that EGCG could reduce hepatic lipid content through epigenetic modifications. The findings suggest that prenatal EGCG exposure can have detrimental impacts on the liver among adult individuals and emphasize the need for a comprehensive evaluation of the potential risks associated with EGCG consumption during pregnancy.

Non-electrophysiological techniques targeting transient receptor potential (TRP) gene of gastrointestinal tract

Transient receptor potential (TRP) channels are cation channels related to a wide range of physical and chemical stimuli, they are expressed all along the gastrointestinal system, and a myriad of diseases are often associated with aberrant expression or mutation of the TRP gene, suggesting that TRPs are promising targets for drug therapy. Therefore, a better understanding of the information of TRPs in health and disease could facilitate the development of effective drugs for the treatment of gastrointestinal diseases like IBD. But there are very few generalizations about the experimental techniques studied in this field. In view of the promise of TRP as a therapeutic target, we discuss experimental methods that can be used for TRPs including their distribution, function and interaction with other proteins, as well as some promising emerging technologies to provide experimental methods for future studies.

Ultra-high-throughput mass spectrometry in drug discovery: fundamentals and recent advances

INTRODUCTION

Ultra-high-throughput mass spectrometry, uHT-MS, is a technology that utilizes ionization and sample delivery technologies optimized to enable sampling from well plates at > 1 sample per second. These technologies do not need a chromatographic separation step and can be utilized in a wide variety of assays to detect a broad range of analytes including small molecules, lipids, and proteins.

AREAS COVERED

This manuscript provides a brief historical review of high-throughput mass spectrometry and the recently developed technologies that have enabled uHT-MS. The report also provides examples and references on how uHT-MS has been used in biochemical and chemical assays, nuisance compound profiling, protein analysis and high throughput experimentation for chemical synthesis.

EXPERT OPINION

The fast analysis time provided by uHT-MS is transforming how biochemical and chemical assays are performed in drug discovery. The potential to associate phenotypic responses produced by 1000's of compound treatments with changes in endogenous metabolite and lipid signals is becoming feasible. With the augmentation of simple, fast, high-throughput sample preparation, the scope of uHT-MS usage will increase. However, it likely will not supplant LC-MS for analyses that require low detection limits from complex matrices or characterization of complex biotherapeutics such as antibody-drug conjugates.

Loss of mitochondrial pyruvate carrier 1 supports proline-dependent proliferation and collagen biosynthesis in ovarian cancer

The pyruvate transporter MPC1 (mitochondrial pyruvate carrier 1) acts as a tumour-suppressor, loss of which correlates with a pro-tumorigenic phenotype and poor survival in several tumour types. In high-grade serous ovarian cancers (HGSOC), patients display copy number loss of MPC1 in around 78% of cases and reduced MPC1 mRNA expression. To explore the metabolic effect of reduced expression, we demonstrate that depleting MPC1 in HGSOC cell lines drives expression of key proline biosynthetic genes; PYCR1, PYCR2 and PYCR3, and biosynthesis of proline. We show that altered proline metabolism underpins cancer cell proliferation, reactive oxygen species (ROS) production, and type I and type VI collagen formation in ovarian cancer cells. Furthermore, exploring The Cancer Genome Atlas, we discovered the PYCR3 isozyme to be highly expressed in a third of HGSOC patients, which was associated with more aggressive disease and diagnosis at a younger age. Taken together, our study highlights that targeting proline metabolism is a potential therapeutic avenue for the treatment of HGSOC.

Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer

Gastric cancer (GC) represents a significant burden of cancer-related mortality worldwide, underscoring an urgent need for the development of early detection strategies and precise postoperative interventions. However, the identification of non-invasive biomarkers for early diagnosis and patient risk stratification remains underexplored. Here, we conduct a targeted metabolomics analysis of 702 plasma samples from multi-center participants to elucidate the GC metabolic reprogramming. Our machine learning analysis reveals a 10-metabolite GC diagnostic model, which is validated in an external test set with a sensitivity of 0.905, outperforming conventional methods leveraging cancer protein markers (sensitivity < 0.40). Additionally, our machine learning-derived prognostic model demonstrates superior performance to traditional models utilizing clinical parameters and effectively stratifies patients into different risk groups to guide precision interventions. Collectively, our findings reveal the metabolic landscape of GC and identify two distinct biomarker panels that enable early detection and prognosis prediction respectively, thus facilitating precision medicine in GC.

Untargeted metabolomics reveals potential health risks associated with chronic exposure to environmentally relevant concentrations of 2-Phenylphenol

Chronic exposure to endocrine-disrupting chemicals through foods of aquatic origin, at levels that are commonly found in the environment, can affect metabolic health and lead to metabolic diseases. One such chemical is 2-phenylphenol (2-PP), a suspected endocrine disruptor that is used extensively in agriculture and industry, and has become a widespread pollutant in aquatic environments. This study evaluated the risk of exposure to 2-PP through foods of aquatic origin from Vembanad Lake, using a Target Hazard Quotient (THQ) and an untargeted metabolomics approach. The study found that 2-PP content was higher in samples from areas with intense industrial, tourism, and agricultural activities. The average concentration of 2-PP in fish, crustaceans, and mollusks from the Vembanad estuary ranged from 0.012 to 0.017 mg/kg. The mean concentration of 2-PP was used to assess the THQ of exposure to the coastal population. The results showed that the THQ value was <1, indicating a low to moderate health risk for both adults and children. Furthermore, an untargeted metabolomics approach using HPLC-Q-Orbitrap MS was used to study the metabolome changes associated with chronic exposure to 2-PP (at the environmentally relevant concentration) over 60 days in the Wistar albino rat model. The findings indicated significant alterations in the phospholipid, fatty acid, sterol lipid, and amino acid profiles, suggesting that chronic exposure to 2-PP at environmentally relevant concentrations could affect purine, phenylalanine, tyrosine, and cholesterol metabolism.

Advances in free fatty acid profiles in gestational diabetes mellitus

The morbidity of gestational diabetes mellitus (GDM) is increasing and is associated with adverse perinatal outcomes and long-term maternal and infant health. The exact mechanism underlying changes in plasma free fatty acid (FFA) profiles in patients with GDM is unknown. However, it is believed that changes in diet and lipid metabolism may play a role. Fatty acids contain many specific FFAs, and the type of FFA has different impacts on physiological processes; hence, determining changes in FFAs in individual plasma is essential. Alterations in FFA concentration or profile may facilitate insulin resistance. Additionally, some FFAs show potential to predict GDM in early pregnancy and are strongly associated with the growth and development of the fetus and occurrence of macrosomia. Here, we aimed to review changes in FFAs in women with GDM and discuss the relationship of FFAs with GDM incidence and adverse outcomes.

Non-targeted metabolomics study for discovery of hepatocellular carcinoma serum diagnostic biomarker

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant cancers worldwide. Due to the asymptomatic features of HCC at early stages, patients are often diagnosed at advanced stages and missed effective treatment. Thus, there is an urgent need to identify sensitive and specific biomarkers for HCC early diagnosis. In the present study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) approach was used to profile serum metabolites from HCC patients, liver cirrhosis (LC) patients, and normal controls (NC). Univariate and multivariate statistical analyses were performed to obtain the metabolomic differences of the three groups and select significantly changed metabolites that can be used as diagnostic biomarkers. In total, 757 differential metabolites were quantified among the three groups, and pathway enrichment analysis of these metabolites indicated that glycerophospholipid metabolism, pentose and glucuronate interconversions, phenylalanine, tyrosine and tryptophan biosynthesis, and linoleic acid metabolism were the most altered pathways involved in HCC development. Receiver operating characteristic (ROC) curve analysis was performed to select and evaluate the diagnostic biomarker performance. Seven metabolites were identified as potential biomarkers that can differentiate HCC from LC and NC, and LC from NC with the good diagnostic performance of area under the curve (AUC) from 0.890 to 0.990. In summary, our findings provide highly effective biomarker candidates to differentiate HCC from LC and NC, LC, and NC, which shed insight into HCC pathological mechanisms and will be helpful in better understanding and managing HCC.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

Effects of maternal methyl donor intake during pregnancy on ileum methylation and function in an intrauterine growth restriction pig model

BACKGROUND

Intrauterine growth retardation (IUGR) affects intestinal growth, morphology, and function, which leads to poor growth performance and high mortality. The present study explored whether maternal dietary methyl donor (MET) supplementation alleviates IUGR and enhances offspring's growth performance by improving intestinal growth, function, and DNA methylation of the ileum in a porcine IUGR model.

METHODS

Forty multiparous sows were allocated to the control or MET diet groups from mating until delivery. After farrowing, 8 pairs of IUGR and normal birth weight piglets from 8 litters were selected for sampling before suckling colostrum.

