Metabolomics: a global biochemical approach to drug response and disease

Personalized Medicine Approach to Proteomics and Metabolomics of Cytochrome P450 Enzymes: A Narrative Review

Cytochrome P450 enzymes (CYPs) represent a diverse family of heme-thiolate proteins involved in the metabolism of a wide range of endogenous compounds and xenobiotics. In recent years, proteomics and metabolomics have been used to obtain a comprehensive insight into the role of CYPs in health and disease aspects. The objective of the present work is to better understand the status of proteomics and metabolomics in CYP research in optimizing therapeutics and patient safety from a personalized medicine approach. The literature used in this narrative review was procured by electronic search of PubMed, Medline, Embase, and Google Scholar databases. The following keywords were used in combination to identify related literature: "proteomics," "metabolomics," "cytochrome P450," "drug metabolism," "disease conditions," "proteome," "liquid chromatography-mass spectrometry," "integration," "metabolites," "pathological conditions." We reviewed studies that utilized proteomics and metabolomics approaches to explore the multifaceted roles of CYPs in identifying disease markers and determining the contribution of CYP enzymes in developing treatment strategies. The applications of various cutting-edge analytical techniques, including liquid chromatography-mass spectrometry, nuclear magnetic resonance, and bioinformatics analyses in CYP proteomics and metabolomics studies, have been highlighted. The identification of CYP enzymes through metabolomics and/or proteomics in various disease conditions provides key information in the diagnostic and therapeutic landscape. Leveraging both proteomics and metabolomics presents a powerful approach for an exhaustive exploration of the multifaceted roles played by CYP enzymes in personalized medicine. Proteomics and metabolomics have enabled researchers to unravel the complex connection between CYP enzymes and metabolic markers associated with specific diseases. As technology and methodologies evolve, an integrated approach promises to further elucidate the role of CYPs in human health and disease, potentially ushering in a new era of personalized medicine.

Melatonin alleviates brain injury in copper-laden rats: Underlying benefits for Wilson's disease

Copper serves as an indispensable cofactor for all living organisms, and its excessive accumulation has been associated with a variety of diseases. Wilson's disease (WD) serves as an illustrative example of copper toxicity in humans, frequently presenting with liver and/or neuropsychiatric symptoms. The current therapeutic drugs, penicillamine (PA) and zinc gluconate (ZnG), have constraints, and research on their combination efficacy remains insufficient. It has been reported that melatonin (MLT) plays a vital role in binding to transition metals and exhibits strong antioxidant capacity. To investigate the therapeutic efficacy of MLT and combined treatment, rats were randomly divided into the following seven groups: the control (Con) group, copper-laden model rat (Mod) group, PA-treated group, ZnG-treated group, MLT- treated group, PA-ZnG-treated group, and PA-MLT-treated group. Then potential mechanisms and targets were investigated using a combination of metabolomics and network pharmacology and verified by molecular docking and qPCR. The findings revealed that MLT and the combination significantly improved behavior, pathology and copper levels in copper-laden rats. The results of the metabolomics study showed that profoundly altered metabolites were identified, and alanine, aspartate and glutamate metabolism, pyruvate metabolism, citrate cycle (TCA cycle), and glycolysis/gluconeogenesis were explored. In addition, molecular docking showed that MLT had high binding affinity with key targets, and qPCR results revealed that MLT could reverse the mRNA expression of targets GOT2 and PKM2. It was concluded that MLT effectively improves brain injury in copper-laden rats, and this effect was linked with the altered features of the metabolite profiles.

Applications of chromatographic methods in metabolomics: A review

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

Pioglitazone-induced alterations of purine metabolism in healthy male subjects

Pioglitazone is class of thiazolidinediones that activates peroxisome proliferator-activated receptors (PPARs) in adipocytes to improve glucose metabolism and insulin sensitivity and has been used as a treatment for type 2 diabetes. However, the underlying mechanisms of associated pioglitazone-induced effects remain unclear. Our study aimed to investigate endogenous metabolite alterations associated with pioglitazone administration in healthy male subjects using an untargeted metabolomics approach. All subjects received 30 mg of pioglitazone once daily in the assigned sequence and period. Urine samples were collected before pioglitazone administration and for 24 h after 7 days of administration. A total of 1465 compounds were detected and filtered using a coefficient of variance below 30% and 108 metabolites were significantly altered upon pioglitazone administration via multivariate statistical analysis. Fourteen significant metabolites were identified using authentic standards and public libraries. Additionally, pathway analysis revealed that metabolites from purine and beta-alanine metabolisms were significantly altered after pioglitazone administration. Further analysis of quantification of metabolites from purine metabolism, revealed that the xanthine/hypoxanthine and uric acid/xanthine ratios were significantly decreased at post-dose. Pioglitazone-dependent endogenous metabolites and metabolic ratio indicated the potential effect of pioglitazone on the activation of PPAR and fatty acid synthesis. Additional studies involving patients are required to validate these findings.

Breaking barriers in trauma research: A narrative review of opportunities to leverage veterinary trauma for accelerated translation to clinical solutions for pets and people

Trauma is a common cause of morbidity and mortality in humans and companion animals. Recent efforts in procedural development, training, quality systems, data collection, and research have positively impacted patient outcomes; however, significant unmet need still exists. Coordinated efforts by collaborative, translational, multidisciplinary teams to advance trauma care and improve outcomes have the potential to benefit both human and veterinary patient populations. Strategic use of veterinary clinical trials informed by expertise along the research spectrum (i.e., benchtop discovery, applied science and engineering, large laboratory animal models, clinical veterinary studies, and human randomized trials) can lead to increased therapeutic options for animals while accelerating and enhancing translation by providing early data to reduce the cost and the risk of failed human clinical trials. Active topics of collaboration across the translational continuum include advancements in resuscitation (including austere environments), acute traumatic coagulopathy, trauma-induced coagulopathy, traumatic brain injury, systems biology, and trauma immunology. Mechanisms to improve funding and support innovative team science approaches to current problems in trauma care can accelerate needed, sustainable, and impactful progress in the field. This review article summarizes our current understanding of veterinary and human trauma, thereby identifying knowledge gaps and opportunities for collaborative, translational research to improve multispecies outcomes. This translational trauma group of MDs, PhDs, and DVMs posit that a common understanding of injury patterns and resulting cellular dysregulation in humans and companion animals has the potential to accelerate translation of research findings into clinical solutions.

VIBRANT: spectral profiling for single-cell drug responses

High-content cell profiling has proven invaluable for single-cell phenotyping in response to chemical perturbations. However, methods with improved throughput, information content and affordability are still needed. We present a new high-content spectral profiling method named vibrational painting (VIBRANT), integrating mid-infrared vibrational imaging, multiplexed vibrational probes and an optimized data analysis pipeline for measuring single-cell drug responses. Three infrared-active vibrational probes were designed to measure distinct essential metabolic activities in human cancer cells. More than 20,000 single-cell drug responses were collected, corresponding to 23 drug treatments. The resulting spectral profile is highly sensitive to phenotypic changes under drug perturbation. Using this property, we built a machine learning classifier to accurately predict drug mechanism of action at single-cell level with minimal batch effects. We further designed an algorithm to discover drug candidates with new mechanisms of action and evaluate drug combinations. Overall, VIBRANT has demonstrated great potential across multiple areas of phenotypic screening.

Metabolic Signatures: Pioneering the Frontier of Rectal Cancer Diagnosis and Response to Neoadjuvant Treatment with Biomarkers-A Systematic Review

Colorectal cancer (CRC) is one of the most aggressive, heterogenous, and fatal types of human cancer for which screening, and more effective therapeutic drugs are urgently needed. Early-stage detection and treatment greatly improve the 5-year survival rate. In the era of targeted therapies for all types of cancer, a complete metabolomic profile is mandatory before neoadjuvant therapy to assign the correct drugs and check the response to the treatment given. The aim of this study is to discover specific metabolic biomarkers or a sequence of metabolomic indicators that possess precise diagnostic capabilities in predicting the efficacy of neoadjuvant therapy. After searching the keywords, a total of 108 articles were identified during a timeframe of 10 years (2013-2023). Within this set, one article was excluded due to the use of non-English language. Six scientific papers were qualified for this investigation after eliminating all duplicates, publications not referring to the subject matter, open access restriction papers, and those not applicable to humans. Biomolecular analysis found a correlation between metabolomic analysis of colorectal cancer samples and poor progression-free survival rates. Biomarkers are instrumental in predicting a patient's response to specific treatments, guiding the selection of targeted therapies, and indicating resistance to certain drugs.

