Comprehensive Metabolic Profiling of Inflammation Indicated Key Roles of Glycerophospholipid and Arginine Metabolism in Coronary Artery Disease

Longitudinal associations of an exposome score with serum metabolites from childhood to adolescence

Environmental and lifestyle factors, including air pollution, impaired diet, and low physical activity, have been associated with cardiometabolic risk factors in childhood and adolescence. However, environmental and lifestyle exposures do not exert their physiological effects in isolation. This study investigated associations between an exposome score to measure the impact of multiple exposures, including diet, physical activity, sleep duration, air pollution, and socioeconomic status, and serum metabolites measured using LC-MS and NMR, compared to the individual components of the score. A general population of 504 children aged 6-9 years at baseline was followed up for eight years. Data were analysed with linear mixed-effects models using the R software. The exposome score was associated with 31 metabolites, of which 12 metabolites were not associated with any individual exposure category. These findings highlight the value of a composite score to predict metabolic changes associated with multiple environmental and lifestyle exposures since childhood.

Multi-Omics Reveals the Effects of Spirulina platensis Powder Replacement of Fish Meal on Intestinal Metabolism and Stress in Zig-Zag Eel (Mastacembelus armatus)

The booming aquaculture industry has created a strong demand for fishmeal and increased environmental pressures. Spirulina, as a potential alternative to fishmeal, has been shown to have growth-promoting and animal health-enhancing properties. In this study, 600 large spiny loaches, divided into five experimental groups, F0, F1, F2, F3, and F4, were reared for 10 weeks using Spirulina platensis powder (SPP) as a substitute for 0%, 5%, 10%, 15%, and 20% of fishmeal, respectively. The results of intestinal physiological indexes showed that superoxide dismutase was lower than F0 in all treatment groups, and the activity of F3 was significantly lower than F0 (p < 0.05). The activity of malondialdehyde was significantly higher than that of F0 in all groups except F3 (p < 0.05). The addition of SPP also led to a decrease in the activity of acid phosphatase in the intestine, which was significantly lower in all treatment groups compared to the F0 group (p < 0.05). The results of serum physiology showed that the activity of superoxide dismutase in serum gradually increased with the increase in the percentage of SPP addition, and the F3 group produced a significant difference from the F0 group (p < 0.05). The transcriptomics results showed that DEGs in the low percentage substitution group (<15%) were mostly enriched in metabolism-related pathways, such as bile secretion; DEGs in the high percentage substitution group (>15%) were mostly enriched in inflammation-related pathways, such as complement p and coagulation cascades. Metabolomics confirmed that nicotinate and nicotinamide metabolism and glycerophospholipid metabolism were the two pathways that were significantly enriched in the treatment groups of fishmeal replacement by SPP. The present study demonstrated that a low percentage (<15%) of fishmeal replacement by SPP in feed mobilized MA digestive metabolism, whereas a high percentage (>15%) of replacement induced intestinal stress. Considering the health and farm efficiency aspects, the proportion of SPP in feed formulation for MA should be less than 15%.

Alterations in metabolome and lipidome in patients with in-stent restenosis

CONTEXT

In-stent restenosis (ISR) can lead to blood flow obstruction, insufficient blood supply to the brain, and may even result in serious complications such as stroke. Endothelial cell hyperproliferation and thrombosis are the primary etiologies, frequently resulting in alterations in intravascular metabolism. However, the metabolic changes related to this process are still undermined.

OBJECTIVE

We tried to characterize the serum metabolome of patients with ISR and those with non-restenosis (NR) using metabolomics and lipidomics, exploring the key metabolic pathways of this pathological phenomenon.

RESULTS

We observed that the cysteine and methionine pathways, which are associated with cell growth and oxidative homeostasis, showed the greatest increase in the ISR group compared to the NR group. Within this pathway, the levels of N-formyl-l-methionine and L-methionine significantly increased in the ISR group, along with elevated levels of downstream metabolites such as 2-ketobutyric acid, pyruvate, and taurocholate. Additionally, an increase in phosphatidylcholine (PC) and phosphatidylserine (PS), as well as a decrease in triacylglycerol in the ISR group, indicated active lipid metabolism in these patients, which could be a significant factor contributing to the recurrence of blood clots after stent placement. Importantly, phenol sulfate and PS(38:4) were identified as potential biomarkers for distinguishing ISR, with an area under the curve of more than 0.85.

CONCLUSIONS

Our study revealed significant metabolic alterations in patients with ISR, particularly in the cysteine and methionine pathways, with phenol sulfate and PS(38:4) showing promise for ISR identification.

