Metabolomics of Benzene Exposure and Development of Biomarkers for Exposure Hazard Assessment.

Benzene, a common industrial solvent, poses significant health risks including poisoning and hematopoietic diseases. However, its precise toxicity mechanisms remain unclear. To assess the health impact of prolonged benzene exposure through metabolomic analyses of exposed workers and benzene-poisoned mice, aiming to identify biomarkers and minimize occupational hazards. This study compared 18 benzene-exposed workers with 18 non-exposed workers, matching for age, lifestyle, and BMI. The metabolites in the workers' samples were analyzed using ultra-high-performance liquid chromatography and mass spectrometry. A larger study included 118 exposed and 158 non-exposed workers, incorporating surveys and routine blood and urine tests with differential metabolites targeted via an enzyme-linked immunosorbent assay. The animal studies consisted of two 15- and 60-day benzene staining and control experiments on 28 C57BL/6J mice, followed by sample collection and organ analysis. The data analysis employed eXtensible Computational Mass Spectrometry (XCMS), Python, MetaboAnalyst 6.0, and SPSS24.0. The exposed workers exhibited altered metabolites indicating external benzene exposure, lower glucose levels, and changes in white blood cell counts and urinary ketone bodies. The plasma metabolomics revealed disturbances in energy and lipid metabolism. The benzene-exposed mice displayed reduced weight gain, behavioral changes, and organ damage. Oxidative stress and abnormal purine and lipid metabolism were observed in both the long-term benzene-exposed workers and benzene-exposed mice. Metabolic markers for the early detection of benzene exposure hazards were identified, underscoring the need to mitigate occupational risks.

Macronutrient-differential dietary pattern impacts on body weight, hepatic inflammation, and metabolism.

Introduction: Obesity is a multi-factorial disease frequently associated with poor nutritional habits and linked to many detrimental health outcomes. Individuals with obesity are more likely to have increased levels of persistent inflammatory and metabolic dysregulation. The goal of this study was to compare four dietary patterns differentiated by macronutrient content in a postmenopausal model. Dietary patterns were high carbohydrate (HC), high fat (HF), high carbohydrate plus high fat (HCHF), and high protein (HP) with higher fiber. Methods: Changes in body weight and glucose levels were measured in female, ovariectomized C57BL/6 mice after 15 weeks of feeding. One group of five mice fed the HCHF diet was crossed over to the HP diet on day 84, modeling a 21-day intervention. In a follow-up study comparing the HCHF versus HP dietary patterns, systemic changes in inflammation, using an 80-cytokine array and metabolism, by untargeted liquid chromatography-mass spectrometry (LCMS)-based metabolomics were evaluated. Results: Only the HF and HCHF diets resulted in obesity, shown by significant differences in body weights compared to the HP diet. Body weight gains during the two-diet follow-up study were consistent with the four-diet study. On Day 105 of the 4-diet study, glucose levels were significantly lower for mice fed the HP diet than for those fed the HC and HF diets. Mice switched from the HCHF to the HP diet lost an average of 3.7 grams by the end of the 21-day intervention, but this corresponded with decreased food consumption. The HCHF pattern resulted in dramatic inflammatory dysregulation, as all 80 cytokines were elevated significantly in the livers of these mice after 15 weeks of HCHF diet exposure. Comparatively, only 32 markers changed significantly on the HP diet (24 up, 8 down). Metabolic perturbations in several endogenous biological pathways were also observed based on macronutrient differences and revealed dysfunction in several nutritionally relevant biosynthetic pathways. Conclusion: Overall, the HCHF diet promoted detrimental impacts and changes linked to several diseases, including arthritis or breast neoplasms. Identification of dietary pattern-specific impacts in this model provides a means to monitor the effects of disease risk and test interventions to prevent poor health outcomes through nutritional modification.

Association of Ultraprocessed Food Consumption with Risk of Cardiovascular Disease Among Individuals with Type 2 Diabetes: Findings from the UK Biobank.

