Numerous studies have explored the health impacts of individual metal exposures, yet the effects of metal mixtures on human endogenous metabolism remain largely unexplored. We aimed to assess the serum metabolic signatures of people exposed to metal mixtures. Serum and urine samples were collected from 186 workers at a steel factory in Anhui, China, in September 2019. Inductively coupled plasma mass spectrometry was used to analyze the concentrations of 23 metal elements. The serum metabolome was determined by liquid chromatography-mass spectrometry (LC-MS). A metabolome-wide association study (MWAS) was performed across the metal exposures and metabolism using quantile g-computation modeling. Pathway enrichment analysis was performed using MetaboAnalyst. We identified 226 metabolites associated with metal mixtures, primarily involving lipid metabolism (glycerophospholipids, sphingolipids), amino acid metabolism (arginine and proline, alanine, aspartate and glutamate metabolism) and caffeine metabolic pathways. Exposure to metal mixtures is mainly associated with alterations in lipid metabolism and amino acid metabolism, particularly in the glycerophospholipid and arginine and proline metabolism pathways.

BACKGROUND: Coronary heart disease (CHD) is a common cardiovascular disease that is associated with altered gut microbiota. Enteroviruses, an essential component of the gut microbiome, may play an important role in disease progression. However, the relationship between enteroviruses and CHD remains unclear. The development of high-throughput sequencing technologies has facilitated research on the interconnections between viruses and disease-related metabolites.
RESULTS: Mice were fed a high-fat diet (CHD group) or chow diet (Sham group) for 12 weeks, and ligation of the left anterior descending coronary artery was performed at the end of week 8. After 4 weeks, all animals were euthanised. Subsequently, the animals were evaluated for basic haemato-biochemical parameters and cardiac function, and aorta staining was performed. Based on enteroviral metagenomics and serum UPLC-MS/MS metabolomics analyses, we evaluated the association between enteroviral groups and serum metabolites of CHD mouse model. A high-fat diet and coronary ligation enabled the establishment of the CHD mouse model. Notably, the enterovirus spectrum of the sham group was significantly different from that of the CHD group, with 24 viral communities of different family and species classification, such as Tsarbombavirus, Mingyongvirus, Claudivirus, and Firehammervirus, exhibiting significant differences. In addition, 731 Differential metabolites were detected in the serum of both groups of mice. Correlation network analysis revealed a close relationship between various metabolites related to lipid metabolism and different viruses, including Tsarbombavirus, Mingyongvirus, Claudivirus, and Firehammervirus.
CONCLUSIONS: An animal model of CHD, characterised by lipid disturbance and myocardial ischaemia, was established using a high-fat diet and ligation of the left anterior descending branch of the coronary artery. Tsarbombavirus, Firehammervirus, Mingyongvirus, and Claudivirus were associated with metabolites in the lipid metabolism pathway. The results indicate that Tsarbombavirus may be the main genus interacting with CHD-related metabolites in mice. Conclusively, the findings of our study provide novel insights into the potential relationship enterovirus groups and metabolites associated with CHD.

(1) Background: Dyslipidemia represents a major risk factor for atherosclerosis-driven cardiovascular disease. Emerging evidence suggests a close relationship between cholesterol metabolism and gut microbiota. Recently, we demonstrated that the short-chain fatty acid (SCFA) propionate (PA) reduces serum cholesterol levels through an immunomodulatory mechanism. Here, we investigated the effects of oral PA supplementation on the human serum metabolome and analyzed changes in the serum metabolome in relation to the cholesterol-lowering properties of PA. (2) Methods: The serum metabolome of patients supplemented with either placebo or propionate orally for 8 weeks was assessed using a combination of flow injection analysis-tandem (FIA-MS/MS) as well as liquid chromatography (LC-MS/MS) and mass spectrometry using a targeted metabolomics kit (MxP®Quant 500 kit: BIOCRATES Life Sciences AG, Innsbruck, Austria). A total of 431 metabolites were employed for further investigation in this study. (3) Results: We observed a significant increase in distinct bile acids (GCDCA: fold change = 1.41, DCA: fold change = 1.39, GUDCA: fold change = 1.51) following PA supplementation over the study period, with the secondary bile acid DCA displaying a significant negative correlation with the serum cholesterol levels. (4) Conclusions: Oral supplementation with PA modulates the serum metabolome with a particular impact on the circulatory bile acid profile. Since cholesterol and bile acid metabolism are interconnected, the elevation of the secondary bile acid DCA may contribute to the cholesterol-lowering effect of PA.

