Serum Metabolite Biomarkers Discriminate Healthy Smokers from COPD Smokers

Metabolic pathways in immune senescence and inflammaging: Novel therapeutic strategy for chronic inflammatory lung diseases. An EAACI position paper from the Task Force for Immunopharmacology

The accumulation of senescent cells drives inflammaging and increases morbidity of chronic inflammatory lung diseases. Immune responses are built upon dynamic changes in cell metabolism that supply energy and substrates for cell proliferation, differentiation, and activation. Metabolic changes imposed by environmental stress and inflammation on immune cells and tissue microenvironment are thus chiefly involved in the pathophysiology of allergic and other immune-driven diseases. Altered cell metabolism is also a hallmark of cell senescence, a condition characterized by loss of proliferative activity in cells that remain metabolically active. Accelerated senescence can be triggered by acute or chronic stress and inflammatory responses. In contrast, replicative senescence occurs as part of the physiological aging process and has protective roles in cancer surveillance and wound healing. Importantly, cell senescence can also change or hamper response to diverse therapeutic treatments. Understanding the metabolic pathways of senescence in immune and structural cells is therefore critical to detect, prevent, or revert detrimental aspects of senescence-related immunopathology, by developing specific diagnostics and targeted therapies. In this paper, we review the main changes and metabolic alterations occurring in senescent immune cells (macrophages, B cells, T cells). Subsequently, we present the metabolic footprints described in translational studies in patients with chronic asthma and chronic obstructive pulmonary disease (COPD), and review the ongoing preclinical studies and clinical trials of therapeutic approaches aiming at targeting metabolic pathways to antagonize pathological senescence. Because this is a recently emerging field in allergy and clinical immunology, a better understanding of the metabolic profile of the complex landscape of cell senescence is needed. The progress achieved so far is already providing opportunities for new therapies, as well as for strategies aimed at disease prevention and supporting healthy aging.

Exploring the Potential Role of Metabolomics in COPD: A Concise Review

Chronic Obstructive Pulmonary Disease (COPD) is a pathological condition of the respiratory system characterized by chronic airflow obstruction, associated with changes in the lung parenchyma (pulmonary emphysema), bronchi (chronic bronchitis) and bronchioles (small airways disease). In the last years, the importance of phenotyping and endotyping COPD patients has strongly emerged. Metabolomics refers to the study of metabolites (both intermediate or final products) and their biological processes in biomatrices. The application of metabolomics to respiratory diseases and, particularly, to COPD started more than one decade ago and since then the number of scientific publications on the topic has constantly grown. In respiratory diseases, metabolomic studies have focused on the detection of metabolites derived from biomatrices such as exhaled breath condensate, bronchoalveolar lavage, and also plasma, serum and urine. Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy are powerful tools in the precise identification of potentially prognostic and treatment response biomarkers. The aim of this article was to comprehensively review the relevant literature regarding the applications of metabolomics in COPD, clarifying the potential clinical utility of the metabolomic profile from several biologic matrices in detecting biomarkers of disease and prognosis for COPD. Meanwhile, a complete description of the technological instruments and techniques currently adopted in the metabolomics research will be described.

Plasma metabolomics and quantitative interstitial abnormalities in ever-smokers

BACKGROUND

Quantitative interstitial abnormalities (QIA) are an automated computed tomography (CT) finding of early parenchymal lung disease, associated with worse lung function, reduced exercise capacity, increased respiratory symptoms, and death. The metabolomic perturbations associated with QIA are not well known. We sought to identify plasma metabolites associated with QIA in smokers. We also sought to identify shared and differentiating metabolomics features between QIA and emphysema, another smoking-related advanced radiographic abnormality.

METHODS

In 928 former and current smokers in the Genetic Epidemiology of COPD cohort, we measured QIA and emphysema using an automated local density histogram method and generated metabolite profiles from plasma samples using liquid chromatography-mass spectrometry (Metabolon). We assessed the associations between metabolite levels and QIA using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, pack-years, and inhaled corticosteroid use, at a Benjamini-Hochberg False Discovery Rate p-value of ≤ 0.05. Using multinomial regression models adjusted for these covariates, we assessed the associations between metabolite levels and the following CT phenotypes: QIA-predominant, emphysema-predominant, combined-predominant, and neither- predominant. Pathway enrichment analyses were performed using MetaboAnalyst.

RESULTS

We found 85 metabolites significantly associated with QIA, with overrepresentation of the nicotinate and nicotinamide, histidine, starch and sucrose, pyrimidine, phosphatidylcholine, lysophospholipid, and sphingomyelin pathways. These included metabolites involved in inflammation and immune response, extracellular matrix remodeling, surfactant, and muscle cachexia. There were 75 metabolites significantly different between QIA-predominant and emphysema-predominant phenotypes, with overrepresentation of the phosphatidylethanolamine, nicotinate and nicotinamide, aminoacyl-tRNA, arginine, proline, alanine, aspartate, and glutamate pathways.

CONCLUSIONS

Metabolomic correlates may lend insight to the biologic perturbations and pathways that underlie clinically meaningful quantitative CT measurements like QIA in smokers.

Update on metabolomic findings in COPD patients

COPD is a heterogeneous disorder that shows diverse clinical presentations (phenotypes and "treatable traits") and biological mechanisms (endotypes). This heterogeneity implies that to carry out a more personalised clinical management, it is necessary to classify each patient accurately. With this objective, and in addition to clinical features, it would be very useful to have well-defined biological markers. The search for these markers may either be done through more conventional laboratory and hypothesis-driven techniques or relatively blind high-throughput methods, with the omics approaches being suitable for the latter. Metabolomics is the science that studies biological processes through their metabolites, using various techniques such as gas and liquid chromatography, mass spectrometry and nuclear magnetic resonance. The most relevant metabolomics studies carried out in COPD highlight the importance of metabolites involved in pathways directly related to proteins (peptides and amino acids), nucleic acids (nitrogenous bases and nucleosides), and lipids and their derivatives (especially fatty acids, phospholipids, ceramides and eicosanoids). These findings indicate the relevance of inflammatory-immune processes, oxidative stress, increased catabolism and alterations in the energy production. However, some specific findings have also been reported for different COPD phenotypes, demographic characteristics of the patients, disease progression profiles, exacerbations, systemic manifestations and even diverse treatments. Unfortunately, the studies carried out to date have some limitations and shortcomings and there is still a need to define clear metabolomic profiles with clinical utility for the management of COPD and its implicit heterogeneity.