SCOPE: Among patients with diabetes, who have modified nutritional behavior and a higher risk of cardiovascular disease (CVD), the influence of ultraprocessed foods (UPFs) on CVD remains unknown. The study aims to evaluate the association between UPF intake and the risk of CVD among individuals with type 2 diabetes (T2D) and further examine the potential biological pathways linking the association. METHODS AND RESULTS: This study includes 5405 participants with T2D who provided at least one 24-h dietary recall from the UK Biobank study. In the fully adjusted models, a 10% increase in the proportion of UPFs is associated with higher hazards of overall CVD (hazard ratio [HR]: 1.10; 95% confidence interval [CI]: 1.04, 1.15), coronary heart disease (HR: 1.10; 95% CI: 1.04, 1.16), heart failure (HR: 1.14; 95% CI: 1.05, 1.25), but not stroke (HR: 1.01; 95% CI: 0.90, 1.12). Cystatin C, high-density lipoprotein cholesterol (HDL-C), apolipoprotein A, C-reactive protein, and body mass index collectively explain 26.9% (12.8%, 48.5%) of the association between UPF intake and the risk of overall CVD. CONCLUSION: Higher UPF intakes are associated with increased hazards of CVD among individuals with T2D, and the association is partly mediated through worsening biomarkers of renal function, lipid metabolism, inflammation, and body weight.

Iron Metabolic Biomarkers and the Mortality Risk in the General Population: A Nationwide Population-Based Cohort Study.

Context: Iron is an essential element in the human body and plays a critical role in many physiological and cellular processes. However, the association between iron status and the risk of all-cause or cause-specific mortality has not been well-investigated. And it is unclear whether the association between iron metabolic biomarkers and the risk of mortality differs between people with and without diabetes mellitus (DM). Objective: This work aimed to investigate associations between iron metabolic biomarkers and all-cause and cause-specific mortality risk in the general population, and heterogeneities in the associations among population with and without DM.. Methods: A total of 29 166 adults from the National Health and Nutrition Examination Survey (NHANES) III and NHANES 1999 to 2010 were included, with linkage to the National Death Index to December 31, 2019. Cox proportional-hazard models and Fine-Gray subdistribution hazard models were used to estimate associations between iron metabolic biomarkers and outcomes. Results: During a median follow-up of 18.83 years, 9378 deaths were observed, including 3420 cardiovascular disease (CVD) deaths and 1969 cancer deaths. A significant linear association between serum ferritin (SF) and all-cause mortality was observed among the overall population and those without DM. J-shaped associations between transferrin saturation (TSAT) and all-cause and CVD mortality were observed among all populations. In the overall population, compared to the first quartile (Q1) group, the adjusted hazard ratio (HR) (95% CI) for all-cause mortality was 1.07 (1.00-1.15), 1.05 (0.98-1.12), 1.13 (1.05-1.21) in Q2, Q3, and Q4 groups for SF, while the HR was 0.94 (0.88-0.99), 0.92 (0.86-0.97), and 0.93 (0.88-0.99) for TSAT. In individuals without DM, the adjusted HR of the Q4 of SF were 1.19 (1.03-1.37) for CVD mortality and 1.25 (1.05-1.48) for cancer mortality. In individuals with DM, the adjusted HRs of the Q4 of TSAT were 0.76 (0.62-0.93) for CVD mortality and 1.47 (1.07-2.03) for cancer mortality. Conclusion: Iron metabolism abnormalities increase mortality risk in the general population. The associations of iron status with mortality were significantly different between individuals with and without DM, which indicated tailored strategies for iron homeostasis are needed.

VLDL and LDL Subfractions Enhance the Risk Stratification of Individuals Who Underwent Epstein-Barr Virus-Based Screening for Nasopharyngeal Carcinoma: A Multicenter Cohort Study.

