Application of metabolomics approaches to the study of respiratory diseases

Multiscale metabolomics techniques: Insights into neuroscience research

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Metabolomic analysis of aqueous humor reveals potential metabolite biomarkers for differential detection of macular edema

BACKGROUND

Macular edema (ME) is a major complication of retinal disease with multiple mechanisms involved in its development. This study aimed to investigate the metabolite profile of aqueous humor (AH) in patients with ME of different etiologies and identify potential metabolite biomarkers for early diagnosis of ME.

METHODS

Samples of AH were collected from 60 patients with ME and 20 age- and sex-matched controls and analyzed by liquid chromatography-mass spectrometry (LC/MS)-based metabolomics. A series of univariate and multivariate statistical analyses were performed to identify differential metabolites and enriched metabolite pathways.

RESULTS

The metabolic profile of AH differed significantly between ME patients and healthy controls, and differentially expressed metabolites were identified. Pathway analysis revealed that these differentially expressed metabolites are mainly involved in lipid metabolism and amino acid metabolism. Moreover, significant differences were identified in the metabolic composition of AH from patients with ME due to different retinal diseases including age-related macular degeneration (AMD-ME), diabetic retinopathy (DME) and branch retinal vein occlusion (BRVO-ME). In total, 39 and 79 etiology-specific altered metabolites were identified for AMD-ME and DME, respectively. Finally, an AH-derived machine learning-based diagnostic model was developed and successfully validated in the test cohort with an area under the receiver operating characteristic (ROC) curve of 0.79 for AMD-ME, 0.94 for DME and 0.77 for BRVO-ME.

CONCLUSIONS

Our study illustrates the potential underlying metabolic basis of AH of different etiologies across ME populations. We also identify AH-derived metabolite biomarkers that may improve the differential diagnosis and treatment stratification of ME patients with different etiologies.

Effect of Acupuncture on Blood Pressure and Metabolic Profile Among Patients With Essential Hypertension: Protocol of a Randomized Clinical Trial

Essential hypertension is a polygenic cardiovascular disease that is associated with maladaptive metabolic changes. Acupuncture as a non-pharmacologic intervention is used to lower blood pressure and improve metabolic dysfunction. However, such effects have not been clinically characterized. We will conduct a randomized clinical trial to evaluate the antihypertensive effect of acupuncture among patients with essential hypertension and determine the associated metabolic improvements. This study is a phase II, two-arm, randomized, sham-controlled trial (Trial registration: ChiCTR2100043737), in which biospecimens will be collected for metabolic profiling. A total of 64 patients with a clinical diagnosis of essential hypertension will be randomly assigned to either the acupuncture or the sham acupuncture group in a 1:1 ratio. All participants will receive 10 treatments over 4 weeks, with three sessions per week for the first 2 weeks and two sessions per week for the remaining weeks. The primary outcome is the change of the systolic and diastolic blood pressure measured by the 24-h ambulatory blood pressure monitoring from baseline to 4 weeks. Secondary outcomes include the circadian rhythm of blood pressure, sleep quality measured by the Insomnia Severity Index, cognitive function measured by the Montreal Cognitive Assessment, and others. Fasting blood serum and urine samples will be collected at baseline and 4 weeks for targeted and untargeted metabolomics analysis. We will use the mixed-effects model and other related bioinformatics approaches to analyze the clinical and metabolome data. This metabolomic-based trial will provide important clinical data regarding the efficacy of acupuncture for essential hypertension to better inform evidence-based care delivery for hypertension patients. Moreover, the findings will offer important insights into the mechanism of action of acupuncture for hypertension by revealing its effect on metabolism. The results of this study will be used to inform the design of a statistically powered, multicenter, randomized trial. We will publish the study findings in peer-reviewed journals. The ethical approval of this study has been reviewed and approved by the Sichuan Regional Ethics Review Committee on Traditional Chinese Medicine (ID: 2021KL-006). The outcomes of the trial will be disseminated through peer-reviewed publications.

Role of Cellular Metabolism in the Formation of Neutrophil Extracellular Traps in Airway Diseases

Neutrophil extracellular traps (NETs) are a recently described mechanism of neutrophils that play an important role in health and disease. NETs are an innate defense mechanism that participate in clearance of pathogens, but they may also cause collateral damage in unrelated host tissues. Neutrophil dysregulation and NETosis occur in multiple lung diseases, such as pathogen-induced acute lung injury, pneumonia, chronic obstructive pulmonary disease (COPD), severe asthma, cystic fibrosis, and recently, the novel coronavirus SARS-CoV-2. More recently, research into immunometabolism has surged due to the possibility of reprogramming metabolism in order to modulate immune functions. The present review analyzes the different metabolic pathways associated with NETs formation, and how these impact on pathologies of the airways.

Disentangling Independent and Mediated Causal Relationships Between Blood Metabolites, Cognitive Factors, and Alzheimer's Disease

Background

Education and cognition demonstrate consistent inverse associations with Alzheimer's disease (AD). The biological underpinnings, however, remain unclear. Blood metabolites reflect the end point of biological processes and are accessible and malleable. Identifying metabolites with etiological relevance to AD and disentangling how these relate to cognitive factors along the AD causal pathway could, therefore, offer unique insights into underlying causal mechanisms.

Methods

Using data from the largest metabolomics genome-wide association study (N ≈ 24,925) and three independent AD cohorts (N = 4725), cross-trait polygenic scores were generated and meta-analyzed. Metabolites genetically associated with AD were taken forward for causal analyses. Bidirectional two-sample Mendelian randomization interrogated univariable causal relationships between 1) metabolites and AD; 2) education and cognition; 3) metabolites, education, and cognition; and 4) education, cognition, and AD. Mediating relationships were computed using multivariable Mendelian randomization.

Results

Thirty-four metabolites were genetically associated with AD at p < .05. Of these, glutamine and free cholesterol in extra-large high-density lipoproteins demonstrated a protective causal effect (glutamine: 95% confidence interval [CI], 0.70 to 0.92; free cholesterol in extra-large high-density lipoproteins: 95% CI, 0.75 to 0.92). An AD-protective effect was also observed for education (95% CI, 0.61 to 0.85) and cognition (95% CI, 0.60 to 0.89), with bidirectional mediation evident. Cognition as a mediator of the education-AD relationship was stronger than vice versa, however. No evidence of mediation via any metabolite was found.

Conclusions

Glutamine and free cholesterol in extra-large high-density lipoproteins show protective causal effects on AD. Education and cognition also demonstrate protection, though education's effect is almost entirely mediated by cognition. These insights provide key pieces of the AD causal puzzle, important for informing future multimodal work and progressing toward effective intervention strategies.

Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma

The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.

Biomarkers of Mycoplasma pneumoniae pneumonia in children by urine metabolomics based on Q Exactive liquid chromatography/tandem mass spectrometry

RATIONALE

Mycoplasma pneumoniae has become one of the common pathogens causing pediatric respiratory infections. In clinical diagnosis, throat swabs are very difficult to obtain from children, and there is a possibility of false positive results; hence, there are few clinically available diagnostic methods.