Multi-omics and gut microbiome: Unveiling the pathogenic mechanisms of early-life pesticide exposure

The extensive application of pesticides in agricultural production has raised significant concerns about its impact on human health. Different pesticides, including fungicides, insecticides, and herbicides, cause environmental pollution and health problems for non-target organisms. Infants and young children are so vulnerable to the harmful effects of pesticide exposure that early-life exposure to pesticides deserves focused attention. Recent research lays emphasis on understanding the mechanism between negative health impacts and early-life exposure to various pesticides. Studies have explored the impacts of exposure to these pesticides on model organisms (zebrafish, rats, and mice), as well as the mechanism of negative health effects, based on advanced methodologies like gut microbiota and multi-omics. These methodologies help comprehend the pathogenic mechanisms associated with early-life pesticide exposure. In addition to presenting health problems stemming from early-life exposure to pesticides and their pathogenic mechanisms, this review proposes expectations for future research. These proposals include focusing on identifying biomarkers that indicate early-life pesticide exposure, investigating transgenerational effects, and seeking effective treatments for diseases arising from such exposure. This review emphasizes how to understand the pathogenic mechanisms of early-life pesticide exposure through gut microbiota and multi-omics, as well as the adverse health effects of such exposure.

Developing a model to predict the early risk of hypertriglyceridemia based on inhibiting lipoprotein lipase (LPL): a translational study

Hypertriglyceridemia (HTG) is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). One of the multiple origins of HTG alteration is impaired lipoprotein lipase (LPL) activity, which is an emerging target for HTG treatment. We hypothesised that early, even mild, alterations in LPL activity might result in an identifiable metabolomic signature. The aim of the present study was to assess whether a metabolic signature of altered LPL activity in a preclinical model can be identified in humans. A preclinical LPL-dependent model of HTG was developed using a single intraperitoneal injection of poloxamer 407 (P407) in male Wistar rats. A rat metabolomics signature was identified, which led to a predictive model developed using machine learning techniques. The predictive model was applied to 140 humans classified according to clinical guidelines as (1) normal, less than 1.7 mmol/L; (2) risk of HTG, above 1.7 mmol/L. Injection of P407 in rats induced HTG by effectively inhibiting plasma LPL activity. Significantly responsive metabolites (i.e. specific triacylglycerols, diacylglycerols, phosphatidylcholines, cholesterol esters and lysophospholipids) were used to generate a predictive model. Healthy human volunteers with the impaired predictive LPL signature had statistically higher levels of TG, TC, LDL and APOB than those without the impaired LPL signature. The application of predictive metabolomic models based on mechanistic preclinical research may be considered as a strategy to stratify subjects with HTG of different origins. This approach may be of interest for precision medicine and nutritional approaches.

Metabolomics reveals the effects of hydroxysafflor yellow A on neurogenesis and axon regeneration after experimental traumatic brain injury

CONTEXT

Hydroxysafflor yellow A (HSYA) is the main bioactive ingredient of safflower (Carthamus tinctorius L., [Asteraceae]) for traumatic brain injury (TBI) treatment.

OBJECTIVE

To explore the therapeutic effects and underlying mechanisms of HSYA on post-TBI neurogenesis and axon regeneration.

MATERIALS AND METHODS

Male Sprague-Dawley rats were randomly assigned into Sham, controlled cortex impact (CCI), and HSYA groups. Firstly, the modified Neurologic Severity Score (mNSS), foot fault test, hematoxylin-eosin staining, Nissl's staining, and immunofluorescence of Tau1 and doublecortin (DCX) were used to evaluate the effects of HSYA on TBI at the 14th day. Next, the effectors of HSYA on post-TBI neurogenesis and axon regeneration were screened out by pathology-specialized network pharmacology and untargeted metabolomics. Then, the core effectors were validated by immunofluorescence.

RESULTS

HSYA alleviated mNSS, foot fault rate, inflammatory cell infiltration, and Nissl's body loss. Moreover, HSYA increased not only hippocampal DCX but also cortical Tau1 and DCX following TBI. Metabolomics demonstrated that HSYA significantly regulated hippocampal and cortical metabolites enriched in 'arginine metabolism' and 'phenylalanine, tyrosine and tryptophan metabolism' including l-phenylalanine, ornithine, l-(+)-citrulline and argininosuccinic acid. Network pharmacology suggested that neurotrophic factor (BDNF) and signal transducer and activator of transcription 3 (STAT3) were the core nodes in the HSYA-TBI-neurogenesis and axon regeneration network. In addition, BDNF and growth-associated protein 43 (GAP43) were significantly elevated following HSYA treatment in the cortex and hippocampus.

DISCUSSION AND CONCLUSIONS

HSYA may promote TBI recovery by facilitating neurogenesis and axon regeneration through regulating cortical and hippocampal metabolism, BDNF and STAT3/GAP43 axis.

Targeted quantitative metabolic profiling of brain-derived cell cultures by semi-automated MEPS and LC-MS/MS

The accurate characterisation of metabolic profiles is an important prerequisite to determine the rate and the efficiency of the metabolic pathways taking place in the cells. Changes in the balance of metabolites involved in vital processes such as glycolysis, tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS), as well as in the biochemical pathways related to amino acids, lipids, nucleotides, and their precursors reflect the physiological condition of the cells and may contribute to the development of various human diseases. The feasible and reliable measurement of a wide array of metabolites and biomarkers possesses great potential to elucidate physiological and pathological mechanisms, aid preclinical drug development and highlight potential therapeutic targets. An effective, straightforward, sensitive, and selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach was developed for the simultaneous quali-quantitative analysis of 41 compounds in both cell pellet and cell growth medium obtained from brain-derived cell cultures. Sample pretreatment miniaturisation was achieved thanks to the development and optimisation of an original extraction/purification approach based on digitally programmed microextraction by packed sorbent (eVol®-MEPS). MEPS allows satisfactory and reproducible clean-up and preconcentration of both low-volume homogenate cell pellet lysate and cell growth medium with advantages including, but not limited to, minimal sample handling and method sustainability in terms of sample, solvents, and energy consumption. The MEPS-LC-MS/MS method showed good sensitivity, selectivity, linearity, and precision. As a proof of concept, the developed method was successfully applied to the analysis of both cell pellet and cell growth medium obtained from a line of mouse immortalised oligodendrocyte precursor cells (OPCs; Oli-neu cell line), leading to the unambiguous determination of all the considered target analytes. This method is thus expected to be suitable for targeted, quantitative metabolic profiling in most brain cell models, thus allowing accurate investigations on the biochemical pathways that can be altered in central nervous system (CNS) neuropathologies, including e.g., mitochondrial respiration and glycolysis, or use of specific nutrients for growth and proliferation, or lipid, amino acid and nucleotide metabolism.

NMR-Based Mitochondria Metabolomic Profiling: A New Approach To Reveal Cancer-Associated Alterations

Studying metabolism may assist in understanding the relationship between normal and dysfunctional mitochondrial activity and various diseases, such as neurodegenerative, cardiovascular, autoimmune, psychiatric, and cancer. Nuclear magnetic resonance-based metabolomics represents a powerful method to characterize the chemical content of complex samples and has been successfully applied to studying a range of conditions. However, an optimized methodology is lacking for analyzing isolated organelles, such as mitochondria. In this study, we report the development of a protocol to metabolically profile mitochondria from healthy, tumoral, and metastatic tissues. Encouragingly, this approach provided quantitative information about up to 45 metabolites in one comprehensive and robust analysis. Our results revealed significant differences between whole-cell and mitochondrial metabolites, which supports a more refined approach to metabolic analysis. We applied our optimized methodology to investigate aggressive and metastatic breast cancer in mouse tissues, discovering that lung mitochondria exhibit an altered metabolic fingerprint. Specific amino acids, organic acids, and lipids showed significant increases in levels when compared with mitochondria from healthy tissues. Our optimized methodology could promote a better understanding of the molecular mechanisms underlying breast cancer aggressiveness and mitochondrial-related diseases and support the optimization of new advanced therapies.

Serum metabolomics of treatment response in myasthenia gravis

OBJECTIVE

High-dose prednisone use, lasting several months or longer, is the primary initial therapy for myasthenia gravis (MG). Upwards of a third of patients do not respond to treatment. Currently no biomarkers can predict clinical responsiveness to corticosteroid treatment. We conducted a discovery-based study to identify treatment responsive biomarkers in MG using sera obtained at study entry to the thymectomy clinical trial (MGTX), an NIH-sponsored randomized, controlled study of thymectomy plus prednisone versus prednisone alone.

