A reference map of potential determinants for the human serum metabolome

Sinensetin attenuates LPS-induced acute pulmonary inflammation in mice and RAW264.7 cells by modulating NF-κB p65-mediated immune resistance and STAT3-mediated tissue resilience

Acute pulmonary inflammation is a severe lower respiratory tract infection. Sinensetin (SIN), a polymethoxyflavone with strong anti-inflammatory properties, is known to ameliorate LPS-induced acute inflammatory lung injury, but its molecular mechanisms are not fully understood. This study aimed to provide insight into the pharmacological mechanisms of SIN in attenuating acute pulmonary inflammation. In LPS-induced inflammation assays in vivo and in vitro, SIN significantly reduced the mRNA levels of inflammatory genes including MCP-1, ICAM1, Ccl3, Ccl4, Ccl5, Ccl7, Cxcl9, Cxcl10, IL1α, IL1β, IL6, IL11, IL18, IL27, TNF-α, IFN-γ, TLR4, MyD88, F4/80, COX2, iNOS, NLRP3, ASC, JAK2, STAT3, STAT4, and Bcl2l1, as well as increased the mRNA levels of anti-inflammatory genes such as IL4, IL10, and IL12α. Besides, SIN markedly decreased the expression of CD68, TLR4, MyD88, phospho-IκBα (S32/S36), phospho-NF-κB p65 (S536), MCP-1, ICAM1, phospho-JAK2 (Tyr1008), phospho-STAT1 (S727), phospho-STAT3 (Y705), and phospho-STAT4 (Y693), inhibited NF-κB p65 translocation into the nucleus, thereby blocking in combination with STAT transcription factors to induce target gene expression. Further GC-MS/MS and LC-MS/MS metabolomic analysis revealed that SIN significantly increased the abundance of anti-inflammatory metabolites, such as L-alanine, L-carnitine, L-glutamic acid, Glycine, and L-cysteine. In conclusion, the results indicated that SIN attenuated LPS-induced acute pulmonary inflammation by modulating NF-κB p65-mediated immune resistance and STAT3-mediated tissue resilience. All these favorable findings presented critical insights into the remarkable abilities and health benefits of SIN in ameliorating inflammatory lung disease.

Metabolomic insights into pathogenesis and therapeutic potential in adult acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) poses challenges in adult patients, considering its heterogeneous nature and often suboptimal treatment outcomes. Here, we performed a study on 201 newly diagnosed adult ALL cases (age ≥ 15 y) to generate intracellular and dynamic serum metabolomic profiles. Our findings revealed a predominant increase in bile acid (BA) metabolites in serum, alongside metabolic rewiring that supported highly proliferative states and actively metabolic signaling, such as enriched nucleotide metabolism in leukemic blasts. By integrating intracellular metabolomics and transcriptomics, we constructed the Comprehensive Metabolic Information Dataset (CMID), which facilitated the development of a clustering system to supplement current risk stratification. Furthermore, we explored potential metabolic interventions targeting the serum BA profile and energy metabolism in blasts. The combined use of simvastatin with vincristine and dexamethasone regimen demonstrated a synergistic therapeutic effect in a murine ALL model, effectively lowering key BA levels in serum and suppressing the infiltration of leukemic blasts in the liver. In light of the enhanced intracellular redox metabolism, combining FK866 (a nicotinamide phosphoribosyltransferase inhibitor) and venetoclax significantly prolonged survival in a patient-derived xenograft ALL model. Our findings, along with the resulting resources (http://www.genetictargets.com/MALL), provide a framework for the metabolism-centered management of ALL.

Psychobiotics and the gut-brain axis: advances in metabolite quantification and their implications for mental health

Psychobiotics are live microorganisms that, when administered in adequate amounts, confer mental health benefits to the host. Several clinical studies have demonstrated significant mental health benefits from psychobiotic administration, making them an emerging topic in food science. Certain strains of Lactobacillus, Bifidobacterium, Streptococcus, Escherichia, and Enterococcus species are known for their ability to modulate the gut-brain axis and provide mental health benefits. Proposed action mechanisms include the production of neuroactive compounds or their precursors, which may cross the blood-brain barrier, or transported by their extracellular vesicles. However, there is a lack of in vivo evidence directly confirming these mechanisms, although indirect evidence from recent studies suggest potential pathways for further investigation. To advance our understanding, it is crucial to study these mechanisms within the host, with accurate quantification of neuroactive compounds and/or their precursors being key in such studies. Current quantification methods, however, face challenges, such as low sensitivity for detecting trace metabolites and limited specificity due to interference from other compounds, impacting the reliability of measurements. This review discusses the emerging field of psychobiotics, their potential action mechanisms, neuroactive compound estimation techniques, and perspectives for improvement in quantifying neuroactive compounds and/or precursors within the host.

Genetic Architecture and Analysis Practices of Circulating Metabolites in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

Circulating metabolite levels partly reflect the state of human health and diseases and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single-study analyses. Leveraging the rich metabolomics resources generated by the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally diverse samples. We provided a set of reasonable strategies for outlier and imputation handling to process metabolite data. Following the practical analysis framework, we further performed a genome-wide association analysis on 1,135 selected metabolites using whole genome sequencing data from 16,359 individuals passing the quality control filters, and discovered 1,778 independent loci associated with 667 metabolites. Among 108 novel locus-metabolite pairs, we detected not only novel loci within previously implicated metabolite associated genes but also novel genes (such as GAB3 and VSIG4 located in the X chromosome) that have putative roles in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, including well-known metabolic genes such as FADS2 , D2HGDH , SUGP1 , UTG2B17 , strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.

The Role of the Intestinal Flora and Its Derivatives in Neurocognitive Disorders: A Narrative Review from Surgical Perspective

Perioperative neurocognitive dysfunction is a significant concern for population health, impacting postoperative recovery and increasing the financial burden on patients. With an increasing number of surgical procedures being performed, the prevention and management of perioperative neurocognitive dysfunction have garnered significant attention. While factors such as age, lifestyle, genetics, and education are known to influence the development of cognitive dysfunction, recent research has highlighted the role of the gut microbiota in neurological health. An increased abundance of pro-inflammatory gut microbiota can trigger and worsen neuroinflammation, neuronal cell damage, and impaired cellular autophagy. Moreover, the inflammation-promoting gut microbiota can disrupt immune function, impair neuroautophagy, and affect the production and circulation of extracellular vesicles and neurotransmitters. These factors collectively play a role in the onset and advancement of cognitive impairment. This narrative review delves into the molecular mechanisms through which gut microbiota and their derivatives contribute to cognitive impairment, focusing on the impact of anesthesia surgery, changes in gut microbial populations, and perioperative cognitive impairment associations. The study suggests that alterations in the abundance of various bacterial species and their metabolites pre- and post-surgery may be linked to postoperative cognitive impairment. Furthermore, the potential of probiotics or prebiotics in addressing cognitive impairment is discussed, offering a promising avenue for investigating the treatment of perioperative neurocognitive disorders.

Global metabolomic alterations associated with endocrine-disrupting chemicals among pregnant individuals and newborns

BACKGROUND

Gestational exposure to non-persistent endocrine-disrupting chemicals (EDCs) may be associated with adverse pregnancy outcomes. While many EDCs affect the endocrine system, their effects on endocrine-related metabolic pathways remain unclear. This study aims to explore the global metabolome changes associated with EDC biomarkers at delivery.

METHODS

This study included 75 pregnant individuals who delivered at the University of Cincinnati Hospital from 2014 to 2017. We measured maternal urinary biomarkers of paraben/phenol (12), phthalate (13), and phthalate replacements (4) from the samples collected during the delivery visit. Global serum metabolome profiles were analyzed from maternal blood (n = 72) and newborn (n = 63) cord blood samples collected at delivery. Fifteen of the 29 urinary biomarkers were excluded due to low detection frequency or potential exposures during hospital stay. We assessed metabolome-wide associations between 14 maternal urinary biomarkers and maternal/newborn metabolome profiles. Additionally, performed enrichment analysis to identify potential alterations in metabolic pathways.

RESULTS

We observed metabolome-wide associations between maternal urinary concentrations of phthalate metabolites (mono-isobutyl phthalate), phthalate replacements (mono-2-ethyl-5-carboxypentyl terephthalate, mono-2-ethyl-5-hydroxyhexyl terephthalate) and phenols (bisphenol-A, bisphenol-S) and maternal serum metabolome, using q-value < 0.2 as a threshold. Additionally, associations of phthalate metabolites (mono-n-butyl phthalate, monobenzyl phthalate) and phenols (2,5-dichlorophenol, BPA) with the newborn metabolome were noted. Enrichment analyses revealed associations (p-gamma < 0.05) with amino acid, carbohydrate, lipid, glycan, vitamin, and other cofactor metabolism pathways.