METHODS

In this study, Q Exactive liquid chromatography/tandem mass spectrometry was used to analyze the metabolites in the urine of healthy children (HC) and M. pneumoniae pneumonia in children (MPPC) patients. A multivariate statistical analysis was performed to screen the differential metabolites. Based on the HMDB and KEGG, the possible metabolic pathways subject to biological alteration were identified.

RESULTS

Compared with HC, 73 different metabolites in MPPC patients disrupted nine metabolic pathways through different change trends; after integrating various parameters, 20 significantly different metabolites were identified as MPPC potential biomarkers. Through the above two analysis modes, acetylphosphate and 2,5-dioxopentanoate were both screened out and used as potential biomarkers for the early diagnosis of MPPC for the first time.

CONCLUSIONS

The characterization of 20 potential biomarkers provides a scientific basis for predicting and diagnosing MPPC. This article further indicates that urine metabolic profiling has great potential in diagnosing MPPC and can effectively prevent the disease from causing further deterioration.

The Application of Metabolomics in Forensic Science with Focus on Forensic Toxicology and Time-of-Death Estimation

Recently, the diagnostic methods used by scientists in forensic examinations have enormously expanded. Metabolomics provides an important contribution to analytical method development. The main purpose of this review was to investigate and summarize the most recent applications of metabolomics in forensic science. The primary research method was an extensive review of available international literature in PubMed. The keywords “forensic” and “metabolomics” were used as search criteria for the PubMed database scan. Most authors emphasized the analysis of different biological sample types using chromatography methods. The presented review is a summary of recently published implementations of metabolomics in forensic science and types of biological material used and techniques applied. Possible opportunities for valuable metabolomics’ applications are discussed to emphasize the essential necessities resulting in numerous nontargeted metabolomics’ assays.

Metabolomic diferences between COVID-19 and H1N1 influenza induced ARDS

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a type of respiratory failure characterized by lung inflammation and pulmonary edema. Coronavirus disease 2019 (COVID-19) is associated with ARDS in the more severe cases. This study aimed to compare the specificity of the metabolic alterations induced by COVID-19 or Influenza A pneumonia (IAP) in ARDS.

METHODS

Eighteen patients with ARDS due to COVID-19 and twenty patients with ARDS due to IAP, admitted to the intensive care unit. ARDS was defined as in the American-European Consensus Conference. As compared with patients with COVID-19, patients with IAP were younger and received more often noradrenaline to maintain a mean arterial pressure > 65 mm Hg. Serum samples were analyzed by Nuclear Magnetic Resonance Spectroscopy. Multivariate Statistical Analyses were used to identify metabolic differences between groups. Metabolic pathway analysis was performed to identify the most relevant pathways involved in ARDS development.

RESULTS

ARDS due to COVID-19 or to IAP induces a different regulation of amino acids metabolism, lipid metabolism, glycolysis, and anaplerotic metabolism. COVID-19 causes a significant energy supply deficit that induces supplementary energy-generating pathways. In contrast, IAP patients suffer more marked inflammatory and oxidative stress responses. The classificatory model discriminated against the cause of pneumonia with a success rate of 100%.

CONCLUSIONS

Our findings support the concept that ARDS is associated with a characteristic metabolomic profile that may discriminate patients with ARDS of different etiologies, being a potential biomarker for the diagnosis, prognosis, and management of this condition.

Benchtop nuclear magnetic resonance-based metabolomic approach for the diagnosis of bovine tuberculosis

Even though enormous efforts and control strategies have been implemented, bovine tuberculosis (TB) remains a significant source of health and socioeconomic concern. The standard method used in TB eradication programs for in vivo detection is the tuberculin skin test. However, the specificity of the tuberculin skin test is affected by infection with non-tuberculous mycobacteria or by vaccination. Thus, some animals are not correctly diagnosed. This study aimed first to identify a plasma metabolic TB profile by high-field (HF) nuclear magnetic resonance (NMR) spectroscopy and second measure this characteristic TB metabolic profile using low-field benchtop (LF) NMR as an affordable molecular technology for TB diagnosis. Plasma samples from cattle diagnosed with TB (derivation set, n = 11), diagnosed with paratuberculosis (PTB, n = 10), PTB-vaccinated healthy control (n = 10) and healthy PTB-unvaccinated control (n = 10) were analyzed by NMR. Unsupervised Principal Component Analysis (PCA) was used to identify metabolic differences between groups. We identified 14 metabolites significantly different between TB and control animals. The second group of TB animals was used to validate the results (validation set, n = 14). Predictive models based on metabolic fingerprint acquired by both HF and LF NMR spectroscopy successfully identified TB versus control subjects (Area under the curve of Receiver Operating Characteristic over 0.92, in both models; Confidence Interval 0.77-1). In summary, plasma fingerprinting using HF and LF-NMR differentiated TB subjects from uninfected animals, and PTB and PTB-vaccinated subjects who may provide a TB-false positive, highlighting the use of LF-NMR-based metabolomics as a complementary or alternative diagnostic tool to the current diagnostic methods.

Breath Biomarkers in Diagnostic Applications

The detection of chemical compounds in exhaled human breath presents an opportunity to determine physiological state, diagnose disease or assess environmental exposure. Recent advancements in metabolomics research have led to improved capabilities to explore human metabolic profiles in breath. Despite some notable challenges in sampling and analysis, exhaled breath represents a desirable medium for metabolomics applications, foremost due to its non-invasive, convenient and practically limitless availability. Several breath-based tests that target either endogenous or exogenous gas-phase compounds are currently established and are in practical and/or clinical use. This review outlines the concept of breath analysis in the context of these unique tests and their applications. The respective breath biomarkers targeted in each test are discussed in relation to their physiological production in the human body and the development and implementation of the associated tests. The paper concludes with a brief insight into prospective tests and an outlook of the future direction of breath research.

Multi-Omics study on biomarker and pathway discovery of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a common heterogeneous respiratory disease characterized by persistent and incompletely reversible airflow limitation. Due to the heterogeneity and phenotypes complexity of COPD, traditionally diagnostic methods can only give limited information on predicted results and treatment, which are not sufficient for accurate diagnosis and evaluation. With the development of omics technologies in recent years, genomics, proteomics, and metabolomics are widely used in the study of COPD, providing good tools for discovering biomarkers to diagnose and elucidate the complex mechanism of COPD. In this review, we summarized the biomarkers of COPD based on metabolomic, proteomic and transcriptomic studies that have been reported in recent years. Furthermore, protein-protein interactions and multi-omics integrated analysis were carried out to explore the important metabolites and proteins that involved in significant pathways in the progression of COPD for explanation the pathogenesis of COPD. Finally, the prospective and challenges in the study of COPD were proposed. It is expected that this review will provide some references for the development of diagnostic methods and elucidation of the pathogenesis of COPD.

