Metabolomics and Personalized Medicine

Network Pharmacology of Adaptogens in the Assessment of Their Pleiotropic Therapeutic Activity

The reductionist concept, based on the ligand–receptor interaction, is not a suitable model for adaptogens, and herbal preparations affect multiple physiological functions, revealing polyvalent pharmacological activities, and are traditionally used in many conditions. This review, for the first time, provides a rationale for the pleiotropic therapeutic efficacy of adaptogens based on evidence from recent gene expression studies in target cells and where the network pharmacology and systems biology approaches were applied. The specific molecular targets and adaptive stress response signaling mechanisms involved in nonspecific modes of action of adaptogens are identified.

Evaluation of Metabolic Profiles of Patients with Anorexia Nervosa at Inpatient Admission, Short- and Long-Term Weight Regain-Descriptive and Pattern Analysis

Acute anorexia nervosa (AN) constitutes an extreme physiological state. We aimed to detect state related metabolic alterations during inpatient admission and upon short- and long-term weight regain. In addition, we tested the hypothesis that metabolite concentrations adapt to those of healthy controls (HC) after long-term weight regain. Thirty-five female adolescents with AN and 25 female HC were recruited. Based on a targeted approach 187 metabolite concentrations were detected at inpatient admission (T₀), after short-term weight recovery (T₁; half of target-weight) and close to target weight (T₂). Pattern hunter and time course analysis were performed. The highest number of significant differences in metabolite concentrations (N = 32) were observed between HC and T₁. According to the detected main pattern, metabolite concentrations at T₂ became more similar to those of HC. The course of single metabolite concentrations (e.g., glutamic acid) revealed different metabolic subtypes within the study sample. Patients with AN after short-term weight regain are in a greater “metabolic imbalance” than at starvation. After long-term weight regain, patients reach a metabolite profile similar to HC. Our results might be confounded by different metabolic subtypes of patients with AN.

Supercritical fluid chromatography - Mass spectrometry in metabolomics: Past, present, and future perspectives

Metabolomics, which consists of the comprehensive analysis of metabolites within a biological system, has been playing a growing role in the implementation of personalized medicine in modern healthcare. A wide range of analytical approaches are used in metabolomics, notably mass spectrometry (MS) combined to liquid chromatography (LC), gas chromatography (GC), or capillary electrophoresis (CE). However, none of these methods enable a comprehensive analysis of the metabolome, due to its extreme complexity and the large differences in physico-chemical properties between metabolite classes. In this context, supercritical fluid chromatography (SFC) represents a promising alternative approach to improve the metabolome coverage, while further increasing the analysis throughput. SFC, which uses supercritical CO₂ as mobile phase, leads to numerous advantages such as improved kinetic performance and lower environmental impact. This chromatographic technique has gained a significant interest since the introduction of advanced instrumentation, together with the introduction of dedicated interfaces for hyphenating SFC to MS. Moreover, new developments in SFC column chemistry (including sub-2 µm particles), as well as the use of large amounts of organic modifiers and additives in the CO₂-based mobile phase, significantly extended the application range of SFC, enabling the simultaneous analysis of a large diversity of metabolites. Over the last years, several applications have been reported in metabolomics using SFC-MS - from lipophilic compounds, such as steroids and other lipids, to highly polar compounds, such as carbohydrates, amino acids, or nucleosides. With all these advantages, SFC-MS is promised to a bright future in the field of metabolomics.

Current Strategies and Future Perspectives for Precision Medicine in Pancreatic Cancer

Current standard-of-care for patients with pancreatic ductal adenocarcinoma (PDAC) focusses on chemotherapeutic regimens and pancreatic cancer surgery. However, limited treatment options, late diagnosis in advanced tumor stages and the aggressive behavior of PDAC contribute to the high mortality of the disease. Consequently, there is an urgent need of precision medicine for pancreatic cancer patients. All over the world, numerous initiatives started in recent years to translate novel scientific discoveries into prospective clinical trials. One major approach pursues the stratification of PDAC patients according the tumor transcriptome to predict treatment response. Other strategies concentrate on genomic alterations and the identification of individualized targeted therapies. Further experimental studies are ongoing to detect novel biomarkers for cancer diagnosis, subtyping, treatment response prediction or clinical outcome. However, the challenge remains to transfer the knowledge into clinical practice. In this review, we summarize current literature and knowledge and highlight novel concepts of basic and clinical research uncovering suitable biomarkers and targeted therapies. Thus, we provide an overview of preclinical and clinical efforts of precision medicine in pancreatic cancer.