CONCLUSION

Maternal paraben, phenol, phthalate, and phthalate replacement biomarker concentrations at delivery were associated with maternal and newborn serum global metabolome.

Research progress on the mechanism and markers of metabolic disorders in the occurrence and development of cognitive dysfunction after ischemic stroke

Post-stroke cognitive impairment (PSCI) is a common complication following a stroke that significantly affects patients' quality of life and rehabilitation outcomes. It also imposes a heavy economic burden. There is an urgent need to better understand the pathophysiology and pathogenesis of PSCI, as well as to identify markers that can predict PSCI early in the clinical stage, facilitating early prevention, monitoring, and treatment. Although the mechanisms underlying PSCI are complex and multifaceted, involving factors such as atherosclerosis and neuroinflammation, metabolic disorders also play a critical role. This article primarily reviews the relationship between metabolic disorders of the three major nutrients-sugar, fat, and protein-and the development of cognitive dysfunction following ischemic stroke (IS). It aims to elucidate how these metabolic disturbances contribute to cognitive dysfunction post-stroke and to explore potential metabolic biomarkers for PSCI. We believe that this review will offer new insights into the early identification, treatment, and prognostic assessment of PSCI.

Impact of omega-3 fatty acids on hypertriglyceridemia, lipidomics, and gut microbiome in patients with type 2 diabetes

BACKGROUND

Fish oil (FO), a mixture of omega-3 fatty acids mainly comprising docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), has been recommended for patients with type 2 diabetes (T2D) and hypertriglyceridemia. However, its effects on lipidomic profiles and gut microbiota and the factors influencing triglyceride (TG) reduction remain unclear.

METHODS

We conducted a 12-week, randomized, double-blind, placebo-controlled trial in 309 Chinese patients with T2D with hypertriglyceridemia (ClinicalTrials.gov: NCT03120299). Participants were randomly assigned (1:1) to receive either 4 g FO or corn oil for 12 weeks. The primary outcome was changes in serum TGs and the lipidomic profile, and the secondary outcome included changes in the gut microbiome and other metabolic variables.

FINDINGS

The FO group had significantly better TG reduction (mean [95% confidence interval (CI)]: -1.51 [-2.01, -1.01] mmol/L) compared to the corn oil group (-0.66 [-1.15, -0.16] mmol/L, p = 0.02). FO significantly altered the serum lipid profile by reducing low-unsaturated TG species and increasing those containing DHA or EPA. FO had minor effects on gut microbiota, while baseline microbial features predicted the TG response to FO better than phenotypic or lipidomic features, potentially mediated by specific lipid metabolites. A total of 9 lipid metabolites significantly mediated the link between 4 baseline microbial variables and the TG response to FO supplementation.

CONCLUSIONS

Our findings demonstrate differential impacts of omega-3 fatty acids on lipidomic and microbial profiles in T2D and highlight the importance of baseline gut microbiota characteristics in predicting the TG-lowering efficacy of FO.

FUNDING

This study was funded by the National Nature Science Foundation.

Decoding aging clocks: New insights from metabolomics

Chronological age is a crucial risk factor for diseases and disabilities among older adults. However, individuals of the same chronological age often exhibit divergent biological aging states, resulting in distinct individual risk profiles. Chronological age estimators based on omics data and machine learning techniques, known as aging clocks, provide a valuable framework for interpreting molecular-level biological aging. Metabolomics is an intriguing and rapidly growing field of study, involving the comprehensive profiling of small molecules within the body and providing the ultimate genome-environment interaction readout. Consequently, leveraging metabolomics to characterize biological aging holds immense potential. The aim of this review was to provide an overview of metabolomics approaches, highlighting the establishment and interpretation of metabolomic aging clocks while emphasizing their strengths, limitations, and applications, and to discuss their underlying biological significance, which has the potential to drive innovation in longevity research and development.

Data reuse in agricultural genomics research: challenges and recommendations

The scientific community has long benefited from the opportunities provided by data reuse. Recognizing the need to identify the challenges and bottlenecks to reuse in the agricultural research community and propose solutions for them, the data reuse working group was started within the AgBioData consortium framework. Here, we identify the limitations of data standards, metadata deficiencies, data interoperability, data ownership, data availability, user skill level, resource availability, and equity issues, with a specific focus on agricultural genomics research. We propose possible solutions stakeholders could implement to mitigate and overcome these challenges and provide an optimistic perspective on the future of genomics and transcriptomics data reuse.

Oral administration of pioglitazone inhibits pulmonary hypertension by regulating the gut microbiome and plasma metabolome in male rats

The oral administrated thiazolidinediones (TZDs) have been widely reported to alleviate experimental pulmonary hypertension (PH). However, previous studies mainly focused on their beneficial effects on the cardiopulmonary vascular system but failed to determine their potential roles on gut microenvironment. This study aims to investigate the effects of pioglitazone, an oral TZD drug, on gut microbiome in classic PH rat models induced by hypoxia (HPH) or SU5416/hypoxia (SuHx-PH) and evaluate the therapeutic potential of supplementation of selective probiotics for experimental PH. Pioglitazone remarkably inhibited the PH pathogenesis in both models and reshaped the gut microbiome and plasma metabolome. Correlation analyses represented strong and unique association between the protective metabolites and bacteria genera (Roseburia, Lactobacillus, and Streptococcus) that were positively stimulated by pioglitazone. Supplementation of selective probiotics Roseburia intestinalis (R. intestinalis) partially attenuated SuHx-PH and rebuilt a novel gut microbiome and host metabolome. This study reports for the first time that oral administration of pioglitazone protects PH by regulating the gut microbiome and host metabolome, providing novel insights for the TZD drugs. The data also supports that modulation of gut microbiota by supplementation of selective probiotics could be a novel effective therapeutic strategy for the treatment of PH.

C. Calado C. Early Mortality Prediction in Intensive Care Unit Patients Based on Serum Metabolomic Fingerprint

Predicting mortality in intensive care units (ICUs) is essential for timely interventions and efficient resource use, especially during pandemics like COVID-19, where high mortality persisted even after the state of emergency ended. Current mortality prediction methods remain limited, especially for critically ill ICU patients, due to their dynamic metabolic changes and heterogeneous pathophysiological processes. This study evaluated how the serum metabolomic fingerprint, acquired through Fourier-Transform Infrared (FTIR) spectroscopy, could support mortality prediction models in COVID-19 ICU patients. A preliminary univariate analysis of serum FTIR spectra revealed significant spectral differences between 21 discharged and 23 deceased patients; however, the most significant spectral bands did not yield high-performing predictive models. By applying a Fast-Correlation-Based Filter (FCBF) for feature selection of the spectra, a set of spectral bands spanning a broader range of molecular functional groups was identified, which enabled Naïve Bayes models with AUCs of 0.79, 0.97, and 0.98 for the first 48 h of ICU admission, seven days prior, and the day of the outcome, respectively, which are, in turn, defined as either death or discharge from the ICU. These findings suggest FTIR spectroscopy as a rapid, economical, and minimally invasive diagnostic tool, but further validation is needed in larger, more diverse cohorts.

Recent findings on metabolomics and the microbiome of oral bacteria involved in dental caries and periodontal disease

Periodontal disease is characterized by bacterial toxins within the oral biofilm surrounding the teeth, leading to gingivitis and the gradual dissolution of the alveolar bone, which supports the teeth. Notably, symptoms in the early stages of the disease are often absent. Similarly, dental caries occurs when oral bacteria metabolize dietary sugars, producing acids that dissolve tooth enamel and dentin. These bacteria are commonly present in the oral cavity of most individuals. Metabolomics, a relatively recent addition to the "omics" research landscape, involves the comprehensive analysis of metabolites in vivo to elucidate pathological mechanisms and accelerate drug discovery. Meanwhile, the term "microbiome" refers to the collection of microorganisms within a specific environmental niche or their collective genomes. The human microbiome plays a critical role in health and disease, influencing a wide array of physiological and pathological processes. Recent advances in microbiome research have identified numerous bacteria implicated in dental caries and periodontal disease. Additionally, studies have uncovered various pathogenic factors associated with these microorganisms. This review focuses on recent findings in metabolomics and the microbiome, specifically targeting oral bacteria linked to dental caries and periodontal disease. We acknowledge the limitation of relying exclusively on the MEDLINE database via PubMed, while excluding other sources such as gray literature, conference proceedings, and clinical practice guidelines.