Metabolomics in asthma: A platform for discovery

Asthma, characterized by airway hyperresponsiveness, inflammation and remodeling, is a chronic airway disease with complex etiology. Severe asthma is characterized by frequent exacerbations and poor therapeutic response to conventional asthma therapy. A clear understanding of cellular and molecular mechanisms of asthma is critical for the discovery of novel targets for optimal therapeutic control of asthma. Metabolomics is emerging as a powerful tool to elucidate novel disease mechanisms in a variety of diseases. In this review, we summarize the current status of knowledge in asthma metabolomics at systemic and cellular levels. The findings demonstrate that various metabolic pathways, related to energy metabolism, macromolecular biosynthesis and redox signaling, are differentially modulated in asthma. Airway smooth muscle cell plays pivotal roles in asthma by contributing to airway hyperreactivity, inflammatory mediator release and remodeling. We posit that metabolomic profiling of airway structural cells, including airway smooth muscle cells, will shed light on molecular mechanisms of asthma and airway hyperresponsiveness and help identify novel therapeutic targets.

Potential Metabolic Biomarkers in Adult Asthmatics

Asthma is the most common chronic airway inflammation, with multiple phenotypes caused by complicated interactions of genetic, epigenetic, and environmental factors. To date, various determinants have been suggested for asthma pathogenesis by a new technology termed omics, including genomics, transcriptomics, proteomics, and metabolomics. In particular, the systematic analysis of all metabolites in a biological system, such as carbohydrates, amino acids, and lipids, has helped identify a novel pathway related to complex diseases. These metabolites are involved in the regulation of hypermethylation, response to hypoxia, and immune reactions in the pathogenesis of asthma. Among them, lipid metabolism has been suggested to be related to lung dysfunction in mild-to-moderate asthma. Sphingolipid metabolites are an important mediator contributing to airway inflammation in obese asthma and aspirin-exacerbated respiratory disease. Although how these molecular variants impact the disease has not been completely determined, identification of new causative factors may possibly lead to more-personalized and precise pathway-specific approaches for better diagnosis and treatment of asthma. In this review, perspectives of metabolites related to asthma and clinical implications have been highlighted according to various phenotypes.

STRATEGIES AND CHALLENGES IN METHOD DEVELOPMENT AND VALIDATION FOR THE ABSOLUTE QUANTIFICATION OF ENDOGENOUS BIOMARKER METABOLITES USING LIQUID CHROMATOGRAPHY-TANDEM MASS SPECTROMETRY

Metabolomics is a dynamically evolving field, with a major application in identifying biomarkers for drug development and personalized medicine. Numerous metabolomic studies have identified endogenous metabolites that, in principle, are eligible for translation to clinical practice. However, few metabolomic-derived biomarker candidates have been qualified by regulatory bodies for clinical applications. Such interruption in the biomarker qualification process can be largely attributed to various reasons including inappropriate study design and inadequate data to support the clinical utility of the biomarkers. In addition, the lack of robust assays for the routine quantification of candidate biomarkers has been suggested as a potential bottleneck in the biomarker qualification process. In fact, the nature of the endogenous metabolites precludes the application of the current validation guidelines for bioanalytical methods. As a result, there have been individual efforts in modifying existing guidelines and/or developing alternative approaches to facilitate method validation. In this review, three main challenges for method development and validation for endogenous metabolites are discussed, namely matrix effects evaluation, alternative analyte-free matrices, and the choice of internal standards (ISs). Some studies have modified the equations described by the European Medicines Agency for the evaluation of matrix effects. However, alternative strategies were also described; for instance, calibration curves can be generated in solvents and in biological samples and the slopes can be compared through ratios, relative standard deviation, or a modified Stufour suggested approaches while quantifying mainly endogenous metabolitesdent t-test. ISs, on the contrary, are diverse; in which seven different possible types, used in metabolomics-based studies, were identified in the literature. Each type has its advantages and limitations; however, isotope-labeled ISs and ISs created through isotope derivatization show superior performance. Finally, alternative matrices have been described and tested during method development and validation for the quantification of endogenous entities. These alternatives are discussed in detail, highlighting their advantages and shortcomings. The goal of this review is to compare, apprise, and debate current knowledge and practices in order to aid researchers and clinical scientists in developing robust assays needed during the qualification process of candidate metabolite biomarkers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Metabolomic fingerprinting and systemic inflammatory profiling of asthma COPD overlap (ACO)

Background

Asthma-COPD overlap (ACO) refers to a group of poorly studied and characterised patients reporting with disease presentations of both asthma and COPD, thereby making both diagnosis and treatment challenging for the clinicians. They exhibit a higher burden in terms of both mortality and morbidity in comparison to patients with only asthma or COPD. The pathophysiology of the disease and its existence as a unique disease entity remains unclear. The present study aims to determine whether ACO has a distinct metabolic and immunological mediator profile in comparison to asthma and COPD.

Methods

Global metabolomic profiling using two different groups of patients [discovery (D) and validation (V)] were conducted. Serum samples obtained from moderate and severe asthma [n = 34(D); n = 32(V)], moderate and severe COPD [n = 30(D); 32(V)], ACO patients [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using gas chromatography mass spectrometry (GC-MS). Multiplexed analysis of 25 immunological markers (IFN-γ (interferon gamma), TNF-α (tumor necrosis factor alpha), IL-12p70 (interleukin 12p70), IL-2, IL-4, IL-5, IL-13, IL-10, IL-1α, IL-1β, TGF-β (transforming growth factor), IL-6, IL-17E, IL-21, IL-23, eotaxin, GM-CSF (granulocyte macrophage-colony stimulating factor), IFN-α (interferon alpha), IL-18, NGAL (neutrophil gelatinase-associated lipocalin), periostin, TSLP (thymic stromal lymphopoietin), MCP-1 (monocyte chemoattractant protein- 1), YKL-40 (chitinase 3 like 1) and IL-8) was also performed in the discovery cohort.

Results

Eleven metabolites [serine, threonine, ethanolamine, glucose, cholesterol, 2-palmitoylglycerol, stearic acid, lactic acid, linoleic acid, D-mannose and succinic acid] were found to be significantly altered in ACO as compared with asthma and COPD. The levels and expression trends were successfully validated in a fresh cohort of subjects. Thirteen immunological mediators including TNFα, IL-1β, IL-17E, GM-CSF, IL-18, NGAL, IL-5, IL-10, MCP-1, YKL-40, IFN-γ, IL-6 and TGF-β showed distinct expression patterns in ACO. These markers and metabolites exhibited significant correlation with each other and also with lung function parameters.

Conclusions

The energy metabolites, cholesterol and fatty acids correlated significantly with the immunological mediators, suggesting existence of a possible link between the inflammatory status of these patients and impaired metabolism. The present findings could be possibly extended to better define the ACO diagnostic criteria, management and tailoring therapies exclusively for the disease.