RESULTS

The results showed that maternal MET supplementation tended to decrease the IUGR incidence and increased the average weaning weight of piglets. Moreover, maternal MET supplementation significantly reduced the plasma concentrations of isoleucine, cysteine, urea, and total amino acids in sows and newborn piglets. It also increased lactase and sucrase activity in the jejunum of newborn piglets. MET addition resulted in lower ileal methionine synthase activity and increased betaine homocysteine S-methyltransferase activity in the ileum of newborn piglets. DNA methylation analysis of the ileum showed that MET supplementation increased the methylation level of DNA CpG sites in the ileum of newborn piglets. Down-regulated differentially methylated genes were enriched in folic acid binding, insulin receptor signaling pathway, and endothelial cell proliferation. In contrast, up-regulated methylated genes were enriched in growth hormone receptor signaling pathway and nitric oxide biosynthetic process.

CONCLUSIONS

Maternal MET supplementation can reduce the incidence of IUGR and increase the weaning litter weight of piglets, which may be associated with better intestinal function and methylation status.

Triglyceride-glucose index is capable of identifying metabolically obese, normal-weight older individuals

BACKGROUND

The concept of metabolically obese, normal weight (MONW) has emerged to describe individuals with a normal body mass index (BMI) who are at a relatively high risk of chronic diseases. However, BMI itself is a suboptimal index for the assessment of the health risks associated with visceral fat. The triglyceride-glucose (TyG) index is considered to be a reliable and cost-effective marker of insulin resistance. Therefore, in the present study, we aimed to determine the TyG index cut-off values that could be used to define MONW in older people and to determine the usefulness of these values for the prediction of chronic diseases.

METHODS

A total of 4,721 participants in the Korea National Health and Nutritional Examination Survey who were ≥ 60 years of age and did not have underweight or obesity were included. MONW was defined using the criteria for metabolic syndrome (MS), and the TyG index was calculated on the basis of the fasting plasma triglyceride and glucose concentrations. Chronic diseases, including T2DM, hypertension, and non-alcoholic fatty liver disease (NAFLD), were diagnosed.

RESULTS

The prevalence of MS increased from the lowest to the highest TyG index tertile. The cut-off values of the TyG index for MONW were calculated as 8.88 and 8.80 for males and females, respectively. MONW, defined using these cut-off values, was associated with high odds ratios for NAFLD, T2DM, and hypertension in both males and females.

CONCLUSIONS

The TyG index cut-off values calculated in the present study can be used to discriminate individuals with MONW from other older individuals without obesity and to predict the risk of chronic diseases. These findings show that the TyG index is an effective and cost-efficient method of assessing the risk of chronic diseases in people with MONW.

The role of gut microbiota on obesity management: a review of the evidence

In the last 40 years, there has been a significant increase in the number of people who are overweight, obese and experience combined metabolic disorders. Gut microbiota has been shown to influence energy metabolism and is therefore a significant factor in the development of obesity. A person's diet, in particular, the nutritional value of that diet, is a crucial connection between gut microbiota composition and metabolism. This review explores the role of normal colonic microbiota and the gut environment. These mechanisms connect microbiota with obesity, the presence of gut microbiota in obese individuals and the impact of bioactive compounds in dairy products on gut microbiota. Research shows that gut microbiota play a crucial role in regulating energy metabolism and influencing the development of obesity. Changes in diet can alter the composition and levels of gut microbiota, and consuming bioactive components can help reshape the metabolic profile of obese individuals.

Maternal methyl donor supplementation: A potential therapy for metabolic disorder in offspring

The prevalences of diabetes mellitus and obesity are increasing yearly and has become a serious social burden. In addition to genetic factors, environmental factors in early life development are critical in influencing the prevalence of metabolic disorders in offspring. A growing body of evidence suggests the critical role of early methyl donor intervention in offspring health. Emerging studies have shown that methyl donors can influence offspring metabolism through epigenetic modifications and changing metabolism-related genes. In this review, we focus on the role of folic acid, betaine, vitamin B12, methionine, and choline in protecting against metabolic disorders in offspring. To address the current evidence on the potential role of maternal methyl donors, we summarize clinical studies as well as experimental animal models that support the impact of maternal methyl donors on offspring metabolism and discuss the mechanisms of action that may bring about these positive effects. Given the worldwide prevalence of metabolic disorders, these findings could be utilized in clinical practice, in which methyl donor supplementation in the early life years may reverse metabolic disorders in offspring and block the harmful intergenerational effect.

Urine biomarkers for Alzheimer's disease: A new opportunity for wastewater-based epidemiology?

While Alzheimer's disease (AD) diagnosis, management, and care have become priorities for healthcare providers and researcher's worldwide due to rapid population aging, epidemiologic surveillance efforts are currently limited by costly, invasive diagnostic procedures, particularly in low to middle income countries (LMIC). In recent years, wastewater-based epidemiology (WBE) has emerged as a promising tool for public health assessment through detection and quantification of specific biomarkers in wastewater, but applications for non-infectious diseases such as AD remain limited. This early review seeks to summarize AD-related biomarkers and urine and other peripheral biofluids and discuss their potential integration to WBE platforms to guide the first prospective efforts in the field. Promising results have been reported in clinical settings, indicating the potential of amyloid β, tau, neural thread protein, long non-coding RNAs, oxidative stress markers and other dysregulated metabolites for AD diagnosis, but questions regarding their concentration and stability in wastewater and the correlation between clinical levels and sewage circulation must be addressed in future studies before comprehensive WBE systems can be developed.

Vaspin: A Novel Biomarker Linking Gluteofemoral Body Fat and Type 2 Diabetes Risk

OBJECTIVE

To determine whether adiposity depots modulate vaspin levels and whether vaspin predicts type 2 diabetes (T2D) risk, through epidemiological and genetic analyses.

RESEARCH DESIGN AND METHODS

We assessed the relationship of plasma vaspin concentration with incident and prevalent T2D and adiposity-related variables in 1) the Prospective Urban and Rural Epidemiology (PURE) biomarker substudy (N = 10,052) and 2) the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial (N = 7,840), using regression models. We then assessed whether vaspin is causally associated with T2D and whether genetic variants associated with MRI-measured adiposity depots modulate vaspin levels, using two-sample Mendelian randomization (MR).

RESULTS

A 1-SD increase in circulating vaspin levels was associated with a 16% increase in incident T2D in the PURE cohort (hazard ratio 1.16; 95% CI 1.09-1.23; P = 4.26 × 10-7) and prevalent T2D in the ORIGIN cohort (odds ratio [OR] 1.16; 95% CI 1.07-1.25; P = 2.17 × 10-4). A 1-unit increase in BMI and triglyceride levels was associated with a 0.08-SD (95% CI 0.06-0.10; P = 2.04 × 10-15) and 0.06-SD (95% CI 0.04-0.08; P = 4.08 × 10-13) increase, respectively, in vaspin in the PURE group. Consistent associations were observed in the ORIGIN cohort. MR results reinforced the association between vaspin and BMI-adjusted T2D risk (OR 1.01 per 1-SD increase in vaspin level; 95% CI 1.00-1.02; P = 2.86 × 10-2) and showed that vaspin was increased by 0.10 SD per 1-SD decrease in genetically determined gluteofemoral adiposity (95% CI 0.02-0.18; P = 2.01 × 10-2). No relationships were found between subcutaneous or visceral adiposity and vaspin.

CONCLUSIONS

These findings support that higher vaspin levels are related to increased T2D risk and reduced gluteofemoral adiposity, positioning vaspin as a promising clinical predictor for T2D.

Comparing plasma and skin imprint metabolic profiles in COVID-19 diagnosis and severity assessment

As SARS-CoV-2 continues to produce new variants, the demand for diagnostics and a better understanding of COVID-19 remain key topics in healthcare. Skin manifestations have been widely reported in cases of COVID-19, but the mechanisms and markers of these symptoms are poorly described. In this cross-sectional study, 101 patients (64 COVID-19 positive patients and 37 controls) were enrolled between April and June 2020, during the first wave of COVID-19, in São Paulo, Brazil. Enrolled patients had skin imprints sampled non-invasively using silica plates; plasma samples were also collected. Samples were used for untargeted lipidomics/metabolomics through high-resolution mass spectrometry. We identified 558 molecular ions, with lipids comprising most of them. We found 245 plasma ions that were significant for COVID-19 diagnosis, compared to 61 from the skin imprints. Plasma samples outperformed skin imprints in distinguishing patients with COVID-19 from controls, with F1-scores of 91.9% and 84.3%, respectively. Skin imprints were excellent for assessing disease severity, exhibiting an F1-score of 93.5% when discriminating between patient hospitalization and home care statuses. Specifically, oleamide and linoleamide were the most discriminative biomarkers for identifying hospitalized patients through skin imprinting, and palmitic amides and N-acylethanolamine 18:0 were also identified as significant biomarkers. These observations underscore the importance of primary fatty acid amides and N-acylethanolamines in immunomodulatory processes and metabolic disorders. These findings confirm the potential utility of skin imprinting as a valuable non-invasive sampling method for COVID-19 screening; a method that may also be applied in the evaluation of other medical conditions. KEY MESSAGES: Skin imprints complement plasma in disease metabolomics. The annotated markers have a role in immunomodulation and metabolic diseases. Skin imprints outperformed plasma samples at assessing disease severity. Skin imprints have potential as non-invasive sampling strategy for COVID-19.