The mediating role of the genetically predicted N6, N6, N6-trimethyllysine levels in the association between HLA DR on CD14- CD16+ monocytes and ankylosing spondylitis

This study explores the hidden connection between HLA DR on CD14- CD16+ monocytes and ankylosing spondylitis (AS), with a particular emphasis on investigating and measuring the impact of 1091 blood metabolites as potential mediators. We harnessed the power of summary-level data extracted from a comprehensive genome-wide association study to delve into the intricate relationship between genetically predicted HLA DR on CD14- CD16+ monocytes (3621 cases) and AS (1193 cases and 374,621 controls). Furthermore, we employed a two-step Mendelian randomization (MR) methodology to elucidate the extent to which blood metabolites contribute to the effects observed in CD14- CD16+ monocytes, ultimately influencing the development of AS. This methodological approach provides a comprehensive and rigorous exploration of the interplay between blood metabolites and AS, shedding light on the underlying mechanisms governing this intricate association. Through MR analysis, our investigation revealed an increase in HLA DR on CD14- CD16+ monocytes within plasma, which correspondingly led to a reduction in the incidence of AS. The primary MR analysis yielded an odds ratio of 0.64 with a 95% confidence interval spanning from 0.53 to 0.78, underscoring the protective effect of elevated HLA DR on CD14- CD16+ monocytes against the development of AS. Furthermore, our study found no compelling evidence to suggest that AS exerts any discernible influence on HLA DR on CD14- CD16+ monocytes. Instead, our investigation identified N6, N6, N6-trimethyllysine levels (TML), a blood metabolite, as the sole mediator in the relationship between HLA DR on CD14- CD16+ monocytes and AS. Notably, the genetic prediction of AS mediated by TML accounted for a substantial -2.98% proportion of the observed variance. Our investigation has delineated a causal association between HLA DR on CD14- CD16+ monocytes and AS. Specifically, HLA DR on CD14- CD16+ monocytes exhibited a protective effect against the development of AS. Conversely, AS mediated by TML emerged as a risk factor, though the precise impact of HLA DR on CD14- CD16+ monocytes on AS pathogenesis remains enigmatic. It is imperative to embark on further investigations into potential mediators. In a clinical setting, it is imperative to carefully monitor the patient's HLA DR on CD14- CD16+ monocytes levels.

Data-driven cluster analysis identifies distinct types of metabolic dysfunction-associated steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD) exhibits considerable variability in clinical outcomes. Identifying specific phenotypic profiles within MASLD is essential for developing targeted therapeutic strategies. Here we investigated the heterogeneity of MASLD using partitioning around medoids clustering based on six simple clinical variables in a cohort of 1,389 individuals living with obesity. The identified clusters were applied across three independent MASLD cohorts with liver biopsy (totaling 1,099 participants), and in the UK Biobank to assess the incidence of chronic liver disease, cardiovascular disease and type 2 diabetes. Results unveiled two distinct types of MASLD associated with steatohepatitis on histology and liver imaging. The first cluster, liver-specific, was genetically linked and showed rapid progression of chronic liver disease but limited risk of cardiovascular disease. The second cluster, cardiometabolic, was primarily associated with dysglycemia and high levels of triglycerides, leading to a similar incidence of chronic liver disease but a higher risk of cardiovascular disease and type 2 diabetes. Analyses of samples from 831 individuals with available liver transcriptomics and 1,322 with available plasma metabolomics highlighted that these two types of MASLD exhibited distinct liver transcriptomic profiles and plasma metabolomic signatures, respectively. In conclusion, these data provide preliminary evidence of the existence of two distinct types of clinically relevant MASLD with similar liver phenotypes at baseline, but each with specific underlying biological profiles and different clinical trajectories, suggesting the need for tailored therapeutic strategies.

Disentangling the consequences of type 2 diabetes on targeted metabolite profiles using causal inference and interaction QTL analyses

Circulating metabolite levels have been associated with type 2 diabetes (T2D), but the extent to which T2D affects metabolite levels and their genetic regulation remains to be elucidated. In this study, we investigate the interplay between genetics, metabolomics, and T2D risk in the UK Biobank dataset using the Nightingale panel composed of 249 metabolites, 92% of which correspond to lipids (HDL, IDL, LDL, VLDL) and lipoproteins. By integrating these data with large-scale T2D GWAS from the DIAMANTE meta-analysis through Mendelian randomization analyses, we find 79 metabolites with a causal association to T2D, all spanning lipid-related classes except for Glucose and Tyrosine. Twice as many metabolites are causally affected by T2D liability, spanning almost all tested classes, including branched-chain amino acids. Secondly, using an interaction quantitative trait locus (QTL) analysis, we describe four metabolites consistently replicated in an independent dataset from the Estonian Biobank, for which genetic loci in two different genomic regions show attenuated regulation in T2D cases compared to controls. The significant variants from the interaction QTL analysis are significant QTLs for the corresponding metabolites in the general population but are not associated with T2D risk, pointing towards consequences of T2D on the genetic regulation of metabolite levels. Finally, through differential level analyses, we find 165 metabolites associated with microvascular, macrovascular, or both types of T2D complications, with only a few discriminating between complication classes. Of the 165 metabolites, 40 are not causally linked to T2D in either direction, suggesting biological mechanisms specific to the occurrence of complications. Overall, this work provides a map of the consequences of T2D on Nightingale targeted metabolite levels and on their genetic regulation, enabling a better understanding of the T2D trajectory leading to complications.

Gut Microbiome-Driven metabolites influence skin pigmentation in TYRP1 mutant Oujiang Color Common Carp

The gut microbiome plays a key role in regulating the gut-skin axis, and host genetics partially influence this regulation. The study investigated the role of gut microbiota and host genetics in the gut-skin axis, focusing on the unusual "coffee-like" color phenotype observed in TYRP1 mutant Oujiang Color Common Carp. We employed comparative high-throughput omics data from wild-type and mutant fish to quantify the influence of both genetics and gut microbes on skin transcriptomic expression and blood metabolites. We found 525 differential metabolites (DMs) and 45 distinct gut microbial genera in TYRP1 mutant fish compared to wild type. Interaction and causal mediation analyses revealed a complex interplay. The TYRP1 mutation likely triggers an inflammatory pathway involving Acinetobacter bacteria, Leukotrience-C4 and Spermine. This inflammatory response appears to be counterbalanced by an anti-inflammatory cardiovascular genetic network. The net effect is the upregulation of COMT, PLG, C2, C3, F10, TDO2, MHC1, and SERPINF2, leading to unusual coffee-like coloration. This study highlights the intricate interplay between gut microbiota, host genetics, and metabolic pathways in shaping complex phenotypes.

Blood metabolomic profiling reveals new targets in the management of psychological symptoms associated with severe alcohol use disorder

Background

Alcohol use disorder (AUD) is a global health problem with limited therapeutic options. The biochemical mechanisms that lead to this disorder are not yet fully understood, and in this respect, metabolomics represents a promising approach to decipher metabolic events related to AUD. The plasma metabolome contains a plethora of bioactive molecules that reflects the functional changes in host metabolism but also the impact of the gut microbiome and nutritional habits.

Methods

In this study, we investigated the impact of severe AUD (sAUD), and of a 3-week period of alcohol abstinence, on the blood metabolome (non-targeted LC-MS metabolomics analysis) in 96 sAUD patients hospitalized for alcohol withdrawal.

Results

We found that the plasma levels of different lipids ((lyso)phosphatidylcholines, long-chain fatty acids), short-chain fatty acids (i.e. 3-hydroxyvaleric acid) and bile acids were altered in sAUD patients. In addition, several microbial metabolites, including indole-3-propionic acid, p-cresol sulfate, hippuric acid, pyrocatechol sulfate, and metabolites belonging to xanthine class (paraxanthine, theobromine and theophylline) were sensitive to alcohol exposure and alcohol withdrawal. 3-Hydroxyvaleric acid, caffeine metabolites (theobromine, paraxanthine, and theophylline) and microbial metabolites (hippuric acid and pyrocatechol sulfate) were correlated with anxiety, depression and alcohol craving. Metabolomics analysis in postmortem samples of frontal cortex and cerebrospinal fluid of those consuming a high level of alcohol revealed that those metabolites can be found also in brain tissue.