Advances and challenges in pursuing biomarkers for obstructive sleep apnea: Implications for the cardiovascular risk

Obstructive sleep apnea (OSA) is a common clinical condition associated with increased cardiovascular morbidity and mortality. Recent evidence from clinical studies and animal models suggest that OSA can promote cardiovascular disease by inducing autonomic, hemodynamic, inflammatory and metabolic dysregulation. However, most of the evidence addressing hard endpoints in humans is derived from observational studies. Several challenges have been noted in the pursuit of a comprehensive knowledge base about the impact of OSA including: 1) the precise mechanisms by which OSA causes metabolic and cardiovascular consequences are not clear, which limits our current ability to address potential targets in OSA; 2) several patients with OSA, even with severe forms, present with no or mild daytime symptoms. Beyond the obvious challenges for obtaining good adherence for conventional OSA treatments, there is evidence that symptomatic vs. asymptomatic patients with OSA do not necessarily have the same metabolic and cardiovascular outcomes; and 3) the cardiovascular response to OSA treatment may vary even in those patients with good adherence. In this scenario, there is an obvious need to develop biomarkers in the OSA research area. This review focuses on describing the advances that have occurred so far in exploring potential OSA biomarkers with clear emphasis for the cardiovascular risk. Particular attention will be devoted to discuss molecular biomarkers including the potential role of microRNAs, proteomics and metabolomics. We also discuss the major challenges and perspectives in this growing research field.

An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders

Cerebrospinal fluid analyses and neuroimaging can identify the underlying pathophysiology at the earliest stage of some neurodegenerative disorders, but do not have the scalability needed for population screening. Therefore, a blood-based marker for such pathophysiology would have greater utility in a primary care setting and in eligibility screening for clinical trials. Rapid advances in ultra-sensitive assays have enabled the levels of pathological proteins to be measured in blood samples, but research has been predominantly focused on Alzheimer disease (AD). Nonetheless, proteins that were identified as potential blood-based biomarkers for AD, for example, amyloid-β, tau, phosphorylated tau and neurofilament light chain, are likely to be relevant to other neurodegenerative disorders that involve similar pathological processes and could also be useful for the differential diagnosis of clinical symptoms. This Review outlines the neuropathological, clinical, molecular imaging and cerebrospinal fluid features of the most common neurodegenerative disorders outside the AD continuum and gives an overview of the current status of blood-based biomarkers for these disorders.

An NMR based panorama of the heterogeneous biology of acute respiratory distress syndrome (ARDS) from the standpoint of metabolic biomarkers

Acute respiratory distress syndrome (ARDS), manifested by intricate etiology and pathophysiology, demands careful clinical surveillance due to its high mortality and imminent life support measures. NMR based metabolomics provides an approach for ARDS which culminates from a wide spectrum of illness thereby confounding early manifestation and prognosis predictors. ¹ H NMR with its manifold applications in critical disease settings can unravel the biomarker of ARDS thus holding potent implications by providing surrogate endpoints of clinical utility. NMR metabolomics which is the current apogee platform of omics trilogy is contributing towards the possible panacea of ARDS by subsequent validation of biomarker credential on larger datasets. In the present review, the physiological derangements that jeopardize the whole metabolic functioning in ARDS are exploited and the biomarkers involved in progression are addressed and substantiated. The following sections of the review also outline the clinical spectrum of ARDS from the standpoint of NMR based metabolomics which is an emerging element of systems biology. ARDS is the main premise of intensivists textbook, which has been thoroughly reviewed along with its incidence, progressive stages of severity, new proposed diagnostic definition, and the preventive measures and the current pitfalls of clinical management. The advent of new therapies, the need for biomarkers, the methodology and the contemporary promising approaches needed to improve survival and address heterogeneity have also been evaluated. The review has been stepwise illustrated with potent biometrics employed to selectively pool out differential metabolites as diagnostic markers and outcome predictors. The following sections have been drafted with an objective to better understand ARDS mechanisms with predictive and precise biomarkers detected so far on the basis of underlying physiological parameters having close proximity to diseased phenotype. The aim of this review is to stimulate interest in conducting more studies to help resolve the complex heterogeneity of ARDS with biomarkers of clinical utility and relevance.

Amino Acid-Based Metabolic Indexes Identify Patients With Chronic Obstructive Pulmonary Disease And Further Discriminates Patients In Advanced BODE Stages

Background

The BODE index is a multidimensional grading system for predicting the prognoses of patients with chronic obstructive pulmonary disease (COPD). This study investigated whether an amino acids-based metabolic profile developed for heart failure patients (including histidine, ornithine, phenylalanine, and leucine) could identify COPD patients and further discriminates COPD patients in advanced BODE stages.

Methods

Ultra-performance liquid chromatography was performed on 119 participants, including 75 COPD patients at different BODE stages and 44 normal controls. Albumin, pre-albumin, transferrin, high sensitivity C-reactive protein, and hand grip strength were also measured. Receiver operating characteristic curves and area under curves were used for estimation.

Results

The BODE points in our patients were 3.29 [95% confidence interval (CI) = 2.74-3.85]. Compared to normal controls, COPD patients had lower leucine but higher ornithine levels. A COPD score, developed based on leucine and ornithine, significantly discriminated COPD from normal controls [odds ratio (OR) = 2.71, 95% CI = 1.83-4.04, p <0.001]. A COPD score of ≥ 3.00 had an OR of 15.58 (95% CI = 5.96-40.73, p <0.001). In COPD patients from BODE 1 to BODE 4, the levels of histidine, ornithine and phenylalanine increased significantly. In multivariable analysis, histidine and phenylalanine were independently able to distinguish BODE stages 3 and 4 from BODE 1 and were adopted to develop a metabolic score. Metabolic scores identified patients at BODE 3 and 4 (OR = 2.74, 95% CI =1.41-5.29, p = 0.003) better than hand grip strength, high sensitive C-reactive protein, albumin, pre-albumin, and transferrin value. A metabolic score of ≥9.53 significantly discriminated BODE 3 and 4 from BODE 1 and 2 (OR = 8.56, 95% CI = 2.77-26.39, p <0.001).

Conclusion

Amino acid-based COPD score and metabolic score discriminate COPD patients from normal controls, and identify patients in advanced stages of COPD.

Untargeted metabolomics analysis of the upper respiratory tract of ferrets following influenza A virus infection and oseltamivir treatment

INTRODUCTION

Influenza is a highly contagious respiratory disease that causes high global morbidity and mortality each year. The dynamics of an influenza infection on the host metabolism, and how metabolism is altered in response to neuraminidase inhibitor drug therapy, is still in its infancy but of great importance.

OBJECTIVES

We aim to investigate the suitability of ferret nasal wash samples for metabolomics-based analysis and characterization of influenza infections and oseltamivir treatment.

