Novel Time-dependent Multi-omics Integration in Sepsis-associated Liver Dysfunction

The recently developed technologies that allow the analysis of each single omics have provided an unbiased insight into ongoing disease processes. However, it remains challenging to specify the study design for the subsequent integration strategies that can associate sepsis pathophysiology and clinical outcomes. Here, we conducted a time-dependent multi-omics integration (TDMI) in a sepsis-associated liver dysfunction (SALD) model. We successfully deduced the relation of the Toll-like receptor 4 (TLR4) pathway with SALD. Although TLR4 is a critical factor in sepsis progression, it is not specified in single-omics analyses but only in the TDMI analysis. This finding indicates that the TDMI-based approach is more advantageous than single-omics analyses in terms of exploring the underlying pathophysiological mechanism of SALD. Furthermore, TDMI-based approach can be an ideal paradigm for insightful biological interpretations of multi-omics datasets that will potentially reveal novel insights into basic biology, health, and diseases, thus allowing the identification of promising candidates for therapeutic strategies.

The Dose-Dependent Effect of Curcumin Supplementation on Inflammatory Response and Gut Microbiota Profile in High-Fat Fed C57BL/6 Mice

SCOPE

The prevalence of obesity has increased, with excessive consumption of high-fat foods being one of the primary causes. Curcumin, a polyphenol extracted from Curcuma longa L., exhibits anti-inflammatory activity.  The study aims to investigate the effects of curcumin supplementation in different doses on the biochemical profile, inflammatory response, and gut microbiota profile in mice that are fed with high-fat diet (HFD).

METHODS AND RESULTS

C57BL/6 male mice are fed a standard diet, or a HFD with or without different doses of curcumin (50, 250, and 500 mg kg-1 of body weight). Throughout the experimental period, food intake and body weight are assessed weekly. At euthanasia, blood, stool, and tissue samples are collected for biochemical, histological, and molecular analyses. Curcumin increases the IL-10 protein expression in the white adipose tissue. In the liver, there is a reduction in tumor necrosis factor alpha (TNF-α) and an increase in IL-10 gene expression. Also, curcumin promotes the growth of butyrogenic bacteria, such as Clostridium clusters IV and XIVa.

CONCLUSIONS

The findings suggest that curcumin has the potential to improve the inflammatory response and modulate healthy gut microbiota. Further studies are needed to clarify the role of curcumin as a preventive and effective strategy for obesity.

The link between obesity and insulin resistance among children: Effects of key metabolites

BACKGROUND

Childhood obesity became a severe public health challenge, and insulin resistance (IR) was one of the common complications. Both obesity and IR were considered as the basis of metabolic disorders. However, it is unclear which common key metabolites are associated with childhood obesity and IR.

METHODS

The children were divided into normal weight and overweight/obese groups. Fasting blood glucose and fasting insulin were measured, and homeostasis model assessment of insulin resistance was calculated. Liquid chromatography-tandem mass spectrometry was applied for metabonomic analysis. Multiple linear regression analysis and correlation analysis explored the relationships between obesity, IR, and metabolites. Random forests were used to rank the importance of differential metabolites, and relative operating characteristic curves were used for prediction.

RESULTS

A total of 88 normal-weight children and 171 obese/overweight children participated in the study. There was a significant difference between the two groups in 30 metabolites. Childhood obesity was significantly associated with 10 amino acid metabolites and 20 fatty acid metabolites. There were 12 metabolites significantly correlated with IR. The ranking of metabolites in random forest showed that glutamine, tyrosine, and alanine were important in amino acids, and pyruvic-ox-2, ethylmalonic-2, and phenyllactic-2 were important in fatty acids. The area under the curve of body mass index standard deviation  score (BMI-SDS) combined with key amino acid metabolites and fatty acid metabolites for predicting IR was 80.0% and 76.6%, respectively.

CONCLUSIONS

There are common key metabolites related to IR and obese children, and these key metabolites combined with BMI-SDS could effectively predict the risk of IR.

Metabolome subtyping reveals multi-omics characteristics and biological heterogeneity in major psychiatric disorders

Growing evidence suggests that major psychiatric disorders (MPDs) share common etiologies and pathological processes. However, the diagnosis is currently based on descriptive symptoms, which ignores the underlying pathogenesis and hinders the development of clinical treatments. This highlights the urgency of characterizing molecular biomarkers and establishing objective diagnoses of MPDs. Here, we collected untargeted metabolomics, proteomics and DNA methylation data of 327 patients with MPDs, 131 individuals with genetic high risk and 146 healthy controls to explore the multi-omics characteristics of MPDs. First, differential metabolites (DMs) were identified and we classified MPD patients into 3 subtypes based on DMs. The subtypes showed distinct metabolomics, proteomics and DNA methylation signatures. Specifically, one subtype showed dysregulation of complement and coagulation proteins, while the DNA methylation showed abnormalities in chemical synapses and autophagy. Integrative analysis in metabolic pathways identified the important roles of the citrate cycle, sphingolipid metabolism and amino acid metabolism. Finally, we constructed prediction models based on the metabolites and proteomics that successfully captured the risks of MPD patients. Our study established molecular subtypes of MPDs and elucidated their biological heterogeneity through a multi-omics investigation. These results facilitate the understanding of pathological mechanisms and promote the diagnosis and prevention of MPDs.

Associations between body composition profile and hypertension in different fatty liver phenotypes

Background

It is currently unclear whether and how the association between body composition and hypertension varies based on the presence and severity of fatty liver disease (FLD).

Methods

FLD was diagnosed using ultrasonography among 6,358 participants. The association between body composition and hypertension was analyzed separately in the whole population, as well as in subgroups of non-FLD, mild FLD, and moderate/severe FLD populations, respectively. The mediation effect of FLD in their association was explored.

Results

Fat-related anthropometric measurements and lipid metabolism indicators were positively associated with hypertension in both the whole population and the non-FLD subgroup. The strength of this association was slightly reduced in the mild FLD subgroup. Notably, only waist-to-hip ratio and waist-to-height ratio showed significant associations with hypertension in the moderate/severe FLD subgroup. Furthermore, FLD accounted for 17.26% to 38.90% of the association between multiple body composition indicators and the risk of hypertension.

Conclusions

The association between body composition and hypertension becomes gradually weaker as FLD becomes more severe. FLD plays a significant mediating role in their association.

Next Generation of Mass Spectrometry Imaging: from Micrometer to Subcellular Resolution

Developing an imaging method with micrometer-to-subcellular resolution is of great significance for visualizing biological samples of different sizes. The label-free and high-throughput mass spectrometry imaging (MSI) technology has shown potential in the implementation of this view. Despite many improvements in MSI witnessed over the past decades, it remains a challenge to achieve a flexible resolution from micrometer down to subcellular level with high detection sensitivity. In this Perspective, we focus on the recent development of MSI techniques based on different ionization resources. Furthermore, several designs of instruments and applications in bioimaging have been reviewed and compared. Additionally, we proposed the perspectives and challenges for MSI methods, including pursuing the matrix free and multiscale resolution with high detection sensitivity and deeply combining machine learning in omics research.

The digestion and absorption characteristics of human milk phospholipid analogs: a combination study between in vitro and in vivo

Phospholipids play a crucial role in the growth and neurodevelopment of infants. Currently, soybean phospholipids (SPLs) are the common phospholipid component in most infant formulas (IFs), which, however, shows an obvious difference with the phospholipid (PL) composition of human milk fat. Therefore, in the present study, human milk phospholipid analogs (HMPAs) were prepared by mimicking the composition of PE, PC, PI, PS, and SM in breast milk phospholipids and the composition of the major fatty acids (C16:0, C18:0, C18:1, and C18:2), and their digestion and absorption characteristics were explored using in vitro and mice models. The prepared HMPA contained 26.48% PE, 24.64% PC, 36.19% SM, 6.35% PI, and 6.32% PS, with 40.51% C16:0, 17.02% C18:0, 29.19% C18:1, and 13.26% C18:2, showing different digestive properties relative to SPL. There was little effect on the physical and chemical properties of HMPA under in vitro gastric conditions. The hydrolysis degree, fatty acids release rate, and average particle size decreasing rate of HMPA was significantly higher than that of SPL during digestion in vitro intestine (P < 0.05), showing better digestive process relative to SPL. In terms of the mice model, HMPA had a higher hydrolysis degree in the intestinal tract. Based on the area under curve (AUC) analysis of serum fatty acids, it was found that despite HMPA being absorbed at a slower rate than SPL, it was absorbed more than SPL. In summary, the digestion and absorption of HMPA were preferred to SPL, and these obtained results might provide a theoretical basis for the development and utilization of HMPA in IF.