Physiological Adaptation of Fenneropenaeus chinensis in Response to Saline-Alkaline Stress Revealed by a Combined Proteomics and Metabolomics Method

The rapid development of the mariculture industry has been hindered by limited coastal aquaculture space. To utilize the abundant inland saline-alkaline water, we studied the physiological effects of high carbonate alkalinity stress and high pH stress on Fenneropenaeus chinensis. The study employed quantitative proteomics by tandem mass tag (TMT) and non-targeted metabolomics analysis using a liquid chromatograph mass spectrometer (LC-MS) to understand the physiological and biochemical adaptive mechanisms of the hepatopancreas of F. chinensis in response to saline-alkaline stress at the molecular level. We designed two stress groups as follows: a high carbonate alkalinity (CA) group and a combined high carbonate alkalinity and high pH (CP) group. The study found that the protein and metabolic profiles of the two stress groups were changed, and the CP group, which was exposed to dual stresses, incurred more severe damage to the hepatopancreas compared to that of the CA group. After exposure to CA and CP, the hepatopancreas of F. chinensis showed significant alterations in 455 proteins and 50 metabolites, and 1988 proteins and 272 metabolites, respectively. In addition, F. chinensis upregulated the level of energy metabolism in the hepatopancreas to defend against osmotic imbalance caused by CA or CP stress, which was demonstrated by the significant upregulation of important proteins and metabolites in glycolysis, pyruvate metabolism, TCA cycle, and fatty acid oxidation. Additionally, pattern recognition receptors, the phenol oxidase system, and various immune-related metabolic enzymes and metabolites were also affected. The immune homeostasis of F. chinensis was affected by the alteration of the antioxidant system following exposure to CA or CP. These findings provide valuable information for F. chinensis saline-alkaline water cultivation practices.

Identification of the serum metabolites associated with cow milk consumption in Chinese Peri-/Postmenopausal women

Cow milk consumption (CMC) and downstream alterations of serum metabolites are commonly considered important factors regulating human health status. Foods may lead to metabolic changes directly or indirectly through remodelling gut microbiota (GM). We sought to identify the metabolic alterations in Chinese Peri-/Postmenopausal women with habitual CMC and explore if the GM mediates the CMC-metabolite associations. 346 Chinese Peri-/Postmenopausal women participants were recruited in this study. Fixed effects regression and partial least squares discriminant analysis (PLS-DA) were applied to reveal alterations of serum metabolic features in different CMC groups. Spearman correlation coefficient was computed to detect metabolome-metagenome association. 36 CMC-associated metabolites including palmitic acid (FA(16:0)), 7alpha-hydroxy-4-cholesterin-3-one (7alphaC4), citrulline were identified by both fixed effects regression (FDR < 0.05) and PLS-DA (VIP score > 2). Some significant metabolite-GM associations were observed, including FA(16:0) with gut species Bacteroides ovatus, Bacteroides sp.D2. These findings would further prompt our understanding of the effect of cow milk on human health.

Integrated time-series biochemical, transcriptomic, and metabolomic analyses reveal key metabolites and signaling pathways in the liver of the Chinese soft-shelled turtle (Pelodiscus sinensis) against Aeromonas hydrophila infection

Introduction

Aeromonas hydrophila, a bacterium widely distributed in the natural environment, causes multiple diseases in various animals. Exploring the mechanism of the host defense against A. hydrophila can help develop efficient strategies against Aeromonas infection.

Methods

Herein, we investigated the temporal influence of A. hydrophila on the Chinese soft-shelled turtle, an economically important species, at the biochemical, transcriptomic, and metabolomic levels. Plasma parameters were detected with the test kits. Transcriptome and metabolome were respectively applied to screen the differentially expressed genes and metabolites.

Results

The contents or activities of these plasma parameters were significantly increased at 24 hpi and declined at 96 hpi, indicating that 24 and 96 hpi were two important time points during infection. Totals of 3121 and 274 differentially expressed genes (DEGs) from the transcriptome while 74 and 91 differentially abundant metabolites (DAMs) from the metabolome were detected at 24 and 96 hpi. The top DEGs at 24 hpi included Ccl2, Ccl3, Ccl4, Il1β, Il6, Il7, Il15, Tnf, and Tnfr1 while Zap70, Cd3g, Cd8a, Itk, Pik3r3, Cd247, Malt1, and Cd4 were the most abundant at 96 hpi. The predominant DAMs included O-phospho-L-serine, γ-Aminobutyric acid, orotate, L-tyrosine, and L-tryptophan at 24 hpi, as well as L-glutamic acid, L-arginine, glutathione, glutathione disulfide, and citric acid at 96 hpi.

Discussion

The combined analysis of DEGs and DAMs revealed that tryptophan metabolism, nicotinate and nicotinamide metabolism, as well as starch and sucrose metabolism, were the most important signaling pathways at the early infective stage while tyrosine metabolism, pyrimidine metabolism, as well as alanine, aspartate and glutamate metabolism were the most crucial pathways at the later stage. In general, our results indicated that the Chinese soft-shelled turtle displays stage-specific physiological responses to resist A. hydrophila infection.