Serological tests for Epstein-Barr virus (EBV) antibodies have been widely conducted for the screening of nasopharyngeal carcinoma (NPC) in endemic areas. Further risk stratification of NPC can be achieved through plasma lipoprotein and metabolic profiles. A total of 297 NPC patients and 149 EBV-positive participants are enrolled from the NCT03919552 and NCT05682703 cohorts for plasma nuclear magnetic resonance (NMR) metabolomic analysis. Small, dense very low density lipoprotein particles (VLDL-5) and large, buoyant low density lipoprotein particles (LDL-1) are found to be closely associated with nasopharyngeal carcinogenesis. Herein, an NMR-based risk score (NRS), which combines lipoprotein subfractions and metabolic biomarkers relevant to NPC, is developed and well validated within a multicenter cohort. Combining the median cutoff value of the NRS (N50) with that of the serological test for EBV antibodies, the risk stratification model achieves a satisfactory performance in which the area under the curve (AUC) is 0.841 (95% confidence interval: 0.811-0.871), and the positive predictive value (PPV) reaches 70.08% in the combined cohort. These findings not only suggest that VLDL-5 and LDL-1 particles can serve as novel risk factors for NPC but also indicate that the NRS has significant potential in personalized risk prediction for NPC.

Metabolomics of Ramadan fasting and associated risk of chronic diseases.

BACKGROUND: The dramatic change in lifestyle associated with Ramadan fasting raises questions about its effect on metabolism and health. Metabolites, as the end product of metabolism, are excellent candidates to be studied in this regard. OBJECTIVE: This study aims to investigate the effect of Ramadan fasting on the metabolic profile and risk of chronic diseases. METHODS: The London Ramadan study (LORANS) is an observational study in which 2 blood samples were collected from 72 participants a few days before and after the fasting month of Ramadan. We conducted metabolomic profiling using nuclear magnetic resonance spectroscopy to assess the change in individual metabolites from before to after Ramadan. Also, we generated metabolic scores (scaled from 0 to 100) for 7 chronic diseases in the UK Biobank and assessed the association of Ramadan fasting with these scores in LORANS. RESULTS: Of the 72 participants, 35 were male (48.6%); the mean (± standard deviation) age was 45.7 (±16) y. Ramadan fasting was associated with changes in 14 metabolites (1 inflammation marker, 1 amino acid, 2 glycolysis-related metabolites, 2 ketone bodies, 2 triglyceride, and 6 lipoprotein subclasses), independent of changes in body composition. Using data from 117,981 participants in the UK Biobank, we generated metabolic scores for diabetes, hypertension, coronary artery disease, renal failure, colorectal cancer, breast cancer, and lung cancer. The metabolic scores for lung cancer, colorectal cancer, and breast cancer were lower after Ramadan in LORANS (-4.74, 9.6%, 95% confidence interval -6.56, -2.91, P < 0.001), (-1.09, -2.4%, -1.69, -0. 50, P < 0.001), and (-0.48, -1.1%, -0. 81, -0.15, P = 0.006), respectively. CONCLUSIONS: Ramadan fasting is associated with short-term favorable changes in the metabolic profile concerning risk of some chronic diseases. These findings should be further investigated in future, larger studies of longer follow-up with clinical outcomes.

Oral supplementation with crocin (a constituent of saffron) in subjects with cigarette smoking: a clinical trial.