Prediction of sepsis mortality using metabolite biomarkers in the blood: a meta-analysis of death-related pathways and prospective validation

BACKGROUND

Sepsis is a leading cause of death in intensive care units (ICUs), but outcomes of individual patients are difficult to predict. The recently developed clinical metabolomics has been recognized as a promising tool in the clinical practice of critical illness. The objective of this study was to identify the unique metabolic biomarkers and their pathways in the blood of sepsis nonsurvivors and to assess the prognostic value of these pathways.

METHODS

We searched PubMed, EMBASE, Cochrane, Web of Science, CNKI, Wangfang Data, and CQVIP from inception until July 2019. Eligible studies included the metabolomic analysis of blood samples from sepsis patients with the outcome. The metabolic pathway was assigned to each metabolite biomarker. The meta-analysis was performed using the pooled fold changes, area under the receiver operating characteristic curve (AUROC), and vote-counting of metabolic pathways. We also conducted a prospective cohort metabolomic study to validate the findings of our meta-analysis.

RESULTS

The meta-analysis included 21 cohorts reported in 16 studies with 2509 metabolite comparisons in the blood of 1287 individuals. We found highly limited overlap of the reported metabolite biomarkers across studies. However, these metabolites were enriched in several death-related metabolic pathways (DRMPs) including amino acids, mitochondrial metabolism, eicosanoids, and lysophospholipids. Prediction of sepsis death using DRMPs yielded a pooled AUROC of 0.81 (95% CI 0.76-0.87), which was similar to the combined metabolite biomarkers with a merged AUROC of 0.82 (95% CI 0.78-0.86) (P > 0.05). A prospective metabolomic analysis of 188 sepsis patients (134 survivors and 54 nonsurvivors) using the metabolites from DRMPs produced an AUROC of 0.88 (95% CI 0.78-0.97). The sensitivity and specificity for the prediction of sepsis death were 80.4% (95% CI 66.9-89.4%) and 78.8% (95% CI 62.3-89.3%), respectively.

CONCLUSIONS

DRMP analysis minimizes the discrepancies of results obtained from different metabolomic methods and is more practical than blood metabolite biomarkers for sepsis mortality prediction.

TRIAL REGISTRATION

The meta-analysis was registered on OSF Registries, and the prospective cohort study was registered on the Chinese Clinical Trial Registry (ChiCTR1800015321).

Synergistic therapeutic effects of Duzhong Jiangya Tablets and amlodipine besylate combination in spontaneously hypertensive rats using 1 H-NMR- and MS-based metabolomics

Duzhong Jiangya Tablet (DJT) composed of Eucommia ulmoides Oliv. and several other traditional Chinese medicines is a Chinese herbal compound, which is clinically used to treat hypertension. The aim of this study was to evaluate the antihypertensive effect of DJT and amlodipine besylate (AB) on the synergistic treatment of spontaneously hypertensive rats (SHRs), and to explore its antihypertensive mechanism. The synergistic therapeutic effect of DJT in combination with AB on SHR was studied using two metabolomics methods based on mass spectrum (MS) and nuclear magnetic resonance. Metabolomics analysis of plasma, urine, liver, and kidney and the combination of orthogonal partial least squares discriminant analysis was performed to expose potential biomarkers. Then, the overall metabolic characteristics and related abnormal metabolic pathways in hypertensive rats were constructed. Blood pressure measurements showed that DJT combined with AB has better effects in treating hypertension than it being alone. A total of 30 biomarkers were identified, indicating that hypertension disrupted the balance of multiple metabolic pathways in the body, and that combined administration restored metabolite levels better than their administration alone. The changes of biomarkers revealed the synergistic therapeutic mechanism of DJT combined with AB, which provided a reference for the combination of Chinese and Western medicines.