Prenatal exposure to environmental contaminants and cord serum metabolite profiles in future immune-mediated diseases

BACKGROUND

Prenatal exposure to environmental contaminants is a significant health concern because it has the potential to interfere with host metabolism, leading to adverse health effects in early childhood and later in life. Growing evidence suggests that genetic and environmental factors, as well as their interactions, play a significant role in the development of autoimmune diseases.

OBJECTIVE

In this study, we hypothesized that prenatal exposure to environmental contaminants impacts cord serum metabolome and contributes to the development of autoimmune diseases.

METHODS

We selected cord serum samples from All Babies in Southeast Sweden (ABIS) general population cohort, from infants who later developed one or more autoimmune-mediated and inflammatory diseases: celiac disease (CD), Crohn's disease (IBD), hypothyroidism (HT), juvenile idiopathic arthritis (JIA), and type 1 diabetes (T1D) (all cases, N = 62), along with matched controls (N = 268). Using integrated exposomics and metabolomics mass spectrometry (MS) based platforms, we determined the levels of environmental contaminants and metabolites.

RESULTS

Differences in exposure levels were found between the controls and those who later developed various diseases. High contaminant exposure levels were associated with changes in metabolome, including amino acids and free fatty acids. Specifically, we identified marked associations between metabolite profiles and exposure levels of deoxynivalenol (DON), bisphenol S (BPS), and specific per- and polyfluorinated substances (PFAS).

IMPACT STATEMENT

Abnormal metabolism is a common feature preceding several autoimmune and inflammatory diseases. However, few studies compared common and specific metabolic patterns preceding these diseases. Here we hypothesized that exposure to environmental contaminants impacts cord serum metabolome, which may contribute to the development of autoimmune diseases. We found differences in exposure levels between the controls and those who later developed various diseases, and importantly, on the metabolic changes associated with the exposures. High contaminant exposure levels were associated with specific changes in metabolome. Our study suggests that prenatal exposure to specific environmental contaminants alters the cord serum metabolomes, which, in turn, might increase the risk of various immune-mediated diseases.

Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets

Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.

Guidance for assessment of the inflammation etiologic criterion for the GLIM diagnosis of malnutrition: A modified Delphi approach

BACKGROUND

The Global Leadership Initiative on Malnutrition (GLIM) approach to malnutrition diagnosis is based on assessment of three phenotypic (weight loss, low body mass index, and reduced skeletal muscle mass) and two etiologic (reduced food intake/assimilation and disease burden/inflammation) criteria, with diagnosis confirmed by fulfillment of any combination of at least one phenotypic and at least one etiologic criterion. The original GLIM description provided limited guidance regarding assessment of inflammation, and this has been a factor impeding further implementation of the GLIM criteria. We now seek to provide practical guidance for assessment of inflammation.

METHODS

A GLIM-constituted working group with 36 participants developed consensus-based guidance through a modified Delphi review. A multiround review and revision process served to develop seven guidance statements.

RESULTS

The final round of review was highly favorable, with 99% overall "agree" or "strongly agree" responses. The presence of acute or chronic disease, infection, or injury that is usually associated with inflammatory activity may be used to fulfill the GLIM disease burden/inflammation criterion, without the need for laboratory confirmation. However, we recommend that recognition of underlying medical conditions commonly associated with inflammation be supported by C-reactive protein (CRP) measurements when the contribution of inflammatory components is uncertain. Interpretation of CRP requires that consideration be given to the method, reference values, and units (milligrams per deciliter or milligram per liter) for the clinical laboratory that is being used.

CONCLUSION

Confirmation of inflammation should be guided by clinical judgment based on underlying diagnosis or condition, clinical signs, or CRP.

Serum metabolome responses induced by long-term inoculation of suspended PM2.5 in chicken

The adverse effects of exposure to fine particulate matter (PM2.5) on body health have attracted global public attention. However, there is limited research on PM2.5 in animal houses. Numerous studies have indicated that long-term exposure to high levels of PM2.5 can cause damage to multiple systems in animals. Poultry houses are one of the primary sources of PM2.5 emissions. However, there is limited research on the effects of PM2.5 exposure on poultry organisms. This study analyzed the histopathological changes in the lung tissue of poultry under PM2.5 exposure conditions. It used the LC-MS method to analyze the alterations in the serum metabolomic profile of poultry. This study confirmed that long-term exposure to high levels of PM2.5 had significantly reduced the growth performance of poultry. Histopathological slides of the lung tissue in chickens exposed to long-term retention of PM2.5 clearly showed significant damage. Furthermore, the serum metabolome analysis revealed significant changes in the serum metabolic profile of chickens exposed to long-term PM2.5 exposure. Specifically, there were notable alterations in the Glycerophospholipid metabolism, Steroid hormone biosynthesis, and Phenylalanine, tyrosine, and tryptophan biosynthesis pathways.