Proteomics and metabolomics profiling reveal panels of circulating diagnostic biomarkers and molecular subtypes in stable COPD

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease with high morbidity and mortality, especially in advanced patients. We aimed to develop multi-omics panels of biomarkers for the diagnosis and explore its molecular subtypes.

METHODS

A total of 40 stable patients with advanced COPD and 40 controls were enrolled in the study. Proteomics and metabolomics techniques were applied to identify potential biomarkers. An additional 29 COPD and 31 controls were enrolled for validation of the obtained proteomic signatures. Information on demographic, clinical manifestation, and blood test were collected. The ROC analyses were carried out to evaluate the diagnostic performance, and experimentally validated the final biomarkers on mild-to-moderate COPD. Next, molecular subtyping was performed using proteomics data.

RESULTS

Theophylline, palmitoylethanolamide, hypoxanthine, and cadherin 5 (CDH5) could effectively diagnose advanced COPD with high accuracy (auROC = 0.98, sensitivity of 0.94, and specificity of 0.95). The performance of the diagnostic panel was superior to that of other single/combined results and blood tests. Proteome based stratification of COPD revealed three subtypes (I-III) related to different clinical outcomes and molecular feature: simplex COPD, COPD co-existing with bronchiectasis, and COPD largely co-existing with metabolic syndrome, respectively. Two discriminant models were established using the auROC of 0.96 (Principal Component Analysis, PCA) and 0.95 (the combination of RRM1 + SUPV3L1 + KRT78) in differentiating COPD and COPD with co-morbidities. Theophylline and CDH5 were exclusively elevated in advanced COPD but not in its mild form.

CONCLUSIONS

This integrative multi-omics analysis provides a more comprehensive understanding of the molecular landscape of advanced COPD, which may suggest molecular targets for specialized therapy.

Metabolomic Analysis of Respiratory Epithelial Lining Fluid in Patients with Chronic Obstructive Pulmonary Disease—A Systematic Review

Chronic obstructive pulmonary disease (COPD), as the third leading cause of death among adults, is a significant public health problem around the world. However, about 75% of smokers do not develop the disease despite the severe smoking burden. COPD is a heterogeneous disease, and several phenotypes, with differences in their clinical picture and response to treatment, have been distinguished. Metabolomic studies provide information on metabolic pathways, and therefore are a promising tool for understanding disease etiopathogenesis and the development of effective causal treatment. The aim of this systematic review was to analyze the metabolome of the respiratory epithelial lining fluid of patients with COPD, compared to healthy volunteers, refractory smokers, and subjects with other lung diseases. We included observational human studies. Sphingolipids, phosphatidylethanolamines, and sphingomyelins distinguished COPD from non-smokers; volatile organic compounds, lipids, and amino acids distinguished COPD from smokers without the disease. Five volatile organic compounds were correlated with eosinophilia and four were associated with a phenotype with frequent exacerbations. Fatty acids and ornithine metabolism were correlated with the severity of COPD. Metabolomics, by searching for biomarkers and distinguishing metabolic pathways, can allow us to understand the pathophysiology of COPD and the development of its phenotypes.

Metabolomics in COPD

The clinical presentation of chronic obstructive pulmonary disease (COPD) is highly heterogeneous. Attempts have been made to define subpopulations of patients who share clinical characteristics (phenotypes and treatable traits) and/or biological characteristics (endotypes), in order to offer more personalized care. Assigning a patient to any of these groups requires the identification of both clinical and biological markers. Ideally, biological markers should be easily obtained from blood or urine, but these may lack specificity. Biomarkers can be identified initially using conventional or more sophisticated techniques. However, the more sophisticated techniques should be simplified in the future if they are to have clinical utility. The -omics approach offers a methodology that can assist in the investigation and identification of useful markers in both targeted and blind searches. Specifically, metabolomics is the science that studies biological processes involving metabolites, which can be intermediate or final products. The metabolites associated with COPD and their specific phenotypic and endotypic features have been studied using various techniques. Several compounds of particular interest have emerged, namely, several types of lipids and derivatives (mainly phospholipids, but also ceramides, fatty acids and eicosanoids), amino acids, coagulation factors, and nucleic acid components, likely to be involved in their function, protein catabolism, energy production, oxidative stress, immune-inflammatory response and coagulation disorders. However, clear metabolomic profiles of the disease and its various manifestations that may already be applicable in clinical practice still need to be defined.

Metabolome Features of COPD: A Scoping Review

Chronic obstructive pulmonary disease (COPD) is a complex heterogeneous disease state with multiple phenotypic presentations that include chronic bronchitis and emphysema. Although COPD is a lung disease, it has systemic manifestations that are associated with a dysregulated metabolome in extrapulmonary compartments (e.g., blood and urine). In this scoping review of the COPD metabolomics literature, we identified 37 publications with a primary metabolomics investigation of COPD phenotypes in human subjects through Google Scholar, PubMed, and Web of Science databases. These studies consistently identified a dysregulation of the TCA cycle, carnitines, sphingolipids, and branched-chain amino acids. Many of the COPD metabolome pathways are confounded by age and sex. The effects of COPD in young versus old and male versus female need further focused investigations. There are also few studies of the metabolome's association with COPD progression, and it is unclear whether the markers of disease and disease severity are also important predictors of disease progression.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

The adverse inflammatory response of tobacco smoking in COVID-19 patients: biomarkers from proteomics and metabolomics

Whether tobacco smoking affects the occurrence and development of COVID-19 is still a controversial issue, and potential biomarkers to predict the adverse outcomes of smoking in the progression of COVID-19 patients have not yet been elucidated. To further uncover their linkage and explore the effective biomarkers, three proteomics and metabolomics databases (i.e. smoking status, COVID-19 status, and basic information of population) from human serum proteomic and metabolomic levels were established by literature search. Bioinformatics analysis was then performed to analyze the interactions of proteins or metabolites among the above three databases and their biological effects. Potential confounding factors (age, BMI, and gender) were controlled to improve the reliability. The obtained data indicated that smoking may increase the relative risk of conversion from non-severe to severe COVID-19 patients by inducing the dysfunctional immune response. Seven interacting proteins (C8A, LBP, FCN2, CRP, SAA1, SAA2, and VTN) were found to promote the deterioration of COVID-19 by stimulating the complement pathway and macrophage phagocytosis as well as inhibiting the associated negative regulatory pathways, which can be biomarkers to reflect and predict adverse outcomes in smoking COVID-19 patients. Three crucial pathways related to immunity and inflammation, including tryptophan, arginine, and glycerophospholipid metabolism, were considered to affect the effect of smoking on the adverse outcomes of COVID-19 patients. Our study provides novel evidence and corresponding biomarkers as potential predictors of severe disease progression in smoking COVID-19 patients, which is of great significance for preventing further deterioration in these patients.