Metabolomics toward personalized medicine

Metabolomics, which is the metabolites profiling in biological matrices, is a key tool for biomarker discovery and personalized medicine and has great potential to elucidate the ultimate product of the genomic processes. Over the last decade, metabolomics studies have identified several relevant biomarkers involved in complex clinical phenotypes using diverse biological systems. Most diseases result in signature metabolic profiles that reflect the sums of external and internal cellular activities. Metabolomics has a major role in clinical practice as it represents >95% of the workload in clinical laboratories worldwide. Many of these metabolites require different analytical platforms, such as Nuclear Magnetic Resonance (NMR), Mass Spectrometry (MS), and Ultra Performance Liquid Chromatography (UPLC), while many clinically relevant metabolites are still not routinely amenable to detection using currently available assays. Combining metabolomics with genomics, transcriptomics, and proteomics studies will result in a significantly improved understanding of the disease mechanisms and the pathophysiology of the target clinical phenotype. This comprehensive approach will represent a major step forward toward providing precision medical care, in which individual is accounted for variability in genes, environment, and personal lifestyle. In this review, we compare and evaluate the metabolomics strategies and studies that focus on the discovery of biomarkers that have "personalized" diagnostic, prognostic, and therapeutic value, validated for monitoring disease progression and responses to various management regimens.

Urinary profiles associated with bacterial metabolites from asymptomatic pregnant women with at term or preterm premature rupture of membranes: a pilot study

Objective: Premature rupture of membranes (PROM) and preterm premature rupture of membranes (pPROM) are frequent conditions with a not fully understood multifactorial etiology. It has been suggested that infection may be the leading cause of pPROM. Metabolomics is nowadays recognized as a successful and versatile approach for the investigation of several pathological conditions, including pregnancy-related ones. However, collecting samples such as fetal fluids or placenta poses a limit on the clinical application of this strategy. Therefore, the aim of this study was to detect urinary metabolites that could be associated with bacterial infection in PROM and pPROM and to understand its role in these different conditions, using readily available samples such as urines.Methods: Urine samples were collected from pregnant women who experienced rupture of membranes: (1) at term (≥37 weeks) not in labor (NLPROM); (2) at term in labor (LPROM); (3) preterm (<37 weeks) not in labor (pPROM). Samples were analyzed using a GC-MS platform. Student's t-test, Pearson correlation coefficient, principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) were applied to observe differences between groups.Results: Results showed that lactic acid, erythritol, and ethanolamine levels were significantly higher in pPROM than in PROM (NLPROM + LPROM considered as one single group). These three metabolites might be associated with bacterial infections since they derive from bacterial metabolic processes and environments.Conclusions: This study might be useful to understand the mechanisms underlying the etiology of pPROM and PROM, and urine samples might represent a useful and readily available sample to discriminate preterm high-risk women.

Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing

Metabolomics is the untargeted measurement of the metabolome, which is composed of the complement of small molecules detected in a biological sample. As such, metabolomic analysis produces a global biochemical phenotype. It is a technology that has been utilized in the research setting for over a decade. The metabolome is directly linked to and is influenced by genetics, epigenetics, environmental factors, and the microbiome-all of which affect health. Metabolomics can be applied to human clinical diagnostics and to other fields such as veterinary medicine, nutrition, exercise, physiology, agriculture/plant biochemistry, and toxicology. Applications of metabolomics in clinical testing are emerging, but several aspects of its use as a clinical test differ from applications focused on research or biomarker discovery and need to be considered for metabolomics clinical test data to have optimum impact, be meaningful, and be used responsibly. In this review, we deconstruct aspects and challenges of metabolomics for clinical testing by illustrating the significance of test design, accurate and precise data acquisition, quality control, data processing, n-of-1 comparison to a reference population, and biochemical pathway analysis. We describe how metabolomics technology is integral to defining individual biochemical phenotypes, elaborates on human health and disease, and fits within the precision medicine landscape. Finally, we conclude by outlining some future steps needed to bring metabolomics into the clinical space and to be recognized by the broader medical and regulatory fields.

Next-generation biomarker discovery in Alzheimer's disease using metabolomics - from animal to human studies

Alzheimer's disease (AD) is a complex disease driven mainly by neuronal loss due to accumulation of intracellular neurofibrillary tangles and amyloid β aggregates in the brain. The diagnosis of AD currently relies on clinical symptoms while the disease can only be confirmed at autopsy. The few available biomarkers allowing for diagnosis are typically detected many years after the onset of the disease. New diagnostic approaches, particularly in easily-accessible biofluids, are essential. By providing an exhaustive information of the phenotype, metabolomics is an ideal approach for identification of new biomarkers. This review investigates the current position of metabolomics in the field of AD research, focusing on animal and human studies, and discusses the improvements carried out over the past decade.