Increased Systemic Immune-Inflammation Index Was Associated with Type 2 Diabetic Peripheral Neuropathy: A Cross-Sectional Study in the Chinese Population

Background

Systemic immune-inflammation index (SII), a novel inflammatory marker, has been demonstrated to be associated with type 2 diabetes mellitus (T2DM) and its vascular complications, however, the relation between SII and diabetic peripheral neuropathy (DPN) has been never reported. We aimed to explore whether SII is associated with DPN in Chinese population.

Methods

A cross-sectional study was conducted among 1460 hospitalized patients with T2DM. SII was calculated as the platelet count × neutrophil count/lymphocyte count, and its possible association with DPN was investigated by correlation and multivariate logistic regression analysis, and subgroup analyses.

Results

Patients with higher SII quartiles had higher vibration perception threshold and prevalence of DPN (all P<0.01), and SII was independently positively associated with the prevalence of DPN (P<0.01). Multivariate logistic regression analysis showed that the risk of prevalence of DPN increased progressively across SII quartiles (P for trend <0.01), and participants in the highest quartile of SII was at a significantly increased risk of prevalent DPN compared to those in the lowest quartile after adjustment for potential confounding factors (odds rate: 1.211, 95% confidence intervals 1.045-1.404, P<0.05). Stratified analysis revealed positive associations of SII quartiles with risk of prevalent DPN only in men, people less than 65 years old, with body mass index <24 kg/m2, duration of diabetes >5 years, hypertension, dyslipidaemia, poor glycaemic control, and estimated glomerular filtration rate <90 mL/min/1.73 m2 (P for trend <0.01 or P for trend <0.05). The receiver operating characteristic curve analysis revealed that the optimal cut-off point of SII for predicting DPN was 617.67 in patients with T2DM, with a sensitivity of 45.3% and a specificity of 73%.

Conclusion

The present study showed that higher SII is independently associated with increased risk of DPN, and SII might serve as a new risk biomarker for DPN in Chinese population.

A serum metabolomics study of vascular cognitive impairment patients based on Traditional Chinese medicine syndrome differentiation

Objective: Vascular cognitive impairment (VCI) accounts for approximately 50%-70% of all dementia cases and poses a significant burden on existing medical systems. Identifying an optimal strategy for preventing VCI and developing efficient symptomatic treatments remains a significant challenge. Syndrome differentiation represents a fundamental approach for personalized diagnosis and treatment in Traditional Chinese Medicine (TCM) and aligns with the principles of precision medicine. The objective of this study was to elucidate the metabolic characteristics of VCI based on TCM syndrome differentiation, thus providing novel insights into the diagnosis and treatment of VCI. Methods: A 2-year cross-sectional cognitive survey was conducted in four communities in Beijing between September 2020 and November 2022. The syndrome differentiation of participants was based on the Kidney-Yang Deficiency Syndrome Scale (KYDSS), which was originally developed by Delphi expert consultation. The identification of serum metabolites was performed by Ultra performance liquid chromatography (UPLC) analysis coupled with an electrospray ionization quadruple time-of-flight mass spectrometer (ESI-QTOF MS). Multivariate, univariate, and pathway analyses were used to investigate metabolic changes. Logistic regression models were also used to construct metabolite panels that were capable of discerning distinct groups. Phospholipase A2 (PLA2) levels were measured by a commercial ELISA kit. Results: A total of 2,337 residents completed the survey, and the prevalence of VCI was 9.84%. Of the patients with VCI, those with Kidney-Yang deficiency syndrome (VCIS) accounted for 70.87% of cases and exhibited more severe cognitive impairments. A total of 80 participants were included in metabolomics study, including 30 with VCIS, 20 without Kidney-Yang deficiency syndrome (VCINS), and 30 healthy control participants (C). Ultimately, 45 differential metabolites were identified when comparing the VCIS group with group C, 65 differential metabolites between the VCINS group and group C, and 27 differential metabolites between the VCIS group and the VCINS group. The downregulation of phosphatidylethanolamine (PE), and phosphatidylcholine (PC) along with the upregulation of lysophosphatidylethanolamine (LPE), lysophosphatidylcholine (LPC), phosphatidic acid (PA) and phospholipase A2 (PLA2) can be considered as the general metabolic characteristics associated with VCI. Dysfunction of glycerophospholipids, particularly LPEs and PCs, was identified as a key metabolic characteristic of VCIS. In particular Glycerophospho-N-Arachidonoyl Ethanolamine (GP-NArE) was discovered for the first time in VCI patients and is considered to represent a potential biomarker for VCIS. The upregulation of PLA2 expression was implicated in the induction of alterations in glycerophospholipid metabolism in both VCIS and VCINS. Moreover, robust diagnostic models were established based on these metabolites, achieving high AUC values of 0.9322, 0.9550, and 0.9450, respectively. Conclusion: These findings contribute valuable information relating to the intricate relationship between metabolic disorders in VCI, neurodegeneration and vascular/neuroinflammation. Our findings also provide a TCM perspective for the precise diagnosis and treatment of VCI in the context of precision medicine.