METHODS

Virological and metabolic analyses were performed on nasal wash samples collected from ferrets treated with oseltamivir or a placebo. Untargeted metabolomics was performed using a gas chromatography coupled with mass spectrometery (GC-MS) based protocol that comprised a retention time (RT) locked method and the use of a commercial metabolomics library.

RESULTS

Ferret activity was reduced at 2-3 days post infection, which coincided with the highest influenza viral titre. The metabolomics data indicated a shift in metabolism during various stages of infection. The neuraminidase inhibitor oseltamivir created considerable downregulation of energy center metabolites (glucose, sucrose, glycine and glutamine), which generated high levels of branched amino acids. This further increased branched amino acid degradation and deregulation via glycerate-type intermediates and biosynthesis of fatty acids in oseltamivir-treated animals where abrogated weight loss was observed.

CONCLUSION

Metabolomics was used to profile influenza infection and antiviral drug treatment in ferrets. This has the potential to provide indicators for the early diagnosis of influenza infection and assess the effectiveness of drug therapies.

Application of Metabolomics in Lung Research

Advancements in omics technologies have increased our potential to evaluate molecular changes in a rapid and comprehensive manner. This is especially true in mass spectrometry-based metabolomics where improvements, including ease of use, in high-performance liquid chromatography (HPLC), column chemistries, instruments, software, and molecular databases, have advanced the field considerably. Applications of this relatively new omics technology in clinical research include discovering disease biomarkers, finding new drug targets, and elucidating disease mechanisms. Here we describe a typical clinical metabolomics workflow, which includes the following steps: (1) extraction of metabolites from the lung, plasma, bronchoalveolar lavage, or cells; (2) sample analysis via liquid chromatography-mass spectrometry; and (3) data analysis using commercial and freely available software packages. Overall, the methods delineated here can help investigators use metabolomics to discovery novel biomarkers and to understand lung diseases.

Allergic asthma: an overview of metabolomic strategies leading to the identification of biomarkers in the field

Allergic asthma is a prominent disease especially during childhood. Indoor allergens, in general, and particularly house dust mites (HDM) are the most prevalent sensitizers associated with allergic asthma. Available data show that 65-130 million people are mite-sensitized world-wide and as many as 50% of these are asthmatic. In fact, sensitization to HDM in the first years of life can produce devastating effects on pulmonary function leading to asthmatic syndromes that can be fatal. To date, there has been considerable research into the pathological pathways and structural changes associated with allergic asthma. However, limitations related to the disease heterogeneity and a lack of knowledge into its pathophysiology have impeded the generation of valuable data needed to appropriately phenotype patients and, subsequently, treat this disease. Here, we report a systematic and integral analysis of the disease, from airway remodelling to the immune response taking place throughout the disease stages. We present an overview of metabolomics, the management of complex multifactorial diseases through the analysis of all possible metabolites in a biological sample, obtaining a global interpretation of biological systems. Special interest is placed on the challenges to obtain biological samples and the methodological aspects to acquire relevant information, focusing on the identification of novel biomarkers associated with specific phenotypes of allergic asthma. We also present an overview of the metabolites cited in the literature, which have been related to inflammation and immune response in asthma and other allergy-related diseases.

Metabolic changes of different high-resolution computed tomography phenotypes of COPD after budesonide-formoterol treatment

BACKGROUND

Metabolomics is the global unbiased analysis of all the small-molecule metabolites within a biological system. Metabolic profiling of different high-resolution computed tomography (HRCT) phenotypes of COPD patients before and after treatment may identify discriminatory metabolites that can serve as biomarkers and therapeutic agents.

PATIENTS AND METHODS

1H nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomics was performed on a discovery set of plasma samples from 50 patients with stable COPD. Patients were assigned into two groups on the basis of HRCT findings including phenotype E (n=22) and phenotype M (n=28). After budesonide-formoterol treatment (160/4.5 µg ×2 inhalations twice daily for 3 months), clinical characteristics and metabolites were then compared between phenotype E pretreatment and posttreatment, phenotype M pretreatment and posttreatment, phenotype E pretreatment and phenotype M pretreatment, and phenotype E posttreatment and phenotype M posttreatment.

RESULTS

Inhaled budesonide-formoterol therapy for both phenotype E (emphysema without bronchial wall thickening) and phenotype M (emphysema with bronchial wall thickening) was effective. However, phenotype E and phenotype M were different in response to therapy. Patients with phenotype M in response to therapeutic effects were significantly greater compared with phenotype E. Certain metabolites were identified, which were closely related to the treatment and phenotype. Metabolic changes in phenotype E or phenotype M after treatment may be involved with adenosine diphosphate (ADP), guanosine, choline, malonate, tyrosine, glycine, proline, l-alanine, l-valine, l-threonine leucine, uridine, pyruvic acid, acetone and metabolism disturbance. Metabolic differences between phenotype E and phenotype M in pretreatment and posttreatment covered glycine, d-glucose, pyruvic acid, succinate, lactate, proline, l-valine and leucine.

CONCLUSION

Bronchial wall thickening in COPD may be an indicator for predicting the better response to the treatment with bronchodilator and corticosteroid. The identification of metabolic alterations provides new insights into different HRCT phenotypes and therapeutic assessment of COPD.

New Strategies and Challenges in Lung Proteomics and Metabolomics. An Official American Thoracic Society Workshop Report

This document presents the proceedings from the workshop entitled, "New Strategies and Challenges in Lung Proteomics and Metabolomics" held February 4th-5th, 2016, in Denver, Colorado. It was sponsored by the National Heart Lung Blood Institute, the American Thoracic Society, the Colorado Biological Mass Spectrometry Society, and National Jewish Health. The goal of this workshop was to convene, for the first time, relevant experts in lung proteomics and metabolomics to discuss and overcome specific challenges in these fields that are unique to the lung. The main objectives of this workshop were to identify, review, and/or understand: (1) emerging technologies in metabolomics and proteomics as applied to the study of the lung; (2) the unique composition and challenges of lung-specific biological specimens for metabolomic and proteomic analysis; (3) the diverse informatics approaches and databases unique to metabolomics and proteomics, with special emphasis on the lung; (4) integrative platforms across genetic and genomic databases that can be applied to lung-related metabolomic and proteomic studies; and (5) the clinical applications of proteomics and metabolomics. The major findings and conclusions of this workshop are summarized at the end of the report, and outline the progress and challenges that face these rapidly advancing fields.