Pharmacological properties of mangiferin: bioavailability, mechanisms of action and clinical perspectives

This review aims to provide an in-depth analysis of the pharmacological properties of mangiferin, focusing primarily on its bioavailability and mechanisms of action, and its potential therapeutic applications, especially in the context of chronic diseases. We conducted a comprehensive examination of in vitro and in vivo studies, as well as clinical trials involving mangiferin or plant extracts containing mangiferin. The primary source of mangiferin is Mangifera indica, but it's also found in other plant species from the families Anacardiaceae, Gentianaceae, and Iridaceae. Mangiferin has exhibited a myriad of therapeutic properties, presenting itself as a promising candidate for treating various chronic conditions including neurodegenerative disorders, cardiovascular diseases, renal and pulmonary diseases, diabetes, and obesity. Despite the promising results showcased in many in vitro studies and certain animal studies, the application of mangiferin has been limited due to its poor solubility, absorption, and overall bioavailability. Mangiferin offers significant therapeutic potential in treating a spectrum of chronic diseases, as evidenced by both in vitro and clinical trials. However, the challenges concerning its bioavailability necessitate further research, particularly in optimizing its delivery and absorption, to harness its full medicinal potential. This review serves as a comprehensive update on the health-promoting and therapeutic activities of mangiferin.

Predictors of High Cardiovascular Risk Among Nonobese Patients with Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease in a Chinese Population

Purpose

This study aims to investigate cardiovascular risk factors in nonobese patients with type 2 diabetes (T2DM) and non-alcoholic fatty liver disease (NAFLD) and to determine whether they might be used to predict high-risk individuals effectively.

Patients and Methods

This cross-sectional study included 245 nonobese patients with T2DM who underwent FibroTouch in the National Metabolic Management Center of the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University from January 2021 to December 2022. All individuals were divided into NAFLD and non-NAFLD groups. Patients with NAFLD were further grouped by UAP tertiles (T1, T2 and T3). We created a Cardiovascular Score (total scale: 0-5 points; ≥3 points was defined as high-risk individual) based on baPWV, carotid ultrasound, and urinary microalbumin creatinine ratio (UA/CR) to assess the risk of cardiovascular disease in non-obese T2DM patients with NAFLD. Risk factors were evaluated using univariate and multivariate analysis. The performance of risk factors was compared according to the area under the receiver operating characteristic (ROC) curve.

Results

Atherogenic index of plasma (AIP), atherosclerosis index (AI), prevalence of hypertension, body mass index (BMI) and homeostatic model assessment of insulin resistance (HOMA-IR) were higher in the NAFLD group compared to the non-NAFLD group. In T3 group, AIP, AI, BMI and HOMA-IR were higher than those of T1 group. Multivariate logistic regression showed that age, systolic blood pressure, low-density lipoprotein-cholesterol (LDL-C) and AIP were risk factors for cardiovascular disease among nonobese patients with T2DM and NAFLD. The area under the ROC curve for age, systolic blood pressure, LDL-C and AIP were 0.705, 0.688, 0.738 and 0.642, respectively. The area under the ROC curve was 0.895 when combining them.

Conclusion

Age, systolic blood pressure, AIP and LDL-C are all independent risk factors for cardiovascular disease in non-obese individuals with T2DM and NAFLD, which can be combined to identify high-risk populations and carry out intervention.

Metabolomic Effects of Folic Acid Supplementation in Adults: Evidence from the FACT Trial

BACKGROUND

Folic acid (FA) is the oxidized form of folate found in supplements and FA-fortified foods. Most FA is reduced by dihydrofolate reductase to 5-methyltetrahydrofolate (5mTHF); the latter is the form of folate naturally found in foods. Ingestion of FA increases the plasma levels of both 5mTHF and unmetabolized FA (UMFA). Limited information is available on the downstream metabolic effects of FA supplementation, including potential effects associated with UMFA.

OBJECTIVE

We aimed to assess the metabolic effects of FA-supplementation, and the associations of plasma 5mTHF and UMFA with the metabolome in FA-naïve Bangladeshi adults.

METHODS

Sixty participants were selected from the Folic Acid and Creatine Trial; half received 800 μg FA/day for 12 weeks and half placebo. Plasma metabolome profiles were measured by high-resolution mass spectrometry, including 170 identified metabolites and 26,541 metabolic features. Penalized regression methods were used to assess the associations of targeted metabolites with FA-supplementation, plasma 5mTHF, and plasma UMFA. Pathway analyses were conducted using Mummichog.

RESULTS

In penalized models of identified metabolites, FA-supplementation was associated with higher choline. Changes in 5mTHF concentrations were positively associated with metabolites involved in amino acid metabolism (5-hydroxyindoleacetic acid, acetylmethionine, creatinine, guanidinoacetate, hydroxyproline/n-acetylalanine) and 2 fatty acids (docosahexaenoic acid and linoleic acid). Changes in 5mTHF concentrations were negatively associated with acetylglutamate, acetyllysine, carnitine, propionyl carnitine, cinnamic acid, homogentisate, arachidonic acid, and nicotine. UMFA concentrations were associated with lower levels of arachidonic acid. Together, metabolites selected across all models were related to lipids, aromatic amino acid metabolism, and the urea cycle. Analyses of nontargeted metabolic features identified additional pathways associated with FA supplementation.

CONCLUSION

In addition to the recapitulation of several expected metabolic changes associated with 5mTHF, we observed additional metabolites/pathways associated with FA-supplementation and UMFA. Further studies are needed to confirm these associations and assess their potential implications for human health.

TRIAL REGISTRATION NUMBER

This trial was registered at https://clinicaltrials.gov as NCT01050556.

Lactate levels in the brain and blood of schizophrenia patients: A systematic review and meta-analysis

BACKGROUND

The pathophysiological mechanisms of schizophrenia are still unclear. Converging evidence suggests that energy metabolism abnormalities are involved in schizophrenia, and support its role in the pathophysiology of this disease. Lactate plays an important role in energy metabolism. Many studies have reported changes in the levels of lactate in the brain and serum of schizophrenia patients; however, the results from these studies are not consistent. To overcome this limitation, the goal of the present meta-analysis is to analyze the changes in lactate levels in the brain and blood of schizophrenia patients.

METHODS

For this systematic review and meta-analysis, we performed a thorough search of relevant literature in the English language, using the MEDLINE, Cochrane, and Embase databases.

RESULTS

In the present meta-analysis, 20 studies were scrutinized, including 13 studies on brain lactate levels, which involved 322 schizophrenia patients and 324 healthy individuals as controls. 7 studies on blood lactate levels, involving 234 schizophrenia patients and 238 healthy individuals, were also included. Brain lactate levels were elevated in schizophrenia patients, both in vivo and in post-mortem studies. Nevertheless, blood lactate levels in schizophrenia patients have revealed no statistically significant difference, as compared with control individuals.

CONCLUSIONS

In comparison with healthy individuals, schizophrenia patients had higher lactate levels in the brain, rather than in the blood. These findings suggest independent regulatory mechanisms of lactate levels in the brain and peripheral tissues. Abnormal lactate metabolism in the brain may be an important pathological mechanism in schizophrenia.

Physicochemical, microbiological and metabolomics changes in yogurt supplemented with lactosucrose

Lactosucrose (LS) is a known prebiotic that has gained recognition for its low caloric content and various health benefits. However, its potential in food applications remains largely unexplored. In this study the effects of adding LS to milk at concentrations (0 %, 2 %, 5 % and 8 % w/v) for yogurt production, and the relevant changes in yogurt texture, microbial composition and metabolomics were investigated. Our findings revealed that LS played a role in promoting the formation of a structured gel during fermentation, resulting in increased elasticity and viscosity while reducing fluidity. Additionally incorporating high doses of LS into yogurt led to reduced post-acidification, enhanced survival of starter bacteria, improved water retention capacity and overall texture throughout a refrigerated storage period of 21 days. Notably higher concentrations of LS (8 % w/v) exhibited effects on enhancing yogurt quality. Furthermore, untargeted metabolomics analysis using UPLC Q TOF MS/MS revealed 45 differentially expressed metabolites, including up-regulated L-arginine, L-proline and L-glutamic acid along with the down-regulated glutathione, L-tyrosine, L-phenylalanyl and L-proline. These differential metabolites were primarily associated with amino acid metabolism such as thiamine metabolism, nicotinic acid salt and nicotinamide metabolism, and pyrimidine metabolism. As a result, the inclusion of LS in yogurt had an impact on the production of various beneficial metabolites in yogurt, highlighting the importance of combining prebiotic LS with probiotics to obtain desired physiological benefits of yogurt.