Smoking is one of the main causes of death in the world. Cigarette use is related with various components of metabolic syndrome (e.g., insulin resistance, raised blood pressure, dyslipidemia, oxidative stress, inflammation state) and psychiatric disorders. This study was conducted to determine the effect of crocin (Cro) supplementation on nicotine dependence, anxiety, depression, and metabolic indices in smokers. A total of 50 smokers were selected and randomly categorized into two groups (crocin and placebo). The intervention group received crocin (30 mg per day; n = 25) and placebo (containing Avicel; n = 25) once a day. The primary (nicotine dependence, depression, and anxiety inventory) and secondary (metabolic indices) outcomes were assessed at the start of the intervention and after the 3 months. Multiple linear regression models were used to assess the treatment effects on the outcomes adjusting for confounding variables. The primary outcome results such as nicotine dependence, depression, and anxiety inventory did not have a significant difference among the intervention groups (P > 0.05). Also in the secondary outcomes, fasting plasma glucose (FPG), insulin, and homeostasis model of assessment-insulin resistance (HOMA-IR) levels did indicate a significant difference by Cro intervention (ß - 3.27 mg/dL; 95% CI, - 5.23, - 1.31; P = 0.002; ß - 0.76 µIU/mL; 95% CI, - 1.38, - 0.15; P = 0.01; ß - 0.18; 95% CI, - 0.29, - 0.07; P = 0.002), respectively. There were also significant reductions in serum levels of high-sensitivity C-reactive protein (hs-CRP) (ß - 0.72 mg/L; 95% CI, - 1.37, - 0.07; P = 0.03), compared with the placebo. Cro intake may have favorable effects on the level of FPG, insulin, HOMA-IR, and hs-CRP in smokers. However, due to the small sample size and limited scientific reports on smokers, further studies are necessary. ClinicalTrial.gov Identifier: IRCT20170420033551N11.

Early Diagnosis and Prognosis Prediction of Pancreatic Cancer Using Engineered Hybrid Core-Shells in Laser Desorption/Ionization Mass Spectrometry.

Effective detection of bio-molecules relies on the precise design and preparation of materials, particularly in laser desorption/ionization mass spectrometry (LDI-MS). Despite significant advancements in substrate materials, the performance of single-structured substrates remains suboptimal for LDI-MS analysis of complex systems. Herein, designer Au@SiO2@ZrO2 core-shell substrates are developed for LDI-MS-based early diagnosis and prognosis of pancreatic cancer (PC). Through controlling Au core size and ZrO2 shell crystallization, signal amplification of metabolites up to 3 orders is not only achieved, but also the synergistic mechanism of the LDI process is revealed. The optimized Au@SiO2@ZrO2 enables a direct record of serum metabolic fingerprints (SMFs) by LDI-MS. Subsequently, SMFs are employed to distinguish early PC (stage I/II) from controls, with an accuracy of 92%. Moreover, a prognostic prediction scoring system is established with enhanced efficacy in predicting PC survival compared to CA19-9 (p < 0.05). This work contributes to material-based cancer diagnosis and prognosis.

Clinical metabolomics by NMR revealed serum metabolic signatures for differentiating sarcoidosis from tuberculosis.

BACKGROUND: Pulmonary sarcoidosis (SAR) and tuberculosis (TB) are two granulomatous lung-diseases and often pose a diagnostic challenge to a treating physicians. OBJECTIVE: The present study aims to explore the diagnostic potential of NMR based serum metabolomics approach to differentiate SAR from TB. MATERIALS AND METHOD: The blood samples were obtained from three study groups: SAR (N = 35), TB (N = 28) and healthy normal subjects (NC, N = 56) and their serum metabolic profiles were measured using 1D 1H CPMG (Carr-Purcell-Meiboom-Gill) NMR spectra recorded at 800 MHz NMR spectrometer. The quantitative metabolic profiles were compared employing a combination of univariate and multivariate statistical analysis methods and evaluated for their diagnostic potential using receiver operating characteristic (ROC) curve analysis. RESULTS: Compared to SAR, the sera of TB patients were characterized by (a) elevated levels of lactate, acetate, 3-hydroxybutyrate (3HB), glutamate and succinate (b) decreased levels of glucose, citrate, pyruvate, glutamine, and several lipid and membrane metabolites (such as very-low/low density lipoproteins (VLDL/LDL), polyunsaturated fatty acids, etc.). CONCLUSION: The metabolic disturbances not only found to be well in concordance with various previous reports, these further demonstrated very high sensitivity and specificity to distinguish SAR from TB patients suggesting serum metabolomics analysis can serve as surrogate method in the diagnosis and clinical management of SAR.