In most cases, the number of honeybee stings received by the body is generally small, but honeybee stings can still cause serious allergic reactions. This study fully simulated bee stings under natural conditions and used 1H Nuclear Magnetic Resonance (1H NMR) to analyze the changes in the serum metabolome of Sprague-Dawley (SD) rats stung once or twice by honeybees to verify the impact of this mild sting on the body and its underlying mechanism. The differentially abundant metabolites between the blank control rats and the rats stung by honeybees included four amino acids (aspartate, glutamate, glutamine, and valine) and four organic acids (ascorbic acid, lactate, malate, and pyruvate). There was no separation between the sting groups, indicating that the impact of stinging once or twice on the serum metabolome was similar. Using the Principal Component Discriminant Analysis ( PCA-DA) and Variable Importance in Projection (VIP) methods, glucose, lactate, and pyruvate were identified to help distinguish between sting groups and non-sting groups. Metabolic pathway analysis revealed that four metabolic pathways, namely, the tricarboxylic acid cycle, pyruvate metabolism, glutamate metabolism, and alanine, aspartate, and glutamate metabolism, were significantly affected by bee stings. The above results can provide a theoretical basis for future epidemiological studies of bee stings and medical treatment of patients stung by honeybees.

Increasing evidence has indicated that the gut microbiome plays an important role in chicken growth traits. However, the cecal microbial taxa associated with the growth rates of the Chinese Ningdu yellow chickens are unknown. In this study, shotgun metagenomic sequencing was used to identify cecal bacterial species associated with the growth rate of the Chinese Ningdu yellow chickens. We found that nine cecal bacterial species differed significantly between high and low growth rate chickens, including three species (Succinatimonas hippei, Phocaeicola massiliensis, and Parabacteroides sp. ZJ-118) that were significantly enriched in high growth rate chickens. We identified six Bacteroidales that were significantly enriched in low growth rate chickens, including Barnesiella sp. An22, Barnesiella sp. ET7, and Bacteroidales bacterium which were key biomarkers in differentiating high and low growth rate chickens and were associated with alterations in the functional taxa of the cecal microbiome. Untargeted serum metabolome analysis revealed that 8 metabolites showing distinct enrichment patterns between high and low growth rate chickens, including triacetate lactone and N-acetyl-a-neuraminic acid, which were at higher concentrations in low growth rate chickens and were positively and significantly correlated with Barnesiella sp. An22, Barnesiella sp. ET7, and Bacteroidales bacterium. Furthermore, the results suggest that serum cytokines, such as IL-5, may reduce growth rate and are related to changes in serum metabolites and gut microbes (e.g., Barnesiella sp. An22 and Barnesiella sp. ET7). These results provide important insights into the effects of the cecal microbiome, serum metabolism and cytokines in Ningdu yellow chickens.

SARS-CoV-2 infection has been associated with the increased incidence of acute macular neuroretinopathy (AMN), an infrequent ocular disorder. However, the precise mechanisms underpinning AMN in the context of SARS-CoV-2 infection (AMN-SARS-CoV-2) remain elusive. In this case-control study, 14 patients diagnosed with AMN-SARS-CoV-2 between 2022/12 and 2023/3 were enrolled and compared with 14 SARS-CoV-2-infected individuals without AMN, who served as controls (SARS-CoV-2-no AMN). Metabolomic profiling using ultrahigh-performance liquid chromatography-online electrospray mass spectrometry revealed significant alterations in serum metabolites in AMN-SARS-CoV-2 patients. Coagulation abnormalities were observed in AMN-SARS-CoV-2 patients, and their relationship with metabolic disorders was studied. Finally, a predictive model for AMN-SARS-CoV-2 was established. Seventy-six upregulated and 42 downregulated metabolites were identified in AMN-SARS-CoV-2 cases. Notably, arginine metabolism within the urea cycle was significantly altered, evidenced by variations in ornithine, citrulline,  l-proline, and ADAM levels, correlating with abnormal coagulation markers like platelet crit, fibrinogen degradation product, and fibrinogen. Additionally, increased arginase 1 (AGR1) activity within the urea cycle and reduced nitric oxide synthase activity were observed in AMN-SARS-CoV-2. The integration of urea cycle metabolite levels with coagulation parameters yielded a robust discriminatory model for AMN-SARS-CoV-2, as evidenced by an area under the curve of 0.96. The findings of the present study enhance our comprehension of the underlying metabolic mechanisms associated with AMN-SARS-CoV-2 and offer potential diagnostic markers for this uncommon ocular disorder within the context of SARS-CoV-2 infection.

UNASSIGNED: The progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers.
UNASSIGNED: We analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions.
UNASSIGNED: Despite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95).
UNASSIGNED: In conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker.