Multi-omics analysis reveals NNMT as a master metabolic regulator of metastasis in esophageal squamous cell carcinoma

Metabolic reprogramming has been observed in cancer metastasis, whereas metabolic changes required for malignant cells during lymph node metastasis of esophageal squamous cell carcinoma (ESCC) are still poorly understood. Here, we performed single-cell RNA sequencing (scRNA-seq) of paired ESCC tumor tissues and lymph nodes to uncover the reprogramming of tumor microenvironment (TME) and metabolic pathways. By integrating analyses of scRNA-seq data with metabolomics of ESCC tumor tissues and plasma samples, we found nicotinate and nicotinamide metabolism pathway was dysregulated in ESCC patients with lymph node metastasis (LN+), exhibiting as significantly increased 1-methylnicotinamide (MNA) in both tumors and plasma. Further data indicated high expression of N-methyltransferase (NNMT), which converts active methyl groups from the universal methyl donor, S-adenosylmethionine (SAM), to stable MNA, contributed to the increased MNA in LN+ ESCC. NNMT promotes epithelial-mesenchymal transition (EMT) and metastasis of ESCC in vitro and in vivo by inhibiting E-cadherin expression. Mechanically, high NNMT expression consumed too much active methyl group and decreased H3K4me3 modification at E-cadherin promoter and inhibited m6A modification of E-cadherin mRNA, therefore inhibiting E-cadherin expression at both transcriptional and post-transcriptional level. Finally, a detection method of lymph node metastasis was build based on the dysregulated metabolites, which showed good performance among ESCC patients. For lymph node metastasis of ESCC, this work supports NNMT is a master regulator of the cross-talk between cellular metabolism and epigenetic modifications, which may be a therapeutic target.

Triglycerides Mediate the Influence of Body Mass Index on Non-Alcoholic Fatty Liver Disease in a Non-Obese Chinese Population with Normal Low-Density Lipoprotein Cholesterol Levels

INTRODUCTION

Over 25% of the world's population has non-obese or lean non-alcoholic fatty liver disease (NAFLD), and the prevalence is higher than average in Asia. The present study focused on the relationship between body mass index (BMI) and non-obese NAFLD in non-overweight people in China, particularly the influence of triglycerides (TG) in the pathogenesis of non-obese NAFLD. The findings suggest new treatments for NAFLD patients with normal BMI, as well as provide an early warning system for the understanding and prevention of NAFLD in non-obese patients.

METHODS

This cross-sectional study enrolled 159,959 Chinese subjects with BMI <24 kg/m2 and normal levels of low-density lipoprotein cholesterol (LDL-c). The average age was 40.21 ± 13.88 years, and males accounted for 45.7%. A total of 15,907 (9.94%) patients with NAFLD were diagnosed by ultrasonography. Biochemical indicators were measured using an automated analyzer (Abbott AxSYM). The BMI (kg/m2) was calculated from the weight (kg)/height in square meters (m2). The BMI quartile was used as the column-stratified variable to determine the baseline distribution, and logistic regression analysis was used to assess the relationship between NAFLD and its risk factors, with multiple logistic regression used to assess the relationships between BMI or TG and NAFLD and multivariate linear regression used to analyze the association between BMI and TG, while mediation analysis was used to assess the mediation effect of TG.

RESULTS

After adjustment of all covariates, the odds ratios were 1.788 (95% CI: 1.749-1.829; p < 0.00001) and 1.491 (95% CI: 1.451-1.532; p < 0.00001) for the association between BMI and TG with NAFLD incidence. The multivariate linear regression coefficient of BMI and TG was β = 0.027 (95% CI: 0.023-0.030; p < 0.00001). Mediation analysis showed that BMI contributed to 10.81% of lean NAFLD with a mediation effect of 2.98%.

CONCLUSION

In a Chinese population with BMI <24 kg/m2 and normal LDL-c levels, BMI and TG were found to be independent predictors of NAFLD. The direct effect of BMI on non-obese NAFLD was 10.41%. The TG level was found to partially mediate the association.

Exploring the causal role of multiple metabolites on ovarian cancer: a two sample Mendelian randomization study

BACKGROUND

The mechanisms and risk factors underlying ovarian cancer (OC) remain under investigation, making the identification of new prognostic biomarkers and improved predictive factors critically important. Recently, circulating metabolites have shown potential in predicting survival outcomes and may be associated with the pathogenesis of OC. However, research into their genetic determinants is limited, and there are some inadequacies in understanding the distinct subtypes of OC. In this context, we conducted a Mendelian randomization study aiming to provide evidence for the relationship between genetically determined metabolites (GDMs) and the risk of OC and its subtypes.

METHODS

In this study, we consolidated genetic statistical data of GDMs with OC and its subtypes through a genome-wide association study (GWAS) and conducted a two-sample Mendelian randomization (MR) analysis. The inverse variance weighted (IVW) method served as the primary approach, with MR-Egger and weighted median methods employed for cross-validation to determine whether a causal relationship exists between the metabolites and OC risk. Moreover, a range of sensitivity analyses were conducted to validate the robustness of the results. MR-Egger intercept, and Cochran's Q statistical analysis were used to evaluate possible heterogeneity and pleiotropy. False discovery rate (FDR) correction was applied to validate the findings. We also conducted a reverse MR analysis to validate whether the observed blood metabolite levels were influenced by OC risk. Additionally, metabolic pathway analysis was carried out using the MetaboAnalyst 5.0 software.

RESULTS

In MR analysis, we discovered 18 suggestive causal associations involving 14 known metabolites, 8 metabolites as potential risk factors, and 6 as potential cancer risk reducers. In addition, three significant pathways, "caffeine metabolism," "arginine biosynthesis," and "citrate cycle (TCA cycle)" were associated with the development of mucinous ovarian cancer (MOC). The pathways "caffeine metabolism" and "alpha-linolenic acid metabolism" were associated with the onset of endometrioid ovarian cancer (OCED).

CONCLUSIONS

Our MR analysis revealed both protective and risk-associated metabolites, providing insights into the potential causal relationships between GDMs and the metabolic pathways related to OC and its subtypes. The metabolites that drive OC could be potential candidates for biomarkers.

Transient Elastography Is the Best-Performing Non-Invasive Test of Liver Fibrosis in Obese Asian Patients with Non-Alcoholic Fatty Liver Disease: A Pilot, Cross-Sectional Study

Background and Objectives: The prevalence of NAFLD (non-alcoholic fatty liver disease) is increasing, and up to 64% of Asian patients with NAFLD are obese. Non-invasive tests (NITs) for the assessment of liver fibrosis are increasingly being used, but data on their performance in obese Asian patients are lacking. In this pilot cross-sectional study, we aim to compare the distribution of serum and radiological markers of fibrosis between obese Asian biopsy-proven NAFLD patients with and without fibrosis and estimate the diagnostic accuracies of these indices. Materials and Methods: Obese Asian patients with NAFLD and who had undergone a liver biopsy showing histological evidence of NAFLD were invited to participate. Liver fibrosis was assessed using laboratory (APRI, AAR, BARD, FIB4, NFS, and Asia-Pacific NAFLD advanced fibrosis score) and imaging modalities (TE: transient elastography, MRE: magnetic resonance elastography, and SWU: shear wave ultrasonography). Results: A total of 16 patients were included in the final analysis. On liver biopsy, nine patients (56.3%) had significant fibrosis (F2 or higher), and six of these patients had advanced fibrosis (F3 or higher). F4 fibrosis was present in one patient (6.3%). For the laboratory markers, we found that the BARD score correctly identified five out of six patients with advanced fibrosis (83.4%, p value 0.045). Among all the NITs studied, liver stiffness measured by TE had the highest accuracy of 87.5% in its established threshold of 8.5 kPa for the detection of advanced fibrosis. MRE also performed well (81.2% in 3.64 kPa). Conclusions: In conclusion, TE has performed well in the detection of advanced fibrosis in obese Asian patients with biopsy-proven NAFLD in our pilot study. Further large-scale definitive studies are needed to validate the results of our findings.

Heterogeneously elevated branched-chain/aromatic amino acids among new-onset type-2 diabetes mellitus patients are potentially skewed diabetes predictors

BACKGROUND

The lack of specific predictors for type-2 diabetes mellitus (T2DM) severely impacts early intervention/prevention efforts. Elevated branched-chain amino acids (BCAAs: Isoleucine, leucine, valine) and aromatic amino acids (AAAs: Tyrosine, tryptophan, phenylalanine)) show high sensitivity and specificity in predicting diabetes in animals and predict T2DM 10-19 years before T2DM onset in clinical studies. However, improvement is needed to support its clinical utility.