Identification of biomarkers in COPD by metabolomics of exhaled breath condensate and serum/plasma

Chronic obstructive pulmonary disease (COPD) is the third cause of death worldwide, presenting poor long-term outcomes and chronic disability. COPD is a condition with a wide spectrum of clinical presentations because its pathophysiological determinants relate to tobacco smoke, genetic factors, alteration of several metabolic pathways, and oxidative stress. As a consequence, patients present different phenotypes even with comparable degrees of airflow limitation. Because of the increasing social and economic costs of COPD, a growing attention is currently payed to "omics" techniques for more personalized treatments and patient-tailored rehabilitation programs. In this regard, the systematic investigation of the metabolome (i.e., the whole set of endogenous molecules) in biomatrices, namely metabolomics, has become indispensable for phenotyping respiratory diseases. The metabolomic profiling of biological samples contains the small molecules produced during biological processes and their identification and quantification help in the diagnosis, comprehension of disease outcome and treatment response. Exhaled breath condensate (EBC), plasma and serum are biofluids readily available, with negligible invasiveness, and, therefore, suitable for metabolomics investigations. In this paper, we describe the latest advances on metabolomic profiling of EBC, plasma and serum in COPD patients.

Metabolomic profiling of exhaled breath condensate and plasma/serum in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is an increasing cause of global morbidity and mortality, with poor long-term outcomes and chronic disability. COPD is a condition with a wide spectrum of clinical presentations, with different phenotypes being identified even among patients with comparable degrees of airflow limitation. Considering the burden of COPD in terms of social and economic costs, in recent years a growing attention has been given to the need of more personalized approaches and patient-tailored rehabilitation programs. In this regard, the systematic analysis of metabolites in biological matrices, namely metabolomics, may become an essential tool in phenotyping diseases. Through the identification and quantification of the small molecules produced during biological processes, metabolomic profiling of biological samples has thus been proposed as an opportunity to identify novel biomarkers of disease outcome and treatment response. Exhaled breath condensate (EBC) and plasma/serum are fluid pools, which can be easily extracted and analyzed. In this review, we discuss the potential clinical applications of the metabolomic profiling of EBC and plasma/serum in COPD.

Rationale and design of REGULATE: an observational study protocol for relationship between plasma metabolome and the efficacy of systemic glucocorticoid in acute exacerbation of chronic obstructive pulmonary disease

Background

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) significantly increases the mortality of patients with COPD. Guidelines have recommended systemic glucocorticoid as a regular treatment. Recently, evidence has shown that systemic glucocorticoid cannot be a benefit to all of the patients with AECOPD. Thus, the problem that how the clinicians can screen the patients who can benefit from systemic glucocorticoid needs to be solved urgently. This study is aimed to detect the metabolic biomarkers and metabolic pathways that are related to the efficacy of systemic glucocorticoid and contribute to the precise treatment of COPD.

Methods and design

In this study, we will utilize ultraperformance liquid chromatography/mass spectrometry (LC–MS) and gas chromatography/mass spectrometry (GC–MS) methods for the analysis of the metabolites in AECOPD patients and compare the metabolites profiles between patients with systemic glucocorticoid treatment success group and treatment failure group. We aim to detect the metabolic biomarkers and metabolic pathways that are related to the efficacy of systemic glucocorticoid and contribute to the precise treatment of COPD.

Discussion

Previous studies have found that plasma metabolome changed significantly after dexamethasone treatment in healthy participants. Furthermore, inter-person variability was high and remained uninfluenced by treatment, suggesting the potential of metabolomics for predicting the efficacy and side effects of systemic glucocorticoid. Therefore, we hypothesized that metabolome changes in patients with AECOPD may be associated with the efficacy of systemic glucocorticoid.

Trial registration Clinicaltrials.gov registration number NCT04710849. Registered 15 January 2021, https://clinicaltrials.gov/ct2/show/NCT04710849.

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.

Differential Expression Study of Lysine Crotonylation and Proteome for Chronic Obstructive Pulmonary Disease Combined with Type II Respiratory Failure

Introduction

The modification of lysine crotonylation (Kcr) is another biological function of histone in addition to modification of lysine acetylation (Kac), which may play a specific regulatory role in diseases.

Objectives

This study compared the expression levels of Kcr and proteome between patients with chronic obstructive pulmonary disease (COPD) combined with type II respiratory failure (RF) to study the relationship between Kcr, proteome, and COPD.

Methods

We tested the Kcr and proteome of COPD combined with type II RF and normal control (NC) using croton acylation enrichment technology and liquid chromatography tandem mass spectrometry (LC-MS/MS) with high resolution.

Results

We found that 32 sites of 23 proteins were upregulated and 914 sites of 295 proteins were downregulated. We performed Kyoto Encyclopedia of Genes and Genomes (KEGG), protein domain, and Gene Ontology (GO) analysis on crotonylated protein. In proteomics research, we found that 190 proteins were upregulated and 151 proteins were downregulated. Among them, 90 proteins were both modified by differentially expressed crotonylation sites and differentially expressed in COPD combined with type II RF and NC.

Conclusion

Differentially expressed crotonylation sites may be involved in the development of COPD combined with type II RF. 90 proteins modified by crotonylation and differentially expressed in COPD combined with type II RF can be used as markers for the study of the molecular pathogenesis of COPD combined with type II RF.

The serum metabolome of COVID-19 patients is distinctive and predictive

BACKGROUND

Metabolism is critical for sustaining life, immunity and infection, but its role in COVID-19 is not fully understood.