Visualization of hydrocarbon chain length and degree of saturation of fatty acids in mouse livers by combining near-infrared hyperspectral imaging and machine learning

Fatty acids play various physiological roles owing to their diverse structural characteristics, such as hydrocarbon chain length (HCL) and degree of saturation (DS). Although the distribution of fatty acids in biological tissues is associated with lipid metabolism, in situ imaging tools are still lacking for HCL and DS. Here, we introduce a framework of near-infrared (1000-1400 nm) hyperspectral label-free imaging with machine learning analysis of the fatty acid HCL and DS distribution in the liver at each pixel, in addition to the previously reported total lipid content. The training data of 16 typical fatty acids were obtained by gas chromatography from liver samples of mice fed with various diets. A two-dimensional mapping of these two parameters was successfully performed. Furthermore, the HCL/DS plot exhibited characteristic clustering among the different diet groups. Visualization of fatty acid distribution would provide insights for revealing the pathophysiological conditions of liver diseases and metabolism.

MSIpixel: a fully automated pipeline for compound annotation and quantitation in mass spectrometry imaging experiments

Mass spectrometry imaging (MSI) is commonly used to map the spatial distribution of small molecules within complex biological matrices. One of the major challenges in imaging MS-based spatial metabolomics is molecular identification and metabolite annotation, to address this limitation, annotation is often complemented with parallel bulk LC-MS2-based metabolomics to confirm and validate identifications. Here we applied MSI method, utilizing data-dependent acquisition, to visualize and identify unknown molecules in a single instrument run. To reach this aim we developed MSIpixel, a fully automated pipeline for compound annotation and quantitation in MSI experiments. It overcomes challenges in molecular identification, and improving reliability and comprehensiveness in MSI-based spatial metabolomics.

Overview of the Association between Non-Alcoholic Fatty Liver Disease and Hypertension

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, and its prevalence is rising. NAFLD is closely associated with metabolic syndrome, with both conditions sharing common clinical characteristics such as obesity, insulin resistance, type 2 diabetes mellitus, hypertension, and hypertriglyceridemia. Several observational studies have evaluated the relationship between NAFLD and hypertension, with the overall evidence suggesting a bidirectional relationship. It is hypothesized that activation of the sympathetic nervous and renin-angiotensin systems, observed in NAFLD with or without insulin resistance promotes the development of hypertension. In patients with hypertension, activation of these systems can lead to hepatic fibrosis and progressive inflammation through increased oxidative stress and activation of hepatic stellate cells and Kupffer cells. The present review examines the pathophysiologic and clinical evidence supporting the bidirectional association between NAFLD and hypertension.

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.

Plasma level of omentin-1, its expression, and its regulation by gonadotropin-releasing hormone and gonadotropins in porcine anterior pituitary cells

Omentin-1 (OMNT1) is an adipokine involved in the regulation of energy metabolism, insulin sensitivity, and reproduction. The present study was the first to investigate the plasma levels and expression of OMNT1 in the anterior pituitary (AP) gland on days 2-3, 10-12, 14-16, and 17-19 of the estrous cycle of normal-weight Large White (LW) and fat Meishan (MS) pigs. Next, we determined the effect of GnRH, LH, and FSH on the OMNT1 levels in cultured AP cells. The gene and protein expression of OMNT1 in AP fluctuated during the estrous cycle, with a higher expression in MS than in LW (except on days 10-12). However, plasma levels of OMNT1 were higher in LW than in MS. OMNT1 was localized in somatotrophs, lactotrophs, thyrotrophs, and gonadotrophs. In LW pituitary cells, GnRH and gonadotropins stimulated OMNT1 protein expression (except FSH on days 14-16) and had no effect on OMNT1 levels in the culture medium. In MS pituitary cells, we observed that GnRH and LH increased while FSH decreased OMNT1 protein expression. These findings showed OMNT1 expression and regulation in the porcine AP and suggested that OMNT1 could be a new player modifying the pituitary functions.

Effects of soda water on blood lipid and metabolic profiling of urine in hyperlipidemia rats using UPLC/Triple-TOF MS

The effects of a natural soda water (Shi Han Quan, SHQ) on hyperlipidemia and the changes of urine metabolic profiling by metabolomics techniques were investigate. Thirty six Wistar rats weighing 160-200 g were divided into control group, hyperlipidemia (HL) group, and hyperlipidemia + SHQ water (SHQ) group. The metabolites in urine were determined using ultra high performance liquid chromatography-triple-time of flight-mass spectrometry (UPLC/Triple-TOF MS). At the end of 1 month and 3 months, the total glyceride (TG) level was significantly lower in SHQ group compared to HL group. There was no significantly difference in total cholesterol (TC) levels in HL group compared with SHQ group. The results showed that dinking SHQ water can improve the TG, but with no effects on TC. After drinking SHQ water for 3 months, the rats in different groups could be classified into different clusters according to the metabolites in urine. Total 15 important metabolites were found and correlated with disturbance of amino acid, phospholipid, fatty acid and vitamin metabolism, which suggested the changes of metabolism in the body and possible mechanism by which SHQ improved the TG. These findings provide a new insight for the prevention and control of hyperlipidemia.

Knockdown of IL4I1 Improved High Glucose-evoked Insulin Resistance in HepG2 Cells by Alleviating Inflammation and Lipotoxicity Through AHR Activation

Insulin resistance (IR) is one of the leading causes of Type 2 diabetes mellitus (T2DM). Inflammation, as a result of the disordered immune response, plays important roles in IR and T2DM. Interleukin-4-induced gene 1 (IL4I1) has been shown to regulate immune response and be involved in inflammation progress. However, there was little known about its roles in T2DM. Here, high glucose (HG)-treated HepG2 cells were used for T2DM investigation in vitro. Our results indicated that the expression of IL4I1 was up-regulated in peripheral blood samples of T2DM-patients and HG-induced HepG2 cells. The silencing of IL4I1 alleviated the HG-evoked IR through elevating the expressions of p-IRS1, p-AKT and GLUT4, and enhancing glucose consumption. Furthermore, IL4I1 knockdown inhibited inflammatory response by reducing the levels of inflammatory mediators, and suppressed the accumulation of lipid metabolites triglyceride (TG) and palmitate (PA) in HG-induced cells. Notably, IL4I1 expression was positively correlated with aryl hydrocarbon receptor (AHR) in peripheral blood samples of T2DM-patients. The silencing of IL4I1 inhibited the AHR signaling by reducing the HG-induced expressions of AHR and CYP1A1. Subsequent experiments confirmed that 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), an agonist of AHR, reversed the suppressive effects of IL4I1 knockdown on HG-caused inflammation, lipid metabolism and IR in cells. In conclusion, we found that the silencing of IL4I1 attenuated inflammation, lipid metabolism and IR in HG-induced cells via inhibiting AHR signaling, suggesting that IL4I1 might be a potential therapy target for T2DM.

Untargeted metabolomic analysis investigating links between unprocessed red meat intake and markers of inflammation

BACKGROUND

Whether red meat consumption is associated with higher inflammation or confounded by increased adiposity remains unclear. Plasma metabolites capture the effects of diet after food is processed, digested, and absorbed, and correlate with markers of inflammation, so they can help clarify diet-health relationships.

OBJECTIVE

To identify whether any metabolites associated with red meat intake are also associated with inflammation.

METHODS

A cross-sectional analysis of observational data from older adults (52.84% women, mean age 63 ± 0.3 y) participating in the Multi-Ethnic Study of Atherosclerosis (MESA). Dietary intake was assessed by food-frequency questionnaire, alongside C-reactive protein (CRP), interleukin-2, interleukin-6, fibrinogen, homocysteine, and tumor necrosis factor alpha, and untargeted proton nuclear magnetic resonance (1H NMR) metabolomic features. Associations between these variables were examined using linear regression models, adjusted for demographic factors, lifestyle behaviors, and body mass index (BMI).

