The supramolecular structure and composition of milk fat globules in breast milk is complex. Lipid droplets in formula milk are typically smaller compared to human milk and differ in their lipid and protein composition. These droplets play an important role in gut and immune maturation, and their components possess antimicrobial and antiviral properties. Here, the influence of a concept infant formula (IF) containing large milk phospholipid-coated lipid droplets on the maturation of the infant microbiota, metabolome, and weight gain in the first year of life was investigated.

Formula-fed infants were randomized to receive either a standard IF (Control) or a Test formula containing large milk phospholipid-coated lipid droplets (Test) until 17 weeks of age. A breast-fed Reference group was also investigated. At 3 months of age, several taxa identified as opportunistic pathogens (e.g., Enterobacter, Klebsiella, Enterococcus, Streptococcus) were less abundant in the Test stools compared to Control, while an enrichment of the butyrate-producing Ruminococcaceae and Lachnospiraceae was observed. These findings indicate that the Test formula resulted in gut microbiota maturation trajectories more comparable to healthy breast-fed infants. This was accompanied by variation in several fecal and plasma metabolites at 3 months of age related to gut microbial metabolism including bile acids, hippurate, phenylacetylglycine, trimethylamine, and various lipids and fatty acids. At 12 months, measures of subcutaneous fat and body mass index (BMI) were significantly higher in infants receiving standard IF compared to those receiving breast milk. However, this weight gain and adiposity was attenuated in the Test group infants.

The presence of large phospholipid-coated lipid droplets in formula milk positively influenced the development of the infants' gut microbiota, their metabolomic profiles, and their body composition to more closely resemble breast-fed infants compared to standard IF. These droplets may further enhance the restriction of pathogenic bacteria seen with standard infant formula and suggest a potential impact on infant metabolic programming that may contribute to physiological development. Video Abstract.

Preeclampsia is a leading cause of morbidity and mortality in pregnant women, affecting 5-8% of gestations worldwide. Its development is influenced by maternal immune abnormalities, metabolic disorders, and gut dysbiosis. In this study, we show that gut dysbiosis in pregnant C57BL/6J dams leads to increased fetal resorption, impaired placental development and altered vascularization. These adverse outcomes are associated with key pathological features of preeclampsia, including hypoxia, endoplasmic reticulum (ER) stress and reduction in uterine natural killer (NK) cell numbers. Furthermore, gut dysbiosis significantly perturbs placental carbohydrate metabolism, which impairs NK cell IFN-γ secretion. Notably, glucose supplementation restores placental NK cell function and reduces fetal resorption, suggesting that the observed impairment is reversible and dependent on a lower glycolytic rate. These findings highlight maternal gut microbiota as a key player in carbohydrate metabolism, with a pivotal role in modulating placental immunity and pregnancy outcome. The results provide valuable insights into potential metabolic biomarkers and suggest that targeting the gut microbiota may offer a strategy for preventing preeclampsia.

Amino acids are fundamental in several metabolic processes, and their levels can reflect metabolism impairments that contribute to obesity and related diseases. Our objective was to identify a urinary amino acid fingerprint in obese and overweight children in prepuberty and to correlate this profile with cardiometabolic alterations.

The study included 110 children, boys and girls aged 9-10 years, they were classified according to their BMI-for-age (Body Mass Index for age) into three groups: normal weight (NW) (n = 45), overweight (OW) (n = 21), and obese (OB) (n = 44). The 12-h urine samples were analyzed by LC-MS/MS to quantify 47 amino acids using the Amino Acids Analysis Kit (Zivak®, Turkey), values were corrected by creatinine concentration. Anthropometric measurements, cardiovascular parameters, and biochemical profiles were assessed following standard protocols.

When compared to NW, anthropometric measures, systolic and diastolic blood pressure, and serum uric acid levels were progressively elevated in the OW and OB groups. The OB group was characterized by elevated alpha-aminoadipic acid, asparagine, cystathionine, 1-methyl-histidine, serine, tryptophan, phenylalanine, and tyrosine. In contrast, the OW group presented the most expressive levels of glutamine, alpha-diaminopimelic, and sarcosine.

Our findings indicate that obese and overweight children exhibit a particular urinary amino acid fingerprint which is similar to that reported in studies with plasma. The altered amino acids, particularly tyrosine, are frequently associated with impairments in glucose homeostasis, insulin resistance, and diabetes mellitus type 2. Potential mechanisms for increasing the levels of these amino acids in excess of weight may include enhanced protein degradation and impaired oxidative metabolism.

Precision health symptom science applies person-centered approaches to elucidate interindividual differences in patients' symptom experiences and incorporates omics methods with social, societal, and environmental determinants of health to develop symptom management strategies. By filling scientific gaps related to patients' symptom experiences and their underlying mechanisms, interventions can be developed to improve quality of life and outcomes. The purposes of this article are to describe symptom phenotype development; review analytical approaches to identify a symptom phenotype; and discuss common and emerging methods for biomarker discovery and their implications in precision health symptom science.

Peer-reviewed research studies, review articles, and scientific expertise were synthesized to provide a broad overview of several methods of biomarker discovery and their implications for precision health symptom science.

Approaches to symptom phenotype development and analytical methods for phenotype identification were reviewed. Common (ie, genomic, epigenomic, transcriptomic, proteomic, metabolomic, microbiome) and emerging (ie, polygenic risk scores, microRNA, epigenetic clocks, allostatic load, wearables) methods for biomarker discovery were described. Each method provides unique information to improve our understanding of the complex biological processes that underlie symptoms and may be used for risk prediction, screening, surveillance, and treatment response.

While the exemplar approaches to conducting precision health symptom science were shared through an oncology lens, they are generalizable across acute and chronic conditions.

Symptom biomarker identification is inherently complex and the methods for biomarker collection, processing, measurement, and analysis are continually evolving. Therefore, symptom scientists need to form transdisciplinary teams with experts in omics methodologies and bioinformatics. Despite the challenges, symptom scientists are well suited to lead the way in precision health symptom science to reduce symptom burden and improve quality of life among patients with various chronic conditions.

Background: Cardiovascular disease (CVD) is a leading cause of death in China. Fried foods are a risk factor for increasing CVD and their consumption in China is rapidly rising. Evaluation of the impact of fried foods on the CVD burden has important implications for future public health and policy making. This study aimed to evaluate the impact of fried foods on the CVD burden. Methods: We estimated the temporal trends of fried food consumption from 1997 to 2011 using data from the China Health and Nutrition Survey. We estimated CVD events attributed to fried food consumption using comparative risk assessment methods. We also projected fried food consumption and the related CVD burden from 2011 to 2031. Results: Fried food consumption continued to increase from 1997 to 2011, reaching 110.2 g per week in 2011. It is estimated that high consumption of fried foods is responsible for 3.4%, 2.3%, and 14.3% of the CVD, CHD, and stroke burden, accounting for 0.112 million CVD cases, 0.036 million CHD cases, and 0.243 million stroke cases, respectively. Notably, fried food consumption is projected to increase to 127.6 g per week by 2031. High consumption levels are projected to cause 0.239 million CVD cases, 0.078 million CHD cases, and 0.529 million stroke cases by 2031. Conclusions: The consumption of fried foods has continued to increase over time, which has an important impact on the burden of CVD in China. Dietary guidelines should continue to emphasize on decreasing the consumption of fried foods to reduce the CVD burden in China.

