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

Cysteamine Nanoemulsion Delivery by Inhalation to Attenuate Adverse Effects of Exposure to Cigarette Smoke: A Metabolomics Study in Wistar Rats

There is a pressing need for novel pharmacological interventions and drug delivery innovations to attenuate the cigarette smoke-associated oxidative stress and lung disease. We report here on the attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) and metabolomics of Wistar rats exposed to cigarette smoke for 28 days. The animals were treated for 15 days with plain cysteamine given orally or cysteamine as nanoemulsion given orally or via inhalation. The study design also included two control groups as follows: rats exposed to cigarette smoke but did not receive a treatment (diseased control group) and rats neither exposed to cigarette smoke nor a treatment (normal control group). The targeted metabolomics using Parallel Reaction Monitoring showed that in the diseased control group, ornithine, nicotinamide, xanthine, hypoxanthine, and caprolactam were increased compared with the normal control group. In addition, (±)8(9)-DiHET, which was initially downregulated in the diseased control group, exhibited a reversal of this trend with cysteamine nanoemulsion given via inhalation. The cysteamine nanoemulsion delivered by inhalation highlighted the importance of the route of drug administration for targeting the lungs. To the best of our knowledge, this is the first work to use ATR-FTIR and metabolomics in Wistar rat lung tissues, suggesting how cysteamine nanoemulsion can potentially reduce cigarette smoke-induced oxidative damage. The metabolites reported herein have potential implications for discovery of novel theranostics and, thus, to cultivate diagnostic and therapeutic innovation for early prevention and treatment of cigarette smoke-associated lung diseases.

3D printer emissions elicit filament-specific and dose-dependent metabolic and genotoxic effects in human airway epithelial cells

Three-dimensional (3D) printers have become popular educational tools in secondary and post-secondary STEM curriculum; however, concerns have emerged regarding inhalation exposures and associated health risks. Current evidence suggests that filament materials and site conditions may cause differences in the chemical profiles and toxicological properties of 3D printer emissions; however, few studies have evaluated exposures directly in the classroom. In this study, we monitored and sampled particulate matter (PM) emitted from acrylonitrile-butadiene-styrene (ABS) and polylactic acid (PLA) filaments during a 3-hour 3D printing session in a high school classroom using aerosol monitoring instrumentation and collection media. To evaluate potential inhalation risks, Multiple Path Particle Dosimetry (MPPD) modeling was used to estimate inhaled doses and calculate in vitro concentrations based on the observed aerosol data and specific lung and breathing characteristics. Dynamic light scattering was used to evaluate the hydrodynamic diameter, zeta potential, and polydispersity index (PDI) of extracted PM emissions dispersed in cell culture media. Small airway epithelial cells (SAEC) were employed to determine cellular viability, genotoxic, inflammatory, and metabolic responses to each emission exposure using MTS, ELISA, and high-performance liquid chromatography-mass spectrometry (HPLC-MS), respectively. Aerosol monitoring data revealed that emissions from ABS and PLA filaments generated similar PM concentrations within the ultrafine and fine ranges. However, DLS analysis showed differences in the physicochemical properties of ABS and PLA PM, where the hydrodynamic diameter of PLA PM was greater than ABS PM, which may have influenced particle deposition rates and cellular outcomes. While exposure to both ABS and PLA PM reduced cell viability and induced MDM2, an indicator of genomic instability, PLA PM alone increased gamma-H2AX, a marker of double-stranded DNA breaks. ABS and PLA emissions also increased the release of pro-inflammatory cytokines, although this did not reach significance. Furthermore, metabolic profiling via high performance liquid chromatography-mass spectrometry (HPLC-MS) and subsequent pathway analysis revealed filament and dose dependent cellular metabolic alterations. Notably, our metabolomic analysis also revealed key metabolites and pathways implicated in PM-induced oxidative stress, DNA damage, and respiratory disease that were perturbed across both tested doses for a given filament. Taken together, these findings suggest that use of ABS and PLA filaments in 3D printers within school settings may potentially contribute to adverse respiratory responses especially in vulnerable populations.

The aging lung: microenvironment, mechanisms, and diseases

With the development of global social economy and the deepening of the aging population, diseases related to aging have received increasing attention. The pathogenesis of many respiratory diseases remains unclear, and lung aging is an independent risk factor for respiratory diseases. The aging mechanism of the lung may be involved in the occurrence and development of respiratory diseases. Aging-induced immune, oxidative stress, inflammation, and telomere changes can directly induce and promote the occurrence and development of lung aging. Meanwhile, the occurrence of lung aging also further aggravates the immune stress and inflammatory response of respiratory diseases; the two mutually affect each other and promote the development of respiratory diseases. Explaining the mechanism and treatment direction of these respiratory diseases from the perspective of lung aging will be a new idea and research field. This review summarizes the changes in pulmonary microenvironment, metabolic mechanisms, and the progression of respiratory diseases associated with aging.