Conclusions

Our data allow the identification of neuroactive metabolites, from interactions between food components and microbiota, which may represent new targets arising in the management of neuropsychiatric diseases such as sAUD.

Funding

Gut2Behave project was initiated from ERA-NET NEURON network (Joint Transnational Call 2019) and was financed by Academy of Finland, French National Research Agency (ANR-19-NEUR-0003-03) and the Fonds de la Recherche Scientifique (FRS-FNRS; PINT-MULTI R.8013.19, Belgium). Metabolomics analysis of the TSDS samples was supported by grant from the Finnish Foundation for Alcohol Studies.

Circulating Metabolite Abundances Associated With Risks of Bipolar Disorder, Schizophrenia, and Depression: A Mendelian Randomization Study

BACKGROUND

Preventive measures and treatments for psychiatric disorders are limited. Circulating metabolites are potential candidates for biomarker and therapeutic target identification, given their measurability and essential roles in biological processes.

METHODS

Leveraging large-scale genome-wide association studies, we conducted Mendelian randomization analyses to assess the associations between circulating metabolite abundances and the risks of bipolar disorder, schizophrenia, and depression. Genetic instruments were selected for 94 metabolites measured in the Canadian Longitudinal Study on Aging cohort (N = 8299). We repeated Mendelian randomization analyses based on the UK Biobank, INTERVAL, and EPIC (European Prospective Investigation into Cancer)-Norfolk studies.

RESULTS

After validating Mendelian randomization assumptions and colocalization evidence, we found that a 1 SD increase in genetically predicted circulating abundances of eicosapentaenoate and docosapentaenoate was associated with odds ratios of 0.72 (95% CI, 0.65-0.79) and 0.63 (95% CI, 0.55-0.72), respectively, for bipolar disorder. Genetically increased Ω-3 unsaturated fatty acids abundance and Ω-3-to-total fatty acids ratio, as well as genetically decreased Ω-6-to-Ω-3 ratio, were negatively associated with the risk of bipolar disorder in the UK Biobank. Genetically increased circulating abundances of 3 N-acetyl-amino acids were associated with an increased risk of schizophrenia with a maximum odds ratio of 1.31 (95% CI, 1.18-1.44) per 1 SD increase. Furthermore, a 1 SD increase in genetically predicted circulating abundance of hypotaurine was associated with an odds ratio of 0.85 (95% CI, 0.78-0.93) for depression.

CONCLUSIONS

The biological mechanisms that underlie Ω-3 unsaturated fatty acids, NAT8-catalyzed N-acetyl-amino acids, and hypotaurine warrant exploration to identify new biomarkers and potential therapeutic targets.

Hypometric genetics: Improved power in genetic discovery by incorporating quality control flags

Balancing the tradeoff between quantity and quality of phenotypic data is critical in omics studies. Measurements below the limit of quantification (BLQ) are often tagged in quality control fields, but these flags are currently underutilized in human genetics studies. Extreme phenotype sampling is advantageous for mapping rare variant effects. We hypothesize that genetic drivers, along with environmental and technical factors, contribute to the presence of BLQ flags. Here, we introduce "hypometric genetics" (hMG) analysis and uncover a genetic basis for BLQ flags, indicating an additional source of genetic signal for genetic discovery, especially from phenotypic extremes. Applying our hMG approach to n = 227,469 UK Biobank individuals with metabolomic profiles, we reveal more than 5% heritability for BLQ flags and report biologically relevant associations, for example, at APOC3, APOA5, and PDE3B loci. For common variants, polygenic scores trained only for BLQ flags predict the corresponding quantitative traits with 91% accuracy, validating the genetic basis. For rare coding variant associations, we find an asymmetric 65.4% higher enrichment of metabolite-lowering associations for BLQ flags, highlighting the impact of putative loss-of-function variants with large effects on phenotypic extremes. Joint analysis of binarized BLQ flags and the corresponding quantitative metabolite measurements improves power in Bayesian rare variant aggregation tests, resulting in an average of 181% more prioritized genes. Our approach is broadly applicable to omics profiling. Overall, our results underscore the benefit of integrating quality control flags and quantitative measurements and highlight the advantage of joint analysis of population-based samples and phenotypic extremes in human genetics studies.

Sex-specific dietary habits and their association with weight change in healthy adults

BACKGROUND

Dietary intake plays a pivotal role in the prevalence and management of obesity. While women and men exhibit differences in dietary habits and food-related behaviors, sex-based weight loss recommendations are lacking. This study aims to examine the impact of specific foods and food categories on weight reduction in men and women over a two-year period.

METHODS

A total of 8,548 participants from the 10K cohort, from 2019 to 2023, were included in the analysis (53.1% women, mean age 51.7 years). Anthropometric measurements and laboratory results were collected at baseline and at the two-year follow-up visit. Dietary assessment was based on daily food intake digitally logged through an application for at least 3 consecutive days at both timepoints. We compared intake of macronutrients, micronutrients, food groups and daily energy consumption between sex and body mass index (BMI) categories at baseline and weight change categories at follow-up. Using linear regression, we assessed the associations between food categories or specific foods and BMI at baseline as well as weight change percentage at follow-up.

RESULTS

Dietary habits varied by BMI and sex. Women and men living with obesity (BMI > 30 kg/m2) reported a greater intake of animal-based protein and lower intake of plant-based proteins and fats at baseline, as compared to participants with normal weight. In linear regression models predicting two-year weight change, including age, income, and baseline weight, the explained variance was 5.6% for men and 5.8% for women. Adding food categories and specific foods increased the explained variance to 20.6% for men and 17.5% for women. Weight reduction in men was linked to daily consumption of an egg (1.2% decrease) and beef (1.5% decrease), while in women, the most pronounced reductions were associated with an apple (1.2% decrease) and cashew nuts (3.4% decrease). Notably, total energy intake changes significantly impacted weight outcomes only in women.

CONCLUSIONS

Sex-specific dietary habits significantly influence weight change over time. In men, weight loss was primarily associated with the addition of animal-based protein, while in women, it was linked to caloric deficit and plant-based fat, suggesting that sex-based nutritional interventions may demonstrate greater efficacy.

TRIAL REGISTRATION

NCT05817734 (retrospectively registered January 31, 2023).

Sources of variation in the serum metabolome of female participants of the HUNT2 study

The aim of this study was to explore the intricate relationship between serum metabolomics and lifestyle factors, shedding light on their impact on health in the context of breast cancer risk. Detailed metabolic profiles of 2283 female participants in the Trøndelag Health Study (HUNT study) were obtained through nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS).We show that lifestyle-related variables can explain up to 30% of the variance in individual metabolites. Age and obesity were the primary factors affecting the serum metabolic profile, both associated with increased levels of triglyceride-rich very low-density lipoproteins (VLDL) and intermediate-density lipoproteins (IDL), amino acids and glycolysis-related metabolites, and decreased levels of high-density lipoproteins (HDL). Moreover, factors like hormonal changes associated with menstruation and contraceptive use or education level influence the metabolite levels.Participants were clustered into three distinct clusters based on lifestyle-related factors, revealing metabolic similarities between obese and older individuals, despite diverse lifestyle factors, suggesting accelerated metabolic aging with obesity. Our results show that metabolic associations to cancer risk may partly be explained by modifiable lifestyle factors.

Xanthohumol Protects Against Neuronal Excitotoxicity and Mitochondrial Dysfunction in APP/PS1 Mice: An Omics-Based Study

Background: Neuronal excitotoxicity and metabolic decline, which begin in the early stages of Alzheimer's disease (AD), pose challenges for effective amelioration. Our previous work suggested that the natural compound xanthohumol, the most abundant prenylated flavonoid in hops, prevents memory deficits in APP/PS1 mice; however, the underlying mechanisms remain unclear. Methods: This study utilized APP/PS1 mice and cutting-edge omics techniques to investigate the effects of xanthohumol on hippocampal proteome, serum metabolome, and microbiome. Results: Our findings revealed that xanthohumol reduces the postsynaptic overexpression of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid, N-methyl-D-aspartate, and metabotropic glutamate receptors, but enhances ATP synthesis and mitophagy in the young AD hippocampus. Further mechanistic analyses suggested systemic regulatory effects, particularly on the decreasing glutamate synthesis in the blood and intestines of AD mice following xanthohumol administration. Conclusions: These results underscore the potential of xanthohumol in mitigating AD pathology through multifaceted mechanisms, sparking interest and curiosity in its preventive and therapeutic potential in AD.