AIM

To evaluate the effects of body mass index (BMI) and sex on BCAAs/AAAs in new-onset T2DM individuals with varying body weight.

METHODS

Ninety-seven new-onset T2DM patients (< 12 mo) differing in BMI [normal weight (NW), n = 33, BMI = 22.23 ± 1.60; overweight, n = 42, BMI = 25.9 ± 1.07; obesity (OB), n = 22, BMI = 31.23 ± 2.31] from the First People's Hospital of Yunnan Province, Kunming, China, were studied. One-way and 2-way ANOVAs were conducted to determine the effects of BMI and sex on BCAAs/AAAs.

RESULTS

Fasting serum AAAs, BCAAs, glutamate, and alanine were greater and high-density lipoprotein (HDL) was lower (P < 0.05, each) in OB-T2DM patients than in NW-T2DM patients, especially in male OB-T2DM patients. Arginine, histidine, leucine, methionine, and lysine were greater in male patients than in female patients. Moreover, histidine, alanine, glutamate, lysine, valine, methionine, leucine, isoleucine, tyrosine, phenylalanine, and tryptophan were significantly correlated with abdominal adiposity, body weight and BMI, whereas isoleucine, leucine and phenylalanine were negatively correlated with HDL.

CONCLUSION

Heterogeneously elevated amino acids, especially BCAAs/AAAs, across new-onset T2DM patients in differing BMI categories revealed a potentially skewed prediction of T2DM development. The higher BCAA/AAA levels in obese T2DM patients would support T2DM prediction in obese individuals, whereas the lower levels of BCAAs/AAAs in NW-T2DM individuals may underestimate T2DM risk in NW individuals. This potentially skewed T2DM prediction should be considered when BCAAs/AAAs are to be used as the T2DM predictor.

Gender-Specific Bile Acid Profiles in Non-Alcoholic Fatty Liver Disease

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is increasing worldwide. A main cause is the obesogenic, so-called Western lifestyle. NAFLD follows a long, unperceived course, and ends potentially fatally. Early diagnosis of aggressive subtypes saves lives. So far, non-invasive means of detection are limited. A better understanding of the pathogenic interplay among insulin resistance, immune inflammation, microbiome, and genetic background is important. Metabolomics may give insight into these interlaced processes.

METHODS

In this study, we measured bile acids (BA) in the plasma of adult NAFLD and alcohol-associated liver disease (ALD) patients and healthy controls with targeted mass spectrometry. We focused on gender-related bile acid production pathology in NAFLD and ALD.

RESULTS

Compared to healthy controls, women with NAFLD had significantly higher concentrations of total BA, total primary BA, total cholic (CA), total chenodeoxycholic (CDCA), total glycine-conjugated, and total non-12-a-OH BA. Concerning subtypes, glycocholic (GCA) and glycochenodeoxycholic (GCDCA), BA were elevated in women with NAFLD. In contrast, men with NAFLD had no significantly altered total BA fractions. However, the subtypes GCA, glycodeoxycholic (GDCA), glycolithocholic (GLCA), lithocholic (LCA), taurolithocholic (TLCA), and tauroursodeoxycholic acid (TUDCA) were elevated, while CA was significantly decreased. In NAFLD, except ursodeoxycholic acid (UDC), all total BA correlated significantly positively in both sexes with the ELF score, while in ALD, only males showed significant correlations exceptive for total UDC BA. In NAFLD, total BA, total primary BA, total secondary BA, total free secondary BA, total CA, total CDCA, total taurine conjugated, total glycine conjugated, total 12-a-OH, and total non-12-a-OH were significantly higher in cases of a high enhanced liver fibrosis (ELF) score above 9.8. In ALD, total UDC was additionally elevated. Between NAFLD with and without NASH, we found no significant differences.

CONCLUSION

Our data show gender-specific bile acid profiles in NAFLD and markedly different BA patterns in ALD. Women with NAFLD had more severe cholestasis. Men may better compensate fat storage-driven bile acid dynamics, indicated by higher levels of taurine-conjugated BA, which associate with beneficial metabolic functions.

Association of metabolic dysfunction with cognitive decline and Alzheimer's disease: A review of metabolomic evidence

The discovery of new biomarkers that can distinguish Alzheimer's disease (AD) from mild cognitive impairment (MCI) in the early stages will help to provide new diagnostic and therapeutic strategies and slow the transition from MCI to AD. Patients with AD may present with a concomitant metabolic disorder, such as diabetes, obesity, and dyslipidemia, as a risk factor for AD that may be involved in the onset of both AD pathology and cognitive impairment. Therefore, metabolite profiling, or metabolomics, can be very useful in diagnosing AD, developing new therapeutic targets, and evaluating both the course of treatment and the clinical course of the disease. In addition, studying the relationship between nutritional behavior and AD requires investigation of the role of conditions such as obesity, hypertension, dyslipidemia, and elevated glucose level. Based on this literature review, nutritional recommendations, including weight loss by reducing calorie and cholesterol intake and omega-3 fatty acid supplementation can prevent cognitive decline and dementia in the elderly. The underlying metabolic causes of the pathology and cognitive decline caused by AD and MCI are not well understood. In this review article, metabolomics biomarkers for diagnosis of AD and MCI and metabolic risk factors for cognitive decline in AD were evaluated.

Research Progress on the Effect and Mechanism of Tea Products with Different Fermentation Degrees in Regulating Type 2 Diabetes Mellitus

A popular non-alcoholic beverage worldwide, tea can regulate blood glucose levels, lipid levels, and blood pressure, and may even prevent type 2 diabetes mellitus (T2DM). Different tea fermentation levels impact these effects. Tea products with different fermentation degrees containing different functional ingredients can lower post-meal blood glucose levels and may prevent T2DM. There are seven critical factors that shed light on how teas with different fermentation levels affect blood glucose regulation in humans. These factors include the inhibition of digestive enzymes, enhancement of cellular glucose uptake, suppression of gluconeogenesis-related enzymes, reduction in the formation of advanced glycation end products (AGEs), inhibition of dipeptidyl peptidase-4 (DPP-4) activity, modulation of gut flora, and the alleviation of inflammation associated with oxidative stress. Fermented teas can be used to lower post-meal blood glucose levels and can help consumers make more informed tea selections.

Lysophosphatidylcholines are associated with P-tau181 levels in early stages of Alzheimer's Disease

Background

We profiled circulating plasma metabolites to identify systemic biochemical changes in clinical and biomarker-assisted diagnosis of Alzheimer's disease (AD).

Methods

We used an untargeted approach with liquid chromatography coupled to high-resolution mass spectrometry to measure small molecule plasma metabolites from 150 clinically diagnosed AD patients and 567 age-matched healthy elderly of Caribbean Hispanic ancestry. Plasma biomarkers of AD were measured including P-tau181, Aβ40, Aβ42, total-tau, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). Association of individual and co-abundant modules of metabolites were tested with clinical diagnosis of AD, as well as biologically-defined AD pathological process based on P-tau181 and other biomarker levels.

Results

Over 6000 metabolomic features were measured with high accuracy. First principal component (PC) of lysophosphatidylcholines (lysoPC) that bind to or interact with docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) and arachidonic acid (AHA) was associated with decreased risk of AD (OR = 0.91 [0.89-0.96], p = 2e-04). Association was restricted to individuals without an APOE ε4 allele (OR = 0.89 [0.84-0.94], p = 8.7e-05). Among individuals carrying at least one APOE ε4 allele, PC4 of lysoPCs moderately increased risk of AD (OR = 1.37 [1.16-1.6], p = 1e-04). Essential amino acids including tyrosine metabolism pathways were enriched among metabolites associated with P-tau181 levels and heparan and keratan sulfate degradation pathways were associated with Aβ42/Aβ40 ratio.

Conclusions

Unbiased metabolic profiling can identify critical metabolites and pathways associated with β-amyloid and phosphotau pathology. We also observed an APOE-ε4 dependent association of lysoPCs with AD and biologically based diagnostic criteria may aid in the identification of unique pathogenic mechanisms.

A Comprehensive Review on the Significance of Cysteine in Various Metabolic Disorders; Particularly CVD, Diabetes, Renal Dysfunction, and Ischemic Stroke

Metabolic disorders have long been a challenge for medical professionals and are a leading cause of mortality in adults. Diabetes, cardiovascular disorders (CVD), renal dysfunction, and ischemic stroke are the most prevalent ailments contributing to a high mortality rate worldwide. Reactive oxygen species are one of the leading factors that act as a fundamental root cause of metabolic syndrome. All of these disorders have their respective treatments, which, to some degree, sabotage the pathological worsening of the disease and an inevitable death. However, they pose a perilous health hazard to humankind. Cysteine, a functional amino acid shows promise for the prevention and treatment of metabolic disorders, such as CVD, Diabetes mellitus, renal dysfunction, and ischemic stroke. In this review, we explored whether cysteine can eradicate reactive oxygen species and subsequently prevent and treat these diseases.