Development of a validated LC- MS/MS method for the quantification of 19 endogenous asthma/COPD potential urinary biomarkers

Obstructive airways inflammatory diseases sometimes show overlapping symptoms that hinder their early and correct diagnosis. Current clinical tests are tedious and are of inadequate specificity in special population such as the elderly and children. Therefore, we are developing tandem mass spectrometric (MS/MS) methods for targeted analysis of urine biomarkers. Recently, proton-nuclear magnetic resonance (¹H-NMR) analysis proposed 50 urinary metabolites as potential diagnostic biomarkers among asthma and chronic obstructive pulmonary disease (COPD) patients. Metabolites are divided into 3 groups based on chemical nature. For group 1 (amines and phenols, 19 urinary metabolites), we developed and validated a high performance liquid chromatographic (HPLC)-MS/MS method using differential isotope labeling (DIL) with dansyl chloride. Method development included the optimization of the derivatization reaction, the MS/MS conditions, and the chromatographic separation. Linearity varied from 2 to 4800 ng/mL and the use of ¹³C₂-labeled derivatives allowed for the correction of matrix effects as well as the unambiguous confirmation of the identity of each metabolite in the presence of interfering isomers in urine. Despite the challenges associated with method validation, the method was fully validated as per the food and drug administration (FDA) and the European medicines agency (EMA) recommendations. Validation criteria included linearity, precision, accuracy, dilution integrity, selectivity, carryover, and stability. Challenges in selectivity experiments included the isotopic contributions of the analyte towards its internal standard (IS), that was addressed via the optimization of the IS concentration. In addition, incurred sample analysis was performed to ensure that results from patient samples are accurate and reliable. The method was robust and reproducible and is currently being applied in a cohort of asthma and COPD patient urine samples for biomarker discovery purposes.

Comparison of Ambient and Atmospheric Pressure Ion Sources for Cystic Fibrosis Exhaled Breath Condensate Ion Mobility-Mass Spectrometry Metabolomics

Cystic fibrosis (CF) is an autosomal recessive disorder caused by mutations in the gene that encodes the cystic fibrosis transmembrane conductance regulator (CFTR) protein. The vast majority of the mortality is due to progressive lung disease. Targeted and untargeted CF breath metabolomics investigations via exhaled breath condensate (EBC) analyses have the potential to expose metabolic alterations associated with CF pathology and aid in assessing the effectiveness of CF therapies. Here, transmission-mode direct analysis in real time traveling wave ion mobility spectrometry time-of-flight mass spectrometry (TM-DART-TWIMS-TOF MS) was tested as a high-throughput alternative to conventional direct infusion (DI) electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) methods, and a critical comparison of the three ionization methods was conducted. EBC was chosen as the noninvasive surrogate for airway sampling over expectorated sputum as EBC can be collected in all CF subjects regardless of age and lung disease severity. When using pooled EBC collected from a healthy control, ESI detected the most metabolites, APCI a log order less, and TM-DART the least. TM-DART-TWIMS-TOF MS was used to profile metabolites in EBC samples from five healthy controls and four CF patients, finding that a panel of three discriminant EBC metabolites, some of which had been previously detected by other methods, differentiated these two classes with excellent cross-validated accuracy. Graphical Abstract ᅟ.

The past decade in bench research into pulmonary infectious diseases: What do clinicians need to know?

Respiratory infections are primarily treated with antibiotics, drugs that are mostly inexpensive and have been widely available since the 1940s and 1950s. Nevertheless, despite antibiotics, the burden of disease in pneumonia, bronchiectasis, cystic fibrosis, COPD and rare respiratory infections remains exceptionally high. There is an urgent need for translational studies to develop new treatments or new biomarkers to improve outcomes in these conditions. The 'translational gaps' between bench science and clinical practice are particularly challenging in respiratory infections. This is partly due to the poor representativeness of animal models of infection to human disease, and a long-term lack of investment into pulmonary infection research. The revolution in genomics and other omics technologies, however, is beginning to unlock clinically important information about the host response to infection, the behaviour of bacterial communities and the development of new antibiotics. It is not possible to review the extensive progress made in the last decade into the pathophysiology of the different respiratory infections and so here, we focus on major technologies that are now changing respiratory infection research, specifically bacterial whole-genome sequencing, the microbiota, personalized medicine with omics technologies, new antibiotic development and host inflammatory cell biology.

Association between fatty acid metabolism in the brain and Alzheimer disease neuropathology and cognitive performance: A nontargeted metabolomic study

BACKGROUND

The metabolic basis of Alzheimer disease (AD) pathology and expression of AD symptoms is poorly understood. Omega-3 and -6 fatty acids have previously been linked to both protective and pathogenic effects in AD. However, to date little is known about how the abundance of these species is affected by differing levels of disease pathology in the brain.

METHODS AND FINDINGS

We performed metabolic profiling on brain tissue samples from 43 individuals ranging in age from 57 to 95 y old who were stratified into three groups: AD (N = 14), controls (N = 14) and "asymptomatic Alzheimer's disease" (ASYMAD), i.e., individuals with significant AD neuropathology at death but without evidence for cognitive impairment during life (N = 15) from the autopsy sample of the Baltimore Longitudinal Study of Aging (BLSA). We measured 4,897 metabolite features in regions both vulnerable in the middle frontal and inferior temporal gyri (MFG and ITG) and resistant (cerebellum) to classical AD pathology. The levels of six unsaturated fatty acids (UFAs) in whole brain were compared in controls versus AD, and the differences were as follows: linoleic acid (p = 8.8 x 10-8, FC = 0.52, q = 1.03 x 10-6), linolenic acid (p = 2.5 x 10-4, FC = 0.84, q = 4.03 x 10-4), docosahexaenoic acid (p = 1.7 x 10-7, FC = 1.45, q = 1.24 x 10-6), eicosapentaenoic acid (p = 4.4 x 10-4, FC = 0.16, q = 6.48 x 10-4), oleic acid (p = 3.3 x 10-7, FC = 0.34, q = 1.46 x 10-6), and arachidonic acid (p = 2.98 x 10-5, FC = 0.75, q = 7.95 x 10-5). These fatty acids were strongly associated with AD when comparing the groups in the MFG and ITG, respectively: linoleic acid (p < 0.0001, p = 0.0006), linolenic acid (p < 0.0001, p = 0.002), docosahexaenoic acid (p < 0.0001, p = 0.0024), eicosapentaenoic acid (p = 0.0002, p = 0.0008), oleic acid (p < 0.0001, p = 0.0003), and arachidonic acid (p = 0.0001, p = 0.001). Significant associations were also observed between the abundance of these UFAs with neuritic plaque and neurofibrillary tangle burden as well as domain-specific cognitive performance assessed during life. Based on the regional pattern of differences in brain tissue levels of these metabolites, we propose that alterations in UFA metabolism represent both global metabolic perturbations in AD as well as those related to specific features of AD pathology. Within the middle frontal gyrus, decrements in linoleic acid, linolenic acid, and arachidonic acid (control>ASYMAD>AD) and increases in docosahexanoic acid (AD>ASYMAD>control) may represent regionally specific threshold levels of these metabolites beyond which the accumulation of AD pathology triggers the expression of clinical symptoms. The main limitation of this study is the relatively small sample size. There are few cohorts with extensive longitudinal cognitive assessments during life and detailed neuropathological assessments at death, such as the BLSA.

CONCLUSIONS

The findings of this study suggest that unsaturated fatty acid metabolism is significantly dysregulated in the brains of patients with varying degrees of Alzheimer pathology.