RESULTS

In analyses that adjust for BMI, neither processed nor unprocessed forms of red meat were associated with any markers of inflammation (all P > 0.01). However, when adjusting for BMI, unprocessed red meat was inversely associated with spectral features representing the metabolite glutamine (sentinel hit: β = -0.09 ± 0.02, P = 2.0 × 10-5), an amino acid which was also inversely associated with CRP level (β = -0.11 ± 0.01, P = 3.3 × 10-10).

CONCLUSIONS

Our analyses were unable to support a relationship between either processed or unprocessed red meat and inflammation, over and above any confounding by BMI. Glutamine, a plasma correlate of lower unprocessed red meat intake, was associated with lower CRP levels. The differences in diet-inflammation associations, compared with diet metabolite-inflammation associations, warrant further investigation to understand the extent that these arise from the following: 1) a reduction in measurement error with metabolite measures; 2) the extent that which factors other than unprocessed red meat intake contribute to glutamine levels; and 3) the ability of plasma metabolites to capture individual differences in how food intake is metabolized.

Identification of canine mammary tumor-associated metabolites using untargeted metabolomics

The canine mammary tumor is the most common tumor type in female dogs and seriously threatens their life. Currently, no effective treatments are available for this condition. Hence, it is essential to identify biomarkers that positively influence the early diagnosis and treatment and prognosis of this disease. To provide a basis for early diagnosis of canine breast tumors, in this study, 23 dogs with mammary tumors were identified via histopathological examination combined with ancillary diagnoses via blood examinations and diagnostic imaging. The canine mammary tumor and tumor-adjacent healthy tissues were collected, and their metabolites were identified utilizing a UHPLC-qTOF-MS-based untargeted metabolomics approach. The metabolic results revealed a total of 979 ion features in the positive polarity mode and 371 ion features in the negative polarity mode in the tissues of two groups; among them, 536 differential metabolites (385 in the positive and 151 in the negative polarity mode) were analyzed by PCA and PLS-DA. Subsequently, the enrichment pathways purine metabolism, alpha-linolenic acid metabolism, vitamin B6 metabolism, and fatty acid biosynthesis were analyzed using Metaboanalyst 4.0, which suggested that these pathways were valuable diagnostic and therapeutic targets. Moreover, the receiver operating characteristic curves further confirmed 13Z,16Z-docosadienoic acid, 23-nordeoxycholic acid, and (±)12(13)-DiHOME as expected candidate biomarkers of canine mammary tumors. In conclusion, the discovery of tumor biomarkers based on untargeted metabolomics is informative for pathological mechanism studies and facilitates the early diagnosis of canine mammary tumors.

Recent advances in LC-MS-based metabolomics for clinical biomarker discovery

The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.

Shift in prevalence and systemic inflammation levels from NAFLD to MAFLD: a population-based cross-sectional study

BACKGROUND

Variations in the prevalence and systemic inflammatory (SI) status between non-alcoholic fatty liver disease (NAFLD) and newly defined metabolic dysfunction-associated fatty liver disease (MAFLD) have only been reported by few studies. Hence, this study aimed to compile data on the prevalence and the systemic inflammation levels of MAFLD and NAFLD in a general population from Southeast China was summarized to explore the potential effect of the transformation of disease definition.

METHODS

A total of 6718 general population participants aged 35-75 were enrolled. Logistic regression and restricted cubic spline (RCS) models were used to examine the relationship between 15 SI indicators and NAFLD and MAFLD. The predicted values of MAFLD and NAFLD were analyzed using the receiver operating characteristic (ROC) curve.

RESULTS

The prevalence of MAFLD and NAFLD was 34.7% and 32.4%, respectively. Their overlapping rate was 89.7%, while only 8.3% and 1.9% of participants were MAFLD-only and NAFLD-only. Among three FLD groups, the MAFLD-only group had the highest levels of 8 SI indicators, including CRP, WBC, LYMPH, NEUT, MONO, ALB, NLR, and SIRI. The non-FLD group had the lower levels of all 15 SI indicators compared with all FLD subgroups. The odds ratios (ORs) of 10 SI indicators were significant in both multivariable-adjusted logistic regression and RCS analyses of MAFLD or NAFLD, including CRP, WBC, LYMPH, NEUT, MONO, ALB, PLR, LMR, ALI and CA. ROC analysis showed that the AUC values of all SI were lower than 0.7 in both MAFLD and NAFLD.

CONCLUSIONS

MAFLD could cover more FLD than NAFLD, and the MAFLD-only group had a more severe inflammation status, whereas the NAFLD-only exhibited lower levels. Moreover, there was not a high AUC and a high sensitivity of SI indicators, suggesting that SI indicators are not good indicators to diagnose NAFLD/MAFLD.

Plant protein consumption is associated with body mass index among women of reproductive age in Indonesia

Introduction

One of the known determinants of obesity in Southeast Asia countries, including Indonesia, is the nutritional transition, which is indicated by fast changes in food production, dietary habits, and physical activity. With rising incomes, plant protein from grains, tubers, and legumes is gradually being replaced by animal protein from poultry, eggs, dairy, and red meat. This change is identified as a protein transition. Different choices of protein sources in the diet have varying health effects. However, there is limited information on the Asian population on the role of protein consumption on the increasing obesity prevalence. Therefore, this study aimed to investigate the association of protein sources consumption with body mass index (BMI) among women of reproductive age in Indonesia.

Methods

This study used secondary data from the 2018 Indonesia Food Barometer (IFB) conducted using a quantitative cross-sectional survey. A total of 467 Indonesian reproductive-aged women (20-49 years) were included in this study. Dietary intake, including protein consumption, was obtained using 24-h dietary recall. Multiple linear regression was applied to find the association of protein consumption with BMI with a p-value <0.05 considered as a significant outcome variable.

Results

The Mean BMI was 25.02 kg/m2, median of animal and plant protein was 28.01 g/day and 25.37 g/day, respectively. Consumption of plant protein was significantly associated with BMI after adjusting for marital status and age (p-value = 0.043; R2 = 0.080). The quality of plant protein should be considered to prevent obesity problems among women of reproductive age.

Palmitoylation-driven PHF2 ubiquitination remodels lipid metabolism through the SREBP1c axis in hepatocellular carcinoma

Palmitic acid (PA) is the most common fatty acid in humans and mediates palmitoylation through its conversion into palmitoyl coenzyme A. Although palmitoylation affects many proteins, its pathophysiological functions are only partially understood. Here we demonstrate that PA acts as a molecular checkpoint of lipid reprogramming in HepG2 and Hep3B cells. The zinc finger DHHC-type palmitoyltransferase 23 (ZDHHC23) mediates the palmitoylation of plant homeodomain finger protein 2 (PHF2), subsequently enhancing ubiquitin-dependent degradation of PHF2. This study also reveals that PHF2 functions as a tumor suppressor by acting as an E3 ubiquitin ligase of sterol regulatory element-binding protein 1c (SREBP1c), a master transcription factor of lipogenesis. PHF2 directly destabilizes SREBP1c and reduces SREBP1c-dependent lipogenesis. Notably, SREBP1c increases free fatty acids in hepatocellular carcinoma (HCC) cells, and the consequent PA induction triggers the PHF2/SREBP1c axis. Since PA seems central to activating this axis, we suggest that levels of dietary PA should be carefully monitored in patients with HCC.