A Metabolomics Approach to Pharmacotherapy Personalization

The optimization of drug therapy according to the personal characteristics of patients is a perspective direction in modern medicine. One of the possible ways to achieve such personalization is through the application of "omics" technologies, including current, promising metabolomics methods. This review demonstrates that the analysis of pre-dose metabolite biofluid profiles allows clinicians to predict the effectiveness of a selected drug treatment for a given individual. In the review, it is also shown that the monitoring of post-dose metabolite profiles could allow clinicians to evaluate drug efficiency, the reaction of the host to the treatment, and the outcome of the therapy. A comparative description of pharmacotherapy personalization (pharmacogenomics, pharmacoproteomics, and therapeutic drug monitoring) and personalization based on the analysis of metabolite profiles for biofluids (pharmacometabolomics) is also provided.

Integrative omics to detect bacteremia in patients with febrile neutropenia

BACKGROUND

Cancer chemotherapy-associated febrile neutropenia (FN) is a common condition that is deadly when bacteremia is present. Detection of bacteremia depends on culture, which takes days, and no accurate predictive tools applicable to the initial evaluation are available. We utilized metabolomics and transcriptomics to develop multivariable predictors of bacteremia among FN patients.

METHODS

We classified emergency department patients with FN and no apparent infection at presentation as bacteremic (cases) or not (controls), according to blood culture results. We assessed relative metabolite abundance in plasma, and relative expression of 2,560 immunology and cancer-related genes in whole blood. We used logistic regression to identify multivariable predictors of bacteremia, and report test characteristics of the derived predictors.

RESULTS

For metabolomics, 14 bacteremic cases and 25 non-bacteremic controls were available for analysis; for transcriptomics we had 7 and 22 respectively. A 5-predictor metabolomic model had an area under the receiver operating characteristic curve of 0.991 (95%CI: 0.972,1.000), 100% sensitivity, and 96% specificity for identifying bacteremia. Pregnenolone steroids were more abundant in cases and carnitine metabolites were more abundant in controls. A 3-predictor gene expression model had corresponding results of 0.961 (95%CI: 0.896,1.000), 100%, and 86%. Genes involved in innate immunity were differentially expressed.

CONCLUSIONS

Classifiers derived from metabolomic and gene expression data hold promise as objective and accurate predictors of bacteremia among FN patients without apparent infection at presentation, and can provide insights into the underlying biology. Our findings should be considered illustrative, but may lay the groundwork for future biomarker development.

Estimation of early postmortem interval in rats by GC-MS-based metabolomics

Accurately predicting the early postmortem interval (PMI) is of great significance in forensic practice. This study aimed to establish a novel method for estimating the early PMI by analyzing endogenous substances in the cardiac blood of male and female rats and compare different model for estimating early PMI using these data. Adult Sprague-Dawley (SD) rats (50% male) were sacrificed by suffocation. Then, cardiac blood was collected at various time intervals (0, 3, 6, 12, 24, 48, and 72 h) after death, and the collected samples were analyzed by gas chromatography-tandem mass spectrometry (GC-MS). The data were analyzed by multivariate statistical analysis. An orthogonal signal correction-partial least squares (OSC-PLS) regression model was constructed with whole endogenous metabolites to validate the PMI. The OSC-PLS regression model successfully predicted the PMI of the forecast set and no significant differences was observed between male and female rats. This is the first study to establish an OSC-PLS regression model for predicting PMI with the metabolome, which provides a new technical method and platform for estimating PMI through metabolomics.

Microdosing, isotopic labeling, radiotracers and metabolomics: relevance in drug discovery, development and safety

This review discusses the use of stable (¹³C, ²D) or radioactive isotopes (¹⁴C, ¹¹C, ¹⁸F, ¹³¹I, ⁶⁴Cu, ⁶⁸Ga) incorporated into the molecular structure of new drug entities for the purpose of pharmacokinetic or -dynamic studies. Metabolite in safety testing requires the administration of pharmacologically active doses. In such studies, radiotracers find application mainly in preclinical animal investigations, whereby LC-MS/MS is used to identify metabolite structure and drug-related effects. In contrast, first-in-human metabolite studies have to be carried out at nonpharmacological doses not exceeding 100 μg (microdose), which is generally too low for metabolite detection by LC-MS/MS. This short-coming can be overcome by specific radio- or isotopic labeling of the drug of interest and measurements using accelerator mass spectroscopy, single-photon emission computed tomography and positron emission tomography. Such combined radioisotope-based approaches permit Phase 0, first-in-human metabolite study.