METHODS

Seventy-nine COVID-19 patients, 78 healthy controls (HCs) and 30 COVID-19-like patients were recruited in a prospective cohort study. Samples were collected from COVID-19 patients with mild or severe symptoms on admission, patients who progressed from mild to severe symptoms, and patients who were followed from hospital admission to discharge. The metabolome was assayed using gas chromatography-mass spectrometry.

RESULTS

Serum butyric acid, 2-hydroxybutyric acid, l-glutamic acid, l-phenylalanine, l-serine, l-lactic acid, and cholesterol were enriched in COVID-19 and COVID-19-like patients versus HCs. Notably, d-fructose and succinic acid were enriched, and citric acid and 2-palmitoyl-glycerol were depleted in COVID-19 patients compared to COVID-19-like patients and HCs, and these four metabolites were not differentially distributed in non-COVID-19 groups. COVID-19 patients had enriched 4-deoxythreonic acid and depleted 1,5-anhydroglucitol compared to HCs and enriched oxalic acid and depleted phosphoric acid compared to COVID-19-like patients. A combination of d-fructose, citric acid and 2-palmitoyl-glycerol distinguished COVID-19 patients from HCs and COVID-19-like patients, with an area under the curve (AUC) > 0.92 after validation. The combination of 2-hydroxy-3-methylbutyric acid, 3-hydroxybutyric acid, cholesterol, succinic acid, L-ornithine, oleic acid and palmitelaidic acid predicted patients who progressed from mild to severe COVID-19, with an AUC of 0.969. After discharge, nearly one-third of metabolites were recovered in COVID-19 patients.

CONCLUSIONS

The serum metabolome of COVID-19 patients is distinctive and has important value in investigating pathogenesis, determining a diagnosis, predicting severe cases, and improving treatment.

Distinct metabolic features in the plasma of patients with silicosis and dust-exposed workers in China: a case-control study

BACKGROUND

Silicosis is a progressive pneumoconiosis characterized by interstitial fibrosis following exposure to silica dust. The role of metabolic dysregulation in the pathogenesis of silicosis has not been investigated in detail. This study aimed to identify different metabolic features in the plasma of patients with silicosis and dust-exposed workers without silicosis in metabolomics studies.

METHODS

Patients with silicosis, dust-exposed workers (DEWs) without silicosis and age-matched healthy controls were recruited in a case-control study. The metabolomics analyses by ultra-high performance liquid chromatography-mass spectrometry were conducted. Distinct metabolic features (DMFs) were identified in the pilot study and were validated in the validation study. The enriched signalling pathways of these DMFs were determined. The ability of DMFs to discriminate among the groups was analysed through receiver operating characteristic (ROC) curves. The correlations between DMFs and clinical features were also explored.

RESULTS

Twenty-nine DMFs and 9 DMFs were detected and had the same trend in the pilot study and the validation study in the plasma of the DEW and silicosis groups, respectively. Sphingolipid metabolism was the major metabolic pathway in the DEWs, and arginine and proline metabolism was associated with silicosis. Twenty DMFs in the DEWs and 3 DMFs in the patients with silicosis showed a discriminatory ability with ROC curve analysis. The abundance of kynurenine was higher in Stage III silicosis than in Stage I or Stage II silicosis. L-arginine and kynurenine were both negatively correlated with the percentage of forced vital capacity predicted in silicosis.

CONCLUSIONS

Distinct metabolic features in the plasma of DEWs and the patients with silicosis were found to be different. Sphingolipid metabolism and arginine and proline metabolism were identified as the major metabolic pathway in the DEW and silicosis groups, respectively. L-arginine and kynurenine were correlated with the severity of silicosis.

Polymorphisms rs2745557 in PTGS2 and rs2075797 in PTGER2 are associated with the risk of chronic obstructive pulmonary disease development in a Tunisian cohort

We hypothesized that polymorphisms of genes involved in the prostaglandin pathway could be associated with COPD. In this study we explored the involvement of genetic polymorphisms in PTGS2, PTGER2 and PTGER4 genes in the development and severity of COPD and their effects on plasma concentrations of inflammatory/oxidative stress markers. We identified genotypes of PTGS2, PTGER2 and PTGER4 SNPs in a Tunisian cohort including COPD patients (n = 138) and control subjects (n = 216) using PCR-RFLP and PCR TaqMan. Pulmonary function (FEV1 and FVC) were assessed by plethsmography. PGE₂, PGD₂ and cytokine plasma (IL-6, IL-18, TNF-α, TGF-β) concentrations were measured using ELISA and colorimetric standard methods were used to determine oxidative stress concentrations. Genotype frequencies of rs2745557 in PTGS2 and rs2075797 in PTGER2 were different between COPD cases and controls. There was no correlation between these polymorphisms and lung function parameters. For rs2745557, the A allele frequency was higher in COPD cases than in controls. For rs2075797, carriers of the GG genotype were more frequent in the COPD group than in controls. Only rs2745557 in PTGS2 had an effect on PGD₂ and cytokine plasma concentrations. PGD₂ was significantly decreased in COPD patients with the GA or AA genotypes. In contrast, IL-18 and NO plasma concentrations were increased in COPD rs2745557 A allele carriers as compared to homozygous GG subjects. Our findings suggest that rs2745557 in PTGS2 and rs2075797 in PTGER2 are associated with COPD development but not with its severity.

Plasma Metabolomic Signatures of Chronic Obstructive Pulmonary Disease and the Impact of Genetic Variants on Phenotype-Driven Modules

Background: Small studies have recently suggested that there are specific plasma metabolic signatures in chronic obstructive pulmonary disease (COPD), but there have been no large comprehensive study of metabolomic signatures in COPD that also integrate genetic variants. Materials and Methods: Fresh frozen plasma from 957 non-Hispanic white subjects in COPDGene was used to quantify 995 metabolites with Metabolon's global metabolomics platform. Metabolite associations with five COPD phenotypes (chronic bronchitis, exacerbation frequency, percent emphysema, post-bronchodilator forced expiratory volume at one second [FEV1]/forced vital capacity [FVC], and FEV1 percent predicted) were assessed. A metabolome-wide association study was performed to find genetic associations with metabolite levels. Significantly associated single-nucleotide polymorphisms were tested for replication with independent metabolomic platforms and independent cohorts. COPD phenotype-driven modules were identified in network analysis integrated with genetic associations to assess gene-metabolite-phenotype interactions. Results: Of metabolites tested, 147 (14.8%) were significantly associated with at least 1 COPD phenotype. Associations with airflow obstruction were enriched for diacylglycerols and branched chain amino acids. Genetic associations were observed with 109 (11%) metabolites, 72 (66%) of which replicated in an independent cohort. For 20 metabolites, more than 20% of variance was explained by genetics. A sparse network of COPD phenotype-driven modules was identified, often containing metabolites missed in previous testing. Of the 26 COPD phenotype-driven modules, 6 contained metabolites with significant met-QTLs, although little module variance was explained by genetics. Conclusion: A dysregulation of systemic metabolism was predominantly found in COPD phenotypes characterized by airflow obstruction, where we identified robust heritable effects on individual metabolite abundances. However, network analysis, which increased the statistical power to detect associations missed previously in classic regression analyses, revealed that the genetic influence on COPD phenotype-driven metabolomic modules was modest when compared with clinical and environmental factors.