Noise pollution has grown to be a major public health issue worldwide. We sought to profile serum metabolite expression changes related to occupational noise exposure by untargeted metabolomics, as well as to evaluate the potential roles of serum metabolites in occupational noise-associated arterial stiffness (AS). Our study involved 30 noise-exposed industrial personnel (Lipo group) and 30 noise-free controls (Blank group). The untargeted metabolomic analysis was performed by employing a UPLC-HRMS. The associations of occupational noise and significant differential metabolites (between Blank/Lipo groups) with AS were evaluated using multivariable-adjusted generalized linear models. We performed the least absolute shrinkage and selection operator regression analysis to further screen for AS\'s risk metabolites. We explored 177 metabolites across 21 categories significantly differentially expressed between Blank/Lipo groups, and these metabolites were enriched in 20 metabolic pathways. Moreover, 15 metabolites in 4 classes (including food, glycerophosphocholine, sphingomyelin [SM] and triacylglycerols [TAG]) were adversely associated with AS (all P < 0.05). Meanwhile, five metabolites (homostachydrine, phosphatidylcholine (PC) (32:1e), PC (38:6p), SM (d41:2) and TAG (45:1) have been proven to be useful predictors of AS prevalence. However, none of these 15 metabolites were found to have a mediating influence on occupational noise-induced AS. Our study reveals specific metabolic changes caused by occupational noise exposure, and several metabolites may have protective effects on AS. However, the roles of serum metabolites in noise-AS association remain to be validated in future studies.

BACKGROUND: Blood stasis constitution in traditional Chinese medicine (TCM) is believed to render individuals more susceptible to metabolic diseases. However, the biological underpinnings of this constitutional imbalance remain unclear.
METHODS: This study explored the association between blood stasis constitution, serum metabolic markers including uric acid (UA), high-density lipoprotein cholesterol (HDLC), their ratio (UHR), serum metabolites, and gut microbiota. Clinical data, fecal and serum samples were acquired from 24 individuals with a blood stasis constitution and 80 individuals with a balanced constitution among healthy individuals from Guangdong. Gut microbiota composition analysis and serum metabolomics analysis were performed.
RESULTS: Females with a blood stasis constitution had higher UA levels, lower HDLC levels, and higher UHR in serum, suggesting a higher risk of metabolic abnormalities. Analysis of the gut microbiome revealed two distinct enterotypes dominated by Bacteroides or Prevotella. Intriguingly, blood stasis subjects were disproportionately clustered within the Bacteroides-rich enterotype. Metabolomic analysis identified subtle differences between the groups, including lower phenylalanine and higher trimethylaminoacetone levels in the blood stasis. Several differential metabolites displayed correlations with HDLC, UA, or UHR, unveiling potential new markers of metabolic dysregulation.
CONCLUSIONS: These findings elucidate the intricate interplay between host constitution, gut microbiota, and serum metabolites. The concept of blood stasis offers a unique perspective to identify subtle alterations in microbiome composition and metabolic pathways, potentially signaling underlying metabolic vulnerability, even in the presence of ostensibly healthy profiles. Continued investigation of this TCM principle may reveal critical insights into the early biological processes that foreshadow metabolic deterioration.

Recently, it has been discovered that certain dairy buffaloes can produce higher milk yield and milk fat yield under the same feeding management conditions, which is a potential new trait. It is unknown to what extent, the rumen microbiome and its metabolites, as well as the host metabolism, contribute to milk yield and milk fat yield. Therefore, we will analyze the rumen microbiome and host-level potential regulatory mechanisms on milk yield and milk fat yield through rumen metagenomics, rumen metabolomics, and serum metabolomics experiments. Microbial metagenomics analysis revealed a significantly higher abundance of several species in the rumen of high-yield dairy buffaloes, which mainly belonged to genera, such as Prevotella, Butyrivibrio, Barnesiella, Lachnospiraceae, Ruminococcus, and Bacteroides. These species contribute to the degradation of diets and improve functions related to fatty acid biosynthesis and lipid metabolism. Furthermore, the rumen of high-yield dairy buffaloes exhibited a lower abundance of methanogenic bacteria and functions, which may produce less methane. Rumen metabolome analysis showed that high-yield dairy buffaloes had significantly higher concentrations of metabolites, including lipids, carbohydrates, and organic acids, as well as volatile fatty acids (VFAs), such as acetic acid and butyric acid. Meanwhile, several Prevotella, Butyrivibrio, Barnesiella, and Bacteroides species were significantly positively correlated with these metabolites. Serum metabolome analysis showed that high-yield dairy buffaloes had significantly higher concentrations of metabolites, mainly lipids and organic acids. Meanwhile, several Prevotella, Bacteroides, Barnesiella, Ruminococcus, and Butyrivibrio species were significantly positively correlated with these metabolites. The combined analysis showed that several species were present, including Prevotella.sp.CAG1031, Prevotella.sp.HUN102, Prevotella.sp.KHD1, Prevotella.phocaeensis, Butyrivibrio.sp.AE3009, Barnesiella.sp.An22, Bacteroides.sp.CAG927, and Bacteroidales.bacterium.52-46, which may play a crucial role in rumen and host lipid metabolism, contributing to milk yield and milk fat yield. The \"omics-explainability\" analysis revealed that the rumen microbial composition, functions, metabolites, and serum metabolites contributed 34.04, 47.13, 39.09, and 50.14%, respectively, to milk yield and milk fat yield. These findings demonstrate how the rumen microbiota and host jointly affect milk production traits in dairy buffaloes. This information is essential for developing targeted feeding management strategies to improve the quality and yield of buffalo milk.