Perilipin 2-positive mononuclear phagocytes accumulate in the diabetic retina and promote PPARγ-dependent vasodegeneration

Type 2 diabetes mellitus (T2DM), characterized by hyperglycemia and dyslipidemia, leads to nonproliferative diabetic retinopathy (NPDR). NPDR is associated with blood-retina barrier disruption, plasma exudates, microvascular degeneration, elevated inflammatory cytokine levels, and monocyte (Mo) infiltration. Whether and how the diabetes-associated changes in plasma lipid and carbohydrate levels modify Mo differentiation remains unknown. Here, we show that mononuclear phagocytes (MPs) in areas of vascular leakage in DR donor retinas expressed perilipin 2 (PLIN2), a marker of intracellular lipid load. Strong upregulation of PLIN2 was also observed when healthy donor Mos were treated with plasma from patients with T2DM or with palmitate concentrations typical of those found in T2DM plasma, but not under high-glucose conditions. PLIN2 expression correlated with the expression of other key genes involved in lipid metabolism (ACADVL, PDK4) and the DR biomarkers ANGPTL4 and CXCL8. Mechanistically, we show that lipid-exposed MPs induced capillary degeneration in ex vivo explants that was inhibited by pharmaceutical inhibition of PPARγ signaling. Our study reveals a mechanism linking dyslipidemia-induced MP polarization to the increased inflammatory cytokine levels and microvascular degeneration that characterize NPDR. This study provides comprehensive insights into the glycemia-independent activation of Mos in T2DM and identifies MP PPARγ as a target for inhibition of lipid-activated MPs in DR.

Curcumin and analogues against head and neck cancer: From drug delivery to molecular mechanisms

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most life-threatening diseases which also causes economic burden worldwide. To overcome the limitations of traditional therapies, investigation into alternative adjuvant treatments is crucial.

PURPOSE

Curcumin, a turmeric-derived compound, demonstrates significant therapeutic potential in diverse diseases, including cancer. Furthermore, research focuses on curcumin analogues and novel drug delivery systems, offering approaches for improved efficacy. This review aims to provide a comprehensive overview of curcumin's current findings, emphasizing its mechanisms of anti-HNSCC effects and potential for clinical application.

METHOD

An electronic search of Web of Science, MEDLINE, and Embase was conducted to identify literature about the application of curcumin or analogues in HNSCC. Titles and abstracts were screened to identify potentially eligible studies. Full-text articles will be obtained and independently evaluated by two authors to make the decision of inclusion in the review.

RESULTS

Curcumin's clinical application is hindered by poor bioavailability, prompting the exploration of methods to enhance it, such as curcumin analogues and novel drug delivery systems. Curcumin could exhibit anti-cancer effects by targeting cancer cells and modulating the tumor microenvironment in HNSCC. Mechanisms of action include cell cycle arrest, apoptosis promotion, reactive oxygen species induction, endoplasmic reticulum stress, inhibition of epithelial-mesenchymal transition, attenuation of extracellular matrix degradation, and modulation of tumor metabolism in HNSCC cells. Curcumin also targets various components of the tumor microenvironment, including cancer-associated fibroblasts, innate and adaptive immunity, and lymphovascular niches. Furthermore, curcumin enhances the anti-cancer effects of other drugs as adjunctive therapy. Two clinical trials report its potential clinical applications in treating HNSCC.

CONCLUSION

Curcumin has demonstrated therapeutic potential in HNSCC through in vitro and in vivo studies. Its effectiveness is attributed to its ability to modulate cancer cells and interact with the intricate tumor microenvironment. The development of curcumin analogues and novel drug delivery systems has shown promise in improving its bioavailability, thereby expanding its clinical applications. Further research and exploration in this area hold great potential for harnessing the full therapeutic benefits of curcumin in HNSCC treatment.

Exosome-mediated metabolic reprogramming: Implications in esophageal carcinoma progression and tumor microenvironment remodeling

Esophageal carcinoma is among the most fatal malignancies with increasing incidence globally. Tumor onset and progression can be driven by metabolic reprogramming, especially during esophageal carcinoma development. Exosomes, a subset of extracellular vesicles, display an average size of ∼100 nanometers, containing multifarious components (nucleic acids, proteins, lipids, etc.). An increasing number of studies have shown that exosomes are capable of transferring molecules with biological functions into recipient cells, which play crucial roles in esophageal carcinoma progression and tumor microenvironment that is a highly heterogeneous ecosystem through rewriting the metabolic processes in tumor cells and environmental stromal cells. The review introduces the reprogramming of glucose, lipid, amino acid, mitochondrial metabolism in esophageal carcinoma, and summarize current pharmaceutical agents targeting such aberrant metabolism rewiring. We also comprehensively overview the biogenesis and release of exosomes, and recent advances of exosomal cargoes and functions in esophageal carcinoma and their promising clinical application. Moreover, we discuss how exosomes trigger tumor growth, metastasis, drug resistance, and immunosuppression as well as tumor microenvironment remodeling through focusing on their capacity to transfer materials between cells or between cells and tissues and modulate metabolic reprogramming, thus providing a theoretical reference for the design potential pharmaceutical agents targeting these mechanisms. Altogether, our review attempts to fully understand the significance of exosome-based metabolic rewriting in esophageal carcinoma progression and remodeling of the tumor microenvironment, bringing novel insights into the prevention and treatment of esophageal carcinoma in the future.

Inflammation and the pathological progression of Alzheimer's disease are associated with low circulating choline levels

Deficiency of dietary choline, an essential nutrient, is observed worldwide, with ~ 90% of Americans being deficient. Previous work highlights a relationship between decreased choline intake and an increased risk for cognitive decline and Alzheimer's disease (AD). The associations between blood circulating choline and the pathological progression in both mild cognitive impairment (MCI) and AD remain unknown. Here, we examined these associations in a cohort of patients with MCI with presence of either sparse or high neuritic plaque density and Braak stage and a second cohort with either moderate AD (moderate to frequent neuritic plaques, Braak stage = IV) or severe AD (frequent neuritic plaques, Braak stage = VI), compared to age-matched controls. Metabolomic analysis was performed on serum from the AD cohort. We then assessed the effects of dietary choline deficiency (Ch-) in 3xTg-AD mice and choline supplementation (Ch+) in APP/PS1 mice, two rodent models of AD. The levels of circulating choline were reduced while pro-inflammatory cytokine TNFα was elevated in serum of both MCI sparse and high pathology cases. Reduced choline and elevated TNFα correlated with higher neuritic plaque density and Braak stage. In AD patients, we found reductions in choline, its derivative acetylcholine (ACh), and elevated TNFα. Choline and ACh levels were negatively correlated with neuritic plaque load, Braak stage, and TNFα, but positively correlated with MMSE, and brain weight. Metabolites L-Valine, 4-Hydroxyphenylpyruvic, Methylmalonic, and Ferulic acids were significantly associated with circuiting choline levels. In 3xTg-AD mice, the Ch- diet increased amyloid-β levels and tau phosphorylation in cortical tissue, and TNFα in both blood and cortical tissue, paralleling the severe human-AD profile. Conversely, the Ch+ diet increased choline and ACh while reducing amyloid-β and TNFα levels in brains of APP/PS1 mice. Collectively, low circulating choline is associated with AD-neuropathological progression, illustrating the importance of adequate dietary choline intake to offset disease.

Multi-omics approach to socioeconomic disparity in metabolic syndrome reveals roles of diet and microbiome

The epidemy of metabolic syndrome (MetS) is typically preceded by adoption of a "risky" lifestyle (e.g., dietary habit) among populations. Evidence shows that those with low socioeconomic status (SES) are at an increased risk for MetS. To investigate this, we recruited 123 obese subjects (body mass index [BMI] ≥ 30) from Chicago. Multi-omic data were collected to interrogate fecal microbiota, systemic markers of inflammation and immune activation, plasma metabolites, and plasma glycans. Intestinal permeability was measured using the sugar permeability testing. Our results suggest a heterogenous metabolic dysregulation among obese populations who are at risk of MetS. Systemic inflammation, linked to poor diet, intestinal microbiome dysbiosis, and gut barrier dysfunction may explain the development of MetS in these individuals. Our analysis revealed 37 key features associated with increased numbers of MetS features. These features were used to construct a composite metabolic-inflammatory (MI) score that was able to predict progression of MetS among at-risk individuals. The MI score was correlated with several markers of poor diet quality as well as lower levels of gut microbial diversity and abnormalities in several species of bacteria. This study reveals novel targets to reduce the burden of MetS and suggests access to healthy food options as a practical intervention.