Hippuric acid (HA), a host-microbe cometabolite, normally derives from gut microbial catabolism of dietary polyphenols.

We investigated the potential interplay between dietary polyphenols and gut microbiota on circulating HA concentrations and examined the associations between serum concentrations of HA and cardiometabolic risk markers.

In a 1-y cohort of 754 community-dwelling adults, serum HA and its precursor [benzoic acid (BA)], and fecal microbiota were assayed using liquid chromatography-tandem mass spectrometry and 16S ribosomal RNA sequencing, respectively. Diet, blood pressure, blood glucose, and lipid concentrations were measured twice, 1 y apart. Arterial stiffness [indicated by brachial-ankle pulse wave velocity (baPWV) and ankle-brachial index] and liver fat accumulation [indicated by controlled attenuation parameter (CAP)] were measured after 1 y.

We identified 27 microbial genera whose relative abundance was positively associated with serum HA concentrations (PFDR < 0.05) and constructed a microbial score to reflect the overall HA-producing potential. In multivariate-adjusted linear models, dietary intake of catechins and chlorogenic acids was positively associated with serum HA concentrations among participants with a higher microbial score (β = 0.26, P = 0.03) but not among those with a lower score (β = -0.13, P = 0.30, Pinteraction = 0.03). Participants with higher intake of dietary catechins and chlorogenic acids had lower triglyceride concentrations (Percentage change = -5.9%, P < 0.05). Each 1 μmol/L increase in serum HA, but not in BA, was associated with 5.7%, 1.5%, 1.7%, 1.7%, and 1.7% decrease in triglyceride, systolic blood pressure, diastolic blood pressure, baPWV, and CAP, respectively (all P < 0.05).

The gut microbial genera that predicted circulating HA concentrations might modify the association between dietary polyphenol intake and circulating HA concentrations, and elevated serum HA concentrations are favorably associated with multiple cardiometabolic risk markers.

A growing number of studies have shown that hypertension symptoms are closely related to intestinal flora. The body's metabolites are closely related to disease states. Tianma Gouteng Granules (TG), a traditional Chinese medicine compound, has been proven to be an effective compound for the treatment of hypertension by traditional Chinese medicine diagnosis, but the target and therapeutic mechanism of TG on hypertension are still unclear.

We explored the mechanism of action of TG on hypertension by 16S rDNA gene sequencing and non-targeted metabolomics, verified the correlation between hypertension and intestinal flora, searched for potential markers of intestinal flora, and screened for the correlation between different flora and different metabolites, which facilitates a more scientific and reasonable guidance for the administration of TG.

The hypertensive model rats were induced by L-NAME. After drug administration, 16S rDNA gene sequencing and non-targeted metabolomics were applied to detect and analyze the intestinal flora and fecal metabolites of the rats in each group. The Spearman coefficient method was used to construct the interactions system of different flora and metabolites, which explore the potential mechanism of TG treatment hypertension.

After TG administration, the symptoms of hypertension were significantly reduced to normal in SD rats.16S rDNA gene sequencing and non-targeted metabolomics screened for differential flora p_Actinobacteriota, o_Micrococcaceae, f_ Micrococcales, g_Rothias_Rothia_unclassified, etc. and differential metabolites such as L-Alanine and Hydroxyprolyl-Leucine. TG treatment of hypertension was found to be associated with vitamin B6 metabolic pathway and lipid metabolic pathway.

TG can treat hypertension by affecting differential strains and differential metabolites, providing a scientific basis for guiding the rational use of TG.

Pinelliae Rhizoma (PR), known as Banxia in Chinese, Hange in Japanese, and Banha in Korean, is a renowned herbal medicine in East Asia derived from the dry tuber of Pinellia ternata (Thunb.) Breit. (PT). It is extensively utilized in dispensing granules, classical prescriptions, and herbal formulas to treat various conditions, including cough, infection, phlegm, nausea, asthma, and inflammation. Despite numerous studies on PR and its classical prescriptions over recent decades, a comprehensive synthesis of available evidence regarding its multifunctional roles and therapeutic potential is lacking. This review aims to address this gap by examining emerging evidence from metabonomics, preclinical studies, and clinical trials, while exploring potential trends and prospects for future research. A systematic literature search was conducted across six electronic databases, including PubMed, Web of Science, Scopus, ScienceDirect, Wanfang, and China National Knowledge Infrastructure, to identify relevant articles on PR published until March 2023. PR contains 107 compounds with diverse pharmacological activities, including anti-inflammatory, immune regulatory, anti-viral, anti-cancer, anti-asthma, antitussive and expectorant, antioxidant, anti-obesity, anti-atherosclerosis, anti-microbial, emetic and anti-emetic, anti-convulsant and anti-epileptic, sedative and hypnotic, learning and memory enhancement, and anti-depressant effects. Metabonomic studies suggest that raw PR may exhibit cardiotoxicity and pregnancy toxicity while showing no apparent hepatorenal toxicity. However, limited pharmacokinetic investigations on PR constrain its clinical translation. Furthermore, clinical safety data on PR is scarce, with only four clinical trials assessing its positive effects in pediatric epilepsy, nausea and vomiting, soft tissue injury, and chronic sinus tract. This review aims to enhance understanding of PR and provide valuable information and recommendations for further research and development of herbal medicine.

Epidemiologic evidence linking blood pressure (BP) and body weight-lowering effects with fruit and vegetable consumption mostly relies on self-reported dietary assessment prone to misreport and under- or overestimation of relationships.

We aimed to characterize objective 24-h urinary metabolites and a derived metabolite score associated with fruit and vegetable intake and assessed their associations with BP and BMI, with validation across cohorts.

We used untargeted proton nuclear magnetic resonance spectroscopy (1H NMR) of 2 timed repeated 24-h urine collections from free-living participants from the US (n = 2032) and the UK (n = 449) of the cross-sectional International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP). We evaluated correlations between fruit and vegetable intake assessed by 24-h dietary recalls with 7100 1H NMR features, adjusted for confounders and multiple testing. We related identified metabolites and a metabolite score with BP and BMI using extensively adjusted multiple linear regression models.