Multinomial machine learning identifies independent biomarkers by integrated metabolic analysis of acute coronary syndrome

A multi-class classification model for acute coronary syndrome (ACS) remains to be constructed based on multi-fluid metabolomics. Major confounders may exert spurious effects on the relationship between metabolism and ACS. The study aims to identify an independent biomarker panel for the multiclassification of HC, UA, and AMI by integrating serum and urinary metabolomics. We performed a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics study on 300 serum and urine samples from 44 patients with unstable angina (UA), 77 with acute myocardial infarction (AMI), and 29 healthy controls (HC). Multinomial machine learning approaches, including multinomial adaptive least absolute shrinkage and selection operator (LASSO) regression and random forest (RF), and assessment of the confounders were applied to integrate a multi-class classification biomarker panel for HC, UA and AMI. Different metabolic landscapes were portrayed during the transition from HC to UA and then to AMI. Glycerophospholipid metabolism and arginine biosynthesis were predominant during the progression from HC to UA and then to AMI. The multiclass metabolic diagnostic model (MDM) dependent on ACS, including 2-ketobutyric acid, LysoPC(18:2(9Z,12Z)), argininosuccinic acid, and cyclic GMP, demarcated HC, UA, and AMI, providing a C-index of 0.84 (HC vs. UA), 0.98 (HC vs. AMI), and 0.89 (UA vs. AMI). The diagnostic value of MDM largely derives from the contribution of 2-ketobutyric acid, and LysoPC(18:2(9Z,12Z)) in serum. Higher 2-ketobutyric acid and cyclic GMP levels were positively correlated with ACS risk and atherosclerosis plaque burden, while LysoPC(18:2(9Z,12Z)) and argininosuccinic acid showed the reverse relationship. An independent multiclass biomarker panel for HC, UA, and AMI was constructed using the multinomial machine learning methods based on serum and urinary metabolite signatures.

Association of Asymmetric and Symmetric Dimethylarginine with Inflammation in the Population-Based Study of Health in Pomerania

The amino acids arginine (Arg), asymmetric (ADMA) and symmetric dimethylarginine (SDMA) are related to nitric oxide (NO) metabolism and potential markers of two different disease entities: cardiovascular disease such as atherosclerosis and systemic inflammation in critically ill patients with sepsis. Although very different in their pathophysiological genesis, both entities involve the functional integrity of blood vessels. In this context, large population-based data associating NO metabolites with proinflammatory markers, e.g., white blood cell count (WBC), high-sensitivity C-reactive protein (hsCRP), and fibrinogen, or cytokines are sparse. We investigated the association of Arg, ADMA and SDMA with WBC, hsCRP, and fibrinogen in 3556 participants of the Study of Health in Pomerania (SHIP)-TREND study. Furthermore, in a subcohort of 456 subjects, 31 inflammatory markers and cytokines were analyzed. We identified Arg and SDMA to be positively associated with hsCRP (β coefficient 0.010, standard error (SE) 0.002 and 0.298, 0.137, respectively) as well as fibrinogen (β 5.23 × 10-3, SE 4.75 × 10-4 and 0.083, 0.031, respectively). ADMA was not associated with WBC, hsCRP, or fibrinogen. Furthermore, in the subcohort, Arg was inversely related to a proliferation-inducing ligand (APRIL). SDMA was positively associated with osteocalcin, tumor necrosis factor receptor 1 and 2, and soluble cluster of differentiation 30. Our findings provide new insights into the involvement of Arg, ADMA, and SDMA in subclinical inflammation in the general population.

Study on the Common Molecular Mechanism of Metabolic Acidosis and Myocardial Damage Complicated by Neonatal Pneumonia

Pneumonia is a common clinical disease in the neonatal period and poses a serious risk to infant health. Therefore, the understanding of molecular mechanisms is of great importance for the development of methods for the rapid and accurate identification, classification and staging, and even disease diagnosis and therapy of pneumonia. In this study, a nontargeted metabonomic method was developed and applied for the analysis of serum samples collected from 20 cases in the pneumonia control group (PN) and 20 and 10 cases of pneumonia patients with metabolic acidosis (MA) and myocardial damage (MD), respectively, with the help of ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS). The results showed that compared with the pneumonia group, 23 and 21 differential metabolites were identified in pneumonia with two complications. They showed high sensitivity and specificity, with the area under the curve (ROC) of the receiver operating characteristic curve (ROC) larger than 0.7 for each differential molecule. There were 14 metabolites and three metabolic pathways of sphingolipid metabolism, porphyrin and chlorophyll metabolism, and glycerophospholipid metabolism existing in both groups of PN and MA, and PN and MD, all involving significant changes in pathways closely related to amino acid metabolism disorders, abnormal cell apoptosis, and inflammatory responses. These findings of molecular mechanisms should help a lot to fully understand and even treat the complications of pneumonia in infants.