Nuciferine induces autophagy to relieve vascular cell adhesion molecule 1 activation via repressing the Akt/mTOR/AP1 signal pathway in the vascular endothelium

Pro-inflammatory factor-associated vascular cell adhesion molecule 1 (VCAM1) activation initiates cardiovascular events. This study aimed to explore the protective role of nuciferine on TNFα-induced VCAM1 activation. Nuciferine was administrated to both high-fat diet (HFD)-fed mice and the TNFα-exposed human vascular endothelial cell line. VCAM1 expression and further potential mechanism(s) were explored. Our data revealed that nuciferine intervention alleviated VCAM1 activation in response to both high-fat diet and TNFα exposure, and this protective effect was closely associated with autophagy activation since inhibiting autophagy by either genetic or pharmaceutical approaches blocked the beneficial role of nuciferine. Mechanistical studies revealed that Akt/mTOR inhibition, rather than AMPK, SIRT1, and p38 signal pathways, contributed to nuciferine-activated autophagy, which further ameliorated TNFα-induced VCAM1 via repressing AP1 activation, independent of transcriptional regulation by IRF1, p65, SP1, and GATA6. Collectively, our data uncovered a novel biological function for nuciferine in protecting VCAM1 activation, implying its potential application in improving cardiovascular events.

Serum metabolomics profiling by proton nuclear magnetic resonance spectrometry of the response to single oral macronutrient challenges in women with polycystic ovary syndrome (PCOS) compared with male and female controls

BACKGROUND

The polycystic ovary syndrome (PCOS) is associated with insulin resistance, obesity and cardiometabolic comorbidities. We here challenged the hypothesis, using state-of-the-art proton nuclear magnetic resonance spectrometry (1H-NMRS) metabolomics profiling, that androgen excess in women induces a certain masculinization of postprandial metabolism that is modulated by obesity.

MATERIALS AND METHODS

Participants were 53 Caucasian young adults, including 17 women with classic PCOS consisting of hyperandrogenism and ovulatory dysfunction, 17 non-hyperandrogenic women presenting with regular menses, and 19 healthy men, selected to be similar in terms of age and body mass index (BMI). Half of the subjects had obesity. Patients were submitted to isocaloric separate glucose, lipid and protein oral challenges in alternate days and fasting and postprandial serum samples were submitted to 1H-NMRS metabolomics profiling for quantification of 36 low-molecular-weight polar metabolites.

RESULTS

The largest postprandial changes were observed after glucose and protein intake, with lipid ingestion inducing smaller differences. Changes after glucose intake consisted of a marked increase in carbohydrates and byproducts of glycolysis, and an overall decrease in byproducts of proteolysis, lipolysis and ketogenesis. After the protein load, most amino acids and derivatives increased markedly, in parallel to an increase in pyruvate and a decrease in 3-hydroxybutyric acid and glycerol. Obesity increased β- and D-glucose and pyruvate levels, with this effect being observed mostly after glucose ingestion in women with PCOS. Regardless of the type of macronutrient, men presented increased lysine and decreased 3-hydroxybutyric acid. In addition, non-obese men showed increased postprandial β-glucose and decreased pyroglutamic acid, compared with non-obese control women. We observed a common pattern of postprandial changes in branched-chain and aromatic amino acids, where men showed greater amino acids increases after protein intake than control women and patients with PCOS but only within the non-obese participants. Conversely, this increase was blunted in obese men but not in obese women, who even presented a larger increase in some amino acids compared with their non-obese counterparts. Interestingly, regardless of the type of macronutrient, only obese women with PCOS showed increased leucine, lysine, phenylalanine and tryptophan levels compared with non-obese patients.

CONCLUSIONS

Serum 1H-NMRS metabolomics profiling indicated sexual dimorphism in the responses to oral macronutrient challenges, which were apparently driven by the central role of postprandial insulin effects with obesity, and to a lesser extent PCOS, exerting modifying roles derived from insulin resistance. Hence, obesity impaired metabolic flexibility in young adults, yet sex and sex hormones also influenced the regulation of postprandial metabolism.

Impact of Polyphenols on Inflammatory and Oxidative Stress Factors in Diabetes Mellitus: Nutritional Antioxidants and Their Application in Improving Antidiabetic Therapy

Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycaemia and oxidative stress. Oxidative stress plays a crucial role in the development and progression of diabetes and its complications. Nutritional antioxidants derived from dietary sources have gained significant attention due to their potential to improve antidiabetic therapy. This review will delve into the world of polyphenols, investigating their origins in plants, metabolism in the human body, and relevance to the antioxidant mechanism in the context of improving antidiabetic therapy by attenuating oxidative stress, improving insulin sensitivity, and preserving β-cell function. The potential mechanisms of, clinical evidence for, and future perspectives on nutritional antioxidants as adjuvant therapy in diabetes management are discussed.

The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review

This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.

Advancements in Analyzing Tumor Metabolites through Chemical Derivatization-Based Chromatography

Understanding the metabolic abnormalities of tumors is crucial for early diagnosis, prognosis, and treatment. Accurate identification and quantification of metabolites in biological samples are essential to investigate the relationship between metabolite variations and tumor development. Common techniques like LC-MS and GC-MS face challenges in measuring aberrant metabolites in tumors due to their strong polarity, isomerism, or low ionization efficiency during MS detection. Chemical derivatization of metabolites offers an effective solution to overcome these challenges. This review focuses on the difficulties encountered in analyzing aberrant metabolites in tumors, the principles behind chemical derivatization methods, and the advancements in analyzing tumor metabolites using derivatization-based chromatography. It serves as a comprehensive reference for understanding the analysis and detection of tumor metabolites, particularly those that are highly polar and exhibit low ionization efficiency.

Comparative analysis of bile metabolic profile in patients with biliary obstruction complicated by Clonorchis sinensis infection

Background

Clonorchiasis is an important foodborne parasitic disease. However, eggs of Clonorchis sinensis (C. sinensis) cannot be detected in feces during biliary obstruction. Moreover, many diseases can cause biliary obstruction, such as gallstones, adenocarcinoma, cholangiocarcinoma and Ascaris lumbricoides infection. Therefore, it is of great significance to distinguish between patients of biliary obstruction and biliary obstruction with C. sinensis infection.

Methods

A total of 48 biliary obstruction patients were enrolled, including 23 infected with C. sinensis (C. sinensis) (OB+C.s) and 25 non-infected subjects (OB). The bile samples were collected by endoscopic retrograde cholangiopancreatography and analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MS). Additionally, multivariate statistical analysis methods were employed to identify differential metabolites. Next, bile amino acid levels were determined by targeted metabolomics analysis.

Result

A total of 146 and 132 significant metabolites were identified in electrospray ionization (ESI)+ and ESI- modes, respectively. The levels of amino acids (asparagine, glutamate, ornithine) and polyamines (spermidine and spermine) were significantly changed. Targeted analysis showed that the levels of amino acids (such as L-arginine, L-glutamine, L-lysine, L-propionic, and L-tyrosine) were lower in OB+C.s patients compared to those in OB patients. Marked metabolic pathways were involved in "Glutathione metabolism", "Caffeine metabolism", "Alanine, aspartate and glutamate metabolism", "Arginine and proline metabolism", "Purine metabolism", "Beta-Alanine metabolism", and "D-glutamine and D-glutamate metabolism".

Conclusion

These results show that there were significant differences between OB+C.s and OB patients, especially in amino acids. The metabolic signature and perturbations in metabolic pathways may help to better distinguish OB+C.s and OB patients.

Predicting the 5-Year Risk of Nonalcoholic Fatty Liver Disease Using Machine Learning Models: Prospective Cohort Study

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) has emerged as a worldwide public health issue. Identifying and targeting populations at a heightened risk of developing NAFLD over a 5-year period can help reduce and delay adverse hepatic prognostic events.

OBJECTIVE

This study aimed to investigate the 5-year incidence of NAFLD in the Chinese population. It also aimed to establish and validate a machine learning model for predicting the 5-year NAFLD risk.

METHODS

The study population was derived from a 5-year prospective cohort study. A total of 6196 individuals without NAFLD who underwent health checkups in 2010 at Zhenhai Lianhua Hospital in Ningbo, China, were enrolled in this study. Extreme gradient boosting (XGBoost)-recursive feature elimination, combined with the least absolute shrinkage and selection operator (LASSO), was used to screen for characteristic predictors. A total of 6 machine learning models, namely logistic regression, decision tree, support vector machine, random forest, categorical boosting, and XGBoost, were utilized in the construction of a 5-year risk model for NAFLD. Hyperparameter optimization of the predictive model was performed in the training set, and a further evaluation of the model performance was carried out in the internal and external validation sets.