We characterized 11 1H NMR-derived 24-h urinary metabolites related to fruit and vegetable intake, reproducible across multiple 24-h urine collections of both cohorts. Proline betaine, citrate, N-methylproline, scyllo-inositol, 2-hydroxy-2-(4-methyl cyclohex-3-en-1-yl) propoxyglucuronide, and proline were associated with fruit intake, specifically with Rutaceae intake, whereas S-methyl-L-cysteine sulfoxide and S-methyl-L-cysteine sulfoxide metabolite were associated with Brassicaceae intake. The metabolite score, explaining 39.8% of fruit and vegetable intake, was inversely associated with systolic BP [-1.65 mmHg; 95% confidence interval (CI): -2.68, -0.62; P < 0.002] and BMI (-1.21 kg/m2; 95% CI: -1.62, -0.78; P < 0.0001). These associations were, to a large extent, explained by urinary citrate excretion.

We identified 1H NMR-derived urinary metabolites associated with fruit and vegetable consumption, consistent and reproducible between urine collections and across populations. A higher fruit and vegetable-related metabolite score showed associations with lower systolic BP and BMI, mainly mediated by citrate, but would need confirmation in further studies.

Untargeted analysis by LC-MS is a valuable tool for metabolic profiling (metabonomics/metabolomics), and applications of this technology have grown rapidly over the past decade. LC-MS offers advantages of speed, sensitivity, relative ease of sample preparation, and large dynamic range compared to other platforms in this role. However, like any analytical approach, there are still drawbacks and challenges that have to be overcome, some of which are being addressed by advances in both column chemistries and instrumentation. In particular, the combination of LC-MS with ion mobility offers many new possibilities for improved analyte separation, detection, and structural identification. There are many untargeted LC-MS approaches which can be applied to metabolic phenotyping, and these usually need to be optimized for the type of sample, the nature of the study, or the biological question. Some of the main LC-MS approaches for untargeted metabolic phenotyping are described in detail in the following protocol.

Type 1 diabetes increases the risk of coronary artery disease (CAD). High-throughput metabolomics may be utilized to identify metabolites associated with disease, thus, providing insight into disease pathophysiology, and serving as predictive markers in clinical practice. Urine is less tightly regulated than blood, and therefore, may enable earlier discovery of disease-associated markers. We studied urine metabolomics in relation to incident CAD in individuals with type 1 diabetes.

We prospectively studied CAD in 2501 adults with type 1 diabetes from the Finnish Diabetic Nephropathy Study. 209 participants experienced incident CAD within the 10-year follow-up. We analyzed the baseline urine samples with a high-throughput targeted urine metabolomics platform, which yielded 54 metabolites. With the data, we performed metabolome-wide survival analyses, correlation network analyses, and metabolomic state profiling for prediction of incident CAD.

Urinary 3-hydroxyisobutyrate was associated with decreased 10-year incident CAD, which according to the network analysis, likely reflects younger age and improved kidney function. Urinary xanthosine was associated with 10-year incident CAD. In the network analysis, xanthosine correlated with baseline urinary allantoin, which is a marker of oxidative stress. In addition, urinary trans-aconitate and 4-deoxythreonate were associated with decreased 5-year incident CAD. Metabolomic state profiling supported the usage of CAD-associated urinary metabolites to improve prediction accuracy, especially during shorter follow-up. Furthermore, urinary trans-aconitate and 4-deoxythreonate were associated with decreased 5-year incident CAD. The network analysis further suggested glomerular filtration rate to influence the urinary metabolome differently between individuals with and without future CAD.

We have performed the first high-throughput urinary metabolomics analysis on CAD in individuals with type 1 diabetes and found xanthosine, 3-hydroxyisobutyrate, trans-aconitate, and 4-deoxythreonate to be associated with incident CAD. In addition, metabolomic state profiling improved prediction of incident CAD.

The prevalence of metabolic disorders has been found to increase concomitantly with alternations in habitual diet and lifestyle, indicating the importance of metabolic health monitoring for early warning of high-risk status and suggesting effective intervention strategies. Hippuric acid (HA), as one of the most abundant metabolites from the gut microbiota, holds potential as a regulator of metabolic health. Accordingly, it is imperative to establish an efficient, sensitive, and affordable method for large-scale population monitoring, revealing the association between HA level and metabolic disorders. Upon systematic screening of macrocycle•dye reporter pair, a supramolecular architecture (guanidinomethyl-modified calix[5]arene, GMC5A) was employed to sense urinary HA by employing fluorescein (Fl), whose complexation behavior was demonstrated by theoretical calculations, accomplishing quantification of HA in urine from 249 volunteers in the range of 0.10 mM and 10.93 mM. Excitedly, by restricted cubic spline, urinary HA concentration was found to have a significantly negative correlation with the risk of metabolic disorders when it exceeded 0.76 mM, suggesting the importance of dietary habits, especially the consumption of fruits, coffee, and tea, which was unveiled from a simple questionnaire survey. In this study, we accomplished a high throughput and sensitive detection of urinary HA based on supramolecular sensing with the GMC5A•Fl reporter pair, which sheds light on the rapid quantification of urinary HA as an indicator of metabolic health status and early intervention by balancing the daily diet.

The intestinal microbiota represents a key element in maintaining the homeostasis and health conditions of the host. Vascular pathologies and other risk factors such as aging have been recently associated with dysbiosis. The qualitative and quantitative alteration of the intestinal microbiota hinders correct metabolic homeostasis, causing structural and functional changes of the intestinal wall itself. Impairment of the intestinal microbiota, combined with the reduction of the barrier function, worsen the pathological scenarios of peripheral tissues over time, including the vascular one. Several experimental evidence, collected in this review, describes in detail the changes of the intestinal microbiota in dysbiosis associated with vascular alterations, such as atherosclerosis, hypertension, and endothelial dysfunction, the resulting metabolic disorders and how these can impact on vascular health. In this context, the gut-vascular axis is considered, for the first time, as a merged unit involved in the development and progression of vascular pathologies and as a promising target. Current approaches for the management of dysbiosis such as probiotics, prebiotics and dietary modifications act mainly on the intestinal district. Postbiotics, described as preparation of inanimate microorganisms and/or their components that confers health benefits on the host, represent an innovative strategy for a dual management of intestinal dysbiosis and vascular pathologies. In this context, this review has the further purpose of defining the positive effects of the supplementation of bacterial strains metabolites (short‑chain fatty acids, exopolysaccharides, lipoteichoic acids, gallic acid, and protocatechuic acid) restoring intestinal homeostasis and acting directly on the vascular district through the gut-vascular axis.