Environmental concentrations of cadmium and zinc and associating metabolomics profile alternations in urine of pregnant women in the first trimester: A prospective cohort study in Taiyuan, North China.

especially to pregnant women. In recent years, zinc (Zn) supplementation has attracted increasing attention among pregnant women. Thus, understanding the effects and interactions of Cd and Zn in pregnant women is critical. This study aimed to assess the urinary levels of Cd and Zn in pregnant women during early pregnancy, examine associated alterations in urine metabolomics, and identify potential metabolic biomarkers among distinct Cd and Zn groups. Urine samples from 185 pregnant women were collected, and inductively coupled plasma mass spectrometry (ICP-MS) was used to detect Cd and Zn contents. The women were then divided into four groups according to median contents of Cd and Zn. Alterations in the metabolite profile were assessed using a liquid chromatograph mass spectrometer (LC-MS). The results showed that the gravidity of pregnant women was closely related to urinary Cd levels and that the urinary Zn contents of pregnant women with morning sickness in the first trimester were lower than that of non-morning-sick pregnant women. A total of 51 metabolites exhibited significant differential expression in the high level of Cd and Zn (HCdHZn) compared with low level of Cd and Zn (LCdLZn), the diagnostic performance of these 51 metabolites were assessed using receiver operating characteristic curve analysis and revealed that octadecylamine was a promising diagnostic indicator for evaluating the combined effects of Zn and Cd. Metabolomics analysis showed that the arginine and proline pathways were upregulated in HCdHZn compared with that in LCdLZn, suggesting a potential risk of obesity. Although higer levels of bovinic acid in HCdHZn vs. HCdLZn (high level of Cd and low level of Zn) indicated that Zn has antioxidant and anti-inflammatory properties, excessive Zn may still cause harmful effect to the human health and should be supplemented with caution. The study findings may be valuable for potential risk ahissessment of the combined effects of Cd-Zn and their interactions in pregnant women.

Metabolic biomarkers in lung cancer screening and early diagnosis (Review).

Late diagnosis is one of the major contributing factors to the high mortality rate of lung cancer, which is now the leading cause of cancer-associated mortality worldwide. At present, low-dose CT (LDCT) screening in the high-risk population, in which lung cancer incidence is higher than that of the low-risk population is the predominant diagnostic strategy. Although this has efficiently reduced lung cancer mortality in large randomized trials, LDCT screening has high false-positive rates, resulting in excessive subsequent follow-up procedures and radiation exposure. Complementation of LDCT examination with biofluid-based biomarkers has been documented to increase efficacy, and this type of preliminary screening can potentially reduce potential radioactive damage to low-risk populations and the burden of hospital resources. Several molecular signatures based on components of the biofluid metabolome that can possibly discriminate patients with lung cancer from healthy individuals have been proposed over the past two decades. In the present review, advancements in currently available technologies in metabolomics were reviewed, with particular focus on their possible application in lung cancer screening and early detection.

Genetic associations between circulating metabolic biomarkers and lung cancer in East Asians and Europeans.

BACKGROUND: Metabolic biomarkers are reported to be associated with the risk of lung cancer (LC). However, the observed associations from epidemiological studies are either inconsistent or inconclusive. METHODS: The genetic summary data of high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), total cholesterol (TC), triglyceride (TG), fasting plasma glucose (FPG), and glycated hemoglobin (HbA1c) and those of the LC and its histological subtypes were retrieved from previous GWASs. We performed two-sample Mendelian randomization (MR) and multivariable MR analyses to examine the associations between genetically predicted metabolic biomarkers and LC in East Asians and Europeans. RESULTS: In East Asians, the inverse-variance weighted (IVW) method suggests that LDL (odds ratio [OR] = 0.799, 95% CI 0.712-0.897), TC (OR = 0.713, 95% CI 0.638-0.797), and TG (OR = 0.702, 95% CI 0.613-0.804) were significantly associated with LC after correction for multiple testing. For the remaining three biomarkers, we did not detect significant association with LC by any MR method. Multivariable MR (MVMR) analysis yielded an OR of 0.958 (95% CI 0.748-1.172) for HDL, 0.839 (95% CI 0.738-0.931) for LDL, 0.942 (95% CI 0.742-1.133) for TC, 1.161 (95% CI 1.070-1.252) for TG, 1.079 (95% CI 0.851-1.219) for FPG, and 1.101 (95% CI 0.922-1.191) for HbA1c. In Europeans, the univariate MR analyses did not detect significant association between exposures and outcomes. However, in MVMR analysis integrating circulating lipids and lifestyle risk factors (smoking, alcohol drinking, and body mass index), we found that TG was positively associated with LC in Europeans (OR = 1.660, 95% CI 1.060-2.260). Subgroup and sensitivity analysis yielded similar results to the main analyses. CONCLUSIONS: Our study provides genetic evidence that circulating levels of LDL was negatively associated with LC in East Asians, whereas TG was positively associated with LC in both populations.