METHODS

We applied ultra-performance liquid chromatography coupled with electro-spray quadrupole time of flight mass spectrometry to obtain comparative serum metabolomic and lipidomic profiles at study entry to correlate with treatment response at 6 months. Treatment response was assessed using validated outcome measures of minimal manifestation status (MMS), MG-Activities of Daily Living (MG-ADL), Quantitative MG (QMG) score, or a strictly defined composite measure of response.

RESULTS

Increased serum levels of phospholipids were associated with treatment response as assessed by QMG, MMS, and the Responders classification, but all measures showed limited overlap in metabolomic profiles, in particular the MG-ADL. A panel including histidine, free fatty acid (13:0), γ-cholestenol and guanosine was highly predictive of the strictly defined treatment response measure. The AUC in Responders' prediction for these markers was 0.90 irrespective of gender, age, thymectomy or baseline prednisone use. Pathway analysis suggests that xenobiotic metabolism could play a major role in treatment resistance. There was no association with outcome and gender, age, thymectomy or baseline prednisone use.

INTERPRETATION

We have defined a metabolomic and lipidomic profile that can now undergo validation as a treatment predictive marker for MG patients undergoing corticosteroid therapy. Metabolomic profiles of outcome measures had limited overlap consistent with their assessing distinct aspects of treatment response and supporting unique biological underpinning for each outcome measure. Interindividual variation in prednisone metabolism may be a determinate of how well patients respond to treatment.

Drug-microbiota interactions: an emerging priority for precision medicine

Individual variability in drug response (IVDR) can be a major cause of adverse drug reactions (ADRs) and prolonged therapy, resulting in a substantial health and economic burden. Despite extensive research in pharmacogenomics regarding the impact of individual genetic background on pharmacokinetics (PK) and pharmacodynamics (PD), genetic diversity explains only a limited proportion of IVDR. The role of gut microbiota, also known as the second genome, and its metabolites in modulating therapeutic outcomes in human diseases have been highlighted by recent studies. Consequently, the burgeoning field of pharmacomicrobiomics aims to explore the correlation between microbiota variation and IVDR or ADRs. This review presents an up-to-date overview of the intricate interactions between gut microbiota and classical therapeutic agents for human systemic diseases, including cancer, cardiovascular diseases (CVDs), endocrine diseases, and others. We summarise how microbiota, directly and indirectly, modify the absorption, distribution, metabolism, and excretion (ADME) of drugs. Conversely, drugs can also modulate the composition and function of gut microbiota, leading to changes in microbial metabolism and immune response. We also discuss the practical challenges, strategies, and opportunities in this field, emphasizing the critical need to develop an innovative approach to multi-omics, integrate various data types, including human and microbiota genomic data, as well as translate lab data into clinical practice. To sum up, pharmacomicrobiomics represents a promising avenue to address IVDR and improve patient outcomes, and further research in this field is imperative to unlock its full potential for precision medicine.

Metabolomics study of the hepatoprotective effect of total flavonoids of Mallotus apelta leaf in carbon tetrachloride-induced liver fibrosis in rats

Mallotus apelta leaf, recorded in the quality standard of Yao Medicinal Material in Guangxi Zhuang autonomous region, is commonly used in the treatment of liver diseases. Total flavonoids of M. apelta leaf (TFM) had good anti-fibrosis activity, but the anti-fibrosis mechanism of TFM is still unclear. Nuclear magnetic resonance technology was used to study the dynamic changes of urine metabolites in CCl4 -induced liver fibrosis before and after TFM treatment. Ingenuity Path Analysis (IPA) was used to find potential target genes for TFM to improve liver fibrosis and verify the expression of target genes by real-time fluorescent quantitative PCR and Western blotting. TFM can significantly reduce serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) levels, improve liver steatosis and reduce inflammation; in urine metabolomics, a total of seven potential biomarkers were found, mainly involving two metabolic pathways; IPA analysis showed that TNF may be a potential target for TFM to improve liver fibrosis induced by CCl4 in rats. This study found that TNF may be a potential target gene for TFM treatment of liver fibrosis, and shows that the anti-fibrosis mechanism of TFM could improve liver fibrosis by regulating the tricarboxylic acid cycle and subtaurine metabolism.

Plasma lipidomic analysis to investigate putative biomarkers of P-glycoprotein activity in healthy volunteers

P-glycoprotein (P-gp) is an efflux transporter involved in the bioavailability of many drugs currently on the market. P-gp is responsible for several drug-drug interactions encountered in clinical practice leading to iatrogenic hospital admissions, especially in polypharmacy situations. ABCB1 genotyping only reflects an indirect estimate of P-gp activity. Therefore, it would be useful to identify endogenous biomarkers to determine the P-gp phenotype to predict in vivo activity prior to the initiation of treatment and to assess the effects of drugs on P-gp activity. The objective of this study was to assess changes in plasma lipidome composition among healthy volunteers selected on the basis of their ABCB1 genotype and who received clarithromycin, a known inhibitor of P-gp. Untargeted lipidomic analysis based on liquid chromatography-tandem mass spectrometry was performed before and after clarithromycin administration. Our results revealed changes in plasma levels of some ceramides (Cers) {Cer(d18:1/22:0), Cer(d18:1/22:1), and Cer(d18:1/20:0) by ~38% (p < 0.0001), 13% (p < 0.0001), and 13% (p < 0.0001), respectively} and phosphatidylcholines (PCs) {PC(17:0/14:1), PC(16:0/18:3), and PC(14:0/18:3) by ~24% (p < 0.001), 10% (p < 0.001), and 23.6% (p < 0.001)} associated with both ABCB1 genotype and clarithromycin intake. Through the examination of plasma lipids, our results highlight the relevance of untargeted lipidomics for studying in vivo P-gp activity and, more generally, to safely phenotyping transporters.

Deciphering the metabolic profile and anti-colorectal cancer mechanism of Capilliposide A using ultra performance liquid chromatography mass spectrometry combined with non-targeted metabolomics studies

Colorectal cancer is a highly prevalent malignancy that threatens human health worldwide. Despite the availability of chemotherapy as a primary treatment option, individuals with CRC undergoing frequent chemotherapy are susceptible to developing drug resistance, which can result in poor treatment outcomes. Consequently, there is an urgent need to discover new bioactive compounds for the treatment of CRC. Capilliposide A is a triterpenoid saponin that is extracted from Lysimachia capillipes Hemsl. Although it has been reported that LC-A exhibits good bioactivity, its metabolic profile and potential mechanism underlying its anti-CRC effects remain unknown. In this study, the metabolic products of LC-A in rat plasma, feces, and urine were identified using an LC-MS platform. In addition, LC-MS-based metabolomics was employed to investigate the mechanism of LC-A against CRC. The results showed that LC-A significantly inhibited CRC cell proliferation, attenuated tumor growth, and alleviated metabolic abnormalities in CRC-bearing mice. Furthermore, the levels of p-cresol sulfate and phenylacetylglycine in CRC model plasma decreased, with an increment in sphingosine 1-phosphate, D-tryptophan, and L-2-aminoadipic acid. These metabolite levels can be reversed by LC-A treatment. These metabolite alterations were related to the sphingolipid and amino acid metabolic pathways, demonstrating that LC-A anti-CRC effects were regulated through the modulation of underlying metabolism. Additionally, seven metabolites of LC-A were characterized in rat feces, plasma, and urine. This study offers a scientific foundation for elucidating the metabolism of LC-A and its treatment of colorectal cancer.

Absorption and Metabolism of Urolithin A and Ellagic Acid in Mice and Their Cytotoxicity in Human Colorectal Cancer Cells

Background

Ellagic acid is a natural polyphenol compound found in pomegranates, walnuts, and many berries. It is not easily absorbed, but it could be metabolized to urolithins by the gut microbiota. Urolithin A, one of the ellagic acid metabolites, has been proved to prolong the lifespan of C. elegans and increases muscle function of mice. The purpose of this current study was to analyze the absorption and metabolites of urolithin A and ellagic acid in mice and the anticancer effects of urolithin A, urolithin B, and ellagic acid in colorectal cancer cells.

Methods

Urolithin A and urolithin B were synthesized and analyzed by HPLC and NMR. A pharmacokinetic study of urolithin A was performed in mice by analyzing urolithin A and its metabolites in urines. Absorption and biotransformation of ellagic acid were also studied in mice by analyzing the plasma, liver, and feces. The cytotoxicity of urolithin A, urolithin B, and ellagic acid was assayed in SW480, SW620, HCT 116, and HT-29 cells.