RESULTS

The 5-year incidence of NAFLD was 18.64% (n=1155) in the study population. We screened 11 predictors for risk prediction model construction. After the hyperparameter optimization, CatBoost demonstrated the best prediction performance in the training set, with an area under the receiver operating characteristic (AUROC) curve of 0.810 (95% CI 0.768-0.852). Logistic regression showed the best prediction performance in the internal and external validation sets, with AUROC curves of 0.778 (95% CI 0.759-0.794) and 0.806 (95% CI 0.788-0.821), respectively. The development of web-based calculators has enhanced the clinical feasibility of the risk prediction model.

CONCLUSIONS

Developing and validating machine learning models can aid in predicting which populations are at the highest risk of developing NAFLD over a 5-year period, thereby helping delay and reduce the occurrence of adverse liver prognostic events.

Which Comes First, Nonalcoholic Fatty Liver Disease or Arterial Hypertension?

Non-alcoholic fatty liver disease (NAFLD) and arterial hypertension (AH) are widespread noncommunicable diseases in the global population. Since hypertension and NAFLD are diseases associated with metabolic syndrome, they are often comorbid. In fact, many contemporary published studies confirm the association of these diseases with each other, regardless of whether other metabolic factors, such as obesity, dyslipidemia, and type 2 diabetes mellites, are present. This narrative review considers the features of the association between NAFLD and AH, as well as possible pathophysiological mechanisms.

Current status and progress in the omics of Clonorchis sinensis

Clonorchis sinensis (C. sinensis) is a fish-borne trematode that inhabits the bile duct of mammals including humans, cats, dogs, rats, and so on. In the complex life cycle of C. sinensis, the worm develops successively in two intermediate hosts in fresh water and one definitive host. What's more, it undergoes eight developmental stages with a distinct morphology. Clonorchiasis, caused by C. sinensis infection, is an important food-borne parasitic disease and one of the most common zoonoses. C. sinensis infection could result in hyperplasia of the bile duct epithelium, obstructive jaundice, gall-stones, cholecystitis and cholangitis, even liver cirrhosis and cholangiocarcinoma. Thus, clonorchiasis is a serious public health problem in endemic areas. Integrated strategies should be adopted in the prevention and control of clonorchiasis due to the epidemiological characteristics. The recent advances in high-throughput technologies have made available the profiling of multiple layers of a biological system, genomics, transcriptomics, proteomics, and metabolomics. These data can help us to get more information about the development, physiology, metabolism, and reproduction of the parasite as well as pathogenesis and parasite-host interactions in clonorchiasis. In the present study, we summarized recent progresses in omics studies on C. sinensis providing insights into the studies and future directions on treating and preventing C. sinensis associated diseases.

Adipokines in obesity and metabolic-related-diseases

The discovery of leptin in the 1990s led to a reconsideration of adipose tissue (AT) as not only a fatty acid storage organ, but also a proper endocrine tissue. AT is indeed capable of secreting bioactive molecules called adipokines for white AT or batokines for brown/beige AT, which allow communication with numerous organs, especially brain, heart, liver, pancreas, and/or the vascular system. Adipokines exert pro or anti-inflammatory activities. An equilibrated balance between these two sets ensures homeostasis of numerous tissues and organs. During the development of obesity, AT remodelling leads to an alteration of its endocrine activity, with increased secretion of pro-inflammatory adipokines relative to the anti-inflammatory ones, as shown in the graphical abstract. Pro-inflammatory adipokines take part in the initiation of local and systemic inflammation during obesity and contribute to comorbidities associated to obesity, as detailed in the present review.

Data-driven decision-making for precision diagnosis of digestive diseases

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.

Association between serum ferritin and liver stiffness in adults aged ≥20 years: A cross-sectional study based on NHANES

The importance of serum ferritin has been demonstrated in many liver diseases, but its relationship with liver stiffness remains unclear. The objective of this study was to investigate the association between serum ferritin levels and participants' liver stiffness measurement (LSM) in the United States population. We conducted a screening of participants from National Health and Nutrition Examination Survey (NHANES) 2017.1 to 2020.3 to ensure that participants included in this study had complete serum ferritin and LSM information. Association between the independent variable (serum ferritin) and the dependent variable (LSM) was investigated by multiple linear regression and subgroup analysis was performed to identify sensitive individuals, and we subsequently assessed whether there was a non-linear relationship between the 2 using smoothed curve fitting and threshold effect models. The final 7143 participants were included in this study. There was a positive association between participants' serum ferritin concentration and LSM, with an effect value of (β = 0.0007, 95% confidence interval (CI): 0.0002-0.0011) in the all-adjusted model. The smoothing curve and threshold effect models indicated a non-linear positive correlation between serum ferritin and LSM, which was more pronounced when serum ferritin concentration exceeded 440 ng/mL. Subsequent subgroup analysis showed that this positive correlation was more pronounced in males (β = 0.0007, 95% CI: 0.0001-0.0012), age >60 years (β = 0.00015, 95% CI: 0.0007-0.0023), black participants (β = 0.00018, 95% CI: 0.0009-0.0026), and participants with body mass index (BMI) <25 kg/m2 (β = 0.00012, 95% CI: 0.0005-0.0020). In U.S. adults, there was a positive correlation between serum ferritin levels and liver stiffness, which was more pronounced when serum ferritin exceeded 440 ng/mL. Our study suggested that regular serum ferritin testing would be beneficial in monitoring changes in liver stiffness. Male, age >60 years, black participants, and those with a BMI < 25 kg/m2 should be of greater consideration.

Associations of Fatty Acid Profile with Abdominal Obesity in Men

The content of individual unsaturated fatty acids in blood plasma (measured by HPLC) and their association with abdominal obesity in a group of men (mean age 52.2 years) was analyzed. The abdominal obesity was diagnosed according to the criteria of the All-Russian Scientific Society of Cardiology (waist circumference >94 cm). Men with abdominal obesity had higher levels of ω-6 γ-linolenic and dihomo-γ-linolenic acids, as well as ω-3 eicosapentaenoic and docosahexaenoic acids. They also had significantly elevated plasma levels of triglycerides and glucose and lower levels of HDL. Using single-factor ROC analysis we determined optimal cut-off thresholds for fatty acid levels indicating the presence of abdominal obesity. The results of regression analysis showed that the level of γ-linolenic acid is directly associated with the chance of abdominal obesity.s.

Advances in peripheral blood biomarkers of patients with Alzheimer's disease: Moving closer to personalized therapies

Recently, measurable peripheral biomarkers in the plasma of patients with Alzheimer's disease (AD) have gained considerable clinical interest. Several studies have identified one or more blood signatures that may facilitate the development of novel diagnostic and therapeutic strategies. For instance, changes in peripheral amyloid β42 (Aβ42) levels have been largely investigated in patients with AD and correlated with the progression of the pathology, although with controversial results. In addition, tumor necrosis factor α (TNFα) has been identified as an inflammatory biomarker strongly associated with AD, and several studies have consistently suggested the pharmacological targeting of TNFα to reduce systemic inflammation and prevent neurotoxicity in AD. Moreover, alterations in plasma metabolite levels appear to predict the progression of systemic processes relevant to brain functions. In this study, we analyzed the changes in the levels of Aβ42, TNFα, and plasma metabolites in subjects with AD and compared the results with those in healthy elderly (HE) subjects. Differences in plasma metabolites of patients with AD were analyzed with respect to Aβ42, TNFα, and the Mini-Mental State Examination (MMSE) score, searching for plasma signatures that changed simultaneously. In addition, the phosphorylation levels of the Tyr682 residue of the amyloid precursor protein (APP), which we previously proposed as a biomarker of AD, were measured in five HE and five AD patients, in whom the levels of Aβ42, TNFα, and two plasma lipid metabolites increased simultaneously. Overall, this study highlights the potential of combining different plasma signatures to define specific clinical phenotypes of patient subgroups, thus paving the way for the stratification of patients with AD and development of personalized approaches.