An integrated metabo-lipidomics profile of induced sputum for the identification of novel biomarkers in the differential diagnosis of asthma and COPD

BACKGROUND

Due to their complexity and to the presence of common clinical features, differentiation between asthma and chronic obstructive pulmonary disease (COPD) can be a challenging task, complicated in such cases also by asthma-COPD overlap syndrome. The distinct immune/inflammatory and structural substrates of COPD and asthma are responsible for significant differences in the responses to standard pharmacologic treatments. Therefore, an accurate diagnosis is of central relevance to assure the appropriate therapeutic intervention in order to achieve safe and effective patient care. Induced sputum (IS) accurately mirrors inflammation in the airways, providing a more direct picture of lung cell metabolism in comparison to those specimen that reflect analytes in the systemic circulation.

METHODS

An integrated untargeted metabolomics and lipidomics analysis was performed in IS of asthmatic (n = 15) and COPD (n = 22) patients based on Ultra-High-Pressure Liquid Chromatography-Mass Spectrometry (UHPLC-MS) and UHPLC-tandem MS (UHPLC-MS/MS). Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to resulting dataset. The analysis of main enriched metabolic pathways and the association of the preliminary metabolites/lipids pattern identified to clinical parameters of asthma/COPD differentiation were explored. Multivariate ROC analysis was performed in order to determine the discriminatory power and the reliability of the putative biomarkers for diagnosis between COPD and asthma.

RESULTS

PLS-DA indicated a clear separation between COPD and asthmatic patients. Among the 15 selected candidate biomarkers based on Variable Importance in Projection scores, putrescine showed the highest score. A differential IS bio-signature of 22 metabolites and lipids was found, which showed statistically significant variations between asthma and COPD. Of these 22 compounds, 18 were decreased and 4 increased in COPD compared to asthmatic patients. The IS levels of Phosphatidylethanolamine (PE) (34:1), Phosphatidylglycerol (PG) (18:1;18:2) and spermine were significantly higher in asthmatic subjects compared to COPD.

CONCLUSIONS

This is the first pilot study to analyse the IS metabolomics/lipidomics signatures relevant in discriminating asthma vs COPD. The role of polyamines, of 6-Hydroxykynurenic acid and of D-rhamnose as well as of other important players related to the alteration of glycerophospholipid, aminoacid/biotin and energy metabolism provided the construction of a diagnostic model that, if validated on a larger prospective cohort, might be used to rapidly and accurately discriminate asthma from COPD.

Sex related differences in muscle health and metabolism in chronic obstructive pulmonary disease

BACKGROUND & AIMS

Sex differences in muscle function and mass, dyspnea, and clinical outcomes have been observed in patients with Chronic Obstructive Pulmonary Disease (COPD) despite a similar level of airflow obstruction. Protein and amino acid metabolism is altered in COPD, however, it remains unclear whether a difference in metabolic signature exists between males and females with COPD that may explain the observed differences in muscle health and clinical outcomes.

METHODS

In 234 moderate to severe COPD patients (males/females: 113/121) and 182 healthy controls (males/females: 77/105), we assessed, besides presence of comorbidities and clinical features, muscle function by handgrip and leg dynamometry, and body composition by dual-energy x-ray absorptiometry. In the postabsorptive state, a mixture of 18 stable isotopes of amino acids was administered by pulse and arterialized blood was sampled for 2 h. Amino acid concentrations and enrichments were analyzed by LC-MS/MS to calculate whole body (net) protein breakdown (WBnetPB) and whole body production (WBP) rates (μmol/hour) of the amino acids playing a known role in muscle health. Statistics was done by ANCOVA to examine the effects of sex, COPD, and sex-by-COPD interaction with as covariates age and lean mass. Significance was set as p < 0.05.