Results

Urolithin A and urolithin B were synthesized and purified to reach 98.1% and 99% purity, respectively, and the structures were identified by NMR. In urolithin A intake analysis, urolithin A was only detectable at 3 h, not at 6-24 h; it suggested that urolithin A was rapidly metabolized to some unknown metabolites. Using UPLC-MS/MS analysis, the metabolites might be urolithin A 3-O-glucuronide, urolithin A 3-sulfate, and urolithin A-sulfate glucuronide. After feeding mice with ellagic acid for consecutive 14 days, ellagic acid contents could be detected in the fecal samples, but not in plasma and liver, and urolithin A was not detected in all samples. It suggests that ellagic acid is not easily absorbed and that the biotransformation of ellagic acid to urolithin A by intestinal flora might be very low. From the cytotoxicity assay, it was found that there was anticancer effect in urolithin A and urolithin B but not in ellagic acid. In contrast, ellagic acid promoted the proliferation of SW480 and SW620 cells.

Metabolomics: A useful tool for ischemic stroke research

Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.

The acute effect of different NAD+ precursors included in the combined metabolic activators

NAD+ and glutathione precursors are currently used as metabolic modulators for improving the metabolic conditions associated with various human diseases, including non-alcoholic fatty liver disease, neurodegenerative diseases, mitochondrial myopathy, and age-induced diabetes. Here, we performed a one-day double blinded, placebo-controlled human clinical study to assess the safety and acute effects of six different Combined Metabolic Activators (CMAs) with 1 g of different NAD+ precursors based on global metabolomics analysis. Our integrative analysis showed that the NAD+ salvage pathway is the main source for boosting the NAD+ levels with the administration of CMAs without NAD+ precursors. We observed that incorporation of nicotinamide (Nam) in the CMAs can boost the NAD+ products, followed by niacin (NA), nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN), but not flush free niacin (FFN). In addition, the NA administration led to a flushing reaction, accompanied by decreased phospholipids and increased bilirubin and bilirubin derivatives, which could be potentially risky. In conclusion, this study provided a plasma metabolomic landscape of different CMA formulations, and proposed that CMAs with Nam, NMN as well as NR can be administered for boosting NAD+ levels to improve altered metabolic conditions.

Metabolic fingerprint of patients showing responsiveness to treatment of septic shock in intensive care unit

OBJECTIVE

An early metabolic signature associated with the responsiveness to treatment can be useful in the better management of septic shock patients. This would help clinicians in designing personalized treatment protocols for patients showing non-responsiveness to treatment.

METHODS

We analyzed the serum on Day 1 (n = 60), Day 3 (n = 47), and Day 5 (n = 26) of patients with septic shock under treatment using NMR-based metabolomics. Partial least square discriminant analysis (PLS-DA) was performed to generate the list of metabolites that can be identified as potential disease biomarkers having statistical significance (that is, metabolites that had a VIP score > 1, and p value < 0.05, False discovery rate (FDR) < 0.05).

RESULTS

Common significant metabolites amongst the three time points were obtained that distinguished the patients being responsive (R) and non-responsive (NR) to treatments, namely 3 hydroxybutyrate, lactate, and phenylalanine which were lower, whereas glutamate and choline higher in patients showing responsiveness.

DISCUSSION

The study gave these metabolic signatures identifying patients' responsiveness to treatment. The results of the study will aid in the development of targeted therapy for ICU patients.

Metabolomics of infectious diseases in the era of personalized medicine

Infectious diseases continue to be a major cause of morbidity and mortality worldwide. Diseases cause perturbation of the host's immune system provoking a response that involves genes, proteins and metabolites. While genes are regulated by epigenetic or other host factors, proteins can undergo post-translational modification to enable/modify function. As a result, it is difficult to correlate the disease phenotype based solely on genetic and proteomic information only. Metabolites, however, can provide direct information on the biochemical activity during diseased state. Therefore, metabolites may, potentially, represent a phenotypic signature of a diseased state. Measuring and assessing metabolites in large scale falls under the omics technology known as "metabolomics". Comprehensive and/or specific metabolic profiling in biological fluids can be used as biomarkers of disease diagnosis. In addition, metabolomics together with genomics can be used to differentiate patients with differential treatment response and development of host targeted therapy instead of pathogen targeted therapy where pathogens are more prone to mutation and lead to antimicrobial resistance. Thus, metabolomics can be used for patient stratification, personalized drug formulation and disease control and management. Currently, several therapeutics and in vitro diagnostics kits have been approved by US Food and Drug Administration (FDA) for personalized treatment and diagnosis of infectious diseases. However, the actual number of therapeutics or diagnostics kits required for tailored treatment is limited as metabolomics and personalized medicine require the involvement of personnel from multidisciplinary fields ranging from technological development, bioscience, bioinformatics, biostatistics, clinicians, and biotechnology companies. Given the significance of metabolomics, in this review, we discussed different aspects of metabolomics particularly potentials of metabolomics as diagnostic biomarkers and use of small molecules for host targeted treatment for infectious diseases, and their scopes and challenges in personalized medicine.

Multi-omics in Crohn's disease: New insights from inside

Crohn's disease (CD) is an inflammatory bowel disease (IBD) with complex clinical manifestations such as chronic diarrhea, weight loss and hematochezia. Despite the increasing incidence worldwide, cure of CD remains extremely difficult. The rapid development of high-throughput sequencing technology with integrated-omics analyses in recent years has provided a new means for exploring the pathogenesis, mining the biomarkers and designing targeted personalized therapeutics of CD. Host genomics and epigenomics unveil heredity-related mechanisms of susceptible individuals, while microbiome and metabolomics map host-microbe interactions in CD patients. Proteomics shows great potential in searching for promising biomarkers. Nonetheless, single omics technology cannot holistically connect the mechanisms with heterogeneity of pathological behavior in CD. The rise of multi-omics analysis integrates genetic/epigenetic profiles with protein/microbial metabolite functionality, providing new hope for comprehensive and in-depth exploration of CD. Herein, we emphasized the different omics features and applications of CD and discussed the current research and limitations of multi-omics in CD. This review will update and deepen our understanding of CD from integration of broad omics spectra and will provide new evidence for targeted individualized therapeutics.

Metabolomic Profiling of Bipolar Disorder by 1H-NMR in Serbian Patients

Bipolar disorder (BD) is a brain disorder that causes changes in a person's mood, energy, and ability to function. It has a prevalence of 60 million people worldwide, and it is among the top 20 diseases with the highest global burden. The complexity of this disease, including diverse genetic, environmental, and biochemical factors, and diagnoses based on the subjective recognition of symptoms without any clinical test of biomarker identification create significant difficulties in understanding and diagnosing BD. A ¹H-NMR-based metabolomic study applying chemometrics of serum samples of Serbian patients with BD (33) and healthy controls (39) was explored, providing the identification of 22 metabolites for this disease. A biomarker set including threonine, aspartate, gamma-aminobutyric acid, 2-hydroxybutyric acid, serine, and mannose was established for the first time in BD serum samples by an NMR-based metabolomics study. Six identified metabolites (3-hydroxybutyric acid, arginine, lysine, tyrosine, phenylalanine, and glycerol) are in agreement with the previously determined NMR-based sets of serum biomarkers in Brazilian and/or Chinese patient samples. The same established metabolites (lactate, alanine, valine, leucine, isoleucine, glutamine, glutamate, glucose, and choline) in three different ethnic and geographic origins (Serbia, Brazil, and China) might have a crucial role in the realization of a universal set of NMR biomarkers for BD.

Closing the gap between in vivo and in vitro omics: using QA/QC to strengthen ex vivo NMR metabolomics

Metabolomics aims to achieve a global quantitation of the pool of metabolites within a biological system. Importantly, metabolite concentrations serve as a sensitive marker of both genomic and phenotypic changes in response to both internal and external stimuli. NMR spectroscopy greatly aids in the understanding of both in vitro and in vivo physiological systems and in the identification of diagnostic and therapeutic biomarkers. Accordingly, NMR is widely utilized in metabolomics and fluxomics studies due to its limited requirements for sample preparation and chromatography, its non-destructive and quantitative nature, its utility in the structural elucidation of unknown compounds, and, importantly, its versatility in the analysis of in vitro, in vivo, and ex vivo samples. This review provides an overview of the strengths and limitations of in vitro and in vivo experiments for translational research and discusses how ex vivo studies may overcome these weaknesses to facilitate the extrapolation of in vitro insights to an in vivo system. The application of NMR-based metabolomics to ex vivo samples, tissues, and biofluids can provide essential information that is close to a living system (in vivo) with sensitivity and resolution comparable to those of in vitro studies. The success of this extrapolation process is critically dependent on high-quality and reproducible data. Thus, the incorporation of robust quality assurance and quality control checks into the experimental design and execution of NMR-based metabolomics experiments will ensure the successful extrapolation of ex vivo studies to benefit translational medicine.