The role of metabolomics in tuberculosis treatment research

Despite the fact that tuberculosis (TB) is a curable disease, it still results in approximately 1.8 million deaths annually. Various inadequacies in the current TB treatment strategies are major contributors to this high disease prevalence, including the long duration of therapy, the severe side effects associated with TB drugs, treatment failure due to drug resistance, post-treatment disease relapse, and HIV co-infection. In this review, we describe how metabolomics has contributed toward better explaining/elucidating the mechanisms of drug action/metabolism, drug toxicity and microbial drug resistance, and how metabolite biomarkers may serve as prognostic indicators for predicting treatment outcome as well as for the development of new TB drugs. We also discuss possible future contributions that metabolomics can make toward more efficient, less toxic TB treatment strategies.

Metabolomic biomarkers of pancreatic cancer: a meta-analysis study

Pancreatic cancer (PC) is an aggressive disease with high mortality rates, however, there is no blood test for early detection and diagnosis of this disease. Several research groups have reported on metabolomics based clinical investigations to identify biomarkers of PC, however there is a lack of a centralized metabolite biomarker repository that can be used for meta-analysis and biomarker validation. Furthermore, since the incidence of PC is associated with metabolic syndrome and Type 2 diabetes mellitus (T2DM), there is a need to uncouple these common metabolic dysregulations that may otherwise diminish the clinical utility of metabolomic biosignatures. Here, we attempted to externally replicate proposed metabolite biomarkers of PC reported by several other groups in an independent group of PC subjects. Our study design included a T2DM cohort that was used as a non-cancer control and a separate cohort diagnosed with colorectal cancer (CRC), as a cancer disease control to eliminate possible generic biomarkers of cancer. We used targeted mass spectrometry for quantitation of literature-curated metabolite markers and identified a biomarker panel that discriminates between normal controls (NC) and PC patients with high accuracy. Further evaluation of our model with CRC, however, showed a drop in specificity for the PC biomarker panel. Taken together, our study underscores the need for a more robust study design for cancer biomarker studies so as to maximize the translational value and clinical implementation.

The Pharmacogenomic and Metabolomic Predictors of ACE Inhibitor and Angiotensin II Receptor Blocker Effectiveness and Safety

Hypertension (HTN) is the most common chronic disease in the USA. Hypertensive patients frequently require repeat primary care visits to find an effective drug or drug combination to control their disease. Currently, patients are prescribed drugs for HTN based on race, age, and comorbidities and although the current guidelines are reasonable starting points for prescribing, 50% of hypertensive patients still fail to achieve target blood pressures. Despite numerous strategies to improve compliance, drug effectiveness, and optimization of initial drug choice, effectiveness has remained largely unchanged over the past two decades. Therefore, it is important to pursue alternative strategies to more effectively treat patients and to decrease medical costs. Additional precision medicine work is needed to identify factors associated with effectiveness of commonly used antihypertensive medications. The objective of this manuscript is to present a comprehensive review of the pharmacogenomic and metabolomic factors associated with ACEI and ARB effectiveness and safety.

Basic science and pathogenesis of ageing with HIV: potential mechanisms and biomarkers

: The increased prevalence of age-related comorbidities and mortality is worrisome in ageing HIV-infected patients. Here, we aim to analyse the different ageing mechanisms with regard to HIV infection. Ageing results from the time-dependent accumulation of random cellular damage. Epigenetic modifications and mitochondrial DNA haplogroups modulate ageing. In antiretroviral treatment-controlled patients, epigenetic clock appears to be advanced, and some haplogroups are associated with HIV infection severity. Telomere shortening is enhanced in HIV-infected patients because of HIV and some nucleoside analogue reverse transcriptase inhibitors. Mitochondria-related oxidative stress and mitochondrial DNA mutations are increased during ageing and also by some nucleoside analogue reverse transcriptase inhibitors. Overall, increased inflammation or 'inflammageing' is a major driver of ageing and could result from cell senescence with secreted proinflammatory mediators, altered gut microbiota, and coinfections. In HIV-infected patients, the level of inflammation and innate immunity activation is enhanced and related to most comorbidities and to mortality. This status could result, in addition to age, from the virus itself or viral protein released from reservoirs, from HIV-enhanced gut permeability and dysbiosis, from antiretroviral treatment, from frequent cytomegalovirus and hepatitis C virus coinfections, and also from personal and environmental factors, as central fat accumulation or smoking. Adaptive immune activation and immunosenescence are associated with comorbidities and mortality in the general population but are less predictive in HIV-infected patients. Biomarkers to evaluate ageing in HIV-infected patients are required. Numerous systemic or cellular inflammatory, immune activation, oxidative stress, or senescence markers can be tested in serum or peripheral blood mononuclear cells. The novel European Study to Establish Biomarkers of Human Ageing MARK-AGE algorithm, evaluating the biological age, is currently assessed in HIV-infected patients and reveals an advanced biological age. Some enhanced inflammatory or innate immune activation markers are interesting but still not validated for the patient's follow-up. To be able to assess patients' biological age is an important objective to improve their healthspan.