RESULTS

Lung function was comparable between males and females with COPD. Being a female and presence of COPD were independently associated with lower appendicular lean mass, muscle strength, and WBnetPB (p < 0.05). Being a male was associated with higher visceral adipose tissue, C-reactive protein (CRP) (p < 0.05), and higher prevalence of heart failure and obstructive sleep apnea. Sex-by-COPD interactions were found indicating lower fat mass (p = 0.0005) and WBPs of phenylalanine (measure of whole body protein turnover) and essential amino acids (p < 0.05), particularly in COPD females. Higher visceral adipose tissue (p = 0.025), CRP (p < 0.0001), and WBP of tau-methylhistidine (p = 0.010) (reflecting enhanced myofibrillar protein breakdown) were observed in COPD males.

CONCLUSIONS

Presence of sex specific changes in protein and amino acid metabolism and cardiometabolic health in COPD need to be considered when designing treatment regimens to restore muscle health in males and females with COPD.

CLINICAL TRIAL REGISTRY

www.

CLINICALTRIALS

gov, NCT01787682, NCT01624792, NCT02157844, NCT02065141, NCT02770092, NCT02780219, NCT03327181, NCT03796455, NCT01173354, NCT01154400.

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, oxidative, and inflammatory responses to acute exercise in chronic obstructive pulmonary disease

BACKGROUND

There is currently a need to identify metabolomic responses to acute exercise in chronic obstructive pulmonary disease (COPD).

OBJECTIVE

We investigated the metabolomic, oxidative, and inflammatory responses to constant (CE) and intermittent (IE) work rate exercises in COPD.

METHODS

Sixteen males with COPD performed a symptom-limited incremental cycle exercise test (ICE). Metabolomic, oxidative, and inflammatory responses to CE and IE (based on the performance of ICE) were analyzed in the plasma.

RESULTS

Fructose-6-phosphate, 3-phosphoglyceric acid, l-carnitine, and acylcarnitines levels were significantly decreased, whereas alpha-ketoglutaric, malic, 2-hydroxybutyric, and 3-hydroxybutyric acids were increased, after CE and IE (p<0.05). Increases in citric, isocitric, and lactic acids, as well as decreases in pyruvic and oxalic acids, were only present with IE (p<0.05). Isoleucine was decreased after both exercises (p<0.05). We observed an increase in inosine-5'-diphosphate, uric acid, ascorbic acid, and pantothenic acid, as well as a decrease in 5-hydroxymethyluridine, threonic acid, and dehydroascorbic acid, after IE (p<0.05). Catalase, reduced glutathione, and total antioxidant status difference values for both exercises were similar (p>0.05). The change in glutathione peroxidase (GPx) with CE was more significant than that with IE (p = 0.004). The superoxide dismutase change was greater with IE than with CE (p = 0.015). There were no significant changes in inflammatory markers after exercise (p>0.05).

CONCLUSION

CE and IE cause isoleucine, l-carnitine, and acylcarnitine levels to decrease, whereas ketone bodies were increased, thus indicating the energy metabolism shift from carbohydrates to amino acid utilization and lipid metabolism in COPD. Compared with CE, IE produces significant changes in more metabolomics in terms of carbohydrates, lipids, amino acids, nucleotides, and vitamins. Acute CE and IE alter circulating GPx levels in COPD.

Metabolism-Related Gene TXNRD1 Regulates Inflammation and Oxidative Stress Induced by Cigarette Smoke through the Nrf2/HO-1 Pathway in the Small Airway Epithelium

Chronic obstructive pulmonary disease (COPD), a small airway disease, is regarded as a metabolic disorder. To further uncover the metabolic profile of COPD patients, it is necessary to identify metabolism-related differential genes in small airway epithelium (SAE) of COPD. Metabolism-related differential genes in SAE between COPD patients and nonsmokers were screened from GSE128708 and GSE20257 datasets. KEGG, GO, and PPI analyses were performed to evaluate the pathway enrichment, term enrichment, and protein interaction of candidate metabolism-related differential genes, respectively. RT-PCR was used to verify the mRNA expression of the top ten differential genes. Western blotting was used to evaluate the protein expression of TXNRD1. TXNRD1 inhibitor auranofin (AUR) was used to assess the impact of TXNRD1 on oxidative stress and inflammation induced by cigarette smoke extraction (CSE). Twenty-four metabolism-related differential genes were selected. ALDH3A1, AKR1C3, CYP1A1, AKC1C1, CPY1B1, and TXNRD1 in the top ten genes were significantly upregulated after CSE simulation for 24 h in human bronchial epithelial (16HBE) cells. Among them, CYP1A1 and TXNRD1 also have a significant upregulation in primary SAE after simulation of CSE for 24 h. The overexpression of protein TXNRD1 has also been detected in 16HBE cells, primary SAE stimulated with CSE, and mouse lung exposed to cigarette smoke (CS). Additionally, inhibition of TXNRD1 with 0.1 μM AUR alleviated the expression of IL-6 and reactive oxygen species (ROS) induced by CSE by activating the Nrf2/HO-1 pathway in 16HBE cells. This study identified twenty-four metabolism-related differential genes associated with COPD. TXNRD1 might participate in the oxidative stress and inflammation induced by CS by regulating the activation of the Nrf2/HO-1 pathway.