The role of amino acid metabolism in inflammatory bowel disease and other inflammatory diseases

Inflammation is a characteristic symptom of the occurrence and development of many diseases, which is mainly characterized by the infiltration of inflammatory cells such as macrophages and granulocytes, and the increased release of proinflammatory factors. Subsequently, macrophage differentiates and T cells and other regulated factors exhibit anti-inflammatory function, releasing pro- and anti-inflammatory factors to maintain homeostasis. Although reports define various degrees of metabolic disorders in both the inflamed and non-inflamed parts of inflammatory diseases, little is known about the changes in amino acid metabolism in such conditions. This review aims to summarize amino acid changes and mechanisms involved in the progression of inflammatory bowel disease (IBD) and other inflammatory diseases. Since mesenchymal stem cells (MSCs) and their derived exosomes (MSC-EXO) have been found to show promising effects in the treatment of IBD and other inflammatory diseases,their potential in the modulation of amino acid metabolism in the treatment of inflammation is also discussed.

Assessing Metabolic Differences Associated with Exposure to Polybrominated Biphenyl and Polychlorinated Biphenyls in the Michigan PBB Registry

BACKGROUND

Polybrominated biphenyls (PBB) and polychlorinated biphenyls (PCB) are persistent organic pollutants with potential endocrine-disrupting effects linked to adverse health outcomes.

OBJECTIVES

In this study, we utilize high-resolution metabolomics (HRM) to identify internal exposure and biological responses underlying PCB and multigenerational PBB exposure for participants enrolled in the Michigan PBB Registry.

METHODS

HRM profiling was conducted on plasma samples collected from 2013 to 2014 from a subset of participants enrolled in the Michigan PBB Registry, including 369 directly exposed individuals (F0) who were alive when PBB mixtures were accidentally introduced into the food chain and 129 participants exposed to PBB in utero or through breastfeeding, if applicable (F1). Metabolome-wide association studies were performed for PBB-153 separately for each generation and Σ PCB (PCB-118, PCB-138, PCB-153, and PCB-180) in the two generations combined, as both had direct PCB exposure. Metabolite and metabolic pathway alterations were evaluated following a well-established untargeted HRM workflow.

RESULTS

Mean levels were 1.75  ng / mL [standard deviation (SD): 13.9] for PBB-153 and 1.04  ng / mL (SD: 0.788) for Σ PCB . Sixty-two and 26 metabolic features were significantly associated with PBB-153 in F0 and F1 [false discovery rate (FDR) p < 0.2 ], respectively. There were 2,861 features associated with Σ PCB (FDR p < 0.2 ). Metabolic pathway enrichment analysis using a bioinformatics tool revealed perturbations associated with Σ PCB in numerous oxidative stress and inflammation pathways (e.g., carnitine shuttle, glycosphingolipid, and vitamin B9 metabolism). Metabolic perturbations associated with PBB-153 in F0 were related to oxidative stress (e.g., pentose phosphate and vitamin C metabolism) and in F1 were related to energy production (e.g., pyrimidine, amino sugars, and lysine metabolism). Using authentic chemical standards, we confirmed the chemical identity of 29 metabolites associated with Σ PCB levels (level 1 evidence).

CONCLUSIONS

Our results demonstrate that serum PBB-153 is associated with alterations in inflammation and oxidative stress-related pathways, which differed when stratified by generation. We also found that Σ PCB was associated with the downregulation of important neurotransmitters, serotonin, and 4-aminobutanoate. These findings provide novel insights for future investigations of molecular mechanisms underlying PBB and PCB exposure on health. https://doi.org/10.1289/EHP12657.

Plasma metabolomic profiles associated with mortality and longevity in a prospective analysis of 13,512 individuals

Experimental studies reported biochemical actions underpinning aging processes and mortality, but the relevant metabolic alterations in humans are not well understood. Here we examine the associations of 243 plasma metabolites with mortality and longevity (attaining age 85 years) in 11,634 US (median follow-up of 22.6 years, with 4288 deaths) and 1878 Spanish participants (median follow-up of 14.5 years, with 525 deaths). We find that, higher levels of N2,N2-dimethylguanosine, pseudouridine, N4-acetylcytidine, 4-acetamidobutanoic acid, N1-acetylspermidine, and lipids with fewer double bonds are associated with increased risk of all-cause mortality and reduced odds of longevity; whereas L-serine and lipids with more double bonds are associated with lower mortality risk and a higher likelihood of longevity. We further develop a multi-metabolite profile score that is associated with higher mortality risk. Our findings suggest that differences in levels of nucleosides, amino acids, and several lipid subclasses can predict mortality. The underlying mechanisms remain to be determined.