Smoking status and second-hand smoke biomarkers in COPD, asthma and healthy controls

Introduction

Tobacco smoke worsens COPD and asthma. For healthy individuals, quantifying active and second-hand smoke (SHS) exposure clarifies the epidemiology of tobacco consumption and the efficacy of nonsmoking measures. Identifying tobacco exposure biomarkers and cut-offs might allow the creation of sensitive and specific tests.

Aim

We describe the state-of-the-art serum, urinary cotinine and exhaled carbon monoxide (CO) cut-offs for assessing smoking status and SHS exposure in adult patients with COPD or asthma, and healthy controls.

Methodology

After a keyword research in the PubMed database, we included papers reporting on the cut-offs of the investigated biomarkers in one of the populations of interest. Papers published before 2000, not in English, or reporting only data on nonadult subjects or on pregnant women were excluded from the analysis. 14 papers were included in the final analysis. We summarised diagnostic cut-offs for smoking status or SHS exposure in COPD, asthmatic and healthy control cohorts, reporting sensitivity and specificity when available.

Conclusion

Serum and urinary cotinine and exhaled CO are easy-to-standardise, affordable and objective tests for assessing smoking status and SHS exposure. Evidence on cut-offs with good sensitivity and specificity values is available mainly for healthy controls. For COPD and asthmatic patients, most of the currently available evidence focuses on exhaled CO, while studies on the use of cotinine with definite sensitivity and specificity values are still missing. Solid evidence on SHS exposure is available only for healthy controls. An integrated approach with a combination of these markers still needs evaluation.

Reliable cut-off values for smoking status in COPD and asthmatic adults are only available for exhaled COhttps://bit.ly/34lsHhD

CD73 Blockade Promotes Dendritic Cell Infiltration of Irradiated Tumors and Tumor Rejection

The ability of focal radiotherapy to promote priming of tumor-specific CD8⁺ T cells and increase responses to immunotherapy is dependent on infiltration of the tumor by Batf3-dependent conventional dendritic cell type 1 (cDC1) cells. Such infiltration is driven by radiotherapy-induced IFN type I (IFN-I). Other signals may also modulate cDC1 infiltration of irradiated tumors. Here we found increased expression of adenosine-generating enzymes CD38 and CD73 in irradiated mouse and human breast cancer cells and increased adenosine in mouse tumors following radiotherapy. CD73 blockade alone had no effect. CD73 blockade with radiotherapy restored radiotherapy-induced cDC1 infiltration of tumors in settings where radiotherapy induction of IFN-I was suboptimal. In the absence of radiotherapy-induced IFN-I, blockade of CD73 was required for rejection of the irradiated tumor and for systemic tumor control (abscopal effect) in the context of cytotoxic T-lymphocyte-associated protein 4 blockade. These results suggest that CD73 may be a radiation-induced checkpoint, and that CD73 blockade in combination with radiotherapy and immune checkpoint blockade might improve patient response to therapy.

Smokers with COPD Show a Shift in Energy and Nitrogen Metabolism at Rest and During Exercise

Purpose

There is an ongoing demand for easily accessible biomarkers that reflect the physiological and pathophysiological mechanisms of COPD. To test if an exercise challenge could help to identify clinically relevant metabolic biomarkers in COPD.

Patients and Methods

We performed two constant-load exercise challenges separated by 4 weeks including smokers with COPD (n=23/19) and sex- and age-matched healthy smokers (n=23/20). Two hours after a standardized meal venous blood samples were obtained before, 5 mins after the start, at the end of submaximal exercise, and following a recovery of 20 mins. Data analysis was performed using mixed- effects model, with the metabolite level as a function of disease, time point and interaction terms and using each individual's resting level as reference.

Results

Exercise duration was longer in healthy smokers but lactate levels were comparable between groups at all four time points. Glucose levels were increased in COPD. Glutamine was lower, while glutamate and arginine were higher in COPD. Branched-chain amino acids showed a stronger decline during exercise in healthy smokers. Carnitine and the acyl-carnitines C16 and C18:1 were increased in COPD. These metabolite levels and changes were reproducible in the second challenge.

Conclusion

Higher serum glucose, evidence for impaired utilization of amino acids during exercise and a shift of energy metabolism to enhanced consumption of lipids could be early signs for a developing metabolic syndrome in COPD. In COPD patients, deviations of energy and nitrogen metabolism are amplified by an exercise challenge.

Metabolic Fingerprint of Chronic Obstructive Lung Diseases: A New Diagnostic Perspective

Chronic obstructive lung disease (COLD) is a group of airway diseases, previously known as emphysema and chronic bronchitis. The heterogeneity of COLD does not allow early diagnosis and leads to increased morbidity and mortality. The increasing number of COLD incidences stresses the need for precision medicine approaches that are specific to the patient. Metabolomics is an emerging technology that allows for the discrimination of metabolic changes in the cell as a result of environmental factors and specific genetic background. Thus, quantification of metabolites in human biofluids can provide insights into the metabolic state of the individual in real time and unravel the presence of, or predisposition to, a disease. In this article, the advantages of and potential barriers to putting metabolomics into clinical practice for COLD are discussed. Today, metabolomics is mostly lab-based, and research studies with novel COLD-specific biomarkers are continuously being published. Several obstacles in the research and the market field hamper the translation of these data into clinical practice. However, technological and computational advances will facilitate the clinical interpretation of data and provide healthcare professionals with the tools to prevent, diagnose, and treat COLD with precision in the coming decades.