As environmental and health concerns of beef production and consumption mount, there is growing interest in agroecological production methods, including finishing beef cattle on pastures with phytochemically diverse grasses, forbs, and/or shrubs. The goal of this metabolomics, lipidomics, and fatty acid methyl ester profiling study was to compare meat (pectoralis profundus) of Black Angus cattle from two commercial US beef finishing systems (pasture-finished on Western U.S. rangeland; n = 18 and grain-finished in a Midwest U.S. feedlot; n = 18). A total of 907 out of 1575 compounds differed in abundance between pasture-finished and grain-finished beef samples (all, false discovery rate adjusted P < 0.05). Pasture-finished beef contained higher levels of phenolic antioxidants (2.6-fold), alpha-tocopherol (3.1-fold), nicotinate/vitamin B3 (9.4-fold), choline (1.2-fold), myo-inositol (1.8-fold), and omega-3 fatty acids (4.1-fold). Grain-finished beef contained higher levels of gamma-tocopherol (14.6-fold), nicotinamide/vitamin B3 (1.5-fold), pantothenate/vitamin B5 (1.3-fold), and pyridoxine/vitamin B6 (1.3-fold); indicating that feeding some grain (by-products) could be beneficial to increase levels of certain B-vitamins. Pasture-finished beef samples also displayed lower levels of oxidative stress (homocysteine, 0.6-fold; and 4-hydroxy-nonenal-glutathione, 0.4-fold) and improved mitochondrial function (1.3-fold) compared to grain-finished animals. Two potential metabolites of fluoroquinolone antibiotics, 2,8-quinolinediol and 2,8-quinolinediol sulfate, were only observed in grain-finished beef, though the source remains unknown. While pasture-finished cattle displayed improved markers of metabolic health and concentrated additional, potentially health-promoting compounds in their meat, our findings should not be interpreted as that grain-finished beef is unhealthy to consume. Randomized controlled trials in humans are required to further assess whether observed differences between pasture-finished and feedlot-finished beef have an appreciable effect on human health.

Hypertensive disorders of pregnancy (HDP) are severe complications of pregnancy with high morbidity and are a major cause of increased maternal and infant morbidity and mortality. Currently, there is a lack of effective early diagnostic indicators and safe and effective preventive strategies for HDP in clinical practice, except for monitoring maternal blood pressure levels, the degree of proteinuria, organ involvement and fetal conditions. The intestinal microbiota consists of the gut flora and intestinal environment, which is the largest microecosystem of the human body and participates in material and energy metabolism, gene expression regulation, immunity regulation, and other functions. During pregnancy, due to changes in hormone levels and altered immune function, the intestinal microecological balance is affected, triggering HDP. A dysregulated intestinal microenvironment influences the composition and distribution of the gut flora and changes the intestinal barrier, driving beneficial or harmful bacterial metabolites and inflammatory responses to participate in the development of HDP and promote its malignant development. When the gut flora is dysbiotic and affects blood pressure, supplementation with probiotics and dietary fiber can be used to intervene. In this review, the interaction between the intestinal microbiota and HDP was investigated to explore the feasibility of the gut flora as a novel biomarker of HDP and to provide a new strategy and basis for the prevention and treatment of clinical HDP.

The metabolic network's primary sources of free fatty acids (FFAs) are long- and medium-chain fatty acids of triglyceride origin and short-chain fatty acids produced by intestinal microorganisms through dietary fibre fermentation. Recent studies have demonstrated that FFAs not only serve as an energy source for the body's metabolism but also participate in regulating arterial function. Excess FFAs have been shown to lead to endothelial dysfunction, vascular hypertrophy, and vessel wall stiffness, which are important triggers of arterial hypertension and atherosclerosis. Nevertheless, free fatty acid receptors (FFARs) are involved in the regulation of arterial functions, including the proliferation, differentiation, migration, apoptosis, inflammation, and angiogenesis of vascular endothelial cells (VECs) and vascular smooth muscle cells (VSMCs). They actively regulate hypertension, endothelial dysfunction, and atherosclerosis. The objective of this review is to examine the roles and heterogeneity of FFAs and FFARs in the regulation of arterial function, with a view to identifying the points of intersection between their actions and providing new insights into the prevention and treatment of diseases associated with arterial dysfunction, as well as the development of targeted drugs.

Among all non-communicable diseases, Cardiovascular Diseases (CVDs) stand as the leading global cause of mortality. Within this spectrum, Myocardial Infarction (MI) strikingly accounts for over 15 % of all deaths. The intricate web of risk factors for MI, comprising family history, tobacco use, oral health, hypertension, nutritional pattern, and microbial infections, is firmly influenced by the human gut and oral microbiota, their diversity, richness, and dysbiosis, along with their respective metabolites. Host genetic factors, especially allelic variations in signaling and inflammatory markers, greatly affect the progression or severity of the disease. Despite the established significance of the human microbiome-nutrient-metabolite interplay in associations with CVDs, the unexplored terrain of the gut-heart-oral axis has risen as a critical knowledge gap. Moreover, the pivotal role of the microbiome and the complex interplay with host genetics, compounded by age-related changes, emerges as an area of vital importance in the development of MI. In addition, a distinctive disease susceptibility and severity influenced by gender-based or ancestral differences, adds a crucial insights to the association with increased mortality. Here, we aimed to provide an overview on interactions of microbiome (oral and gut) with major risk factors (tobacco use, alcohol consumption, diet, hypertension host genetics, gender, and aging) in the development of MI and therapeutic regulation.

NMR spectroscopy is a mainstay of metabolic profiling approaches to investigation of physiological and pathological processes. The one-dimensional proton pulse sequences typically used in phenotyping large numbers of samples generate spectra that are rich in information but where metabolite identification is often compromised by peak overlap. Recently developed pure shift (PS) NMR spectroscopy, where all J-coupling multiplicities are removed from the spectra, has the potential to simplify the complex proton NMR spectra that arise from biosamples and hence to aid metabolite identification. Here we have evaluated two complementary approaches to spectral simplification: the HOBS (band-selective with real-time acquisition) and the PSYCHE (broadband with pseudo-2D interferogram acquisition) pulse sequences. We compare their relative sensitivities and robustness for deconvolving both urine and serum matrices. Both methods improve resolution of resonances ranging from doublets, triplets and quartets to more complex signals such as doublets of doublets and multiplets in highly overcrowded spectral regions. HOBS is the more sensitive method and takes less time to acquire in comparison with PSYCHE, but can introduce unavoidable artefacts from metabolites with strong couplings, whereas PSYCHE is more adaptable to these types of spin system, although at the expense of sensitivity. Both methods are robust and easy to implement. We also demonstrate that strong coupling artefacts contain latent connectivity information that can be used to enhance metabolite identification. Metabolite identification is a bottleneck in metabolic profiling studies. In the case of NMR, PS experiments can be included in metabolite identification workflows, providing additional capability for biomarker discovery.