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

Background

We investigated systemic biochemical changes in Alzheimer's disease (AD) by investigating the relationship between circulating plasma metabolites and both clinical and biomarker-assisted diagnosis of AD.

Methods

We used an untargeted approach with liquid chromatography coupled to high-resolution mass spectrometry to measure exogenous and endogenous small molecule metabolites in plasma from 150 individuals clinically diagnosed with AD and 567 age-matched elderly without dementia of Caribbean Hispanic ancestry. Plasma biomarkers of AD were also measured including P-tau181, Aβ40, Aβ42, total tau, neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP). Association of individual and co-expressed modules of metabolites were tested with the clinical diagnosis of AD, as well as biologically-defined AD pathological process based on P-tau181 and other biomarker levels.

Results

Over 4000 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). Restricted to individuals without an APOE ε4 allele (OR=0.89 [0.84-0.94], p= 8.7e-05), the association remained. 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 reflecting different pathways enriched in early and middle stages of disease.

Conclusions

Our findings indicate that 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 that biologically-based diagnostic criteria may aid in the identification of unique pathogenic mechanisms.

Non-alcoholic Steatohepatitis in Asians: Current Perspectives and Future Directions

Non-alcoholic steatohepatitis (NASH) is a subset of non-alcoholic fatty liver disease (NAFLD), which, apart from excess fat in the liver, may be characterised by some level of inflammatory infiltration and fibrogenesis, occasionally progressing to liver cirrhosis or hepatocellular carcinoma (HCC). The objective of the current review is to elucidate the rising prevalence, the role of microbiome and genetics in pathogenesis, diagnostic challenges, and novel treatment alternatives for NASH. Newer diagnostic techniques are being developed since using liver biopsy in a larger population is not a reasonable option and is primarily restricted to clinical research, at least in developing countries. Besides these technical challenges, another important factor leading to deviation from guideline practice is the lack of health insurance coverage in countries like India. It leads to reluctance on the part of physicians and patients to delay required tests to curb out-of-pocket expenditure. There is no cure for NASH, with liver transplantation remaining the last option for those who progress to end-stage liver disease (ESLD) or are detected with early-stage HCC. Thus, lifestyle modification remains the only viable option for many, but compliance and long-term adherence remain major challenges. In obese individuals, bariatric surgery and weight reduction have shown favourable results. In patients with less severe obesity, endoscopic bariatric metabolic therapies (EBMT) are rapidly emerging as less invasive therapies. However, access and acceptability remain poor for these weight reduction methods. Therefore, intense research is being conducted for potential newer drug classes with several agents currently in phase II or III of clinical development. Some of these have demonstrated promising results, such as a reduction in hepatic fat content, and attenuation of fibrosis with an acceptable tolerability profile in phase II studies. The developments in the management of NASH have been fairly encouraging. Further well-designed long-term prospective studies should be undertaken to generate evidence with definitive results.

Pterostilbene could alleviate diabetic cognitive impairment by suppressing TLR4/NF-кB pathway through microbiota-gut-brain axis

Diabetic cognitive impairment (DCI) is a serious neurodegenerative disorder caused by diabetes, with chronic inflammation being a crucial factor in its pathogenesis. Pterostilbene is a well-known natural stilbene derivative that has excellent anti-inflammatory activity, suggesting its potential medicinal advantages for treating DCI. Therefore, this study is to explore the beneficial effects of pterostilbene for improving cognitive dysfunction in DCI mice. A diabetic model was induced by a high-fat diet plus streptozotocin (40 mg·kg-1 ) for consecutive 5 days. After the animals were confirmed to be in a diabetic state, they were treated with pterostilbene (20 or 60 mg·kg-1 , i.g.) for 10 weeks. Pharmacological evaluation showed pterostilbene could ameliorate cognitive dysfunction, regulate glycolipid metabolism disorders, improve neuronal damage, and reduce the accumulation of β-amyloid in DCI mice. Pterostilbene alleviated neuroinflammation by suppressing oxidative stress and carbonyl stress damage, astrocyte and microglia activation, and dopaminergic neuronal loss. Further investigations showed that pterostilbene reduced the level of lipopolysaccharide, modulated colon and brain TLR4/NF-κB signaling pathways, and decreased the release of inflammatory factors, which in turn inhibited intestinal inflammation and neuroinflammation. Furthermore, pterostilbene could also improve the homeostasis of intestinal microbiota, increase the levels of short-chain fatty acids and their receptors, and suppress the loss of intestinal tight junction proteins. In addition, the results of plasma non-targeted metabolomics revealed that pterostilbene could modulate differential metabolites and metabolic pathways associated with inflammation, thereby suppressing systemic inflammation in DCI mice. Collectively, our study found for the first time that pterostilbene could alleviate diabetic cognitive dysfunction by inhibiting the TLR4/NF-κB pathway through the microbiota-gut-brain axis, which may be one of the potential mechanisms for its neuroprotective effects.

Circulating ACE2 level and zinc/albumin ratio as potential biomarkers for a precision medicine approach to COVID-19

Highly mutable influenza is successfully countered based on individual susceptibility and similar precision-like medicine approach should be effective against SARS-COV-2. Among predictive markers to bring precision medicine to COVID-19, circulating ACE2 has potential features being upregulated in both severe COVID-19 and predisposing comorbidities. Spike SARS-CoVs were shown to induce ADAM17-mediated shedding of enzymatic active ACE2, thus accounting for its increased activity that has also been suggested to induce positive feedback loops leading to COVID-19-like manifestations. For this reason, pre-existing ACE2 activity and inhibition of ACE2/ADAM17 zinc-metalloproteases through zinc chelating agents have been proposed to predict COVID-19 outcome before infection and to protect from COVID-19, respectively. Since most diagnostic laboratories are not equipped for enzymatic activity determination, other potential predictive markers of disease progression exploitable by diagnostic laboratories were explored. Concentrations of circulating albumin, zinc, ACE2 protein and its activity were investigated in healthy, diabetic (COVID-19-susceptible) and SARS-CoV-2-negative COVID-19 individuals. ACE2 both protein levels and activity significantly increased in COVID-19 and diabetic patients. Abnormal high levels of ACE2 characterised a subgroup (16-19%) of diabetics, while COVID-19 patients were characterised by significantly higher zinc/albumin ratios, pointing to a relative increase of albumin-unbound zinc species, such as free zinc ones. Data on circulating ACE2 levels are in line with the hypothesis that they can drive susceptibility to COVID-19 and elevated zinc/albumin ratios support the therapeutic use of zinc chelating inhibitors of ACE2/ADAM17 zinc-metalloproteases in a targeted therapy for COVID-19.

Effects of Menaquinone-7 on the Bone Health of Growing Rats under Calcium Restriction: New Insights from Microbiome-Metabolomics

Insufficient calcium intake during growth is a global public health concern. The aim of this study was to investigate the effects of dietary menaquinone-7 (MK-7) on bone accrual in growing Sprague-Dawley rats under calcium restriction. Following 13 weeks of treatment, various bone quality parameters, including microarchitecture, were measured. Fecal and cecal samples were subjected to microbiome (16S rRNA gene sequencing) analyses, while metabolomics analysis of the cecum and humerus samples was analyzed based on UHPLC-Q/TOF-MS. We found that calcium deficiency diminished the richness of the microbiome and disrupted microbiome composition, accompanied by an elevation in the relative abundance of Parasutterella. Furthermore, calcium insufficiency escalated the level of isovaleric acid and modified the metabolic profiles. MK-7 supplementation significantly increased the cortical thickness, cortical bone area, and the calcium content of the femur. Apart from improving bone calcium deposition and diminishing bone resorption, the mechanisms underlying the beneficial effects of MK on bone quality also involve the modulation of the host's metabolic pathways and the composition of gut microbiota. The gut-bone axis holds promise as an efficacious target for ameliorating calcium deficiency in children's bone quality, and MK-7 is a promising dietary supplement from this perspective.