Identification of a novel plasma metabolite panel as diagnostic biomarker for hepatocellular carcinoma.

BACKGROUND AND AIMS: Metabolic reprogramming is one of the hallmarks of cancer. Hepatocellular carcinoma (HCC) is one of the most lethal malignancy camcer, but the early diagnosis of HCC remains difficult. In this study, we searched for potential plasma metabolite biomarkers of HCC. METHODS: A total of plasma samples of 104 HCC, 76 cirrhosis and 10 healthy subjects were assessed and validated through Gas chromatography-Mass spectrometry. Receiver-operating characteristic curves (ROC) combined with multivariate statistical analyses were used to assess the diagnostic performance of metabolites and combinations. RESULTS: 10 metabolites in screening cohort were significantly changed in the plasma of HCC patients. Multivariate logistic regression analysis of candidate metabolites in validation cohort showed that N-formylglycine, oxoglutaric acid, citrulline and heptaethylene glycol could distinguish HCC from cirrhosis. The combination of these four metabolites showed a better performance than AFP with the Area Under the Curve (AUC), sensitivity, specificity as 0.940, 84.00%, 97.56%, respectively. In further, the panel of N-formylglycine, heptaethylene glycol and citrulline can more effectively discriminate early stage HCC from cirrhosis than AFP (AUC: 0.835 vs. 0.634). Finally, heptaethylene glycol could significantly inhibit the proliferation, migration and invasion of HCC cells in vitro. CONCLUSION: The combination of plasma N-formylglycine, oxoglutaric acid, citrulline, and heptaethylene glycol can be an efficient novel diagnostic biomarker for HCC.

Effect of Weight Regain on Body Composition and Metabolic Biomarkers After Sleeve Gastrectomy: a Cross-Sectional Study from a Hospital Database.

INTRODUCTION: Weight regain (WR) is described in approximately 30% of patient's post-bariatric surgery. It is related to the progression or recurrence of associated medical problems and decline in health-related quality of life. This study aimed to test the return of body composition and metabolic biomarkers to pre-operative levels when WR occurs. METHODS: In this cross-sectional study conducted in 2021, patients were randomly selected from the hospital's electronic databases between 2001 and 2020. Patient demographic data, comorbidities, body compositions, and metabolic biomarkers were collected. Three groups were defined: groups A (WR), B (weight loss), and C (control group; patients with obesity who had not yet undergone bariatric surgery). RESULTS: A total of 88 patients were enrolled in this study and matched with the control group. The body mass index in group A was 43.8 ± 6.9 kg/m2; group B was 28.6 ± 4.2; group C was 43.9 ± 7.1. Body muscle mass, body fat mass, and visceral fat significantly differed between groups A and B (p < 0.001) but not between groups A and C (p = 0.8). There was a significant difference in leptin, ghrelin, postprandial glucagon-like peptide-1, insulin, and fibroblast growth factor-21 (but not retinol-binding protein-4) between groups A and B. Most metabolic biomarkers in group A returned to the pre-operative values as in group C. CONCLUSION: WR had a direct negative effect on body composition and metabolic biomarkers, whereby the values returned to pre-operative levels. Early detection of WR and possible additional therapy are necessary to prevent associated medical problems.