Combined Metabolome and Transcriptome Analysis Elucidates Sugar Accumulation in Wucai (Brassica campestris L.)

Wucai (Brassica campestris L.) is a leafy vegetable that originated in China, its soluble sugars accumulate significantly to improve taste quality during maturation, and it is widely accepted by consumers. In this study, we investigated the soluble sugar content at different developmental stages. Two periods including 34 days after planting (DAP) and 46 DAP, which represent the period prior to and after sugar accumulation, respectively, were selected for metabolomic and transcriptomic profiling. Differentially accumulated metabolites (DAMs) were mainly enriched in the pentose phosphate pathway, galactose metabolism, glycolysis/gluconeogenesis, starch and sucrose metabolism, and fructose and mannose metabolism. By orthogonal projection to latent structures-discriminant s-plot (OPLS-DA S-plot) and MetaboAnalyst analyses, D-galactose and β-D-glucose were identified as the major components of sugar accumulation in wucai. Combined with the transcriptome, the pathway of sugar accumulation and the interact network between 26 DEGs and the two sugars were mapped. CWINV4, CEL1, BGLU16, and BraA03g023380.3C had positive correlations with the accumulation of sugar accumulation in wucai. The lower expression of BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, and BraA05g027230.3C promoted sugar accumulation during the ripening of wucai. These findings provide insights into the mechanisms underlying sugar accumulation during commodity maturity, providing a basis for the breeding of sugar-rich wucai cultivars.

Metabolomics in pediatric lower respiratory tract infections and sepsis: a literature review

Lower respiratory tract infections (LRTIs) are a leading cause of morbidity and mortality in children. The ability of healthcare providers to diagnose and prognose LRTIs in the pediatric population remains a challenge, as children can present with similar clinical features regardless of the underlying pathogen or ultimate severity. Metabolomics, the large-scale analysis of metabolites and metabolic pathways offers new tools and insights that may aid in diagnosing and predicting the outcomes of LRTIs in children. This review highlights the latest literature on the clinical utility of metabolomics in providing care for children with bronchiolitis, pneumonia, COVID-19, and sepsis. IMPACT: This article summarizes current metabolomics approaches to diagnosing and predicting the course of pediatric lower respiratory infections. This article highlights the limitations to current metabolomics research and highlights future directions for the field.

Integration of LC-MS-Based and GC-MS-Based Metabolic Profiling to Reveal the Effects of Domestication and Boiling on the Composition of Duck Egg Yolks

Egg yolks contain abundant lipids, proteins, and minerals that provide not only essential nutrients for embryonic development but also cheap sources of nutrients for consumers worldwide. Previous composition analyses of egg yolks primarily focused on nutrients such as lipids and minerals. However, few studies have reported the effects of domestication and heating on yolk composition and characteristics. The objective of this study was to investigate the impact of domestication and boiling on the metabolite contents of egg yolks via untargeted metabolomics using GC-MS and LC-MS. In this study, eggs were collected from Fenghua teals, captive mallards, and Shaoxing ducks. Twelve duck eggs (half raw and half cooked) were randomly selected from each variety, and the egg yolks were separated for metabolic profiling. The analysis identified 1205 compounds in the egg yolks. Domestication generated more differential metabolites than boiling, which indicated that the changes in the metabolome of duck egg yolk caused by domestication were greater than those caused by boiling. In a comparative analysis of domestic and mallard ducks, 48 overlapping differential metabolites were discovered. Among them, nine metabolites were upregulated in domesticated ducks, including monoolein, emodin, daidzein, genistein, and glycitein, which may be involved in lipid metabolism; some of them may also act as phytoestrogens (flavonoids). Another 39 metabolites, including imethylethanolamine, harmalan, mannitol, nornicotine, linoleic acid, diphenylamine, proline betaine, alloxanthin, and resolvin d1, were downregulated by domestication and were linked to immunity, anti-inflammatory, antibacterial, and antioxidant properties. Furthermore, four overlapping differential metabolites that included amino acids and dipeptides were discovered in paired comparisons of the raw and boiled samples. Our findings provided new insights into the molecular response of duck domestication and supported the use of metabolomics to examine the impact of boiling on the composition of egg yolks.

When cancer drug resistance meets metabolomics (bulk, single-cell and/or spatial): Progress, potential, and perspective

Resistance to drug treatment is a critical barrier in cancer therapy. There is an unmet need to explore cancer hallmarks that can be targeted to overcome this resistance for therapeutic gain. Over time, metabolic reprogramming has been recognised as one hallmark that can be used to prevent therapeutic resistance. With the advent of metabolomics, targeting metabolic alterations in cancer cells and host patients represents an emerging therapeutic strategy for overcoming cancer drug resistance. Driven by technological and methodological advances in mass spectrometry imaging, spatial metabolomics involves the profiling of all the metabolites (metabolomics) so that the spatial information is captured bona fide within the sample. Spatial metabolomics offers an opportunity to demonstrate the drug-resistant tumor profile with metabolic heterogeneity, and also poses a data-mining challenge to reveal meaningful insights from high-dimensional spatial information. In this review, we discuss the latest progress, with the focus on currently available bulk, single-cell and spatial metabolomics technologies and their successful applications in pre-clinical and translational studies on cancer drug resistance. We provide a summary of metabolic mechanisms underlying cancer drug resistance from different aspects; these include the Warburg effect, altered amino acid/lipid/drug metabolism, generation of drug-resistant cancer stem cells, and immunosuppressive metabolism. Furthermore, we propose solutions describing how to overcome cancer drug resistance; these include early detection during cancer initiation, monitoring of clinical drug response, novel anticancer drug and target metabolism, immunotherapy, and the emergence of spatial metabolomics. We conclude by describing the perspectives on how spatial omics approaches (integrating spatial metabolomics) could be further developed to improve the management of drug resistance in cancer patients.

Importance of lactate dehydrogenase (LDH) and monocarboxylate transporters (MCTs) in cancer cells

Background

In most regions, cancer ranks the second most frequent cause of death following cardiovascular disorders.

Aim

In this article, we review the various aspects of glycolysis with a focus on types of MCTs and the importance of lactate in cancer cells.

Results and Discussion

Metabolic changes are one of the first and most important alterations in cancer cells. Cancer cells use different pathways to survive, energy generation, growth, and proliferation compared to normal cells. The increase in glycolysis, which produces substances such as lactate and pyruvate, has an important role in metastases and invasion of cancer cells. Two important cellular proteins that play a role in the production and transport of lactate include lactate dehydrogenase and monocarboxylate transporters (MCTs). These molecules by their various isoforms and different tissue distribution help to escape the immune system and expansion of cancer cells under different conditions.

Integrated dose–response metabolomics with therapeutic effects and adverse reactions may demystify the dosage of traditional Chinese medicine

Background

Traditional Chinese medicine (TCM) has been used to treat various diseases for thousands of years. However, the uncertainty of dosage as well as the lack of systemic evaluation of pharmacology and toxicology is one major reason why TCM remains mysterious and is not accepted worldwide. Hence, we aimed to propose an integrated dose–response metabolomics strategy based on both therapeutic effects and adverse reactions to guide the TCM dosage in treatment.

Methods

The proposed methodology of integrated dose–response metabolomics includes four steps: dose design, multiple comparison of metabolic features, response calculation and dose–response curve fitting. By comparing the changes of all metabolites under different doses and calculating these changes through superposition, it is possible to characterize the global disturbance and thus describe the overall effect and toxicity of TCM induced by different doses. Rhubarb, commonly used for constipation treatment, was selected as a representative TCM.

Results

This developed strategy was successfully applied to rhubarb. The dose–response curves clearly showed the efficacy and adverse reactions of rhubarb at different doses. The rhubarb dose of 0.69 g/kg (corresponding to 7.66 g in clinic) was selected as the optimal dose because it was 90% of the effective dose and three adverse reactions were acceptable in this case.