Impact of JAK/STAT inhibitors on human monocyte-derived-macrophages stimulated by cigarette smoke extract and lipopolysaccharide

The main risk factor for chronic obstructive pulmonary disease (COPD) is cigarette smoke (CS). It can alter many immune cells functions such as phagocytosis, efferocytosis and cytokine production. Cytokines play a role in the orchestration of inflammation in COPD. The JAK/STAT pathways are among the most important signalling components of cytokines. The objective of this work was to investigate the role of the JAK/STAT pathway with regard to cytokine release and microsphere uptake capacity (to minimize the non-specific scavenging) in human monocyte-derived-macrophages (MDMs). The MDMs were stimulated by cigarette smoke extract (CSE) alone or in combination with lipopolysaccharide (LPS). CSE alone was not associated with significant changes in the cytokine, with the exception of IL-8/CXCL8 production. However, CSE disturbed cytokine production in LPS-stimulated MDMs. CSE increase CXCL-8 and CCL2 release in LPS-stimulated monocyte-derived macrophages and suppressed the production of IL-6 and CXCL1 in these cells. CSE also decreased microsphere uptake capacity by MDMs. Then, CSE + LPS-stimulated MDMs were treated with two different JAK inhibitors. AG490 (specific inhibitor of JAK2) and ruxolitinib (inhibitor of JAK1 and JAK2). JAK/STAT inhibitors, particularly ruxolitinib, attenuated in cytokine production without completely inhibiting when compared with dexamethasone. On the other hand, the cells exposed to dexamethasone are nearly unable to capture the microspheres, while both JAK inhibitors do not affect the uptake capacity. In summary, our results showed the versatility of ruxolitinib which might bring a better balance disturbance of cytokine release and uptake capacity. The information regarding the distinctive effect of JAK/STAT inhibitors may be useful in the development of novel treatments for COPD.

Metabolomics Reveals Dysregulated Sphingolipid and Amino Acid Metabolism Associated with Chronic Obstructive Pulmonary Disease

Purpose

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease presenting as multiple phenotypes, such as declining lung function, emphysema, or persistent airflow limitation caused by several risk factors, including cigarette smoking and air pollution. The inherent complexity of COPD phenotypes propounds difficulties for accurate diagnosis and prognosis. Although metabolomic profiles on COPD have been reported, the role of metabolism in COPD-related phenotypes is yet to be determined. In this study, we investigated the association between plasma sphingolipids and amino acids, and between COPD and COPD-related phenotypes in a Korean cohort.

Patients and Methods

Blood samples were collected from 120 patients with COPD and 80 control participants who underwent spirometry and quantitative computed tomography. The plasma metabolic profiling was carried out using LC-MS/MS analysis.

Results

Among the evaluated plasma sphingolipids, an increase in the metabolism of two specific sphingomyelins, SM (d18:1/24:0) and SM (d18:1/24:1) were significantly associated with COPD. There was no significant correlation between any of the SMs and the emphysema index, FVC and FEV₁ in the COPD cohort. Meanwhile, Cer (d18:1/18:0) and Cer (d18:1/24:1) were significantly associated with reduced FEV₁. Furthermore, the levels of several amino acids were altered in the COPD group compared to that in the non-COPD group; glutamate and alpha AAA were substantial associated with emphysema in COPD. Kynurenine was the only amino acid significantly associated with reduced FEV₁ in COPD. In contrast, there was no correlation between FVC and the elevated metabolites.

Conclusion

Our results provide dysregulated plasma metabolites impacting COPD phenotypes, although more studies are needed to explore the underlying mechanism related to COPD pathogenesis.