α-synuclein overexpression and the microbiome shape the gut and brain metabolome in mice

Pathological forms of α-synuclein contribute to synucleinopathies, including Parkinson's disease (PD). Most cases of PD arise from gene-environment interactions. Microbiome composition is altered in PD, and gut bacteria are causal to symptoms in animal models. We quantitatively profiled nearly 630 metabolites in the gut, plasma, and brain of α-synuclein-overexpressing (ASO) mice, compared to wild-type (WT) animals, and comparing germ-free (GF) to specific pathogen-free (SPF) animals (n = 5 WT-SPF; n = 6 ASO-SPF; n = 6 WT-GF; n = 6 ASO-GF). Many differentially expressed metabolites in ASO mice are also dysregulated in human PD patients, including amine oxides, bile acids and indoles. The microbial metabolite trimethylamine N-oxide (TMAO) strongly correlates from the gut to the plasma to the brain in mice, notable since TMAO is elevated in the blood and cerebrospinal fluid of PD patients. These findings uncover broad metabolomic changes that are influenced by the intersection of host genetics and microbiome in a mouse model of PD.

Lipid metabolic profiling and diagnostic model development for hyperlipidemic acute pancreatitis

Introduction

Hyperlipidemic acute pancreatitis (HLAP) is a form of pancreatitis induced by hyperlipidemia, posing significant diagnostic challenges due to its complex lipid metabolism disturbances.

Methods

This study compared the serum lipid profiles of HLAP patients with those of a healthy cohort using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to identify distinct lipid metabolites. Logistic regression and LASSO regression were used to develop a diagnostic model based on the lipid molecules identified.

Results

A total of 393 distinct lipid metabolites were detected, impacting critical pathways such as fatty acid, sphingolipid, and glycerophospholipid metabolism. Five specific lipid molecules were selected to construct a diagnostic model, which achieved an area under the curve (AUC) of 1 in the receiver operating characteristic (ROC) analysis, indicating outstanding diagnostic accuracy.

Discussion

These findings highlight the importance of lipid metabolism disturbances in HLAP. The identified lipid molecules could serve as valuable biomarkers for HLAP diagnosis, offering potential for more accurate and early detection.

Comorbidities confound metabolomics studies of human disease

The co-occurrence of multiple chronic conditions, termed multimorbidity, presents an expanding global health challenge, demanding effective diagnostics and treatment strategies. Chronic ailments such as obesity, diabetes, and cardiovascular diseases have been linked to metabolites interacting between the host and microbiota. In this study, we investigated the impact of co-existing conditions on risk estimations for 1375 plasma metabolites in 919 individuals from population-based Estonian Biobank cohort using liquid chromatography mass spectrometry (LC-MS) method. We leveraged annually linked national electronic health records (EHRs) data to delineate comorbidities in incident cases and controls for the 14 common chronic conditions. Among the 254 associations observed across 13 chronic conditions, we primarily identified disease-specific risk factors (92%, 217/235), with most predictors (93%, 219/235) found to be related to the gut microbiome upon cross-referencing recent literature data. Accounting for comorbidities led to a reduction of common metabolite predictors across various conditions. In conclusion, our study underscores the potential of utilizing biobank-linked retrospective and prospective EHRs for the disease-specific profiling of diverse multifactorial chronic conditions.

Protein catabolites as blood-based biomarkers of aging physiology: Findings from the Dog Aging Project

Our understanding of age-related physiology and metabolism has grown through the study of systems biology, including transcriptomics, single-cell analysis, proteomics and metabolomics. Studies in lab organisms in controlled environments, while powerful and complex, fall short of capturing the breadth of genetic and environmental variation in nature. Thus, there is now a major effort in geroscience to identify aging biomarkers and to develop aging interventions that might be applied across the diversity of humans and other free-living species. To meet this challenge, the Dog Aging Project (DAP) is designed to identify cross-sectional and longitudinal patterns of aging in complex systems, and how these are shaped by the diversity of genetic and environmental variation among companion dogs. Here we surveyed the plasma metabolome from the first year of sampling of the Precision Cohort of the DAP. By incorporating extensive metadata and whole genome sequencing information, we were able to overcome the limitations inherent in breed-based estimates of genetic and physiological effects, and to probe the physiological and dietary basis of the age-related metabolome. We identified a significant effect of age on approximately 40% of measured metabolites. Among other insights, we discovered a potentially novel biomarker of age in the post-translationally modified amino acids (ptmAAs). The ptmAAs, which can only be generated by protein hydrolysis, covaried both with age and with other biomarkers of amino acid metabolism, and in a way that was robust to diet. Clinical measures of kidney function mediated about half of the higher ptmAA levels in older dogs. This work identifies ptmAAs as robust indicators of age in dogs, and points to kidney function as a physiological mediator of age-associated variation in the plasma metabolome.

Point-of-care testing for early-stage liver cancer diagnosis and personalized medicine: Biomarkers, current technologies and perspectives

Liver cancer is a highly prevalent and lethal form of cancer worldwide. In the absence of early diagnosis, treatment options for this disease are severely restricted. Recent advancements in genomics and bioinformatics have facilitated the discovery of a multitude of novel biomarkers that accurately depict an individual's disease diagnosis, progression, and treatment response. Leveraging these breakthroughs, personalized medicine employs an individual's biomarker profile to enable early detection of liver cancer and inform decisions regarding treatment selection, dosage determination, and prognosis assessment. The current lack of readily applicable, timely, and economically viable tools for biomarker analysis has hindered the incorporation of personalized medicine into regular clinical procedures. Over the past decade, significant advancements have been achieved in the field of molecular point-of-care testing (POCT) and amplification techniques, leading to substantial improvements in the diagnosis of liver cancer and the implementation of precision medicine. Instrument-free PCR technology or plasma PCR technology can shorten the complex procedure of in vitro detection of nucleic acid-based biomarkers. Also, compared to traditional ELISA, various nanomaterials modified with monoclonal antibodies to target proteins for recognition, capture, and detection have improved the efficiency of protein-based biomarker detection. These advances have reduced the time and cost of clinical detection of early-stage hepatocellular carcinoma and improved the efficiency of timely diagnosis and survival of suspected patients while reducing unnecessary testing costs and procedures. This review aims to provide a comprehensive overview of the current and emerging biomarkers employed in the early detection of liver cancer, as well as the advancements in point-of-care molecular testing technology and platforms. The primary objective is to assess their potential in facilitating the implementation of personalized medicine. This review ultimately revealed that the diagnosis of early-stage hepatocellular carcinoma not only requires sensitive biomarkers, but its various modifications and changes during the progression of cirrhosis to early-stage hepatocellular carcinoma will be a greater focus of our attention in the future. The rapid development of POCT has facilitated the opportunity to readily detect liver cancer in the general population in the future, and the integration of multi-pathway multiplexing and intelligent algorithms has improved the sensitivity and accuracy of early liver cancer biomarker detection. It is expected that the integration of point-of-care technology will be instrumental in the widespread adoption of personalized medicine in the foreseeable future.

Causal relationship between metabolites and embolic stroke: based on Mendelian randomization and metabolomics

Purpose

This research employed Mendelian randomization (MR) methods to explore whether metabolites are causally associated with embolic stroke of undetermined source (ESUS).

Methods

Genome-Wide Association Study (GWAS) data regarding metabolites and ESUS were downloaded from the database. Metabolites were employed as exposure factors, ESUS served as the outcome variable, and single nucleotide polymorphisms (SNPs) exhibiting significant association with ESUS were chosen as instrumental variables. The causal association between exposure factor metabolites and the outcome variable ESUS was assessed using two methods: MR-Egger regression and inverse variance-weighted (IVW) analysis.

Results

A causal relationship was observed between X-11593--O-methylascorbate* and ESUS, indicating a protective factor. Moreover, a causal relationship was identified between cholesterol esters in large very-low-density lipoprotein (VLDL), cholesterol esters in medium low-density lipoprotein (LDL), concentration of medium LDL particles, phospholipids in medium LDL, phenylalanine, total cholesterol in small LDL, total lipids in medium LDL and ESUS, representing risk factor. Funnel plots exhibited a symmetrical distribution of SNPs, while pleiotropic tests (p > 0.05) and leave-one-out tests indicated that the results were relatively stable.

Conclusion

Metabolites are causally associated with ESUS. LDL and VLDL-related metabolites are identified as risk factors for ESUS.