Metabolic Disorder in Chronic Obstructive Pulmonary Disease (COPD) Patients: Towards a Personalized Approach Using Marine Drug Derivatives

Metabolic disorder has been frequently observed in chronic obstructive pulmonary disease (COPD) patients. However, the exact correlation between obesity, which is a complex metabolic disorder, and COPD remains controversial. The current study summarizes a variety of drugs from marine sources that have anti-obesity effects and proposed potential mechanisms by which lung function can be modulated with the anti-obesity activity. Considering the similar mechanism, such as inflammation, shared between obesity and COPD, the study suggests that marine derivatives that act on the adipose tissues to reduce inflammation may provide beneficial therapeutic effects in COPD subjects with high body mass index (BMI).

Andrée Gruslin award lecture: Metabolomics as an important modality to better understand preeclampsia

Preeclampsia (PE) is a complex disorder that affects 3-5% of all pregnancies and is a leading cause of maternal and fetal morbidity and mortality. To date, the heterogeneity of clinical presentation, disease severity and outcomes have limited significant advances in early prediction, diagnosis, and therapeutic intervention of PE. The rapidly expanding field of metabolomics, which has the capacity to quantitatively detect low molecular weight compounds (metabolites) in tissue and biological fluids, shows tremendous promise in gaining a better understanding of PE. This review will discuss this emerging field and its contribution to recent advances in the understanding of PE pathophysiology, and identification of early predictive metabolic biomarkers for this complex disorder.

Urinary gas chromatography mass spectrometry metabolomics in asphyxiated newborns undergoing hypothermia: from the birth to the first month of life

BACKGROUND

Perinatal asphyxia is a severe clinical condition affecting around four million newborns worldwide. It consists of an impaired gas exchange leading to three biochemical components: hypoxemia, hypercapnia and metabolic acidosis.

METHODS

The aim of this longitudinal experimental study was to identify the urine metabolome of newborns with perinatal asphyxia and to follow changes in urine metabolic profile over time. Twelve babies with perinatal asphyxia were included in this study; three babies died on the eighth day of life. Total-body cooling for 72 hours was carried out in all the newborns. Urine samples were collected in each baby at birth, after 48 hours during hypothermia, after the end of the therapeutic treatment (72 hours), after 1 week of life, and finally after 1 month of life. Urine metabolome at birth was considered the reference against which to compare metabolic profiles in subsequent samples. Quantitative metabolic profiling in urine samples was measured by gas chromatography mass spectrometry (GC-MS). The statistical approach was conducted by using the multivariate analysis by means of principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA). Pathway analysis was also performed.

RESULTS

The most important metabolites depicting each time collection point were identified and compared each other. At birth before starting therapeutic hypothermia (TH), urine metabolic profiles of the three babies died after 7 days of life were closely comparable each other and significantly different from those in survivors.

CONCLUSIONS

In conclusion, a plethora of data have been extracted by comparing the urine metabolome at birth with those observed at each time point collection. The modifications over time in metabolites composition and concentration, mainly originated from the depletion of cellular energy and homeostasis, seems to constitute a fingerprint of perinatal asphyxia.

The metabolic role of the gut microbiota in health and rheumatic disease: mechanisms and interventions

The role of the gut microbiome in animal models of inflammatory and autoimmune disease is now well established. The human gut microbiome is currently being studied as a potential modulator of the immune response in rheumatic disorders. However, the vastness and complexity of this host-microorganism interaction is likely to go well beyond taxonomic, correlative observations. In fact, most advances in the field relate to the functional and metabolic capabilities of these microorganisms and their influence on mucosal immunity and systemic inflammation. An intricate relationship between the microbiome and the diet of the host is now fully recognized, with the microbiota having an important role in the degradation of polysaccharides into active metabolites. This Review summarizes the current knowledge on the metabolic role of the microbiota in health and rheumatic disease, including the advances in pharmacomicrobiomics and its potential use in diagnostics, therapeutics and personalized medicine.