The safety of drinking water has always been a concern for people all over the world. N-nitrosamines (NAs), a kind of nitrogenous disinfection by-products (N-DBPs), are generally detected as a mixture in drinking water at home and abroad. Studies have shown that individual NAs posed strong carcinogenicity at high concentrations. However, health risks of NAs at environmental levels (concentrations in drinking water) are still unclear. Therefore, the potential health risks of environmentally relevant NAs exposure in drinking water needs to be conducted. In this study, blood biochemical analysis and metabolomics based on nuclear magnetic resonance (NMR) were performed to comprehensively investigate NAs induced metabolic disturbance in infant rats at environmental levels. Results of blood biochemical indices analysis indicated that AST in the serum of male rats in NAs-treated group exhibited a significant gender-specific difference. Multivariate statistics showed that two and eight significantly disturbed metabolic pathways were identified in the serum samples of NAs-treated male and female rats, respectively. In the urine samples of NAs-treated female rats, glycine, serine, and threonine metabolism pathway was significantly disturbed; while three significantly disturbed metabolic pathways were found in the urine of NAs-treated male rats. Finally, results of spearman correlation coefficients suggested that the disturbances of metabolism profile in serum and urine were correlated with changes in the gut microbiota (data derived from our published paper). Data presented here aimed to generate new health risk data of NAs mixture exposure at environmental levels and provide theoretical support for drinking water safety management. ENVIRONMENTAL IMPLICATION: N-nitrosamines (NAs) are a kind of nitrogenous disinfection by-products (N-DBPs) generated during drinking water disinfection processes. Herein, health risks of NAs at environmental levels (concentrations in drinking water) are investigated using blood biochemical analysis and nuclear magnetic resonance (NMR)-based metabolomics. Results confirmed NAs induced gender-specific on the metabolism in rat and the disturbances of metabolism profile in serum and urine were correlated with changes in the gut microbiota. Data presented here aimed to generate new health risk data of NAs mixture exposure at environmental levels and provide theoretical support for drinking water safety management.

Biomedical researchers tirelessly seek cutting-edge technologies to advance disease diagnosis, drug discovery, and therapeutic interventions, all aimed at enhancing human and animal well-being. Within this realm, proteomics stands out as a pivotal technology, focusing on extensive studies of protein composition, structure, function, and interactions. Proteomics, with its subdivisions of expression, structural, and functional proteomics, plays a crucial role in unraveling the complexities of biological systems. Various sophisticated techniques are employed in proteomics, including polyacrylamide gel electrophoresis, mass spectrometry analysis, NMR spectroscopy, protein microarray, X-ray crystallography, and Edman sequencing. These methods collectively contribute to the comprehensive understanding of proteins and their roles in health and disease. In the biomedical field, proteomics finds widespread application in cancer research and diagnosis, stem cell studies, and the diagnosis and research of both infectious and noninfectious diseases. In addition, it plays a pivotal role in drug discovery and the emerging frontier of personalized medicine. The versatility of proteomics allows researchers to delve into the intricacies of molecular mechanisms, paving the way for innovative therapeutic approaches. As infectious and noninfectious diseases continue to emerge and the field of biomedical research expands, the significance of proteomics becomes increasingly evident. Keeping abreast of the latest developments in proteomics applications becomes paramount for the development of therapeutics, translational research, and study of diverse diseases. This review aims to provide a comprehensive overview of proteomics, offering a concise outline of its current applications in the biomedical domain. By doing so, it seeks to contribute to the understanding and advancement of proteomics, emphasizing its pivotal role in shaping the future of biomedical research and therapeutic interventions.

The rising prevalence of obesity in Saudi Arabia is a major contributor to the nation's high levels of cardiometabolic diseases such as type 2 diabetes. To assess the impact of obesity on the diabetic metabolic phenotype presented in young Saudi Arabian adults, participants (n = 289, aged 18-40 years) were recruited and stratified into four groups: healthy weight (BMI 18.5-24.99 kg/m2) with (n = 57) and without diabetes (n = 58) or overweight/obese (BMI > 24.99 kg/m2) with (n = 102) and without diabetes (n = 72). Distinct plasma metabolic phenotypes associated with high BMI and diabetes were identified using nuclear magnetic resonance spectroscopy and ultraperformance liquid chromatography mass spectrometry. Increased plasma glucose and dysregulated lipoproteins were characteristics of obesity in individuals with and without diabetes, but the obesity-associated lipoprotein phenotype was partially masked in individuals with diabetes. Although there was little difference between diabetics and nondiabetics in the global plasma LDL cholesterol and phospholipid concentration, the distribution of lipoprotein particles was altered in diabetics with a shift toward denser and more atherogenic LDL5 and LDL6 particles, which was amplified in the presence of obesity. Further investigation is warranted in larger Middle Eastern populations to explore the dysregulation of metabolism driven by interactions between obesity and diabetes in young adults.

Urinary metabolomics has demonstrated considerable potential to assess kidney function and its metabolic corollaries in health and disease. However, applications in epidemiology remain sparse due to technical challenges.

We added 17 metabolites to an open-access urinary nuclear magnetic resonance metabolomics platform, extending the panel to 61 metabolites (n = 994). We also introduced automated quantification for 11 metabolites, extending the panel to 12 metabolites (+creatinine). Epidemiological associations between these 12 metabolites and 49 clinical measures were studied in three independent cohorts (up to 5989 participants). Detailed regression analyses with various confounding factors are presented for body mass index (BMI) and smoking.

Sex-specific population reference concentrations and distributions are provided for 61 urinary metabolites (419 men and 575 women), together with methodological intra-assay metabolite variations as well as the biological intra-individual and epidemiological population variations. For the 12 metabolites, 362 associations were found. These are mostly novel and reflect potential molecular proxies to estimate kidney function, as the associations cannot be simply explained by estimated glomerular filtration rate. Unspecific renal excretion results in leakage of amino acids (and glucose) to urine in all individuals. Seven urinary metabolites associated with smoking, providing questionnaire-independent proxy measures of smoking status in epidemiological studies. Common confounders did not affect metabolite associations with smoking, but insulin had a clear effect on most associations with BMI, including strong effects on 2-hydroxyisobutyrate, valine, alanine, trigonelline and hippurate.

Urinary metabolomics provides new insight on kidney function and related biomarkers on the renal-cardiometabolic system, supporting large-scale applications in epidemiology.

Evidence suggests consumption of a Mediterranean diet (MD) can positively impact both maternal and offspring health, potentially mediated by a beneficial effect on inflammatory pathways. We aimed to apply metabolic profiling of serum and urine samples to assess differences between women who were stratified into high and low alignment to a MD throughout pregnancy and investigate the relationship of the diet to inflammatory markers.

From the ORIGINS cohort, 51 pregnant women were stratified for persistent high and low alignment to a MD, based on validated MD questionnaires. 1H Nuclear Magnetic Resonance (NMR) spectroscopy was used to investigate the urine and serum metabolite profiles of these women at 36 weeks of pregnancy. The relationship between diet, metabolite profile and inflammatory status was investigated.