Plasma metabolomics and clinical predictors of survival differences in COPD patients

BACKGROUND

Plasma metabolomics profile (PMP) in COPD has been associated with clinical characteristics, but PMP's relationship to survival has not been reported. We determined PMP differences between patients with COPD who died an average of 2 years after enrollment (Non-survivors, NS) compared to those who survived (S) and also with age matched controls (C).

METHODS

We studied prospectively 90 patients with severe COPD and 30 controls. NS were divided in discovery and validation cohorts (30 patients each) and the results compared to the PMP of 30 S and C. All participants completed lung function tests, dyspnea scores, quality of life, exercise capacity, BODE index, and plasma metabolomics by liquid and gas chromatography / mass spectometry (LC/MS, LC/MS2, GC/MS). Statistically, we used Random Forest Analysis (RFA) and Support Vector Machine (SVM) to determine metabolites that differentiated the 3 groups and compared the ability of metabolites vs. clinical characteristics to classify patients into survivors and non-survivors.

RESULTS

There were 79 metabolites statistically different between S and NS [p < 0.05 and false discovery rate (q value) < 0.1]. RFA and SVM classification of COPD survivors and non-survivors had a predicted accuracy of 74 and 85% respectively. Elevation of tricyclic acid cycle intermediates branched amino acids depletion and increase in lactate, fructose and xylonate showed the most relevant differences between S vs. NS suggesting alteration in mitochondrial oxidative energy generation. PMP had similar predictive power for risk of death as information provided by clinical characteristics.

CONCLUSIONS

A plasma metabolomic profile characterized by an oxidative energy production difference between survivors and non-survivors was observed in COPD patients 2 years before death.

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.

SDHA gain-of-function engages inflammatory mitochondrial retrograde signaling via KEAP1-Nrf2

Whether screening the metabolic activity of immune cells facilitates discovery of molecular pathology remains unknown. Here we prospectively screened the extracellular acidification rate as a measure of glycolysis and the oxygen consumption rate as a measure of mitochondrial respiration in B cells from patients with primary antibody deficiency. The highest oxygen consumption rate values were detected in three study participants with persistent polyclonal B cell lymphocytosis (PPBL). Exome sequencing identified germline mutations in SDHA, which encodes succinate dehydrogenase subunit A, in all three patients with PPBL. SDHA gain-of-function led to an accumulation of fumarate in PPBL B cells, which engaged the KEAP1-Nrf2 system to drive the transcription of genes encoding inflammatory cytokines. In a single patient trial, blocking the activity of the cytokine interleukin-6 in vivo prevented systemic inflammation and ameliorated clinical disease. Overall, our study has identified pathological mitochondrial retrograde signaling as a disease modifier in primary antibody deficiency.

Disruption of histidine and energy homeostasis in chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a systemic condition that is too complex to be assessed by lung function alone. Metabolomics has the potential to help understand the mechanistic underpinnings that contribute to COPD pathogenesis. Since blood metabolomics may be affected by sex and body mass index (BMI), the aim of this study was to determine the metabolomic variability in male smokers with and without COPD who have a narrow BMI range.

Methods

We compared the quantitative proton nuclear magnetic resonance acquired serum metabolomics of a male Chinese Han population of non-smokers without COPD, and smokers with and without COPD. We also assessed the impact of smoking status on metabolite concentrations and the associations between metabolite concentrations and inflammatory markers such as serum interleukin-6 and histamine, and blood cell differential (%). Metabolomics data were log-transformed and auto-scaled for parametric statistical analysis. Mean normalized metabolite concentration values and continuous demographic variables were compared by Student’s t-test with Welch correction or ANOVA with post-hoc Tukey’s test, as applicable; t-test p-values for metabolomics data were corrected for false discovery rate (FDR). A Pearson association matrix was built to evaluate the relationship between metabolite concentrations, clinical parameters and markers of inflammation.

Results

Twenty-eight metabolites were identified and quantified. Creatine, glycine, histidine, and threonine concentrations were reduced in COPD patients compared to non-COPD smokers (FDR ≤15%). Concentrations of these metabolites were inversely correlated with interleukin-6 levels. COPD patients had overall dampening of metabolite concentrations including energy-related metabolic pathways such as creatine metabolism. They also had higher histamine levels and percent basophils compared to smokers without COPD.

Conclusion

COPD is associated with alterations in the serum metabolome, including a disruption in the histidine-histamine and creatine metabolic pathways. These findings support the use of metabolomics to understand the pathogenic mechanisms involved in COPD.

Trial registrationwww.clinicaltrials.gov, NCT03310177.

Serum amino acid concentrations and clinical outcomes in smokers: SPIROMICS metabolomics study

Metabolomics is an emerging science that can inform pathogenic mechanisms behind clinical phenotypes in COPD. We aimed to understand disturbances in the serum metabolome associated with respiratory outcomes in ever-smokers from the SPIROMICS cohort. We measured 27 serum metabolites, mostly amino acids, by ¹H-nuclear magnetic resonance spectroscopy in 157 white ever-smokers with and without COPD. We tested the association between log-transformed metabolite concentrations and one-year incidence of respiratory exacerbations after adjusting for age, sex, current smoking, body mass index, diabetes, inhaled or oral corticosteroid use, study site and clinical predictors of exacerbations, including FEV₁% predicted and history of exacerbations. The mean age of participants was 53.7 years and 58% had COPD. Lower concentrations of serum amino acids were independently associated with 1-year incidence of respiratory exacerbations, including tryptophan (β = −4.1, 95% CI [−7.0; −1.1], p = 0.007) and the branched-chain amino acids (leucine: β = −6.0, 95% CI [−9.5; −2.4], p = 0.001; isoleucine: β = −5.2, 95% CI [−8.6; −1.8], p = 0.003; valine: β = −4.1, 95% CI [−6.9; −1.4], p = 0.003). Tryptophan concentration was inversely associated with the blood neutrophil-to-lymphocyte ratio (p = 0.03) and the BODE index (p = 0.03). Reduced serum amino acid concentrations in ever-smokers with and without COPD are associated with an increased incidence of respiratory exacerbations.