Conclusion

An integrated dose–response metabolomics strategy reflecting both therapeutic effects and adverse reactions was established for the first time, which we believe is helpful to uncover the mysterious veil of TCM dosage. In addition, this strategy benefits the modernization and internationalization of TCM, and broadens the application of metabolomics.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-022-00687-4.

Pharmacometabolomics-Based Translational Biomarkers: How to Navigate the Data Ocean

Metabolome is the end point of the genome-environment interplay, and enables an important holistic overview of individual adaptability and host responses to environmental, ecological, as well as endogenous changes such as disease. Pharmacometabolomics is the application of metabolome knowledge to decipher the mechanisms of interindividual and intraindividual variations in drug efficacy and safety. Pharmacometabolomics also contributes to prediction of drug treatment outcomes on the basis of baseline (predose) and postdose metabotypes through mathematical modeling. Thus, pharmacometabolomics is a strong asset for a diverse community of stakeholders interested in theory and practice of evidence-based and precision/personalized medicine: academic researchers, public health scholars, health professionals, pharmaceutical, diagnostics, and biotechnology industries, among others. In this expert review, we discuss pharmacometabolomics in four contexts: (1) an interdisciplinary omics tool and field to map the mechanisms and scale of interindividual variability in drug effects, (2) discovery and development of translational biomarkers, (3) advance digital biomarkers, and (4) empower drug repurposing, a field that is increasingly proving useful in the current era of Covid-19. As the applications of pharmacometabolomics are growing rapidly in the current postgenome era, next-generation proteomics and metabolomics follow the example of next-generation sequencing analyses. Pharmacometabolomics can also empower data reliability and reproducibility through multiomics integration strategies, which use each data layer to correct, connect with, and inform each other. Finally, we underscore here that contextual data remain crucial for precision medicine and drug development that stand the test of time and clinical relevance.

Insights into the development of pentylenetetrazole-induced epileptic seizures from dynamic metabolomic changes

Epilepsy is often considered to be a progressive neurological disease, and the nature of this progression remains unclear. Understanding the overall and common metabolic changes of epileptic seizures can provide novel clues for their control and prevention. Herein, a chronic kindling animal model was established to obtain generalized tonic-clonic seizures via the repeated injections of pentylenetetrazole (PTZ) at subconvulsive dose. Dynamic metabolomic changes in plasma and urine from PTZ-kindled rats at the different kindling phases were explored using NMR-based metabolomics, in combination with behavioral assessment, brain neurotransmitter measurement, electroencephalography and histopathology. The increased levels of glucose, lactate, glutamate, creatine and creatinine, together with the decreased levels of pyruvate, citrate and succinate, ketone bodies, asparagine, alanine, leucine, valine and isoleucine in plasma and/or urine were involved in the development and progression of seizures. These altered metabolites reflected the pathophysiological processes including the compromised energy metabolism, the disturbed amino acid metabolism, the peripheral inflammation and changes in gut microbiota functions. NMR-based metabolomics could provide brain disease information by the dynamic plasma and urinary metabolic changes during chronic epileptic seizures, yielding classification of seizure stages and profound insights into controlling epilepsy via targeting deficient energy metabolism.

Proteomic and metabolomic profiling of acupuncture for migraine reveals a correlative link via energy metabolism

Migraine is a neurovascular disease with a high disability rate. Acupuncture treatment has emerged as a safe and viable alternative prophylactic therapy that can effectively alleviate the duration and frequency of migraine attacks. However, the therapeutic mechanisms underlying the effects of acupuncture are yet to be systematically elucidated. In this study, we enrolled female patients with migraine without aura (n = 20) and healthy controls (n = 10). Patients received acupuncture treatment on DU20, DU24, bilateral GB13, GB8, and GB20, applied three times per week over the course of 4 weeks for 12 sessions in total. Blood samples were collected from the median cubital vein before and after acupuncture treatment. Proteomic and metabolomic profiling was performed using liquid chromatography-mass spectrometry to determine the characteristics of differentially expressed molecules and expression of their corresponding biological pathways as well as to elucidate the pathogenesis of migraine and the biological effects underlying the treatment of migraine with acupuncture. Proteomic and metabolomic profiling of plasma samples from patients with migraine without aura before and after acupuncture treatment revealed enrichment of immune-related pathway functions and the arginine synthesis pathway. Joint pathway analyses revealed significant enrichment of the pentose phosphate and glycolysis/gluconeogenesis pathways in patients with migraine. The glycolysis/gluconeogenesis and riboflavin metabolism pathways were significantly enriched after acupuncture treatment. The expression levels of various key proteins and metabolites, including α-D-glucose, flavin adenine dinucleotide, biliverdin reductase B, and L-glutamate, were significantly differentially expressed before and after acupuncture treatment in patients with migraine without aura. Treatment of migraine with acupuncture was associated with significant changes in key molecules and pathways, indicative of physiological changes in the trigeminovascular system, glutamate neurotoxicity, and other migraine-related physiological changes. Overall, our comprehensive analysis using proteomic and metabolomic profiling demonstrates that energy metabolism may serve as a key correlative link in the occurrence of migraine and the therapeutic effects of acupuncture treatment. Our findings may facilitate the identification of diagnostic and therapeutic modalities in the ongoing search for effective treatments for migraine attacks.

A serum metabolomics study based on LC-MS: Chemosensitization effects of Rauvolfia vomitoria Afzel. combined with 5- fluorouracil on colorectal cancer mice

Colorectal cancer (CRC) is one of the malignant tumors with high incidence, and is mainly treated by chemotherapy at present. However, during CRC treatment, long-term use of traditional chemotherapeutic drugs will reduce the sensitivity of chemotherapy. Our previous studies have shown that Rauvolfia vomitoria total alkaloids (RVA) played an important role in 5-fluorouracil (5-FU) chemosensitization in CRC therapy, but its intervention mechanism has not been clarified completely in the metabolic level. Therefore, in this study, LC-MS based metabolomics was employed to explore the mechanism of 5-FU chemosensitization in CRC induced by the combination of RVA and conventional chemotherapeutic with 5-FU. The results showed that the final tumor weight of the high-dose combined group was significantly different from that of the 5-FU alone group. To evaluate the chemosensitization effects of RVA, serum samples collected from six groups (six mice in each group) with different administration methods were analyzed by HPLC-Q-Exactive Orbitrap/MS. After multivariate statistical analysis and metabolites identification, 25 different metabolites were identified between the 5-FU treatment group and combined high-dose treatment group, among which lipid and fatty acid metabolism pathways were mostly affected. These results suggest that RVA may sensitize traditional chemotherapeutic drug 5-FU and exert anti-tumor activity through influencing lipid metabolism and cell energy metabolism. Metabolomics provided a new insight into estimate of the therapeutic effect and dissection of the potential mechanisms of traditional Chinese medicine in treating colorectal cancer.

Inhaled glucocorticoid-induced metabolome changes in asthma

OBJECTIVE

The aim of this study was toidentify dose-related systemic effects of inhaled glucocorticoids (GCs) on the global metabolome.

DESIGN AND METHODS

Metabolomics/lipidomic analysis from plasma was obtained from 54 subjects receiving weekly escalating doses (µg/day) of fluticasone furoate (FF; 25, 100, 200, 400 and 800), fluticasone propionate (FP; 50, 200, 500, 1000 and 2000), budesonide (BUD; 100, 400, 800, 1600 and 3200) or placebo. Samples (pre- and post-dose) were analysed using ultrahigh-performance liquid chromatography-tandem mass spectroscopy and liquid chromatography-mass spectrometry. Ions were matched to library standards for identification and quantification. Statistical analysis involved repeated measures ANOVA, cross-over model, random forest and principal component analysis using log-transformed data.

RESULTS

Quantifiable metabolites (1971) had few significant changes (% increases/decreases; P < 0.05) vs placebo: FF 1.34 (0.42/0.92), FP 1.95 (0.41/1.54) and BUD 2.05 (0.60/1.45). Therapeutic doses had fewer changes: FF 0.96 (0.36/0.61), FP 1.66 (0.44/1.22) and BUD 1.45 (0.56/0.90). At highest/supratherapeutic doses, changes were qualitatively similar: reduced adrenal steroids, particularly glucuronide metabolites of cortisol and cortisone and pregnenolone metabolite DHEA-S; increased amino acids and glycolytic intermediates; decreased fatty acid β-oxidation and branched-chain amino acids. Notable qualitative differences were lowered dopamine metabolites (BUD) and secondary bile acid profiles (BUD/FF), suggesting CNS and gut microbiome effects.