Can Leptin/Ghrelin Ratio and Retinol-Binding Protein 4 Predict Improved Insulin Resistance in Patients with Obesity Undergoing Sleeve Gastrectomy?

INTRODUCTION: Obesity is associated with metabolic syndrome (MBS), a cluster of components including central obesity, insulin resistance (IR), dyslipidemia, and hypertension. IR is the major risk factor in the development and progression of type 2 diabetes mellitus in obesity and MBS. Predicting preoperatively whether a patient with obesity would have improved or non-improved IR after bariatric surgery would improve treatment decisions. METHODS: A prospective cohort study was conducted between August 2019 and September 2021. We identified pre- and postoperative metabolic biomarkers in patients who underwent laparoscopic sleeve gastrectomy. Patients were divided into two groups: group A (IR < 2.5), with improved IR, and group B (IR ≥ 2.5), with non-improved IR. A prediction model and receiver operating characteristics (ROC) were used to determine the effect of metabolic biomarkers on IR. RESULTS: Seventy patients with obesity and MBS were enrolled. At 12-month postoperative a significant improvement in lipid profile, fasting blood glucose, and hormonal biomarkers and a significant reduction in the BMI in all patients (p = 0.008) were visible. HOMA-IR significantly decreased in 57.14% of the patients postoperatively. Significant effects on the change in HOMA-IR ≥ 2.5 were the variables; preoperative BMI, leptin, ghrelin, leptin/ghrelin ratio (LGr), insulin, and triglyceride with an OR of 1.6,1.82, 1.33, 1.69, 1.77, and 1.82, respectively (p = 0.009 towards p = 0.041). Leptin had the best predictive cutoff value on ROC (86% sensitivity and 92% specificity), whereas ghrelin had the lowest (70% sensitivity and 73% specificity). CONCLUSION: Preoperative BMI, leptin, ghrelin, LGr, and increased triglycerides have a predictive value on higher postoperative, non-improved patients with HOMA-IR (≥ 2.5). Therefore, assessing metabolic biomarkers can help decide on treatment/extra therapy and outcome before surgery.

Metabolic Biomarkers Affecting Cell Proliferation and Prognosis in Polycythemia Vera.

Polycythemia vera (PV) is a malignant clonal hematological disease of hematopoietic stem cells characterized by the proliferation of peripheral blood cells, and JAK2 mutation is one of the main causes of PV peripheral blood cell proliferation. Abnormal cell metabolism is a new feature of malignant proliferation of tumor cells, but the role of metabolism in the pathogenesis and prognosis of PV remains unclear. We analyzed metabolic differences of peripheral blood sera between 32 PV patients and 20 healthy controls (HCs) by liquid chromatography-mass spectrometry (LC-MS) to investigate their relationship with cell proliferation and to screen for prognosis-related metabolic biomarkers. Compared to HC, 33 endogenous metabolites were significantly changed in PV and were involved in fatty acid metabolism, glucose metabolism, sphingolipid metabolism, and amino acid metabolism pathways. Among them, seven metabolites were closely associated with JAK2 mutations, 2 of which may contribute to the proliferation of peripheral blood cells in PV patients. A set of potential prognostic metabolic biomarkers containing four metabolites was identified by a receiver operating characteristic (ROC) curve according to the risk stratification of the PV patients and their combined AUC value of 0.952, with a sensitivity of 90.905% and specificity of 90.909% at the optimal cutoff point. Metabonomics is an important tool for the study of the pathogenesis of PV and the relationship between JAK2 gene mutation. Furthermore, the potential biomarkers of this study may provide a reference for the prognosis of PV.

Integrative metabolomic profiling reveals aberrations in myometrium associated with adenomyosis: a pilot study.