Diagnosis of Esophageal Squamous Cell Carcinoma by High-Performance Serum Metabolic Fingerprints: A Retrospective Study

Esophageal squamous cell carcinoma (ESCC) is a highly prevalent and aggressive malignancy, and timely diagnosis of ESCC contributes to an increased cancer survival rate. However, current detection methods for ESCC mainly rely on endoscopic examination, limited by a relatively low participation rate. Herein, ferric-particle-enhanced laser desorption/ionization mass spectrometry (FPELDI MS) is utilized to record the serum metabolic fingerprints (SMFs) from a retrospective cohort (523 non-ESCC participants and 462 ESCC patients) to build diagnostic models toward ESCC. The PFELDI MS achieved high speed (≈30 s per sample), desirable reproducibility (coefficients of variation < 15%), and high throughput (985 samples with ≈124 200 data points for each spectrum). Desirable diagnostic performance with area-under-the-curves (AUCs) of 0.925-0.966 is obtained through machine learning of SMFs. Further, a metabolic biomarker panel is constructed, exhibiting superior diagnostic sensitivity (72.2-79.4%, p < 0.05) as compared with clinical protein biomarker tests (4.3-22.9%). Notably, the biomarker panel afforded an AUC of 0.844 (95% confidence interval [CI]: 0.806-0.880) toward early ESCC diagnosis. This work highlighted the potential of metabolic analysis for accurate screening and early detection of ESCC and offered insights into the metabolic characterization of diseases including but not limited to ESCC.

A Novel Score to Predict Individual Risk for Future Alzheimer's Disease: A Longitudinal Study of the ADNI Cohort

Background

Identifying high-risk individuals with mild cognitive impairment (MCI) who are likely to progress to Alzheimer's disease (AD) is crucial for early intervention.

Objective

This study aimed to develop and validate a novel clinical score for personalized estimation of MCI-to-AD conversion.

Methods

The data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study were analyzed. Two-thirds of the MCI patients were randomly assigned to a training cohort (n = 478), and the remaining one-third formed the validation cohort (n = 239). Multivariable logistic regression was performed to identify factors associated with MCI-to-AD progression within 4 years. A prediction score was developed based on the regression coefficients derived from the logistic model and tested in the validation cohort.

Results

A lipidomics-signature was obtained that showed a significant association with disease progression. The MCI conversion scoring system (ranged from 0 to 14 points), consisting of the lipidomics-signature and five other significant variables (Apolipoprotein ɛ4, Rey Auditory Verbal Learning Test immediate and delayed recall, Alzheimer's Disease Assessment Scale delayed recall test, Functional Activities Questionnaire, and cortical thickness of the AD signature), was constructed. Higher conversion scores were associated with a higher proportion of patients converting to AD. The scoring system demonstrated good discrimination and calibration in both the training cohort (AUC = 0.879, p of Hosmer-Lemeshow test = 0.597) and the validation cohort (AUC = 0.915, p of Hosmer-Lemeshow test = 0.991). The risk classification achieved excellent sensitivity (0.84) and specificity (0.75).

Conclusions

The MCI-to-AD conversion score is a reliable tool for predicting the risk of disease progression in individuals with MCI.

Targeted therapies of curcumin focus on its therapeutic benefits in cancers and human health: Molecular signaling pathway-based approaches and future perspectives

The curry powder spices turmeric (Curcuma longa L.), which contains curcumin (diferuloylmethane), an orange-yellow chemical. Polyphenols are the most commonly used sources of curcumin. It combats oxidative stress and inflammation in diseases, such as hyperlipidemia, metabolic syndrome, arthritis, and depression. Most of these benefits are due to their anti-inflammatory and antioxidant properties. Curcumin consumption leads to decreased bioavailability, resulting in limited absorption, quick metabolism, and quick excretion, which hinders health improvement. Numerous factors can increase its bioavailability. Piperine enhances bioavailability when combined with curcumin in a complex. When combined with other enhancing agents, curcumin has a wide spectrum of health benefits. This review evaluates the therapeutic potential of curcumin with a specific emphasis on its approach based on molecular signaling pathways. This study investigated its influence on the progression of cancer, inflammation, and many health-related mechanisms, such as cell proliferation, apoptosis, and metastasis. Curcumin has a significant potential for the prevention and treatment of various diseases. Curcumin modulates several biochemical pathways and targets involved in cancer growth. Despite its limited tissue accumulation and bioavailability when administered orally, curcumin has proven useful. This review provides an in-depth analysis of curcumin's therapeutic applications, its molecular signaling pathway-based approach, and its potential for precision medicine in cancer and human health.

Angiotensin-converting enzyme inhibitory peptide IVGFPAYGH protects against liver injury in mice fed a high‑sodium diet by inhibiting the RAS and remodeling gut microbial communities

Consuming a high‑sodium diet carries serious health risks and significantly influences the activation state of the renin-angiotensin system (RAS). This study evaluates the protective effect of angiotensin-converting enzyme (ACE) inhibitory peptide IVGFPAYGH on a high‑sodium diet-induced liver injury. IVGFPAYGH supplementation increased the activities of liver antioxidase and decreased the levels of liver inflammatory factor in mice fed a high‑sodium diet (8 % NaCl). IVGFPAYGH supplementation also reduced liver fatty acid synthesis and promoted fatty acid oxidation, increased the expression of low-density lipoprotein receptor, and improved liver dyslipidemia. Furthermore, IVGFPAYGH supplementation inhibited the activation of the liver RAS via inhibiting ACE activity and reducing angiotensin II levels in mice fed a high‑sodium diet. Moreover, IVGFPAYGH supplementation could alter the gut microbiota composition toward a normal gut microbiota composition and increase the abundance of the Lactobacillus genus. IVGFPAYGH supplementation also increased the expression levels of small intestinal tight junction protein and cecum short-chain fatty acids. Thus, IVGFPAYGH supplementation may maintain intestinal homeostasis and improve high‑sodium diet-induced liver injury by altering the gut microbiota composition and inhibiting the RAS. IVGFPAYGH is a promising functional ingredient for protecting liver damage caused by a high‑sodium diet.

A Metabolomics Analysis of a Novel Phenotype of Older Adults at Higher Risk of Dementia

Background

Older adults presenting with dual-decline in cognition and walking speed face a 6-fold higher risk for dementia compared with those showing no decline. We hypothesized that the metabolomics profile of dual-decliners would be unique even before they show signs of decline in cognition and gait speed.

Objective

The objective of this study was to determine if plasma metabolomics signatures can discriminate dual-decliners from no decliners, purely cognitive decliners, and purely motor decliners prior to decline.

Methods

A retrospective cross-sectional study using baseline plasma for untargeted metabolomics analyses to investigate early signals of later dual-decline status in study participants (n = 76) with convenient sampling. Dual-decline was operationalized as decline in gait speed (>10 cm/s) and cognition (>2 points decline in Montreal Cognitive Assessment score) on at least two consecutive 6-monthly assessments. The participants' decliner status was evaluated 3 years after the blood sample was collected. Pair-wise comparison of detected compounds was completed using principal components and hierarchical clustering analyses.

Results

Analyses did not detect any cluster separation in untargeted metabolomes across baseline groups. However, follow-up analyses of specific molecules detected 4 compounds (17-Hydroxy-12-(hydroxymethyl)-10-oxo-8 oxapentacyclomethyl hexopyranoside, Fleroxacin, Oleic acid, and 5xi-11,12-Dihydroxyabieta-8(14),9(11),12-trien-20-oic acid) were at significantly higher concentration among the dual-decliners compared to non-decliners. The pure cognitive decliner group had significantly lower concentration of six compounds (1,3-nonanediol acetate, 4-(2-carboxyethyl)-2-methoxyphenyl beta-D-glucopyranosiduronic acid, oleic acid, 2E-3-[4-(sulfo-oxy)phenyl] acrylic acid, palmitelaidic acid, and myristoleic acid) compared to the non-decliner group.

Conclusions

The unique metabolomics profile of dual-decliners warrants follow-up metabolomics analysis. Results may point to modifiable pathways.