CONCLUSIONS

Dose-dependent metabolomic changes occurred with inhaled GCs but were seen predominately at highest/supratherapeutic doses, supporting the safety of low and mid therapeutic doses. At comparable therapeutic doses (FF 100, FP 500 and BUD 800 µg/day), FF had the least effect on the most sensitive markers (adrenal steroids) vs BUD and FP.

Metabolite Signature of Simvastatin Treatment Involves Multiple Metabolic Pathways

Statins inhibit the 3-hydroxy-3-methylglutaryl-CoA reductase enzyme and are the most widely used medication for hypercholesterolemia. Previous studies on the metabolite signature of simvastatin treatment have included only a small number of metabolites. We performed a high-throughput liquid chromatography–tandem mass spectroscopy profiling on the effects of simvastatin treatment on 1098 metabolite concentrations in the participants of the METSIM (Metabolic Syndrome In Men) study including 1332 participants with simvastatin treatment and 6200 participants without statin treatment. We found that simvastatin exerts profound pleiotropic effects on different metabolite pathways, affecting not only lipids, but also amino acids, peptides, nucleotides, carbohydrates, co-factors, vitamins, and xenobiotics. We identified 321 metabolites significantly associated with simvastatin treatment, and 313 of these metabolites were novel. Our study is the first comprehensive evaluation of the metabolic signature of simvastatin treatment in a large population-based study.

A review of study designs and data analyses in metabolomics studies in myopia

Metabolomics analyzes the entire range of small molecule metabolites in biological systems to reveal the response signals that are transmitted from "genetics and environment", which could help us understand complex phenotypes of diseases. Metabolomics has been successfully applied to the study of eye diseases including age-related macular degeneration, glaucoma, and diabetic retinopathy. In this review, we summarize the findings of myopic metabolomics and discuss them from a design and analysis perspective. Finally, we provide new ideas for the future development of myopia metabolomics research based on the broader ocular metabolomics study.

Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants

Cohort studies report inconsistent associations between body mass index (BMI) and all-cause incident dementia. Furthermore, evidence on fat distribution and body composition measures are scarce and few studies estimated the association between early life adiposity and dementia risk. Here, we included 322,336 participants from UK biobank to investigate the longitudinal association between life course adiposity and risk of all-cause incident dementia and to explore the underlying mechanisms driven by metabolites, inflammatory cells and brain structures. Among the 322,336 individuals (mean (SD) age, 62.24 (5.41) years; 53.9% women) in the study, during a median 8.74 years of follow-up, 5083 all-cause incident dementia events occurred. The risk of dementia was 22% higher with plumper childhood body size (p < 0.001). A strong U-shaped association was observed between adult BMI and dementia. More fat and less fat-free mass distribution on arms were associated with a higher risk of dementia. Interestingly, similar U-shaped associations were found between BMI and four metabolites (i.e., 3-hydroxybutrate, acetone, citrate and polyunsaturated fatty acids), four inflammatory cells (i.e., neutrophil, lymphocyte, monocyte and leukocyte) and abnormalities in brain structure that were also related to dementia. The findings that adiposity is associated with metabolites, inflammatory cells and abnormalities in brain structure that were related to dementia risk might provide clues to underlying biological mechanisms. Interventions to prevent dementia should begin early in life and include not only BMI control but fat distribution and body composition.

Identification of Prognostic Metabolomic Biomarkers at the Interface of Mortality and Morbidity in Pre-Existing TB Cases Infected With SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection currently remains one of the biggest global challenges that can lead to acute respiratory distress syndrome (CARDS) in severe cases. In line with this, prior pulmonary tuberculosis (TB) is a risk factor for long-term respiratory impairment. Post-TB lung dysfunction often goes unrecognized, despite its relatively high prevalence and its association with reduced quality of life. In this study, we used a metabolomics analysis to identify potential biomarkers that aid in the prognosis of COVID-19 morbidity and mortality in post-TB infected patients. This analysis involved blood samples from 155 SARS-CoV-2 infected adults, of which 23 had a previous diagnosis of TB (post-TB), while 132 did not have a prior or current TB infection. Our analysis indicated that the vast majority (~92%) of post-TB individuals showed severe SARS-CoV-2 infection, required intensive oxygen support with a significantly high mortality rate (52.2%). Amongst individuals with severe COVID-19 symptoms, we report a significant decline in the levels of amino acids, notably the branched chains amino acids (BCAAs), more so in the post-TB cohort (FDR <= 0.05) in comparison to mild and asymptomatic cases. Indeed, we identified betaine and BCAAs as potential prognostic metabolic biomarkers of severity and mortality, respectively, in COVID-19 patients who have been exposed to TB. Moreover, we identified serum alanine as an important metabolite at the interface of severity and mortality. Hence, our data associated COVID-19 mortality and morbidity with a long-term metabolically driven consequence of TB infection. In summary, our study provides evidence for a higher mortality rate among COVID-19 infection patients who have history of prior TB infection diagnosis, which mandates validation in larger population cohorts.

[Blood Based Biomarker for Optimization of Early and Differential Diagnosis of Alzheimer's Dementia]

AIM

Dementia in Alzheimer´s disease is a global challenge. There is growing evidence that investigating blood biomarkers to diagnose Alzheimer´s disease is a promising fast, minimally invasive, and less costly method. The aim of this study was to review available studies on promising biomarkers for Alzheimer´s disease.

METHOD

The latest studies were collated for this review.

RESULTS

Immunoassays followed by mass spectrometry and immunomagnetic reduction were reported to be highly relevant methods for detecting amyloid-ß 42 (Aß42) and amyloid-ß 40 (Aß40) to calculate the Aß42/Aß40 ratio, thereby improving the early diagnosis of Alzheimer´s disease. Amyloid-ß (Aß) peptides in blood plasma were considered as potential markers, as they correlated with the brain's Aß pathology. Phosphorylated tau protein 181 (p-tau181), phosphorylated tau protein 217 (p-tau217) and phosphorylated tau protein 231 (p-tau231) in blood samples assessed via Simoa technology served as parameters for the early and differential diagnosis of AD, and were markers of tau pathology in the brain. Neurofilament light chain (Nfl) and glial fibrillary acid protein (GFAP) were additional markers possibly facilitating the assessment of axonal and astroglial brain damage in Alzheimer´s disease. GFAP in blood was useful as an additional marker to detect early and to predict the time course of Alzheimer´s disease.

CONCLUSIONS

Determining blood biomarkers represents less invasive and less costly diagnostics for Alzheimer´s disease. The investigation of blood biomarkers such as the Aß42/Aß40 ratio, p-tau217, p-tau231, Nfl and GFAP have been promising in establishing the AT(N) classification for Alzheimer´s disease. High-throughput methods should be evaluated in large patient cohort studies and via meta-analyses of studies. Consensus criteria with standard protocols for measuring these biomarkers while considering ethical issues and Alzheimer´s phenotype should unify normative values from different laboratories. The AT(N) classification of Alzheimer´s disease in blood would be a key element towards the implementation of minimally-invasive precision medicine.

Faecal Metabolomics in Paediatric Inflammatory Bowel Disease: A Systematic Review

BACKGROUND AND AIMS

Paediatric inflammatory bowel disease [IBD] is characterized by altered immunological and metabolic pathways. Metabolomics may therefore increase pathophysiological understanding and could develop into characterization of biomarkers for diagnosis and IBD treatment response. However, no uniform metabolomic profiles have been identified to date. This systematic review aimed to identify faecal metabolomic signatures in paediatric IBD vs controls, and to describe metabolites associated with disease activity and treatment response.

METHODS

A literature search was performed in Embase, Medline, Web of Science and Cochrane Library. Studies assessing faecal metabolomics in paediatric patients < 18 years with IBD [de novo, active, inactive] with comparative groups [IBD vs non-IBD; responders vs non-responders] were included. The quality of included studies was assessed according to the Newcastle-Ottawa Scale.

RESULTS

Nineteen studies were included [540 patients with IBD, 386 controls], assessing faecal short-chain fatty acids [SCFA] [five studies], amino acids [AA] [ten studies], bile acids [BA] [eight studies] and other metabolites [nine studies] using various methodologies. Significantly increased levels of AA [particularly phenylalanine], primary BA and lower levels of secondary BA were described in paediatric IBD compared to controls. Faecal SCFA results varied across studies. Additionally, responders and non-responders to exclusive enteral nutrition and infliximab showed differences in baseline faecal metabolites [based on BA, AA].