An Updated Overview of Metabolomic Profile Changes in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD), a common and heterogeneous respiratory disease, is characterized by persistent and incompletely reversible airflow limitation. Metabolomics is applied to analyze the difference of metabolic profile based on the low-molecular-weight metabolites (<1 kDa). Emerging metabolomic analysis may provide insights into the pathogenesis and diagnosis of COPD. This review aims to summarize the alteration of metabolites in blood/serum/plasma, urine, exhaled breath condensate, lung tissue samples, etc. from COPD individuals, thereby uncovering the potential pathogenesis of COPD according to the perturbed metabolic pathways. Metabolomic researches have indicated that the dysfunctions of amino acid metabolism, lipid metabolism, energy production pathways, and the imbalance of oxidations and antioxidations might lead to local and systematic inflammation by activating the Nuclear factor kappa-light-chain-enhancer of activated B cells signaling pathway and releasing inflammatory cytokines, like interleutin-6 (IL-6), tumor necrosis factor-α, and IL-8. In addition, they might cause protein malnutrition and oxidative stress and contribute to the development and exacerbation of COPD.

Metabolomics Identifies Novel Blood Biomarkers of Pulmonary Function and COPD in the General Population

Determination of metabolomic signatures of pulmonary function and chronic obstructive pulmonary disease (COPD) in the general population could aid in identification and understanding of early disease processes. Metabolome measurements were performed on serum from 4742 individuals (2354 African-Americans and 1529 European-Americans from the Atherosclerosis Risk in Communities study and 859 Europeans from the Cooperative Health Research in the Region of Augsburg study). We examined 368 metabolites in relation to cross-sectional measures of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), their ratio (FEV1/FVC) and COPD using multivariable regression followed by meta-analysis. At a false discovery rate of 0.05, 95 metabolites were associated with FEV1 and 100 with FVC (73 overlapping), including inverse associations with branched-chain amino acids and positive associations with glutamine. Ten metabolites were associated with FEV1/FVC and seventeen with COPD (393 cases). Enriched pathways of amino acid metabolism were identified. Associations with FEV1 and FVC were not driven by individuals with COPD. We identified novel metabolic signatures of pulmonary function and COPD in African and European ancestry populations. These may allow development of biomarkers in the general population of early disease pathogenesis, before pulmonary function has decreased to levels diagnostic for COPD.

Metabolomics and transcriptomics pathway approach reveals outcome-specific perturbations in COPD

Chronic obstructive pulmonary disease (COPD) comprises multiple phenotypes such as airflow obstruction, emphysema, and frequent episodes of acute worsening of respiratory symptoms, known as exacerbations. The goal of this pilot study was to test the usefulness of unbiased metabolomics and transcriptomics approaches to delineate biological pathways associated with COPD phenotypes and outcomes. Blood was collected from 149 current or former smokers with or without COPD and separated into peripheral blood mononuclear cells (PBMC) and plasma. PBMCs and plasma were analyzed using microarray and liquid chromatography mass spectrometry, respectively. Statistically significant transcripts and compounds were mapped to pathways using IMPaLA. Results showed that glycerophospholipid metabolism was associated with worse airflow obstruction and more COPD exacerbations. Sphingolipid metabolism was associated with worse lung function outcomes and exacerbation severity requiring hospitalizations. The strongest associations between a pathway and a certain COPD outcome were: fat digestion and absorption and T cell receptor signaling with lung function outcomes; antigen processing with exacerbation frequency; arginine and proline metabolism with exacerbation severity; and oxidative phosphorylation with emphysema. Overlaying transcriptomic and metabolomics datasets across pathways enabled outcome and phenotypic differences to be determined. Findings are relevant for identifying molecular targets for animal intervention studies and early intervention markers in human cohorts.

Urine Metabolic Signatures of Multiple Environmental Pollutants in Pregnant Women: An Exposome Approach

Exposure to environmental pollutants, particularly during pregnancy, can have adverse consequences on child development but little is known about the effects of pollutant mixtures on endogenous metabolism in pregnant women. We aimed to identify urinary metabolic signatures associated with low level exposure to multiple environmental pollutants in pregnant women from the INMA (INfancia y Medio Ambiente) birth cohort (Spain, N = 750). 35 chemical exposures were quantified in first trimester blood samples (organochlorine pesticides, PCBs, PFAS), in cord blood (mercury), and twice in urine at 12 and 32 weeks of pregnancy (metals, phthalates, bisphenol A). ¹H nuclear magnetic resonance (NMR) metabolic profiles of urine were acquired in the same samples as pollutants. We explored associations between exposures and metabolism through an exposome-metabolome wide association scan and multivariate O2PLS modeling. Novel and reproducible associations were found across two periods of pregnancy for three nonpersistent pollutants and across two subcohorts for four of the persistent pollutants. We found novel metabolic signatures associated with arsenic exposure: TMAO and dimethylamine possibly related to gut microbial methylamine metabolism and homarine related to fish intake. Tobacco smoke exposure was related to coffee metabolism and PCBs with 3-hydroxyvaleric acid, usually released under ketoacidosis. These findings will have implications for further understanding of maternal-fetal health, and health across the life-course.

Study of the metabolomic relationship between lung cancer and chronic obstructive pulmonary disease based on direct infusion mass spectrometry

The high prevalence of lung cancer (LC) has triggered the search of biomarkers for early diagnosis of this disease. For this purpose the study of metabolic changes related to the development of lung cancer could provide interesting information about its early diagnosis. In this sense, chronic obstructive pulmonary disease (COPD), a disease associated with tumor development, is a comorbidity that increases the risk of onset and progression of lung neoplasia and has also to be considered in the study of pathology related to lung cancer. This work develop a metabolomic approach based on direct infusion mass spectrometry using a hybrid triple quadrupole-time of flight mass spectrometer (DI-ESI-QqQ-TOF-MS) in order to identify altered metabolites from serum of LC and COPD patients and evaluate its relationship and implication in the progression of LC. This methodology has been applied to 30 serum samples from LC, 30 healthy patients used as controls (HC) and 30 serum samples from COPD to found altered metabolites from both LC and COPD diseases. In addition, some metabolic differences and similarities were found in Pulmonary Emphysema and Chronic Bronchitis patients. On the other hand, altered metabolites were studied in different stages of LC (II, III and IV) to evaluate the perturbation of them throughout the progression of disease. The sample treatment consisted of the extraction of polar and non-polar metabolites from serum that was later infused into the mass spectrometer using an electrospray ionization source in positive and negative mode. Partial least squares discriminant analysis (PLS-DA) allowed a classification between LC, HC and COPD groups in all acquisition modes. A total of 35 altered and common metabolites between LC and COPD, including amino acids, fatty acids, lysophospholipids, phospholipids and triacylglycerides were identified, being alanine, aspartate and glutamate metabolism the most altered. Finally, ROC curves were applied to the dataset and metabolites with AUC value higher than 0.70 were considered as relevant in the progression of LC.