Untargeted faecal metabolomics for the discovery of biomarkers and treatment targets for inflammatory bowel diseases

The gut microbiome has been recognised as a key component in the pathogenesis of inflammatory bowel diseases (IBD), and the wide range of metabolites produced by gut bacteria are an important mechanism by which the human microbiome interacts with host immunity or host metabolism. High-throughput metabolomic profiling and novel computational approaches now allow for comprehensive assessment of thousands of metabolites in diverse biomaterials, including faecal samples. Several groups of metabolites, including short-chain fatty acids, tryptophan metabolites and bile acids, have been associated with IBD. In this Recent Advances article, we describe the contribution of metabolomics research to the field of IBD, with a focus on faecal metabolomics. We discuss the latest findings on the significance of these metabolites for IBD prognosis and therapeutic interventions and offer insights into the future directions of metabolomics research.

Modulation of anxiety-like behavior in galactooligosaccharide-fed mice: A potential role for bacterial tryptophan metabolites and reduced microglial reactivity

Prebiotic galactooligosaccharides (GOS) reduce anxiety-like behaviors in mice and humans. However, the biological pathways behind these behavioral changes are not well understood. To begin to study these pathways, we utilized C57BL/6 mice that were fed a standard diet with or without GOS supplementation for 3 weeks prior to testing on the open field. After behavioral testing, colonic contents and serum were collected for bacteriome (16S rRNA gene sequencing, colonic contents only) and metabolome (UPLC-MS, colonic contents and serum data) analyses. As expected, GOS significantly reduced anxiety-like behavior (i.e., increased time in the center) and decreased cytokine gene expression (Tnfa and Ccl2) in the prefrontal cortex. Notably, time in the center of the open field was significantly correlated with serum methyl-indole-3-acetic acid (methyl-IAA). This metabolite is a methylated form of indole-3-acetic acid (IAA) that is derived from bacterial metabolism of tryptophan. Sequencing analyses showed that GOS significantly increased Lachnospiraceae UCG006 and Akkermansia; these taxa are known to metabolize both GOS and tryptophan. To determine the extent to which methyl-IAA can affect anxiety-like behavior, mice were intraperitoneally injected with methyl-IAA. Mice given methyl-IAA had a reduction in anxiety-like behavior in the open field, along with lower Tnfa in the prefrontal cortex. Methyl-IAA was also found to reduce TNF-α (as well as CCL2) production by LPS-stimulated BV2 microglia. Together, these data support a novel pathway through which GOS reduces anxiety-like behaviors in mice and suggests that the bacterial metabolite methyl-IAA reduces microglial cytokine and chemokine production, which in turn reduces anxiety-like behavior.

Mapping biological influences on the human plasma proteome beyond the genome

Broad-capture proteomic platforms now enable simultaneous assessment of thousands of plasma proteins, but most of these are not actively secreted and their origins are largely unknown. Here we integrate genomic with deep phenomic information to identify modifiable and non-modifiable factors associated with 4,775 plasma proteins in ~8,000 mostly healthy individuals. We create a data-driven map of biological influences on the human plasma proteome and demonstrate segregation of proteins into clusters based on major explanatory factors. For over a third (N = 1,575) of protein targets, joint genetic and non-genetic factors explain 10-77% of the variation in plasma (median 19.88%, interquartile range 14.01-31.09%), independent of technical factors (median 2.48%, interquartile range 0.78-6.41%). Together with genetically anchored causal inference methods, our map highlights potential causal associations between modifiable risk factors and plasma proteins for hundreds of protein-disease associations, for example, COL6A3, which possibly mediates the association between reduced kidney function and cardiovascular disease. We provide a map of biological and technical influences on the human plasma proteome to help contextualize findings from proteomic studies.

Enhanced cytokine signaling and ferroptosis defense interplay initiates obesity-associated pancreatic ductal adenocarcinoma

Obesity is a significant risk factor for various cancers, including pancreatic cancer (PC), but the underlying mechanisms are still unclear. In our study, pancreatic ductal epithelial cells were cultured using serum from human subjects with diverse metabolic statuses, revealing that serum from patients with obesity alters inflammatory cytokine signaling and ferroptosis, where a mutual enhancement between interleukin 34 (IL-34) expression and ferroptosis defense was observed in these cells. Notably, oncogenic KRASG12D amplified their interaction and this leads to the initiation of pancreatic ductal adenocarcinoma (PDAC) in diet-induced obese mice via macrophage-mediated immunosuppression. Single-cell RNA sequencing (scRNA-seq) of human samples showed that cytokine signaling, ferroptosis defense, and immunosuppression are correlated with the patients' body mass index (BMI) during PDAC progression. Our findings provide a mechanistic link between obesity, inflammation, ferroptosis defense, and pancreatic cancer, suggesting novel therapeutic targets for the prevention and treatment of obesity-associated PDAC.

Recent advances in precision nutrition and cardiometabolic diseases

A growing body of research on nutrition omics has led to recent advances in cardiovascular disease epidemiology and prevention. Within the PREDIMED trial, significant associations between diet-related metabolites and cardiovascular disease were identified, which were subsequently replicated in independent cohorts. Some notable metabolites identified include plasma levels of ceramides, acyl-carnitines, branched-chain amino acids, tryptophan, urea cycle pathways, and the lipidome. These metabolites and their related pathways have been associated with incidence of both cardiovascular disease and type 2 diabetes. Future directions in precision nutrition research include: a) developing more robust multimetabolomic scores to predict long-term risk of cardiovascular disease and mortality; b) incorporating more diverse populations and a broader range of dietary patterns; and c) conducting more translational research to bridge the gap between precision nutrition studies and clinical applications.

Recent advances in precision nutrition and cardiometabolic diseases

A growing body of research on nutrition omics has led to recent advances in cardiovascular disease epidemiology and prevention. Within the PREDIMED trial, significant associations between diet-related metabolites and cardiovascular disease were identified, which were subsequently replicated in independent cohorts. Some notable metabolites identified include plasma levels of ceramides, acyl-carnitines, branched-chain amino acids, tryptophan, urea cycle pathways, and the lipidome. These metabolites and their related pathways have been associated with incidence of both cardiovascular disease and type 2 diabetes. Future directions in precision nutrition research include: a) developing more robust multimetabolomic scores to predict long-term risk of cardiovascular disease and mortality; b) incorporating more diverse populations and a broader range of dietary patterns; and c) conducting more translational research to bridge the gap between precision nutrition studies and clinical applications.

Metabolomic characterization of COVID-19 survivors in Jilin province

BACKGROUND

The COVID-19 pandemic has escalated into a severe global public health crisis, with persistent sequelae observed in some patients post-discharge. However, metabolomic characterization of the reconvalescent remains unclear.

METHODS

In this study, serum and urine samples from COVID-19 survivors (n = 16) and healthy subjects (n = 16) underwent testing via the non-targeted metabolomics approach using UPLC-MS/MS. Univariate and multivariate statistical analyses were conducted to delineate the separation between the two sample groups and identify differentially expressed metabolites. By integrating random forest and cluster analysis, potential biomarkers were screened, and the differential metabolites were subsequently subjected to KEGG pathway enrichment analysis.

RESULTS

Significant differences were observed in the serum and urine metabolic profiles between the two groups. In serum samples, 1187 metabolites were detected, with 874 identified as significant (457 up-regulated, 417 down-regulated); in urine samples, 960 metabolites were detected, with 39 deemed significant (12 up-regulated, 27 down-regulated). Eight potential biomarkers were identified, with KEGG analysis revealing significant enrichment in several metabolic pathways, including arginine biosynthesis.

CONCLUSIONS

This study offers an overview of the metabolic profiles in serum and urine of COVID-19 survivors, providing a reference for post-discharge monitoring and the prognosis of COVID-19 patients.

Serum metabolomics reveals the effectiveness of human placental mesenchymal stem cell therapy for Crohn's disease

Mesenchymal stem cell (MSC) therapy offers a promising cure for Crohn's disease (CD), however, its therapeutic effects vary significantly due to individual differences. Therefore, identifying easily detectable biomarkers is essential to assess the efficacy of MSC therapy. In this study, SAMP1/Yit mice were used as a model of CD, which develop spontaneous chronic ileitis, closely resembling the characteristics present in CD patients. Serum metabolic alterations during treatment were analyzed, through the application of differential 12C-/13C-dansylation labeling liquid chromatography-mass spectrometry. Based on the significant differences and time-varying trends of serum amine/phenol-containing metabolites abundance between the control group, the model group, and the treatment group, four serum biomarkers were ultimately screened for evaluating the efficacy of MSC treatment for CD, namely 4-hydroxyphenylpyruvate, 4-hydroxyphenylacetaldehyde, caffeate, and N-acetyltryptamine, whose abundances both increased in the serum of CD model mice and decreased after MSC treatment. These metabolic alterations were associated with tyrosine metabolism, which was validated by the dysregulation of related enzymes. The discovery of biomarkers may help to improve the targeting and effectiveness of treatment and provide innovative prospects for the clinical application of MSC for CD.