The Effects of 12 Weeks Colostrum Milk Supplementation on the Expression Levels of Pro-Inflammatory Mediators and Metabolic Changes among Older Adults: Findings from the Biomarkers and Untargeted Metabolomic Analysis

Senescence is a normal biological process that is accompanied with a series of deteriorations in physiological function. This study aimed to investigate the effects of bovine colostrum milk supplementation on metabolic changes and the expression of various biomarkers on inflammation, antioxidant and oxidative damage, nutrient metabolism, and genomic stability among older adults. Older adults (50-69 years old) who participated in the 12-week randomized, double-blinded, placebo-controlled trial were instructed to consume the IgCo bovine colostrum-enriched skim milk or regular skim milk (placebo) twice daily. Following 12 weeks of intervention, participants in the intervention group had lower expression levels in pro-inflammatory mediators (CRP, IL-6, and TNF-α), with significant (p < 0.05) interaction effects of the group and time observed. However, no significant interaction effect was observed in the vitamin D, telomerase, 8-OHdG, MDA, and SOD activities. UPLC-MS-based untargeted metabolomics analysis revealed that 22 metabolites were upregulated and 11 were downregulated in the intervention group compared to the placebo group. Glycerophospholipid metabolism, along with cysteine and methionine metabolism were identified as the potential metabolic pathways that are associated with bovine colostrum milk consumption. In conclusion, consuming bovine colostrum milk may induce metabolic changes and reduce the expression of various pro-inflammatory mediators, thus improving the immune function in older adults.

Coronary Artery Disease with Elevated Levels of HDL Cholesterol Is Associated with Distinct Lipid Signatures

Levels of high-density lipoprotein cholesterol (HDL-C) are inversely associated with the incidence of coronary artery disease (CAD). However, the underlying mechanism of CAD in the context of elevated HDL-C levels is unclear. Our study aimed to explore the lipid signatures in patients with CAD and elevated HDL-C levels and to identify potential diagnostic biomarkers for these conditions. We measured the plasma lipidomes of forty participants with elevated HDL-C levels (men with >50 mg/dL and women with >60 mg/dL), with or without CAD, using liquid chromatography-tandem mass spectrometry. We analyzed four hundred fifty-eight lipid species and identified an altered lipidomic profile in subjects with CAD and high HDL-C levels. In addition, we identified eighteen distinct lipid species, including eight sphingolipids and ten glycerophospholipids; all of these, except sphingosine-1-phosphate (d20:1), were higher in the CAD group. Pathways for sphingolipid and glycerophospholipid metabolism were the most significantly altered. Moreover, our data led to a diagnostic model with an area under the curve of 0.935, in which monosialo-dihexosyl ganglioside (GM3) (d18:1/22:0), GM3 (d18:0/22:0), and phosphatidylserine (38:4) were combined. We found that a characteristic lipidome signature is associated with CAD in individuals with elevated HDL-C levels. Additionally, the disorders of sphingolipid as well as glycerophospholipid metabolism may underlie CAD.

Study on the Mechanism of Jiaotai Pill Intervention on Insomnia Animal Model Based on Gut Microbiome and Metabolomics

Background

With the continuous advancement of clinical application and experimental research of JTP, the application prospect of JTP in nervous system diseases and metabolic diseases is becoming increasingly clear. Jiaotai Pill (JTP) is a traditional Chinese medicine formula for insomnia, consisting of Coptidis rhizoma and Cinnamomi cortex, which dates back to Han Shi Yi Tong in the Ming Dynasty of China.

Objective

Based on the brain-gut axis theory, this paper aims to explore the potential mechanism of JTP in the intervention of insomnia by using intestinal microbiome and metabolomics technology, taking the animal model of insomnia as the research object, so as to provide experimental basis for its further application and research.

Methods

The insomnia mouse model was induced by intraperitoneal injection of para-chlorophenylalanine (PCPA). The clinical equivalent dose of JTP was administered by gavage for one week. The efficacy of JTP was evaluated by behavioral tests, serum biochemical detection, and brain histomorphological observation. The contents of cecum were analyzed by microbiomics and metabolomics.

Results

The results show that insomnia caused by PCPA led to daytime dysfunction, higher HPA axis hormone levels, and morphologically impaired hippocampus. JTP reversed these anomalies. Omics research indicates that JTP significantly reduced gut α diversity; at the phylum level, JTP reduced the relative abundance of Firmicutes, Deferribacterota, Cyanobacteria, and Actinobacteriota and increased the relative abundance of Verrucomicrobiota, Proteobacteria, and Desulfobacterota. At the genus level, JTP reduced the relative abundance of Muribaculaceae, Lachnospiraceae_NK4A136_group, Alistipes, Colidextribacter, Muribaculum, and Mucispirillum and increased the relative abundance of Bacteroides and Akkermansia. JTP also reversed the activation of the linoleic acid metabolism pathway induced by insomnia. The combined analysis of omics suggests that JTP may play a role by regulating the inflammatory state of the body. Further gene expression analysis of brain tissue confirmed this.