There were clear differences in both the food choice and metabolic profiles of women who self-reported concordance to a high (HMDA) and low (LMDA) Mediterranean diet, indicating that alignment with the MD was associated with a specific metabolic phenotype during pregnancy. Reduced meat intake and higher vegetable intake in the HMDA group was supported by increased levels of urinary hippurate (p = 0.044) and lower creatine (p = 0.047) levels. Serum concentrations of the NMR spectroscopic inflammatory biomarkers GlycA (p = 0.020) and GlycB (p = 0.016) were significantly lower in the HDMA group and were negatively associated with serum acetate, histidine and isoleucine (p < 0.05) suggesting a greater level of plant-based nutrients in the diet. Serum branched chain and aromatic amino acids were positively associated with the HMDA group while both urinary and serum creatine, urine creatinine and dimethylamine were positively associated with the LMDA group.

Metabolic phenotypes of pregnant women who had a high alignment with the MD were significantly different from pregnant women who had a poor alignment with the MD. The metabolite profiles aligned with reported food intake. Differences were most significant biomarkers of systemic inflammation and selected gut-microbial metabolites. This research expands our understanding of the mechanisms driving health outcomes during the perinatal period and provides additional biomarkers for investigation in pregnant women to assess potential health risks.

Salivary gland hypofunction is an adverse side effect associated with radiotherapy for head and neck cancer patients. This study delineated metabolic changes at acute, intermediate, and chronic radiation damage response stages in mouse salivary glands following a single 5 Gy dose. Ultra-high performance liquid chromatography-mass spectrometry was performed on parotid salivary gland tissue collected at 3, 14, and 30 days following radiation (IR). Pathway enrichment analysis, network analysis based on metabolite structural similarity, and network analysis based on metabolite abundance correlations were used to incorporate both metabolite levels and structural annotation. The greatest number of enriched pathways are observed at 3 days and the lowest at 30 days following radiation. Amino acid metabolism pathways, glutathione metabolism, and central carbon metabolism in cancer are enriched at all radiation time points across different analytical methods. This study suggests that glutathione and central carbon metabolism in cancer may be important pathways in the unresolved effect of radiation treatment.

Large bone lead (Pb) resulting from high environmental exposure during childhood is an important source of endogenous Pb during pregnancy and lactation. Docosahexaenoic acid (DHA) attenuates Pb toxicity, however, the effect of DHA on bone Pb mobilisation during lactation has not been investigated. We aimed to study the effects of DHA supplementation during pregnancy and lactation on bone Pb mobilisation during lactation and its potential mechanisms. Weaning female rats were randomly divided into control (0.05% sodium acetate) and Pb-exposed (0.05% Pb acetate) groups, after a 4-week exposure by ad libitum drinking and a subsequent 4-week washout period, all female rats were mated with healthy males until pregnancy. Then exposed rats were randomly divided into Pb and Pb + DHA groups, and the latter was given a 0.14% DHA diet, while the remaining groups were given normal feed until the end of lactation. Pb and calcium levels, bone microarchitecture, bone turnover markers, mitochondrial function and serum metabolomics were analyzed. The results showed that higher blood and bone Pb levels were observed in the Pb group compared to the control, and there was a significant negative correlation between blood and bone Pb. Also, Pb increased trabecular bone loss along with slightly elevated serum C-telopeptide of type I collagen (CTX-I) levels. However, DHA reduced CTX-I levels and improved trabecular bone microarchitecture. Metabolomics showed that Pb affected mitochondrial function, which was further demonstrated in bone tissue by significant reductions in ATP levels, Na+-K+-ATPase, Ca2+-Mg2+-ATPase and CAT activities, and elevated levels of MDA, IL-1β and IL-18. However, these alterations were partially mitigated by DHA. In conclusion, DHA supplementation during pregnancy and lactation improved bone Pb mobilisation and mitochondrial dysfunction in lactating rats induced by pre-pregnancy Pb exposure, providing potential means of mitigating bone Pb mobilisation levels during lactation, but the mechanism still needs further study.

A nontargeted metabolomics approach was established to characterize serum metabolic profile in type 3c diabetes mellitus (T3cDM) secondary to chronic pancreatitis and compare with T2DM.

Forty patients were recruited for metabolite analysis based on liquid chromatography-mass spectrometry. Cluster heatmap and KEGG metabolic pathway enrichment analysis were used to analyze the specific and differential metabolites. The receiver operating characteristics (ROCs) were generated and correlation analysis with clinical data was conducted.

Metabolites including sphingosine, lipids, carnitine, bile acid, and hippuric acid were found to be different between T2DM and T3cDM, mainly enriched in bile acid biosynthesis, fatty acid biosynthesis, and sphingolipid metabolic pathways. The ROCs were generated with an area under the curve of 0.907 (95% confidence interval, 0.726-1) for the model with 15 metabolites.

T3cDM is characterized by increased sphingosine, carnitine, bile acid, and most lipids, providing novel biomarkers for clinical diagnosis and a future direction in research on pathophysiological mechanisms.

Alanine is an amino acid commonly used as a nutritional supplement and plays a key role in the glucose-alanine cycle. Plasma alanine has been associated in observational studies with a higher risk of coronary artery disease (CAD) and unhealthier lipid profiles. However, evidence from large randomized controlled trials is lacking.

Using Mendelian randomization (MR), we assessed the unconfounded associations of plasma alanine with CAD and CAD risk factors.

We applied single nucleotide polymorphisms that were strongly (P < 5 ×10-8) associated with plasma alanine as genetic instruments to large genome-wide association studies of CAD (63,108 cases; 296,901 controls), diabetes (90,612 cases; 583,493 controls), glucose (515,538 participants), lipids (low-density lipoprotein [LDL] cholesterol, high-density lipoprotein [HDL] cholesterol, triglycerides, total cholesterol, and apolipoprotein B) (>1.1 million participants), blood pressure (BP) (757,601 participants), and body mass index (682,137 participants). Given the potential sex disparity, we also conducted sex-specific analyses. MR estimates per standard deviation increase in alanine concentrations were obtained using inverse variance weighting followed by sensitivity analyses using weighted median, MR-Egger, MR-Pleiotropy RESidual Sum and Outlier, and MR-Robust Adjusted Profile Score.

Genetically predicted plasma alanine was not associated with CAD but with a higher risk of diabetes (odds ratio [OR]: 1.35; 95% confidence interval [CI]: 1.06, 1.72), higher glucose (β: 0.11; 95% CI: 0.02, 0.19), LDL cholesterol (β: 0.08; 95% CI: 0.04, 0.12), triglycerides (β: 0.25; 95% CI: 0.13, 0.38), total cholesterol (β: 0.14; 95% CI: 0.08, 0.20), apolipoprotein B (β: 0.12; 95% CI: 0.03, 0.21), and BP (β: 1.17; 95% CI: 0.31, 2.04 for systolic BP: β: 0.97; 95% CI: 0.49, 1.45 for diastolic BP) overall. The positive associations of serum alanine with LDL cholesterol and triglycerides were more notable in women than in men.

Alanine or factors affecting alanine may have causal effects on diabetes, blood glucose, lipid profiles, and BP but not on CAD. Further studies are needed to clarify possible mechanisms.