Visualization, Quantification, and Alignment of Spectral Drift in Population Scale Untargeted Metabolomics Data

Untargeted liquid-chromatography-mass spectrometry (LC-MS)-based metabolomics analysis of human biospecimens has become among the most promising strategies for probing the underpinnings of human health and disease. Analysis of spectral data across population scale cohorts, however, is precluded by day-to-day nonlinear signal drifts in LC retention time or batch effects that complicate comparison of thousands of untargeted peaks. To date, there exists no efficient means of visualization and quantitative assessment of signal drift, correction of drift when present, and automated filtering of unstable spectral features, particularly across thousands of data files in population scale experiments. Herein, we report the development of a set of R-based scripts that allow for pre- and postprocessing of raw LC-MS data. These methods can be integrated with existing data analysis workflows by providing initial preprocessing bulk nonlinear retention time correction at the raw data level. Further, this approach provides postprocessing visualization and quantification of peak alignment accuracy, as well as peak-reliability-based parsing of processed data through hierarchical clustering of signal profiles. In a metabolomics data set derived from ∼3000 human plasma samples, we find that application of our alignment tools resulted in substantial improvement in peak alignment accuracy, automated data filtering, and ultimately statistical power for detection of metabolite correlates of clinical measures. These tools will enable metabolomics studies of population scale cohorts.

Metabolomics combined with pattern recognition and bioinformatics analysis methods for the development of pharmacodynamic biomarkers on liver fibrosis

Metabolomics combined with pattern recognition and network analysis maybe an attractive strategy for the pharmacodynamics biomarkers development on liver fibrosis.

A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research

The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions.

Metabolic Modifications in Human Biofluids Suggest the Involvement of Sphingolipid, Antioxidant, and Glutamate Metabolism in Alzheimer's Disease Pathogenesis

Alzheimer's disease (AD) is the most common neurodegenerative dementia, with the accumulation of extracellular amyloid-β and formation of neurofibrillary tau tangles as leading explanations of pathology. With the difficulties of studying the brain directly, it is hoped that identifying the effect of AD on the metabolite composition of biofluids will provide insights into underlying mechanisms of pathology. The present review identified 705 distinct metabolite reports representing 448 structurally distinct metabolites in six human biofluids, with 147 metabolites increased and 214 metabolites decreased with AD, while 80 metabolites showed inconsistent shifts. Sphingolipid, antioxidant, and glutamate metabolism were found to be strongly associated with AD and were selected for detailed investigation of their role in pathogenesis. In plasma, two ceramides increased and eight sphingomyelins decreased with AD, with total ceramides shown to increase in both serum and cerebrospinal fluid. In general antioxidants were shown to be depleted, with oxidative stress markers elevated in a range of biofluids in patients suggesting AD produces a pro-oxidative environment. Shifts in glutamate and glutamine and elevation of 4-hydroxy-2-nonenal suggests peroxidation of the astrocyte lipid bilayer resulting in reduced glutamate clearance from the synaptic cleft, suggesting a excitotoxicity component to AD pathology; however, due to inconsistencies in literature reports, reliable interpretation is difficult. The present review has shown that metabolite shifts in biofluids can provide valuable insights into potential pathological mechanisms in the brain, with sphingolipid, antioxidant, and glutamate metabolism being implicated in AD pathology.

Metabolomics studies in brain tissue: A review

Brain is still an organ with a composition to be discovered but beyond that, mental disorders and especially all diseases that curse with dementia are devastating for the patient, the family and the society. Metabolomics can offer an alternative tool for unveiling new insights in the discovery of new treatments and biomarkers of mental disorders. Until now, most of metabolomic studies have been based on biofluids: serum/plasma or urine, because brain tissue accessibility is limited to animal models or post mortem studies, but even so it is crucial for understanding the pathological processes. Metabolomics studies of brain tissue imply several challenges due to sample extraction, along with brain heterogeneity, sample storage, and sample treatment for a wide coverage of metabolites with a wide range of concentrations of many lipophilic and some polar compounds. In this review, the current analytical practices for target and non-targeted metabolomics are described and discussed with emphasis on critical aspects: sample treatment (quenching, homogenization, filtration, centrifugation and extraction), analytical methods, as well as findings considering the used strategies. Besides that, the altered analytes in the different brain regions have been associated with their corresponding pathways to obtain a global overview of their dysregulation, trying to establish the link between altered biological pathways and pathophysiological conditions.

NMR-Based Metabolic Snapshot from Minibronchoalveolar Lavage Fluid: An Approach To Unfold Human Respiratory Metabolomics

The utility of mini bronchoalveolar lavage (mBAL) and its applicability in metabolomics has not been explored in the field of human respiratory disease. mBAL, "an archetype" of the local lung environment, ensures a potent technique to get the snapshot of the epithelial lining fluid afflicted to human lung disorders. Characterization of the mBAL fluid has potential to help in elucidating the composition of the alveoli and airways in the diseased state, yielding diagnostic information on clinical applicability. In this study, one of the first attempts has been made to comprehensively assign and detect metabolites in mBAL fluid, extracted from human lungs, by the composite use of 800 MHz 1D and 2D NMR, J-resolved homonuclear spectroscopy, COSY, TOCSY, and heteronuclear HSQC correlation methods. A foremost all-inclusive sketch of the 50 metabolites has been corroborated and assigned, which can be a resourceful archive to further lung-directed metabolomics, prognosis, and diagnosis. Thus, NMR-based mBALF studies, as proposed in this article, will leverage many more prospective respiratory researches for routine clinical application and prove to be a viable approach to mirror the key predisposing factors contributing to the onset of lung disease.

Metabolic alterations in the sera of Chinese patients with mild persistent asthma: a GC-MS-based metabolomics analysis

AIM

To character the specific metabolomics profiles in the sera of Chinese patients with mild persistent asthma and to explore potential metabolic biomarkers.

METHODS

Seventeen Chinese patients with mild persistent asthma and age- and sex-matched healthy controls were enrolled. Serum samples were collected, and serum metabolites were analyzed using GC-MS coupled with a series of multivariate statistical analyses.

RESULTS

Clear intergroup separations existed between the asthmatic patients and control subjects. A list of differential metabolites and several top altered metabolic pathways were identified. The levels of succinate (an intermediate in tricarboxylic acid cycle) and inosine were highly upregulated in the asthmatic patients, suggesting a greater effort to breathe during exacerbation and hypoxic stress due to asthma. Other differential metabolites, such as 3,4-dihydroxybenzoic acid and phenylalanine, were also identified. Furthermore, the differential metabolites possessed higher values of area under the ROC curve (AUC), suggesting an excellent clinical ability for the prediction of asthma.

CONCLUSION

Metabolic activity is significantly altered in the sera of Chinese patients with mild persistent asthma. The data might be helpful for identifying novel biomarkers and therapeutic targets for asthma.