Natural Drugs: A New Direction for the Prevention and Treatment of Diabetes

Insulin resistance, as a common pathological process of many metabolic diseases, including diabetes and obesity, has attracted much attention due to its relevant influencing factors. To date, studies have mainly focused on the shared mechanisms between mitochondrial stress and insulin resistance, and they are now being pursued as a very attractive therapeutic target due to their extensive involvement in many human clinical settings. In view of the complex pathogenesis of diabetes, natural drugs have become new players in diabetes prevention and treatment because of their wide targets and few side effects. In particular, plant phenolics have received attention because of their close relationship with oxidative stress. In this review, we briefly review the mechanisms by which mitochondrial stress leads to insulin resistance. Moreover, we list some cytokines and genes that have recently been found to play roles in mitochondrial stress and insulin resistance. Furthermore, we describe several natural drugs that are currently widely used and give a brief overview of their therapeutic mechanisms. Finally, we suggest possible ideas for future research related to the unique role that natural drugs play in the treatment of insulin resistance through the above targets.

Updates on Triple-Negative Breast Cancer in Type 2 Diabetes Mellitus Patients: From Risk Factors to Diagnosis, Biomarkers and Therapy

Triple-negative breast cancer (TNBC) is usually the most malignant and aggressive mammary epithelial tumor characterized by the lack of expression for estrogen receptors and progesterone receptors, and the absence of epidermal growth factor receptor (HER)2 amplification. Corresponding to 15-20% of all breast cancers and well-known by its poor clinical outcome, this negative receptor expression deprives TNBC from targeted therapy and makes its management therapeutically challenging. Type 2 diabetes mellitus (T2DM) is the most common ageing metabolic disorder due to insulin deficiency or resistance resulting in hyperglycemia, hyperinsulinemia, and hyperlipidemia. Due to metabolic and hormonal imbalances, there are many interplays between both chronic disorders leading to increased risk of breast cancer, especially TNBC, diagnosed in T2DM patients. The purpose of this review is to provide up-to-date information related to epidemiology and clinicopathological features, risk factors, diagnosis, biomarkers, and current therapy/clinical trials for TNBC patients with T2DM compared to non-diabetic counterparts. Thus, in-depth investigation of the diabetic complications on TNBC onset, development, and progression and the discovery of biomarkers would improve TNBC management through early diagnosis, tailoring therapy for a better outcome of T2DM patients diagnosed with TNBC.

Glucose-Responsive Microgel Comprising Conventional Insulin and Curcumin-Laden Nanoparticles: a Potential Combination for Diabetes Management

Successful management of type 2 diabetes mellitus (T2DM), a complex and chronic disease, requires a combination of anti-hyperglycemic and anti-inflammatory agents. Here, we have conceptualized and tested an integrated "closed-loop mimic" in the form of a glucose-responsive microgel (GRM) based on chitosan, comprising conventional insulin (INS) and curcumin-laden nanoparticles (nCUR) as a potential strategy for effective management of the disease. In addition to mimicking the normal, on-demand INS secretion, such delivery systems display an uninterrupted release of nCUR to combat the inflammation, oxidative stress, lipid metabolic abnormality, and endothelial dysfunction components of T2DM. Additives such as gum arabic (GA) led to a fivefold increased INS loading capacity compared to GRM without GA. The GRMs showed excellent in vitro on-demand INS release, while a constant nCUR release is observed irrespective of glucose concentrations. Thus, this study demonstrates a promising drug delivery technology that can simultaneously, and at physiological/pathophysiological relevance, deliver two drugs of distinct physicochemical attributes in the same formulation.

Dietary intakes of branched-chain amino acids and plasma lipid profiles among filipino women in Korea: the Filipino Women's Diet and Health Study (FiLWHEL)

BACKGROUND

The potential role of dietary branched-chain amino acids (BCAA) in metabolic health, including cardiovascular disease and diabetes, is evolving, and it is yet to be understood if dietary BCAA intakes are associated with plasma lipid profiles or dyslipidaemia. This study tested the association of dietary BCAA intakes with plasma lipid profiles and dyslipidaemia among Filipino women in Korea.

METHODS

Energy-adjusted dietary BCAA intakes (isoleucine, leucine, valine, and total BCAA) and fasting blood profiles of triglycerides (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), and low-density lipoprotein-cholesterol (LDL-C) were determined in a sample of 423 women enrolled in the Filipino Women's Diet and Health Study (FiLWHEL). The generalized linear model was applied to estimate least-square (LS) means and 95% confidence intervals (CIs) and compare plasma TG, TC, HDL-C, and LDL-C across tertile distribution of energy-adjusted dietary BCAA intakes at P < 0.05.

RESULTS

Mean of energy-adjusted dietary total BCAA intake was 8.3 ± 3.9 g/d. Average plasma lipid profiles were 88.5 ± 47.4 mg/dl for TG, 179.7 ± 34.5 mg/dl for TC, 58.0 ± 13.7 mg/dl for HDL-C, and 104.0 ± 30.5 mg/dl for LDL-C. LS means, and 95% CIs across tertiles of energy-adjusted total BCAA intakes were 89.9 mg/dl, 88.8 mg/dl and 85.8 mg/dl (P-trend = 0.45) for TG, 179.1 mg/dl, 183.6 mg/dl and 176.5 mg/dl (P-trend = 0.48) for TC, 57.5 mg/dl, 59.6 mg/dl and 57.1 mg/dl (P-trend = 0.75) for HDL-C and 103.6 mg/dl, 106.2 mg/dl and 102.3 mg/dl (P-trend = 0.68) for LDL-C. Furthermore, the multivariable-adjusted prevalence ratios and 95% confidence intervals for dyslipidaemia across increasing tertile distribution of energy-adjusted total BCAA intake were; 1.00, 0.67 (0.40, 1.13) and 0.45 (0.16, 1.27; P-trend = 0.03) for the first, second and third tertile, respectively.

CONCLUSIONS

Higher dietary intakes of BCAA presented a statistically significant inverse trend with the prevalence of dyslipidaemia among Filipino women in this study and testing these associations in longitudinal studies may be necessary to confirm these findings.

Glycine: The Smallest Anti-Inflammatory Micronutrient

Glycine is a non-essential amino acid with many functions and effects. Glycine can bind to specific receptors and transporters that are expressed in many types of cells throughout an organism to exert its effects. There have been many studies focused on the anti-inflammatory effects of glycine, including its abilities to decrease pro-inflammatory cytokines and the concentration of free fatty acids, to improve the insulin response, and to mediate other changes. However, the mechanism through which glycine acts is not clear. In this review, we emphasize that glycine exerts its anti-inflammatory effects throughout the modulation of the expression of nuclear factor kappa B (NF-κB) in many cells. Although glycine is a non-essential amino acid, we highlight how dietary glycine supplementation is important in avoiding the development of chronic inflammation.

Metabolomic profiles in serum and urine uncover novel biomarkers in children with nephrotic syndrome

BACKGROUND

Nephrotic syndrome is common in children and adults worldwide, and steroid-sensitive nephrotic syndrome (SSNS) accounts for 80%. Aberrant metabolism involvement in early SSNS is sparsely studied, and its pathogenesis remains unclear. Therefore, the goal of this study was to investigate the changes in initiated SSNS patients-related metabolites through serum and urine metabolomics and discover the novel potential metabolites and metabolic pathways.

METHODS

Serum samples (27 SSNS and 56 controls) and urine samples (17 SSNS and 24 controls) were collected. Meanwhile, the non-targeted analyses were performed by ultra-high-performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-QTOF-MS) to determine the changes in SSNS. We applied the causal inference model, the DoWhy model, to assess the causal effects of several selected metabolites. An ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to validate hits (D-mannitol, dulcitol, D-sorbitol, XMP, NADPH, NAD, bilirubin, and α-KG-like) in 41 SSNS and 43 controls. In addition, the metabolic pathways were explored.

RESULTS

Compared to urine, the metabolism analysis of serum samples was more clearly discriminated at SSNS. 194 differential serum metabolites and five metabolic pathways were obtained in the SSNS group. Eight differential metabolites were identified by establishing the diagnostic model for SSNS, and four variables had a positive causal effect. After validation by targeted MS, except XMP, others have similar trends like the untargeted metabolic analysis.

CONCLUSION

With untargeted metabolomics analysis and further targeted quantitative analysis, we found seven metabolites may be new biomarkers for risk prediction and early diagnosis for SSNS.