Conclusions

We hypothesize that JTP may achieve insomnia relief by eliminating inflammation-causing bacteria in the gut and reducing inflammation levels through the brain-gut axis, pointing to potential targets and pathways for future research on JTP.

Small molecule metabolites: discovery of biomarkers and therapeutic targets

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

The Landscape of Lipid Metabolism in Lung Cancer: The Role of Structural Profiling

The aim of this study was to explore the relationship between lipids with different structural features and lung cancer (LC) risk and identify prospective biomarkers of LC. Univariate and multivariate analysis methods were used to screen for differential lipids, and two machine learning methods were used to define combined lipid biomarkers. A lipid score (LS) based on lipid biomarkers was calculated, and a mediation analysis was performed. A total of 605 lipid species spanning 20 individual lipid classes were identified in the plasma lipidome. Higher carbon atoms with dihydroceramide (DCER), phosphatidylethanolamine (PE), and phosphoinositols (PI) presented a significant negative correlation with LC. Point estimates revealed the inverse associated with LC for the n-3 PUFA score. Ten lipids were identified as markers with an area under the curve (AUC) value of 0.947 (95%, CI: 0.879-0.989). In this study, we summarized the potential relationship between lipid molecules with different structural features and LC risk, identified a panel of LC biomarkers, and demonstrated that the n-3 PUFA of the acyl chain of lipids was a protective factor for LC.

Multi-Omics Investigation into Acute Myocardial Infarction: An Integrative Method Revealing Interconnections amongst the Metabolome, Lipidome, Glycome, and Metallome

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. This work aims to investigate the translational potential of a multi-omics study (comprising metabolomics, lipidomics, glycomics, and metallomics) in revealing biomechanistic insights into AMI. Following the N-glycomics and metallomics studies performed by our group previously, untargeted metabolomic and lipidomic profiles were generated and analysed in this work via the use of a simultaneous metabolite/lipid extraction and liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis workflow. The workflow was applied to blood plasma samples from AMI cases (n = 101) and age-matched healthy controls (n = 66). The annotated metabolomic (number of features, n = 27) and lipidomic (n = 48) profiles, along with the glycomic (n = 37) and metallomic (n = 30) profiles of the same set of AMI and healthy samples were integrated and analysed. The integration method used here works by identifying a linear combination of maximally correlated features across the four omics datasets, via utilising both block-partial least squares-discriminant analysis (block-PLS-DA) based on sparse generalised canonical correlation analysis. Based on the multi-omics mapping of biomolecular interconnections, several postulations were derived. These include the potential roles of glycerophospholipids in N-glycan-modulated immunoregulatory effects, as well as the augmentation of the importance of Ca–ATPases in cardiovascular conditions, while also suggesting contributions of phosphatidylethanolamine in their functions. Moreover, it was shown that combining the four omics datasets synergistically enhanced the classifier performance in discriminating between AMI and healthy subjects. Fresh and intriguing insights into AMI, otherwise undetected via single-omics analysis, were revealed in this multi-omics study. Taken together, we provide evidence that a multi-omics strategy may synergistically reinforce and enhance our understanding of diseases.

Prognostic implication of lipidomics in patients with coronary total occlusion undergoing PCI

BACKGROUND

Predictors of prognosis in patients with coronary chronic total occlusion (CTO) undergoing elective percutaneous coronary intervention (PCI) have remained lacking. Lipidomic profiling enables researchers to associate lipid species with disease progression and may improve the prediction of cardiovascular events.

METHODS

In the present study, 781 lipids were measured by targeted lipidomic profiling in 350 individuals (50 healthy controls, 50 patients with coronary artery disease and 250 patients with CTO). L1-regularized logistic regression was used to identify lipid species associated with adverse cardiovascular events and create predicting models, which were verified by 10-fold cross-validation (200 repeats). Comparisons were made between a traditional model constructed with clinical characteristics alone and a combined model built with both lipidomic data and traditional factors.

RESULTS

Twenty-four lipid species were dysregulated exclusively in patients with CTO, most of which belonged to sphingomyelin (SM) and triacylglycerol (TAG). Compared with traditional risk factors, new model combining lipids and traditional factors had significantly improved performance in predicting adverse cardiovascular events in CTO patients after PCI (area under the curve, 0.870 vs. 0.726, p < .05; Akaike information criterion, 129 versus 156; net reclassification improvement, 0.312, p < .001; integrated discrimination improvement, 0.244, p < .001). Nomogram was built based on the incorporated model and proved efficient by Kaplan-Meier method.

CONCLUSIONS

Lipidomic profiling revealed lipid species which may participate in the formation of CTO and could contribute to the risk stratification in CTO patients undergoing PCI.