The intestinal microbiota participates in host physiology and pathology through metabolites, in which short-chain fatty acids (SCFAs) are considered principal products and have extensive influence on intestine homeostasis. It has been reported that skin ulceration syndrome (SUS), the disease of Apostichopus japonicus caused by Vibrio splendidus, is associated with the alteration of the intestinal microbiota composition.

To investigate whether the intestinal microbiota affects A. japonicus health via SCFAs, in this study, we focus on the SCFA profiling and intestinal barrier function in A. japonicus treated with V. splendidus.

We found that V. splendidus could destroy the mid-intestine integrity and downregulate the expression of tight junction proteins ZO-1 and occludin in A. japonicus, which further dramatically decreased microorganism abundance and altered SCFAs contents. Specifically, acetic acid is associated with the largest number of microorganisms and has a significant correlation with occludin and ZO-1 among the seven SCFAs. Furthermore, our findings showed that acetic acid could maintain the intestinal barrier function by increasing the expression of tight junction proteins and rearranging the tight junction structure by regulating F-actin in mid-intestine epithelial cells. Thus, our results provide insights into the effects of the gut microbiome and SCFAs on intestine barrier homeostasis and provide essential knowledge for intervening in SUS by targeting metabolites or the gut microbiota.

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.

Autism Spectrum Disorder (ASD or autism) is a phenotypically and etiologically heterogeneous condition. Identifying biomarkers of clinically significant metabolic subtypes of autism could improve understanding of its underlying pathophysiology and potentially lead to more targeted interventions. We hypothesized that the application of metabolite-based biomarker techniques using decision thresholds derived from quantitative measurements could identify autism-associated subpopulations. Metabolomic profiling was carried out in a case-control study of 499 autistic and 209 typically developing (TYP) children, ages 18-48 months, enrolled in the Children's Autism Metabolome Project (CAMP; ClinicalTrials.gov Identifier: NCT02548442). Fifty-four metabolites, associated with amino acid, organic acid, acylcarnitine and purine metabolism as well as microbiome-associated metabolites, were quantified using liquid chromatography-tandem mass spectrometry. Using quantitative thresholds, the concentrations of 4 metabolites and 149 ratios of metabolites were identified as biomarkers, each identifying subpopulations of 4.5-11% of the CAMP autistic population. A subset of 42 biomarkers could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. Many participants were identified by several metabolic biomarkers. Using hierarchical clustering, 30 clusters of biomarkers were created based on participants' biomarker profiles. Metabolic changes associated with the clusters suggest that altered regulation of cellular metabolism, especially of mitochondrial bioenergetics, were common metabolic phenotypes in this cohort of autistic participants. Autism severity and cognitive and developmental impairment were associated with increased lactate, many lactate containing ratios, and the number of biomarker clusters a participant displayed. These studies provide evidence that metabolic phenotyping is feasible and that defined autistic subgroups can lead to enhanced understanding of the underlying pathophysiology and potentially suggest pathways for targeted metabolic treatments.

Traditionally, a relatively big urine volume (e.g., 500 μL) is used in nuclear magnetic resonance (NMR)-based human metabolomics, which is not feasible for studies with limited/precious samples. Although urine may be diluted before conventional high-throughput metabolomics analysis, the comprehensive effect of urine dilution on metabolic profiles is unknown. Here, for the first time, we systematically investigated the effect of urine dilution on 1H NMR metabolic profiles, by evaluating signal detectability, integration, signal-to-noise ratio (SNR), chemical shift (δ) and its variation, and signal overlapping of 47 metabolites in 10 volunteers. We observed significant linear changes along with increased dilution, including decreased integration and SNR, altered δ, decreased intersample variation of δ, and increased separation between overlapped signals, e.g., lactate and threonine, β-d-glucose and an unassigned signal, and histidine and 3-methylhistidine. We further tested the 40% dilution level (i.e., employing 300 μL urine) in an epidemiological study containing 1018 pregnant women from the Tongji-Shuangliu Birth Cohort, showing acceptable detectability and chemical shift variability for most of the 47 metabolites profiled. It indicated that mild (e.g., 40%) dilution of human urine can largely preserve the high-abundance metabolites profiled, reduce intersample chemical shift variations, and increase separations of overlapped signals, which is an improvement of routine sample preparation methods in NMR-based metabolomics and is applicable for studies with limited urine volumes, including large-scale epidemiological studies.

LDL cholesterol (LDL-C) is a well-established risk factor for coronary artery disease (CAD). However, the optimal LDL-C level with regard to efficacy and safety remains unclear. We aimed to investigate the causal relationships between LDL-C and efficacy and safety outcomes.

We analyzed 353 232 British from the UK Biobank and 41 271 Chinese from the China-PAR project. Linear and non-linear Mendelian randomization (MR) analyses were performed to evaluate the causal relation between genetically proxied LDL-C and CAD, all-cause mortality, and safety outcomes (including haemorrhagic stroke, diabetes mellitus, overall cancer, non-cardiovascular death, and dementia). No significant non-linear associations were observed for CAD, all-cause mortality, and safety outcomes (Cochran Q P > 0.25 in British and Chinese) with LDL-C levels above the minimum values of 50 and 20 mg/dL in British and Chinese, respectively. Linear MR analyses demonstrated a positive association of LDL-C with CAD [British: odds ratio (OR) per unit mmol/L increase, 1.75, P = 7.57 × 10-52; Chinese: OR, 2.06, P = 9.10 × 10-3]. Furthermore, stratified analyses restricted to individuals with LDL-C levels less than the guideline-recommended 70 mg/dL demonstrated lower LDL-C levels were associated with a higher risk of adverse events, including haemorrhagic stroke (British: OR, 0.72, P = 0.03) and dementia (British: OR, 0.75, P = 0.03).

In British and Chinese populations, we confirmed a linear dose-response relationship of LDL-C with CAD and found potential safety concerns at low LDL-C levels, providing recommendations for monitoring adverse events in people with low LDL-C in the prevention of cardiovascular disease.