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.

Using omics approaches to understand pulmonary diseases

Omics approaches are high-throughput unbiased technologies that provide snapshots of various aspects of biological systems and include: 1) genomics, the measure of DNA variation; 2) transcriptomics, the measure of RNA expression; 3) epigenomics, the measure of DNA alterations not involving sequence variation that influence RNA expression; 4) proteomics, the measure of protein expression or its chemical modifications; and 5) metabolomics, the measure of metabolite levels. Our understanding of pulmonary diseases has increased as a result of applying these omics approaches to characterize patients, uncover mechanisms underlying drug responsiveness, and identify effects of environmental exposures and interventions. As more tissue- and cell-specific omics data is analyzed and integrated for diverse patients under various conditions, there will be increased identification of key mechanisms that underlie pulmonary biological processes, disease endotypes, and novel therapeutics that are efficacious in select individuals. We provide a synopsis of how omics approaches have advanced our understanding of asthma, chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), and pulmonary arterial hypertension (PAH), and we highlight ongoing work that will facilitate pulmonary disease precision medicine.

Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry

In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N=79), I (N=80), and II (N=123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis.

A Review of Pulmonary Toxicity of Electronic Cigarettes in the Context of Smoking: A Focus on Inflammation

The use of electronic cigarettes (e-cigs) is increasing rapidly, but their effects on lung toxicity are largely unknown. Smoking is a well-established cause of lung cancer and respiratory disease, in part through inflammation. It is plausible that e-cig use might affect similar inflammatory pathways. E-cigs are used by some smokers as an aid for quitting or smoking reduction, and by never smokers (e.g., adolescents and young adults). The relative effects for impacting disease risk may differ for these groups. Cell culture and experimental animal data indicate that e-cigs have the potential for inducing inflammation, albeit much less than smoking. Human studies show that e-cig use in smokers is associated with substantial reductions in blood or urinary biomarkers of tobacco toxicants when completely switching and somewhat for dual use. However, the extent to which these biomarkers are surrogates for potential lung toxicity remains unclear. The FDA now has regulatory authority over e-cigs and can regulate product and e-liquid design features, such as nicotine content and delivery, voltage, e-liquid formulations, and flavors. All of these factors may impact pulmonary toxicity. This review summarizes current data on pulmonary inflammation related to both smoking and e-cig use, with a focus on human lung biomarkers. Cancer Epidemiol Biomarkers Prev; 26(8); 1175-91. ©2017 AACR.

Alterations in Serum Polyunsaturated Fatty Acids and Eicosanoids in Patients with Mild to Moderate Chronic Obstructive Pulmonary Disease (COPD)

Smoking is a major risk factor for several diseases including chronic obstructive pulmonary disease (COPD). To better understand the systemic effects of cigarette smoke exposure and mild to moderate COPD-and to support future biomarker development-we profiled the serum lipidomes of healthy smokers, smokers with mild to moderate COPD (GOLD stages 1 and 2), former smokers, and never-smokers (n = 40 per group) (ClinicalTrials.gov registration: NCT01780298). Serum lipidome profiling was conducted with untargeted and targeted mass spectrometry-based lipidomics. Guided by weighted lipid co-expression network analysis, we identified three main trends comparing smokers, especially those with COPD, with non-smokers: a general increase in glycero(phospho)lipids, including triglycerols; changes in fatty acid desaturation (decrease in ω-3 polyunsaturated fatty acids, and an increase in monounsaturated fatty acids); and an imbalance in eicosanoids (increase in 11,12- and 14,15-DHETs (dihydroxyeicosatrienoic acids), and a decrease in 9- and 13-HODEs (hydroxyoctadecadienoic acids)). The lipidome profiles supported classification of study subjects as smokers or non-smokers, but were not sufficient to distinguish between smokers with and without COPD. Overall, our study yielded further insights into the complex interplay between smoke exposure, lung disease, and systemic alterations in serum lipid profiles.

Transcriptomics, proteomics and metabolomics driven biomarker discovery in COPD: an update

INTRODUCTION

Diagnosis of chronic obstructive pulmonary disease (COPD), characterized by progressive irreversible airflow limitation, remains a challenge. Lack of sensitive diagnostic markers and alternative treatments have limited patients' survival rate. Herein, we provide for clinicians and scientists a comprehensive review on the various omics platforms used to investigate COPD.

AREAS COVERED

This review consists of articles from PubMed (2009-2016) as well as views of the contributing authors. The review highlights the need for COPD biomarker identification and also provides an update on promising candidate markers identified in various biological fluids using omics technologies. Expert commentary: The multi-omics approach holds promise for the development of robust early stage COPD diagnostic markers, screening of high-risk population, and also improved prognosis which could lead to personalized medicine in future. Various factors regulating an omics study including sample size, control selection, disease phenotyping, usage of complementary techniques and result replication in omics-based research are outlined.

Repair Mechanisms in Oxidant-Driven Chronic Inflammatory Disease

The interplay that governs chronic diseases through pathways specifically associated with chronic inflammation remains undefined. Many metabolic events have been identified during the injury and repair process. Nonetheless, the cellular events that control the pathogenesis of inflammation-induced disease have not been fully characterized. We and others reason that chronic inflammatory diseases associated with a cascade of complex network mediators, such as nitric oxide, arachidonic acid metabolites, cytokines, and reactive oxygen species, play a significant role in the governance of alterations in homeostasis, oxidative stress, and thromboatherosclerosis. In this context, we discuss lipid mediators associated with the maintenance of health, including the specialized proresolving mediators that help drive cellular repair. Emphasis is placed on the pathophysiology of chronic metabolic insults involving both the airways and the cardiovascular system during oxidant-driven inflammatory disease. In this review, we highlight new pathways of inquiry that show promise for the identification of those metabolic targets that can improve therapy for chronic inflammation.