Chromatography/Mass Spectrometry-Based Biomarkers in the Field of Obstructive Sleep Apnea

Biomarker assessment is based on quantifying several proteins and metabolites. Recent developments in proteomics and metabolomics have enabled detection of these small molecules in biological samples and exploration of the underlying disease mechanisms in obstructive sleep apnea (OSA). This systemic review was performed to identify biomarkers, which were only detected by chromatography and/or mass spectrometry (MS) and to discuss the role of these biomarkers in the field of OSA. We systemically reviewed relevant articles from PubMed and EMBASE referring to proteins and metabolite profiles of biological samples in patients with OSA. The analytical platforms in this review were focused on chromatography and/or MS. In total, 30 studies evaluating biomarkers in patients with OSA using chromatography and/or MS methods were included. Numerous proteins and metabolites, including lipid profiles, adrenergic/dopaminergic biomarkers and derivatives, amino acids, oxidative stress biomarkers, and other micromolecules were identified in patients with OSA. Applying chromatography and/or MS methods to detect biomarkers helps develop an understanding of OSA mechanisms. More proteomic and metabolomic studies are warranted to develop potential diagnostic and clinical monitoring methods for OSA.

Metabolomic method: UPLC-q-ToF polar and non-polar metabolites in the healthy rat cerebellum using an in-vial dual extraction

Unbiased metabolomic analysis of biological samples is a powerful and increasingly commonly utilised tool, especially for the analysis of bio-fluids to identify candidate biomarkers. To date however only a small number of metabolomic studies have been applied to studying the metabolite composition of tissue samples, this is due, in part to a number of technical challenges including scarcity of material and difficulty in extracting metabolites. The aim of this study was to develop a method for maximising the biological information obtained from small tissue samples by optimising sample preparation, LC-MS analysis and metabolite identification. Here we describe an in-vial dual extraction (IVDE) method, with reversed phase and hydrophilic liquid interaction chromatography (HILIC) which reproducibly measured over 4,000 metabolite features from as little as 3mg of brain tissue. The aqueous phase was analysed in positive and negative modes following HILIC separation in which 2,838 metabolite features were consistently measured including amino acids, sugars and purine bases. The non-aqueous phase was also analysed in positive and negative modes following reversed phase separation gradients respectively from which 1,183 metabolite features were consistently measured representing metabolites such as phosphatidylcholines, sphingolipids and triacylglycerides. The described metabolomics method includes a database for 200 metabolites, retention time, mass and relative intensity, and presents the basal metabolite composition for brain tissue in the healthy rat cerebellum.

Defining phenotypes in COPD: an aid to personalized healthcare

The diagnosis of chronic obstructive pulmonary disease (COPD) is based on a post-bronchodilator fixed forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) <70 % ratio and the presence of symptoms such as shortness of breath and productive cough. Despite the simplicity in making a diagnosis of COPD, this morbid condition is very heterogeneous, and at least three different phenotypes can be recognized: the exacerbator, the emphysema-hyperinflation and the overlap COPD-asthma. These subgroups show different clinical and radiological features. It has been speculated that there is an enormous variability in the response to drugs among the COPD phenotypes, and it is expected that subjects with the same phenotype will have a similar response to each specific treatment. We believe that phenotyping COPD patients would be very useful to predict the response to a treatment and the progression of the disease. This personalized approach allows identification of the right treatment for each COPD patient, and at the same time, leads to improvement in the effectiveness of therapies, avoidance of treatments not indicated, and reduction in the onset of adverse effects. The objective of the present review is to report the current knowledge about different COPD phenotypes, focusing on specific treatments for each subgroup. However, at present, COPD phenotypes have not been studied by randomized clinical trials and therefore we hope that well designed studies will focus on this topic.

Integrative genomics of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a complex disease with both environmental and genetic determinants, the most important of which is cigarette smoking. There is marked heterogeneity in the development of COPD among persons with similar cigarette smoking histories, which is likely partially explained by genetic variation. Genomic approaches such as genomewide association studies and gene expression studies have been used to discover genes and molecular pathways involved in COPD pathogenesis; however, these "first generation" omics studies have limitations. Integrative genomic studies are emerging which can combine genomic datasets to further examine the molecular underpinnings of COPD. Future research in COPD genetics will likely use network-based approaches to integrate multiple genomic data types in order to model the complex molecular interactions involved in COPD pathogenesis. This article reviews the genomic research to date and offers a vision for the future of integrative genomic research in COPD.

Metabolomics in asthma

Asthma and airway inflammation are responses to infectious stimuli and the mechanisms of how they are mediated, whether by the innate or adaptive immune response systems, are complex and results in a broad spectrum of possible metabolic products. In principle, a syndrome such as asthma should have a characteristic temporal-spatial metabolic signature indicative of its current state and the constituents that caused it. Generally, the term metabolomics refers to the quantitative analysis of sets of small compounds from biological samples with molecular masses less than 1 kDa so unambiguous identification can be difficult and usually requires sophisticated instrumentation. The practical success of clinical metabolomics will largely hinge on a few key issues such as the ability to capture a readily available biofluid that can be analyzed to identify metabolite biomarkers with the required sensitivity and specificity in a cost-effective manner in a clinical setting. In this chapter, we review the current state of the metabolomics of asthma and airway inflammation with a focus on the different methods and instrumentation being used for the discovery of biomarkers in research and their future translation into the clinic as diagnostic aids for the choice of patient-specific therapies.

Sampling and analysis of metabolomes in biological fluids

Metabolome analysis involves the study of small molecules that are involved in the metabolic responses that occur through patho-physiological changes caused by genetic stimuli or chemical agents.

Fingerprinting-based metabolomic approach with LC-MS to sleep apnea and hypopnea syndrome: a pilot study

Sleep apnea and hypopnea syndrome (SAHS) is a multicomponent disorder, with associated cardiovascular and metabolic alterations, second in order of frequency among respiratory disorders. Sleep apnea is diagnosed with an overnight sleep test called a polysomnogram, which requires having the patient in hospital. In addition, a more clear classification of patients according to mild and severe presentations would be desirable. The aim of the present study was to assess the relative metabolic changes in SAHS to identify new potential biomarkers for diagnosis, able to evaluate disease severity to establish response to therapeutic interventions and outcomes. For this purpose, metabolic fingerprinting represents a valuable strategy to monitor, in a nontargeted manner, the changes that are at the base of the pathophysiological mechanism of SAHS. Plasma samples of 33 SAHS patients were collected after polysomnography and analyzed with LC coupled to MS (LC-QTOF-MS). After data treatment and statistical analysis, signals differentiating nonsevere and severe patients were detected. Putative identification of 14 statistically significant features was obtained and changes that can be related to the episodes of hypoxia/reoxygenation (inflammation) have been highlighted. Among them, the patterns of variation of platelet activating factor and lysophospholipids, together with some compounds related to differential activity of the gut microflora (bile pigments and pipecolic acid) open new lines of research that will benefit our understanding of the alterations, offering new possibilities for adequate monitoring of the stage of the disease.