A Mechanistic Review on Therapeutic Potential of Medicinal Plants and their Pharmacologically Active Molecules for Targeting Metabolic Syndrome

Metabolic syndrome (MetS) therapy with phytochemicals is an emerging field of study with therapeutic potential. Obesity, insulin resistance, high blood pressure, and abnormal lipid profiles are all components of metabolic syndrome, which is a major public health concern across the world. New research highlights the promise of phytochemicals found in foods, including fruits, vegetables, herbs, and spices, as a sustainable and innovative method of treating this illness. Anti-inflammatory, antioxidant, and insulin-sensitizing qualities are just a few of the many positive impacts shown by bioactive substances. Collectively, they alleviate the hallmark symptoms of metabolic syndrome by modulating critical metabolic pathways, boosting insulin sensitivity, decreasing oxidative stress, and calming chronic low-grade inflammation. In addition, phytochemicals provide a multimodal strategy by targeting not only adipose tissue but also the liver, skeletal muscle, and vascular endothelium, all of which have a role in the pathogenesis of MetS. Increasing evidence suggests that these natural chemicals may be useful in controlling metabolic syndrome as a complementary treatment to standard medication or lifestyle changes. This review article emphasizes the therapeutic potential of phytochemicals, illuminating their varied modes of action and their ability to alleviate the interconnected causes of metabolic syndrome. Phytochemical-based interventions show promise as a novel and sustainable approach to combating the rising global burden of metabolic syndrome, with the ultimate goal of bettering public health and quality of life.

Oral histidine affects gut microbiota and MAIT cells improving glycemic control in type 2 diabetes patients

Amino acids, metabolized by host cells as well as commensal gut bacteria, have signaling effects on host metabolism. Oral supplementation of the essential amino acid histidine has been shown to exert metabolic benefits. To investigate whether dietary histidine aids glycemic control, we performed a case-controlled parallel clinical intervention study in participants with type 2 diabetes (T2D) and healthy controls. Participants received oral histidine for seven weeks. After 2 weeks of histidine supplementation, the microbiome was depleted by antibiotics to determine the microbial contribution to histidine metabolism. We assessed glycemic control, immunophenotyping of peripheral blood mononucelar cells (PBMC), DNA methylation of PBMCs and fecal gut microbiota composition. Histidine improves several markers of glycemic control, including postprandial glucose levels with a concordant increase in the proportion of MAIT cells after two weeks of histidine supplementation. The increase in MAIT cells was associated with changes in gut microbial pathways such as riboflavin biosynthesis and epigenetic changes in the amino acid transporter SLC7A5. Associations between the microbiome and MAIT cells were replicated in the MetaCardis cohort. We propose a conceptual framework for how oral histidine may affect MAIT cells via altered gut microbiota composition and SLC7A5 expression in MAIT cells directly and thereby influencing glycemic control. Future studies should focus on the role of flavin biosynthesis intermediates and SLC7A5 modulation in MAIT cells to modulate glycemic control.

The Beneficial Effects of Curcumin on Lipids: Possible Effects on Dyslipidemia-induced Cardiovascular Complications

Dyslipidemia and altered lipid metabolism are closely involved in the pathogenesis and clinical manifestation of many metabolic and non-metabolic diseases. Therefore, mitigation of pharmacological and nutritional factors together with lifestyle modifications is paramount. One potential nutraceutical exhibiting cell signaling and lipid-modulating properties implicated in dyslipidemias is curcumin. Specifically, recent evidence suggest that curcumin may improve lipid metabolism and prevent dyslipidemia-induced cardiovascular complications via several pathways. Although the exact molecular mechanisms involved are not well understood, the evidence presented in this review suggests that curcumin can provide significant lipid benefits via modulation of adipogenesis and lipolysis, and prevention or reduction of lipid peroxidation and lipotoxicity via different molecular pathways. Curcumin can also improve the lipid profile and reduce dyslipidemia- dependent cardiovascular problems by impacting important mechanisms of fatty acid oxidation, lipid absorption, and cholesterol metabolism. Although only limited direct supporting evidence is available, in this review we assess the available knowledge regarding the possible nutraceutical effects of curcumin on lipid homeostasis and its possible impacts on dyslipidemic cardiovascular events from a mechanistic viewpoint.

Metabolic profiling of Alzheimer's disease: Untargeted metabolomics analysis of plasma samples

Alzheimer's disease (AD) is often not recognized or is diagnosed very late, which significantly reduces the effectiveness of available pharmacological treatments. Metabolomic analyzes have great potential for improving existing knowledge about the pathogenesis and etiology of AD and represent a novel approach towards discovering biomarkers that could be used for diagnosis, prognosis, and therapy monitoring. In this study, we applied the untargeted metabolomic approach to investigate the changes in biochemical pathways related to AD pathology. We used gas chromatography and liquid chromatography coupled to mass spectrometry (GC-MS and LC-MS, respectively) to identify metabolites whose levels have changed in subjects with AD diagnosis (N = 40) compared to healthy controls (N = 40) and individuals with mild cognitive impairment (MCI, N = 40). The GC-MS identified significant differences between groups in levels of metabolites belonging to the classes of benzene and substituted derivatives, carboxylic acids and derivatives, fatty acyls, hydroxy acids and derivatives, keto acids and derivatives, and organooxygen compounds. Most of the compounds identified by the LC-MS were various fatty acyls, glycerolipids and glycerophospholipids. All of these compounds were decreased in AD patients and in subjects with MCI compared to healthy controls. The results of the study indicate disturbed metabolism of lipids and amino acids and an imbalance of metabolites involved in energy metabolism in individuals diagnosed with AD, compared to healthy controls and MCI subjects.

Serum Metabolomics of Retinoblastoma: Assessing the Differential Serum Metabolic Signatures of Unilateral and Bilateral Patients

Retinoblastoma (Rb) is the most common pediatric eye cancer. To identify the biomarkers for early diagnosis and monitoring the progression of Rb in patients, mapping of the alterations in their metabolic profiles is essential. The present study aims at exploring the metabolic disparity in serum from Rb patients and controls using NMR-based metabolomics. A total of 72 metabolites, including carbohydrates, amino acids, and organic acids, were quantified in serum samples from 24 Rb patients and 26 controls. Distinct clusters of Rb patients and controls were obtained using the partial least-squares discriminant analysis (PLS-DA) model. Further, univariate and multivariate analyses of unilateral and bilateral Rb patients with respect to their age-matched controls depicted their distinct metabolic fingerprints. Metabolites including 2-phosphoglycerate, 4-aminobutyrate, proline, O-phosphocholine, O-phosphoethanolamine, and Sn-glycero-3-phosphocholine (Sn-GPC) showed significant perturbation in both unilateral and bilateral Rb patients. However, metabolic differences among the bilateral Rb cases were more pronounced than those in unilateral Rb cases with respect to controls. In addition to major discriminatory metabolites for Rb, unilateral and bilateral Rb cases showed specific metabolic changes, which might be the result of their differential genetic/somatic mutational backgrounds. This further suggests that the aberrant metabolic perturbation in bilateral patients signifies the severity of the disease in Rb patients. The present study demonstrated that identified serum metabolites have potential to serve as a noninvasive method for detection of Rb, discriminate bilateral from unilateral Rb patients, and aid in better understanding of the RB tumor biology.

Potential therapeutic implications of histidine catabolism by the gut microbiota in NAFLD patients with morbid obesity

The gut microbiota contributes to the pathophysiology of non-alcoholic fatty liver disease (NAFLD). Histidine is a key energy source for the microbiota, scavenging it from the host. Its role in NAFLD is poorly known. Plasma metabolomics, liver transcriptomics, and fecal metagenomics were performed in three human cohorts coupled with hepatocyte, rodent, and Drosophila models. Machine learning analyses identified plasma histidine as being strongly inversely associated with steatosis and linked to a hepatic transcriptomic signature involved in insulin signaling, inflammation, and trace amine-associated receptor 1. Circulating histidine was inversely associated with Proteobacteria and positively with bacteria lacking the histidine utilization (Hut) system. Histidine supplementation improved NAFLD in different animal models (diet-induced NAFLD in mouse and flies, ob/ob mouse, and ovariectomized rats) and reduced de novo lipogenesis. Fecal microbiota transplantation (FMT) from low-histidine donors and mono-colonization of germ-free flies with Enterobacter cloacae increased triglyceride accumulation and reduced histidine content. The interplay among microbiota, histidine catabolism, and NAFLD opens therapeutic opportunities.

Untargeted serum metabolomics reveals potential biomarkers and metabolic pathways associated with the progression of gastroesophageal cancer

BACKGROUND

Previous metabolic studies in upper digestive cancer have mostly been limited to cross-sectional study designs, which hinders the ability to effectively predict outcomes in the early stage of cancer. This study aims to identify key metabolites and metabolic pathways associated with the multistage progression of epithelial cancer and to explore their predictive value for gastroesophageal cancer (GEC) formation and for the early screening of esophageal squamous cell carcinoma (ESCC).