Clinical metabolomics: current state and prospects in Russia

Using analytical technologies it is possible now to measure the entire diversity of molecules even in a small amount of biological samples. Metabolomic technologies simultaneously analyze thousands of low-molecular substances in a single drop of blood. Such analytical performance opens new possibilities for clinical laboratory diagnostics, still relying on the measurement of only a limited number of clinically significant substances. However, there are objective difficulties hampering introduction of metabolomics into clinical practice. The Institute of Biomedical Chemistry (IBMC), consolidating the efforts of leading scientific and medical organizations, has achieved success in this area by developing a clinical blood metabogram (CBM). CBM opens opportunities to obtain overview on the state of the body with the detailed individual metabolic characteristics of the patient. A number of scientific studies have shown that the CBM is an effective tool for monitoring the state of the body, and based on the CBM patterns (signatures), it is possible to diagnose and monitor the treatment of many diseases. Today, the CBM creation determines the current state and prospects of clinical metabolomics in Russia. This article, dedicated to the 80th anniversary of IBMC, is a review of these achievements focused on a discussion of their implementation in clinical practice.

Mitochondrial related variants associated with cardiovascular traits

Introduction

Cardiovascular disease (CVD) is responsible for over 30% of mortality worldwide. CVD arises from the complex influence of molecular, clinical, social, and environmental factors. Despite the growing number of autosomal genetic variants contributing to CVD, the cause of most CVDs is still unclear. Mitochondria are crucial in the pathophysiology, development and progression of CVDs; the impact of mitochondrial DNA (mtDNA) variants and mitochondrial haplogroups in the context of CVD has recently been highlighted.

Aims

We investigated the role of genetic variants in both mtDNA and nuclear-encoded mitochondrial genes (NEMG) in CVD, including coronary artery disease (CAD), hypertension, and serum lipids in the UK Biobank, with sub-group analysis for diabetes.

Methods

We investigated 371,542 variants in 2,527 NEMG, along with 192 variants in 32 mitochondrial genes in 381,994 participants of the UK Biobank, stratifying by presence of diabetes.

Results

Mitochondrial variants showed associations with CVD, hypertension, and serum lipids. Mitochondrial haplogroup J was associated with CAD and serum lipids, whereas mitochondrial haplogroups T and U were associated with CVD. Among NEMG, variants within Nitric Oxide Synthase 3 (NOS3) showed associations with CVD, CAD, hypertension, as well as diastolic and systolic blood pressure. We also identified Translocase Of Outer Mitochondrial Membrane 40 (TOMM40) variants associated with CAD; Solute carrier family 22 member 2 (SLC22A2) variants associated with CAD and CVD; and HLA-DQA1 variants associated with hypertension. Variants within these three genes were also associated with serum lipids.

Conclusion

Our study demonstrates the relevance of mitochondrial related variants in the context of CVD. We have linked mitochondrial haplogroup U to CVD, confirmed association of mitochondrial haplogroups J and T with CVD and proposed new markers of hypertension and serum lipids in the context of diabetes. We have also evidenced connections between the etiological pathways underlying CVDs, blood pressure and serum lipids, placing NOS3, SLC22A2, TOMM40 and HLA-DQA1 genes as common nexuses.

The mediating role of metabolites between gut microbiome and Hirschsprung disease: a bidirectional two-step Mendelian randomization study

Background

Gut microbiome (GM) was observed to be associated with the incidence of Hirschsprung disease (HD). However, the effect and mechanism of GM in HD is still unclear. To investigate the relationship between GM and HD and the effect of metabolites as mediators, a bidirectional two-step Mendelian randomization (MR) study was conducted.

Methods

The study selected instrument variables (IVs) from summary-level genome-wide association studies (GWAS). The MiBioGen consortium provided the GWAS data for GM, while the GWAS data for metabolites and HD were obtained from the GWAS Catalog consortium. Two-sample MR analyses were performed to estimate bidirectional correlations between IVs associated with GM and HD. Then, genetic variants related to 1,400 metabolite traits were selected for further mediation analyses using the Product method.

Results

This study found that seven genus bacteria had a significant causal relationship with the incidence of HD but not vice versa. 27 metabolite traits were significantly correlated with HD. After combining the significant results, three significant GM-metabolites-HD lines have been identified. In the Peptococcus-Stearoyl sphingomyelin (d18:1/18:0)-HD line, the Stearoyl sphingomyelin (d18:1/18:0) levels showed a mediation proportion of 14.5%, while in the Peptococcus-lysine-HD line, the lysine levels had a mediation proportion of 12.9%. Additionally, in the Roseburia-X-21733-HD line, the X-21733 levels played a mediation proportion of 23.5%.

Conclusion

Our MR study indicates a protective effect of Peptococcus on HD risk that is partially mediated through serum levels of stearoyl sphingomyelin (d18:1/18:0) and lysine, and a risk effect of Roseburia on HD that is partially mediated by X-21733 levels. These findings could serve as novel biomarkers and therapeutic targets for HD.

Quantification and Correlation Analysis of Bacteroides Species with Diabetes-Related Amino Acids in Individuals with Prediabetes and Type 2 Diabetes Mellitus

Background: The relationship between gut microbiota and diabetes-related amino acids significantly impacts insulin resistance and obesity. We aimed to quantify two Bacteroidetes species and their correlation with branched-chain amino acids, aromatic amino acids, and glutamate in prediabetes (preDM) and type 2 diabetes mellitus (T2DM). Methods: Fecal samples were collected from 68 participants, including 21 with T2DM, 23 with preDM, and 24 with normal glycemic tolerance (NGT). The abundance of Bacteroides vulgatus and Bacteroides thetaiotaomicron was determined by quantitative real-time polymerase chain reaction. Plasma amino acid measurements were performed using liquid chromatography coupled with tandem mass spectrometry. Results: The quantities of B. vulgatus and B. thetaiotaomicron were reduced in preDM and T2DM than in NGT subjects, but it was not statistically significant. The concentrations of leucine, valine, and tyrosine were significantly higher in preDM and T2DM than in NGT subjects (P < 0.05). A negative correlation was observed between B. thetaiotaomicron abundance and two aromatic amino acids (tyrosine, r = -0.28, P = 0.04; phenylalanine, r = -0.26, P = 0.05). Conclusions: These findings imply that, since gut microbiota varies throughout ethnic groups, further research with many participants will be required to determine the abundance of B. vulgatus and B. thetaiotaomicron in preDM and T2DM and their association with diabetes-related amino acids.

Association between the third trimester maternal serum metabolome and child growth and development through the first year of life

Evidence suggests that maternal metabolome may be associated with child health outcomes. We analyzed the association between the maternal metabolome between 28-35 gestational weeks and child growth and development during the first year. A prospective cohort of 98 mother-child dyads was followed at birth, 1, 6, and 12 months. Maternal serum samples were collected for targeted LC-MS/MS analysis, which measured 132 metabolites. The child's growth and development were assessed at each time-point. Z-scores were calculated based on WHO growth standards, and the domains of development were assessed using the Ages and Stages Questionnaires (ASQ-3). Multiple linear mixed-effects models were performed and confounders were identified using a Diagram Acyclic Graph. The Benjamini-Hochberg correction was used for multiple comparison adjustments. We found a positive association between lysophosphatidylcholines (14:0; 16:0; 16:1; 17:0; 18:0; 18:1; 18:2; 20:4) with the z-score of weight-for-age, and lysophosphatidylcholines (14:0; 16:0; 16:1; 18:0) and taurine with the z-score of weight-for-length, and lysophosphatidylcholines (14:0; 16:0; 16:1; 17:0; 18:0; 18:1; 18:2; 20:4) and glycine with the z-score of BMI-for-age. The leucine, methionine, tryptophan, and valine were negatively associated with the fine motor skills domain. We observed an association between maternal metabolome and the growth and child's development throughout the first year.