BACKGROUND: Uterine adenomyosis is a common gynecologic disease in premenopausal women, the pathological mechanism of which remains largely unknown. The aim of this study was to identify metabolic biomarkers significantly altered in the myometrium of adenomyosis patients. METHODS: The comprehensive metabolomic profiles of 17 myometrium specimens from adenomyosis patients and 25 control specimens were analyzed using untargeted approach by combination of gas chromatography-mass spectrometry and high performance liquid chromatography-mass spectrometry. Metabolic data were filtered using orthogonal partial least square-discriminant analysis and univariate statistics. RESULTS: We firstly demonstrated that the myometrial metabolome of women with adenomyosis is distinct from that of women without adenomyosis. A total of 106 metabolites, mainly including nucleosides, lipids (including acylcarnitines), amino acids, organic acids and carbohydrates, were found to be differentially expressed in myometrium of uteri with adenomyosis compared to the control subjects. Functional inferences of these perturbed metabolites indicated that inflammation, oxidative stress, cell proliferation and apoptosis, and energy metabolism appeared to be involved in the progress of adenomyosis. CONCLUSION: This study firstly described the integrated metabolic signatures of the adenomyosis uterus, which provided novel insights for the pathogenesis study of this disease.

The Acute Effect of a Novel Miso-Type Sauce, Enhanced with a Carotenoid-Rich Extract from Fruit By-Products, on Postprandial Biomarkers of Oxidative Stress and Inflammation.

Several fruit by-products may exert a beneficial role on oxidative stress and inflammation modulation, providing essential bioactive components, such as polyphenols and carotenoids. Recently, the potential bioactivity of miso has been reported. The aim of this dietary intervention−clinical study was to evaluate the acute effect of a novel, functional miso-type sauce based on legumes, on postprandial biomarkers of oxidative stress and inflammation. In this randomized, cross-over design, intervention−clinical trial, 14 healthy volunteers, aged 20−30 years old, consumed a rice meal rich in fat and carbohydrates (258 g), containing a legume-based sauce. After a 1-week washout period, the same subjects consumed the same meal, containing the novel fermented miso-type sauce, enhanced with 50% carotenoid-rich, fruit peel extract. Differences in postprandial total plasma antioxidant capacity according to the FRAP method, serum lipids, glucose, uric acid levels, and antithrombotic activity in platelet-rich plasma were evaluated before, 30 min, 1.5 h, and 3 h after consumption. The results showed that, in comparison to the control group, consumption of the novel sauce resulted in a significantly increased total plasma antioxidant capacity 3 h after consumption (p < 0.05). In addition, we observed a significant attenuation of triglycerides concentration increase in the last 1.5 h in the functional group (p < 0.05). A significant decrease in serum aggregation was found at 30 min and 3 h after functional sauce intake in comparison with the baseline (p < 0.05). Finally, LDL-cholesterol concentrations were significantly reduced 3 h after the functional meal consumption, in comparison with baseline values (p < 0.05). The remaining biomarkers did not show statistically significant differences (p > 0.05). Further investigation is needed in order to validate the current results.

Circulating metabolites serve as diagnostic biomarkers for HER2-positive breast cancer and have predictive value for trastuzumab therapy outcomes.

Human epidermal growth factor receptor 2 (HER2)-positive is a particularly aggressive type of the breast cancer. Trastuzumab-based therapy is a standard treatment for HER2-positive breast cancer, but some patients are resistance to the therapy. There are no known diagnostic biomarkers to improve the early diagnosis of HER2-positive breast cancer and the clinical utility of trastuzumab therapy. Using ultrahigh-performance liquid time of flight mass spectrometry (UPLC-TOF-MS)-based serum metabolomics and multivariate statistical analysis, we investigated and identified the circulating metabolites L-arginine and arachidonic acid were elevated in trastuzumab-responsive and trastuzumab-resistant HER2-positive breast cancer patients, and increased until reaching their peaks in trastuzumab-resistant HER2-positive breast cancer patients. Moreover, an equation for assessing the risk scores based on linear logistic regression models involving L-arginine and arachidonic acid was created, which was beneficial for revealing metabolic changes in HER2-positive breast cancer and enhancing current trastuzumab-based therapy. In summary, we develop serum-based metabolic biomarkers for diagnosis of HER2-positive breast cancers and predicts the therapeutic effects of trastuzumab therapy.