CONCLUSIONS

This systematic review provides evidence for distinct faecal metabolomic profiles in paediatric IBD. However, results varied across studies, possibly due to differences in study design and applied analytical techniques. Faecal metabolomics could provide more insight into host-microbial interactions in IBD, but further studies with standardized methodologies and reporting are needed.

Metabolomics in clinical and forensic toxicology, sports anti-doping and veterinary residues

Metabolomics is a multidisciplinary field providing workflows for complementary approaches to conventional analytical determinations. It allows for the study of metabolically related groups of compounds or even the study of novel pathways within the biological system. The procedural stages of metabolomics; experimental design, sample preparation, analytical determinations, data processing and statistical analysis, compound identification and validation strategies are explored in this review. The selected approach will depend on the type of study being conducted. Experimental design influences the whole metabolomics workflow and thus needs to be properly assessed to ensure sufficient sample size, minimal introduced and biological variation and appropriate statistical power. Sample preparation needs to be simple, yet potentially global in order to detect as many compounds as possible. Analytical determinations need to be optimised either for the list of targeted compounds or a universal approach. Data processing and statistical analysis approaches vary widely and need to be better harmonised for review and interpretation. This includes validation strategies that are currently deficient in many presented workflows. Common compound identification approaches have been explored in this review. Metabolomics applications are discussed for clinical and forensic toxicology, human and equine sports anti-doping and veterinary residues.

In vitro Antimicrobial Activity and the Mechanism of Berberine Against Methicillin-Resistant Staphylococcus aureus Isolated from Bloodstream Infection Patients

Purpose

To investigate the antimicrobial activity of berberine and the mechanism by which it combats methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from patients with bloodstream infections.

Methods

Fifteen clinical MRSA isolates were collected, and their Multi-locus Sequence Types (MLST) were examined. The minimum inhibitory concentration (MIC) and combined antibacterial activity of berberine alone, and when combined with clindamycin and rifampicin separately, were determined. Additionally, two MRSA strains (ST239 and ST5) were selected to perform the time-killing assay and biofilm formation test. Cell wall alterations and cell membrane integrity were measured by confocal laser scanning microscopy (CLSM) and electron microscopy to assess the influence on cell morphology.

Results

Our data showed berberine was effective against MRSA at MIC values varying from 256 to 64 mg*L⁻¹ for different MLST types. Berberine alone, and when combined with clindamycin and rifampicin separately, displayed excellent antibacterial activity which reduced the bacterial counts by 2lgCFU*mL within 24h and significantly weakened biofilm formation compared with control strain. Additionally, bacterial cytological profiling indicates that berberine destroyed the structure of the cell walls, membrane integrity and further changed the cell morphology with concentration increased.

Conclusion

In our study, berberine has excellent anti-MRSA activities and has synergistic antibacterial property when combined with clindamycin and rifamycin separately, and the mechanism of activities involves the destruction of cell wall and membrane.

Chemical exposures assessed via silicone wristbands and endogenous plasma metabolomics during pregnancy

BACKGROUND

Metabolomics is a promising method to investigate physiological effects of chemical exposures during pregnancy, with the potential to clarify toxicological mechanisms, suggest sensitive endpoints, and identify novel biomarkers of exposures.

OBJECTIVE

Investigate the influence of chemical exposures on the maternal plasma metabolome during pregnancy.

METHODS

Data were obtained from participants (n = 177) in the New Hampshire Birth Cohort Study, a prospective pregnancy cohort. Chemical exposures were assessed via silicone wristbands worn for one week at ~13 gestational weeks. Metabolomic features were assessed in plasma samples obtained at ~24-28 gestational weeks via the Biocrates AbsoluteIDQ® p180 kit and nuclear magnetic resonance (NMR) spectroscopy. Associations between chemical exposures and plasma metabolomics were investigated using multivariate modeling.

RESULTS

Chemical exposures predicted 11 (of 226) and 23 (of 125) metabolomic features in Biocrates and NMR, respectively. The joint chemical exposures did not significantly predict pathway enrichment, though some individual chemicals were associated with certain amino acids and related metabolic pathways. For example, N,N-diethyl-m-toluamide was associated with the amino acids glycine, L-glutamic acid, L-asparagine, and L-aspartic acid and enrichment of the ammonia recycling pathway.

SIGNIFICANCE

This study contributes evidence to the potential effects of chemical exposures during pregnancy upon the endogenous maternal plasma metabolome.

Sex-Specific Catabolic Metabolism Alterations in the Critically Ill following High Dose Vitamin D

Pharmacological interventions are essential for the treatment and management of critical illness. Although women comprise a large proportion of the critically ill, sex-specific pharmacological properties are poorly described in critical care. The sex-specific effects of vitamin D₃ treatment in the critically ill are not known. Therefore, we performed a metabolomics cohort study with 1215 plasma samples from 428 patients from the VITdAL-ICU trial to study sex-specific differences in the metabolic response to critical illness following high-dose oral vitamin D₃ intervention. In women, despite the dose of vitamin D₃ being higher, pharmacokinetics demonstrated a lower extent of vitamin D₃ absorption compared to men. Metabolic response to high-dose oral vitamin D₃ is sex-specific. Sex-stratified individual metabolite associations with elevations in 25(OH)D following intervention showed female-specific positive associations in long-chain acylcarnitines and male-specific positive associations in free fatty acids. In subjects who responded to vitamin D₃ intervention, significant negative associations were observed in short-chain acylcarnitines and branched chain amino acid metabolites in women as compared to men. Acylcarnitines and branched chain amino acids are reflective of fatty acid B oxidation, and bioenergesis may represent notable metabolic signatures of the sex-specific response to vitamin D. Demonstrating sex-specific pharmacometabolomics differences following intervention is an important movement towards the understanding of personalized medicine.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

Revealing the Antiepileptic Effect of α-Asaronol on Pentylenetetrazole-Induced Seizure Rats Using NMR-Based Metabolomics

α-Asaronol from Acorus tatarinowii (known as "Shichangpu" in Traditional Chinese medicine) has been proved to possess more efficient antiepileptic activity and lower toxicity than α-asarone (namely "Xixinnaojiaonang" as an antiepileptic drug in China) in our previous study. However, the molecular mechanism of α-asaronol against epilepsy needs to be known if to become a novel antiepileptic medicine. Nuclear magnetic resonance (NMR)-based metabolomics was applied to investigate the metabolic patterns of plasma and the brain tissue extract from pentylenetetrazole (PTZ)-induced seizure rats when treated with α-asaronol or α-asarone. The results showed that α-asaronol can regulate the metabolomic level of epileptic rats to normal to some extent, and four metabolic pathways were associated with the antiepileptic effect of α-asaronol, including alanine, aspartate, and glutamate metabolism; synthesis and degradation of ketone bodies; glutamine and glutamate metabolism; and glycine, serine, and threonine metabolism. It was concluded that α-asaronol plays a vital role in enhancing energy metabolism, regulating the balance of excitatory and inhibitory neurotransmitters, and inhibiting cell membrane damage to prevent the occurrence of epilepsy. These findings are of great significance in developing α-asaronol into a promising antiepileptic drug derived from Traditional Chinese medicine.

Metabolic Phenotyping Predicts Gemcitabine and Cisplatin Chemosensitivity in Patients With Cholangiocarcinoma

Gemcitabine and cisplatin serve as appropriate treatments for patients with cholangiocarcinoma (CCA). Our previous study using histoculture drug response assay (HDRA), demonstrated individual response patterns to gemcitabine and cisplatin. The current study aimed to identify predictive biomarkers for gemcitabine and cisplatin sensitivity in tissues and sera from patients with CCA using metabolomics. Metabolic signatures of patients with CCA were correlated with their HDRA response patterns. The tissue metabolic signatures of patients with CCA revealed the inversion of the TCA cycle that is evident with increased levels of citrate and amino acid backbones as TCA cycle intermediates, and glucose which corresponds to cancer stem cell (CSC) properties. The protein expression levels of CSC markers were examined on tissues and showed the significantly inverse association with the responses of patients to cisplatin. Moreover, the elevation of ethanol level was observed in gemcitabine- and cisplatin-sensitive group. In serum, a lower level of glucose but a higher level of methylguanidine was observed in the gemcitabine-responders as non-invasive predictive biomarker for gemcitabine sensitivity. Collectively, our findings indicate that these metabolites may serve as the predictive biomarkers in clinical practice which not only predict the chemotherapy response in patients with CCA but also minimize the adverse effect from chemotherapy.