Diet is considered a culprit for symptoms in irritable bowel syndrome (IBS), although the mechanistic understanding of underlying causes is lacking. Metabolomics, i.e., the analysis of metabolites in biological samples may offer a diet-responsive fingerprint for IBS. Our aim was to explore alterations in the plasma metabolome after interventions with fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) or gluten versus control in IBS, and to relate such alterations to symptoms. People with IBS (n = 110) were included in a double-blind, randomized, crossover study with 1-wk provocations of FODMAPs, gluten, or placebo. Symptoms were evaluated with the IBS severity scoring system (IBS-SSS). Untargeted metabolomics was performed on plasma samples using LC-qTOF-MS. Discovery of metabolite alterations by treatment was performed using random forest followed by linear mixed modeling. Associations were studied using Spearman correlation. The metabolome was affected by FODMAP [classification rate (CR) 0.88, P < 0.0001], but less by gluten intake CR 0.72, P = 0.01). FODMAP lowered bile acids, whereas phenolic-derived metabolites and 3-indolepropionic acid (IPA) were higher compared with placebo. IPA and some unidentified metabolites correlated weakly to abdominal pain and quality of life. Gluten affected lipid metabolism weakly, but with no interpretable relationship to IBS. FODMAP affected gut microbial-derived metabolites relating to positive health outcomes. IPA and unknown metabolites correlated weakly to IBS severity. Minor symptom worsening by FODMAP intake must be weighed against general positive health aspects of FODMAP. The gluten intervention affected lipid metabolism weakly with no interpretable association to IBS severity. Registration: www.clinicaltrials.gov as NCT03653689.NEW & NOTEWORTHY In irritable bowel syndrome (IBS), fermentable oligo-, di-, monosaccharides, and polyols (FODMAPs) affected microbial-derived metabolites relating to positive health outcomes such as reduced risk of colon cancer, inflammation, and type 2 diabetes, as shown in previous studies. The minor IBS symptom induction by FODMAP intake must be weighed against the positive health aspects of FODMAP consumption. Gluten affected lipids weakly with no association to IBS severity.

Precision microbiome modulation as a novel treatment strategy is a rapidly evolving and sought goal. The aim of this study is to determine relationships among systemic gut microbial metabolite levels and incident cardiovascular disease risks to identify gut microbial pathways as possible targets for personalized therapeutic interventions.

Stable isotope dilution mass spectrometry methods to quantitatively measure aromatic amino acids and their metabolites were used to examine sequential subjects undergoing elective diagnostic cardiac evaluation in two independent cohorts with longitudinal outcome data [US (n = 4000) and EU (n = 833) cohorts]. It was also used in plasma from humans and mice before vs. after a cocktail of poorly absorbed antibiotics to suppress gut microbiota. Multiple aromatic amino acid-derived metabolites that originate, at least in part, from gut bacteria are associated with incident (3-year) major adverse cardiovascular event (MACE) risks (myocardial infarction, stroke, or death) and all-cause mortality independent of traditional risk factors. Key gut microbiota-derived metabolites associated with incident MACE and poorer survival risks include: (i) phenylacetyl glutamine and phenylacetyl glycine (from phenylalanine); (ii) p-cresol (from tyrosine) yielding p-cresol sulfate and p-cresol glucuronide; (iii) 4-OH-phenyllactic acid (from tyrosine) yielding 4-OH-benzoic acid and 4-OH-hippuric acid; (iv) indole (from tryptophan) yielding indole glucuronide and indoxyl sulfate; (v) indole-3-pyruvic acid (from tryptophan) yielding indole-3-lactic acid and indole-3-acetyl-glutamine, and (vi) 5-OH-indole-3-acetic acid (from tryptophan).

Key gut microbiota-generated metabolites derived from aromatic amino acids independently associated with incident adverse cardiovascular outcomes are identified, and thus will help focus future studies on gut-microbial metabolic outputs relevant to host cardiovascular health.

To identify the most differentiated serum lipids, especially concerning particle size and fractions, between Japanese living in Japan and Japanese-Americans in Hawaii, in the absence of possible genetic confounders, and cross-sectionally examine the associated modifiable lifestyle factors.

Overall, 1,241 (aged 40-59 years) Japanese living in Japan and Japanese-Americans in Hawaii were included. We quantified 130 serum lipid profiles (VLDL 1-5, IDL, LDL 1-6, high-density lipoprotein [HDL] 1-4, and their subfractions) using Bruker's 1H-nuclear magnetic resonance spectrometer for the primary outcome. Modifiable lifestyle factors included body mass index (BMI), physical activity, alcohol and smoking habits, and 70 nutrient parameters. We evaluated the different lipids between the groups using partial least squares-discriminant analysis and association between extracted lipids and lifestyle factors using multivariable linear regression analysis.

Concentrations of HDL4, HDL with the smallest particle size, were lower in Japanese than in Japanese-Americans of both sexes. Higher fish-derived omega-3 fatty acid intake and lower alcohol intake were associated with lower HDL4 concentrations. A 1% higher kcal intake of total omega-3 fatty acids was associated with a 9.8-mg/dL lower HDL4. Fish-derived docosapentaenoic acid, eicosapentaenoic acid, and docosahexaenoic acid intake were inversely associated with HDL4 concentration. There was no relationship between country, sex, age, or BMI.

Japanese and Japanese-Americans can be differentiated based on HDL4 concentration. High fish intake among the Japanese may contribute to their lower HDL4 concentration. Thus, HDL particle size may be an important clinical marker for coronary artery diseases or a fish consumption biomarker.

Aging is a major risk factor for Alzheimer's disease (AD). AD mouse models are frequently used to assess pathology, behavior, and memory in AD research. While the pathological characteristics of AD are well established, our understanding of the changes in the metabolic phenotypes with age and pathology is limited. In this work, we used the Promethion cage systems^® to monitor changes in physiological metabolic and behavioral parameters with age and pathology in wild-type and 5xFAD mouse models. Then, we assessed whether these parameters could be altered by treatment with oleocanthal, a phenolic compound with neuroprotective properties. Findings demonstrated metabolic parameters such as body weight, food and water intake, energy expenditure, dehydration, and respiratory exchange rate, and the behavioral parameters of sleep patterns and anxiety-like behavior are altered by age and pathology. However, the effect of pathology on these parameters was significantly greater than normal aging, which could be linked to amyloid-β deposition and blood-brain barrier (BBB) disruption. In addition, and for the first time, our findings suggest an inverse correlation between sleep hours and BBB breakdown. Treatment with oleocanthal improved the assessed parameters and reduced anxiety-like behavior symptoms and sleep disturbances. In conclusion, aging and AD are associated with metabolism and behavior changes, with the changes being greater with the latter, which were rectified by oleocanthal. In addition, our findings suggest that monitoring changes in metabolic and behavioral phenotypes could provide a valuable tool to assess disease severity and treatment efficacy in AD mouse models.

Direct diagnosis and accurate assessment of metabolic syndrome (MetS) allow for prompt clinical interventions. However, traditional diagnostic strategies overlook the complex heterogeneity of MetS. Here, we perform metabolomic analysis in 13,554 participants from the natural cohort and identify 26 hub plasma metabolic fingerprints (PMFs) associated with MetS and its early identification (pre-MetS). By leveraging machine-learning algorithms, we develop robust diagnostic models for pre-MetS and MetS with convincing performance through independent validation. We utilize these PMFs to assess the relative contributions of the four major MetS risk factors in the general population, ranked as follows: hyperglycemia, hypertension, dyslipidemia, and obesity. Furthermore, we devise a personalized three-dimensional plasma metabolic risk (PMR) stratification, revealing three distinct risk patterns. In summary, our study offers effective screening tools for identifying pre-MetS and MetS patients in the general community, while defining the heterogeneous risk stratification of metabolic phenotypes in real-world settings.