METHODS

A case-cohort study within the 7-year prospective Esophageal Cancer Screening Cohort of Shandong Province included 77 GEC cases and 77 sub-cohort individuals. Untargeted metabolic analysis was performed in serum samples. Metabolites, with FDR q value < 0.05 and variable importance in projection (VIP) > 1, were selected as differential metabolites to predict GEC formation using Random Forest (RF) models. Subsequently, we evaluated the predictive performance of these differential metabolites for the early screening of ESCC.

RESULTS

We found a distinct metabolic profile alteration in GEC cases compared to the sub-cohort, and identified eight differential metabolites. Pathway analyses showed dysregulation in D-glutamine and D-glutamate metabolism, nitrogen metabolism, primary bile acid biosynthesis, and steroid hormone biosynthesis in GEC patients. A panel of eight differential metabolites showed good predictive performance for GEC formation, with an area under the receiver operating characteristic curve (AUC) of 0.893 (95% CI = 0.816-0.951). Furthermore, four of the GEC pathological progression-related metabolites were validated in the early screening of ESCC, with an AUC of 0.761 (95% CI = 0.716-0.805).

CONCLUSIONS

These findings indicated a panel of metabolites might be an alternative approach to predict GEC formation, and therefore have the potential to mitigate the risk of cancer progression at the early stage of GEC.

A multi-omics approach to understand the influence of polyphenols in ovarian cancer for precision nutrition: a mini-review

The impact of polyphenols in ovarian cancer is widely studied observing gene expression, epigenetic alterations, and molecular mechanisms based on new 'omics' technologies. Therefore, the combination of omics technologies with the use of phenolic compounds may represent a promising approach to precision nutrition in cancer. This article provides an updated review involving the current applications of high-throughput technologies in ovarian cancer, the role of dietary polyphenols and their mechanistic effects in ovarian cancer, and the current status and challenges of precision nutrition and their relationship with big data. High-throughput technologies in different omics science can provide relevant information from different facets for identifying biomarkers for diagnosis, prognosis, and selection of specific therapies for personalized treatment. Furthermore, the field of omics sciences can provide a better understanding of the role of polyphenols and their function as signaling molecules in the prevention and treatment of ovarian cancer. Although we observed an increase in the number of investigations, there are several approaches to data acquisition, analysis, and integration that still need to be improved, and the standardization of these practices still needs to be implemented in clinical trials.

Vitamin B and One-Carbon Metabolite Profiles Show Divergent Associations with Cardiometabolic Risk Markers but not Cognitive Function in Older New Zealand Adults: A Secondary Analysis of the REACH Study

BACKGROUND

Vitamin B inadequacies and elevated homocysteine status have been associated with impaired cognitive and cardiometabolic health with aging. There is, however, a scarcity of research investigating integrated profiles of one-carbon (1C) metabolites in this context, including metabolites of interconnected folate, methionine, choline oxidation, and transsulfuration pathways.

OBJECTIVES

The study aimed to examine associations between vitamins B and 1C metabolites with cardiometabolic health and cognitive function in healthy older adults, including the interactive effects of Apolipoprotein E-ε4 status.

METHODS

Three hundred and thirteen healthy participants (65-74 y, 65% female) were analyzed. Vitamins B were estimated according to dietary intake (4-d food records) and biochemical status (serum folate and vitamin B12). Fasting plasma 1C metabolites were quantified by liquid chromatography with tandem mass spectrometry. Measures of cardiometabolic health included biochemical (lipid panel, blood glucose) and anthropometric markers. Cognitive function was assessed by the Computerized Mental Performance Assessment System (COMPASS) and Montreal Cognitive Assessment (MoCA). Associations were analyzed using multivariate linear (COMPASS, cardiometabolic health) and Poisson (MoCA) regression modeling.

RESULTS

Over 90% of participants met dietary recommendations for riboflavin and vitamins B6 and B12, but only 78% of males and 67% of females achieved adequate folate intakes. Higher serum folate and plasma betaine and glycine concentrations were associated with favorable cardiometabolic markers, whereas higher plasma choline and homocysteine concentrations were associated with greater cardiometabolic risk based on body mass index and serum lipids concentration values (P< 0.05). Vitamins B and homocysteine were not associated with cognitive performance in this cohort, though higher glycine concentrations were associated with better global cognitive performance (P = 0.017), episodic memory (P = 0.016), and spatial memory (P = 0.027) scores. Apolipoprotein E-ε4 status did not modify the relationship between vitamins B or 1C metabolites with cognitive function in linear regression analyses.

CONCLUSIONS

Vitamin B and 1C metabolite profiles showed divergent associations with cardiometabolic risk markers and limited associations with cognitive performance in this cohort of healthy older adults.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Correlation of plasma adipokines with endometrial atypical hyperplasia and type I/II endometrial cancer

The aim of the study was to systematically explore the relationships between various adipokines and risks of endometrial atypical hyperplasia (EAH), type I endometrial cancer (EC), and type II EC. We enrolled 219 patients in this study, including 39 EAH, 87 type I EC, 38 type II EC and 55 control individuals. We subsequently explored the association of adipokine levels and the leptin-to-adiponectin (L/A) ratio with EAH, type I EC, and type II EC. The plasma leptin level and L/A ratio were significantly higher in the EAH group than in the control group (p = 0.012). Leptin, resistin, vaspin, and visfatin levels were significantly higher in the type I EC group; however, the adiponectin level was lower in the type I EC, which resulted in a higher L/A ratio. Notably, the L/A ratio and visfatin level in the type II EC group were significantly higher. Multiple logistic regression analysis revealed that a higher leptin level was significantly associated with a higher EAH risk (p = 0.012). Higher leptin level (p = 0.042) and L/A ratio (p = 0.027) were significantly associated with an increased type I EC risk. By contrast, higher leptin (p = 0.059) and visfatin (p = 0.003) levels, higher L/A ratio (p = 0.033), and lower adiponectin level (p = 0.042) were associated with an increased type II EC risk. We suggested that adipokines are potentially correlated with EAH and EC risks.

Association between type 2 diabetes and branched chain amino acids (BCAA); a case-control study

Background

Several amino acids and their derivatives have been implicated in insulin resistance (IR) and Type 2 Diabetes Mellitus (T2DM). This research sought to establish a relationship between the dietary levels of branched-chain amino acids (BCAA) and the risk of T2DM.

Methods

This case-control study was carried out on 4200 participants consisting of 589 people with T2DM and 3611 non-diabetic aged 35 to 70 years residents in Sabzevar, Iran. Data on the economic-social, employment status, medical history, lifestyle, and sleep habits were collected via interview. The food frequency questionnaire (FFQ) was used to check the nutritional status. Participants' dietary BCAA consumption was estimated using Nutritionist IV software.

Results

A significant negative association between the incidence of T2DM and the dietary levels of BCAAs after adjustment for age and sex (OR = 0.972, CI 95%:0.648-0.996, P = 0.022). The negative association remained significant after additional adjustments for body mass index (BMI) and physical activity (OR = 0.967, CI 95%: 0.943-0.992, P = 0.010). Interestingly, a positive association was found between T2DM and total BCAAs (OR = 1.067, CI 95%: 1.017-1.119, P = 0.008), Isoleucine (OR = 1.248, CI 95%: 1.043-1.494, P = 0.016), Leucine (OR = 1.165, CI 95%: 1.046-1.299, P = 0.006) and Valine (OR = 1.274, CI 95%: 1.088-1.492, P = 0.003) after further adjustment for calorie intake.

Conclusions

Our results demonstrate branched-chain amino acids (BCAAs) including isoleucine, leucine, and valine are negatively associated with the incidence of type 2 diabetes (T2DM) after adjusting for age and sex, BMI, and physical activity. However, adjusting for calorie intake reversed the association between T2DM and BCAAs. These findings suggest that the association between BCAAs and T2DM may be influenced by calorie intake. Future longitudinal studies are warranted.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01247-9.

Revealing the mechanism of quinoa on type 2 diabetes based on intestinal flora and taste pathways

To investigate the antidiabetic effects and mechanisms of quinoa on type 2 diabetes mellitus (T2DM) mice model. In this context, we induced the T2DM mice model with a high-fat diet (HFD) combined with streptozotocin (STZ), followed by treatment with a quinoa diet. To explore the impact of quinoa on the intestinal flora, we predicted and validated its potential mechanism of hypoglycemic effect through network pharmacology, molecular docking, western blot, and immunohistochemistry (IHC). We found that quinoa could significantly improve abnormal glucolipid metabolism in T2DM mice. Further analysis showed that quinoa contributed to the improvement of gut microbiota composition positively. Moreover, it could downregulate the expression of TAS1R3 and TRPM5 in the colon. A total of 72 active components were identified by network pharmacology. Among them, TAS1R3 and TRPM5 were successfully docked with the core components of quinoa. These findings confirm that quinoa may exert hypoglycemic effects through gut microbiota and the TAS1R3/TRPM5 taste signaling pathway.