Metagenomics-Metabolomics Exploration of Three-Way-Crossbreeding Effects on Rumen to Provide Basis for Crossbreeding Improvement of Sheep Microbiome and Metabolome of Sheep

The objective of this experiment was to explore the effects of three-way hybridization on rumen microbes and metabolites in sheep using rumen metagenomics and metabolomics. Healthy Hu and CAH (Charolais × Australian White × Hu) male lambs of similar birth weight and age were selected for short-term fattening after intensive weaning to collect rumen fluid for sequencing. Rumen metagenomics diversity showed that Hu and CAH sheep were significantly segregated at the species, KEGG-enzyme, and CAZy-family levels. Moreover, the CAH significantly increased the ACE and Chao1 indices. Further, correlation analysis of the abundance of the top 80 revealed that the microorganisms were interrelated at the species, KEGG-enzyme, and CAZy-family levels. Overall, the microbiome significantly affected metabolites of the top five pathways, with the strongest correlation found with succinic acid. Meanwhile, species-level microbial markers significantly affected rumen differential metabolites. In addition, rumen microbial markers in Hu sheep were overall positively correlated with down-regulated metabolites and negatively correlated with up-regulated metabolites. In contrast, rumen microbial markers in CAH lambs were overall negatively correlated with down-regulated metabolites and positively correlated with up-regulated metabolites. These results suggest that three-way crossbreeding significantly affects rumen microbial community and metabolite composition, and that significant interactions exist between rumen microbes and metabolites.

Metaboepigenetic regulation of gene expression in obesity and insulin resistance

INTRODUCTION

Variation in DNA methylation (DNAm) in adipose tissue is associated with the pathogenesis of obesity and insulin resistance. The activity of enzymes involved in altering DNAm levels is dependent on several metabolite cofactors.

OBJECTIVES

To understand the role of metabolites as mechanistic regulators of epigenetic marks, we tested the association between selected plasma metabolites and DNAm levels in the adipose tissue of African Americans.

METHODS

In the AAGMEx cohort (N = 256), plasma levels of metabolites were measured by untargeted liquid chromatography-mass spectrometry; adipose tissue DNAm and transcript levels were measured by reduced representation bisulfite sequencing, and expression microarray, respectively.

RESULTS

Among the 21 one-carbon metabolism pathway metabolites evaluated, six were associated with gluco-metabolic traits (PFDR < 0.05, for BMI, SI, or Matsuda index) in AAGMEx. Methylation levels of 196, 116, and 180 CpG-sites were associated (P < 0.0001) with S-adenosylhomocysteine (SAH), cystine, and hypotaurine, respectively. Cis-expression quantitative trait methylation (cis eQTM) analyses suggested the role of metabolite-level-associated CpG sites in regulating the expression of adipose tissue transcripts, including genes in G-protein coupled receptor signaling pathway. Plasma SAH level-associated CpG sites chr19:3403712 and chr19:3403735 were also associated with the expression of G-protein subunit alpha 15 (GNA15) in adipose. The expression of GNA15 was significantly correlated with BMI (β = 1.87, P = 1.9 × 10-16) and SI (β = -1.61, P = 2.49 × 10-5).

CONCLUSION

Our study suggests that a subset of metabolites modulates the methylation levels of CpG sites in specific loci and, in turn, regulates the expression of transcripts involved in obesity and insulin resistance.

The Food Sources in Western Diets Modulate Obesity Development, Insulin Sensitivity, and the Plasma and Cecal Metabolome in Mice

SCOPE

Dietary constituents modulate development of obesity and type 2 diabetes. The metabolic impact from different food sources in western diets (WD) on obesity development is not fully elucidated. This study aims to identify dietary sources that differentially affect obesity development and the metabolic processes involved.

METHODS AND RESULTS

Mice were fed isocaloric WDs with protein and fat from different food groups, including egg and dairy, terrestrial meat, game meat, marine, vegetarian, and a mixture of all. This study evaluates development of obesity, glucose tolerance, insulin sensitivity, and plasma and cecal metabolome. WD based on marine or vegetarian food sources protects male mice from obesity development and insulin resistance, whereas meat-based diets promote obesity. The intake of different food sources induces marked differences in the lipid-related plasma metabolome, particularly impacting phosphatidylcholines. Fifty-nine lipid-related plasma metabolites are positively associated with adiposity and a distinct cecal metabolome is found in mice fed a marine diet.

CONCLUSION

This study demonstrates differences in obesity development between the food groups. Diet specific metabolomic signatures in plasma and cecum associated with adiposity, where a marine based diet modulates the level of plasma and cecal phosphatidylcholines in addition to preventing obesity development.

Western diets and chronic diseases

'Westernization', which incorporates industrial, cultural and dietary trends, has paralleled the rise of noncommunicable diseases across the globe. Today, the Western-style diet emerges as a key stimulus for gut microbial vulnerability, chronic inflammation and chronic diseases, affecting mainly the cardiovascular system, systemic metabolism and the gut. Here we review the diet of modern times and evaluate the threat it poses for human health by summarizing recent epidemiological, translational and clinical studies. We discuss the links between diet and disease in the context of obesity and type 2 diabetes, cardiovascular diseases, gut and liver diseases and solid malignancies. We collectively interpret the evidence and its limitations and discuss future challenges and strategies to overcome these. We argue that healthcare professionals and societies must react today to the detrimental effects of the Western diet to bring about sustainable change and improved outcomes in the future.

Systematic investigation of genetically determined plasma and urinary metabolites to discover potential interventional targets for colorectal cancer

BACKGROUND

We aimed to identify plasma and urinary metabolites related to colorectal cancer (CRC) risk and elucidate their mediator role in the associations between modifiable risk factors and CRC.

METHODS

Metabolite quantitative trait loci were derived from 2 published metabolomics genome-wide association studies, and summary-level data were extracted for 651 plasma metabolites and 208 urinary metabolites. Genetic associations with CRC were obtained from a large-scale genome-wide association study meta-analysis (100 204 cases, 154 587 controls) and the FinnGen cohort (4957 cases, 304 197 controls). Mendelian randomization and colocalization analyses were performed to evaluate the causal roles of metabolites in CRC. Druggability evaluation was employed to prioritize potential therapeutic targets. Multivariable Mendelian randomization and mediation estimation were conducted to elucidate the mediating effects of metabolites on the associations between modifiable risk factors and CRC.

RESULTS

The study identified 30 plasma metabolites and 4 urinary metabolites for CRC. Plasma sphingomyelin and urinary lactose, which were positively associated with CRC risk, could be modulated by drug interventions (ie, olipudase alfa, tilactase). Thirteen modifiable risk factors were associated with 9 metabolites, and 8 of these modifiable risk factors were associated with CRC risk. These 9 metabolites mediated the effect of modifiable risk factors (Actinobacteria, body mass index, waist to hip ratio, fasting insulin, smoking initiation) on CRC.

CONCLUSION

This study identified key metabolite biomarkers associated with CRC and elucidated their mediator roles in the associations between modifiable risk factors and CRC. These findings provide new insights into the etiology and potential therapeutic targets for CRC and the etiological pathways of modifiable environmental factors with CRC.

Global compositional and functional states of the human gut microbiome in health and disease

The human gut microbiota is of increasing interest, with metagenomics a key tool for analyzing bacterial diversity and functionality in health and disease. Despite increasing efforts to expand microbial gene catalogs and an increasing number of metagenome-assembled genomes, there have been few pan-metagenomic association studies and in-depth functional analyses across different geographies and diseases. Here, we explored 6014 human gut metagenome samples across 19 countries and 23 diseases by performing compositional, functional cluster, and integrative analyses. Using interpreted machine learning classification models and statistical methods, we identified Fusobacterium nucleatum and Anaerostipes hadrus with the highest frequencies, enriched and depleted, respectively, across different disease cohorts. Distinct functional distributions were observed in the gut microbiomes of both westernized and nonwesternized populations. These compositional and functional analyses are presented in the open-access Human Gut Microbiome Atlas, allowing for the exploration of the richness, disease, and regional signatures of the gut microbiota across different cohorts.

Involvement of the gut microbiome-brain axis in alcohol use disorder

The human intestine is colonized by a variety of microorganisms that influence the immune system, the metabolic response, and the nervous system, with consequences for brain function and behavior. Unbalance in this microbial ecosystem has been shown to be associated with psychiatric disorders, and altered gut microbiome composition related to bacteria, viruses, and fungi has been well established in patients with alcohol use disorder. This review describes the gut microbiome-brain communication pathways, including the ones related to the vagus nerve, the inflammatory cytokines, and the gut-derived metabolites. Finally, the potential benefits of microbiota-based therapies for the management of alcohol use disorder, such as probiotics, prebiotics, and fecal microbiota transplantation, are also discussed.