Lung Microbiota and Metabolites Collectively Associate with Clinical Outcomes in Milder Stage Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is variable in its development. Lung microbiota and metabolites collectively may impact COPD pathophysiology, but relationships to clinical outcomes in milder disease are unclear. Objectives: Identify components of the lung microbiome and metabolome collectively associated with clinical markers in milder stage COPD. Methods: We analyzed paired microbiome and metabolomic data previously characterized from bronchoalveolar lavage fluid in 137 participants in the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), or (GOLD [Global Initiative for Chronic Obstructive Lung Disease Stage 0-2). Datasets used included 1) bacterial 16S rRNA gene sequencing; 2) untargeted metabolomics of the hydrophobic fraction, largely comprising lipids; and 3) targeted metabolomics for a panel of hydrophilic compounds previously implicated in mucoinflammation. We applied an integrative approach to select features and model 14 individual clinical variables representative of known associations with COPD trajectory (lung function, symptoms, and exacerbations). Measurements and Main Results: The majority of clinical measures associated with the lung microbiome and metabolome collectively in overall models (classification accuracies, >50%, P < 0.05 vs. chance). Lower lung function, COPD diagnosis, and greater symptoms associated positively with Streptococcus, Neisseria, and Veillonella, together with compounds from several classes (glycosphingolipids, glycerophospholipids, polyamines and xanthine, an adenosine metabolite). In contrast, several Prevotella members, together with adenosine, 5'-methylthioadenosine, sialic acid, tyrosine, and glutathione, associated with better lung function, absence of COPD, or less symptoms. Significant correlations were observed between specific metabolites and bacteria (Padj < 0.05). Conclusions: Components of the lung microbiome and metabolome in combination relate to outcome measures in milder COPD, highlighting their potential collaborative roles in disease pathogenesis.

A Metabolomic Severity Score for Airflow Obstruction and Emphysema

Chronic obstructive pulmonary disease (COPD) is a disease with marked metabolic disturbance. Previous studies have shown the association between single metabolites and lung function for COPD, but whether a combination of metabolites could predict phenotype is unknown. We developed metabolomic severity scores using plasma metabolomics from the Metabolon platform from two US cohorts of ever-smokers: the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) (n = 648; training/testing cohort; 72% non-Hispanic, white; average age 63 years) and the COPDGene Study (n = 1120; validation cohort; 92% non-Hispanic, white; average age 67 years). Separate adaptive LASSO (adaLASSO) models were used to model forced expiratory volume at one second (FEV1) and MESA-adjusted lung density using 762 metabolites common between studies. Metabolite coefficients selected by the adaLASSO procedure were used to create a metabolomic severity score (metSS) for each outcome. A total of 132 metabolites were selected to create a metSS for FEV1. The metSS-only models explained 64.8% and 31.7% of the variability in FEV1 in the training and validation cohorts, respectively. For MESA-adjusted lung density, 129 metabolites were selected, and metSS-only models explained 59.0% of the variability in the training cohort and 17.4% in the validation cohort. Regression models including both clinical covariates and the metSS explained more variability than either the clinical covariate or metSS-only models (53.4% vs. 46.4% and 31.6%) in the validation dataset. The metabolomic pathways for arginine biosynthesis; aminoacyl-tRNA biosynthesis; and glycine, serine, and threonine pathway were enriched by adaLASSO metabolites for FEV1. This is the first demonstration of a respiratory metabolomic severity score, which shows how a metSS can add explanation of variance to clinical predictors of FEV1 and MESA-adjusted lung density. The advantage of a comprehensive metSS is that it explains more disease than individual metabolites and can account for substantial collinearity among classes of metabolites. Future studies should be performed to determine whether metSSs are similar in younger, and more racially and ethnically diverse populations as well as whether a metabolomic severity score can predict disease development in individuals who do not yet have COPD.

Detection of the Disorders of Glycerophospholipids and Amino Acids Metabolism in Lung Tissue From Male COPD Patients

Background: At present, few studies have reported the metabolic profiles of lung tissue in patients with COPD. Our study attempted to analyze the lung metabolome in male COPD patients and to screen the overlapping biomarkers of the lung and plasma metabolomes.

Methods: We performed untargeted metabolomic analysis of normal lung tissue from two independent sets (the discovery set: 20 male COPD patients and 20 controls and the replication set: 47 male COPD patients and 27 controls) and of plasma samples from 80 male subjects containing 40 COPD patients and 40 controls.

Results: We found glycerophospholipids (GPs) and Amino acids were the primary classes of differential metabolites between male COPD patients and controls. The disorders of GPs metabolism and the valine, leucine and isoleucine biosynthesis metabolism pathways were identified in lung discovery set and then also validated in the lung replication set. Combining lung tissue and plasma metabolome, Phytosphingosine and l-tryptophan were two overlapping metabolites biomarkers. Binary logistic regression suggested that phytosphingosine together with l-tryptophan was closely associated with male COPD and showed strong diagnostic power with an AUC of 0.911 (95% CI: 0.8460-0.9765).

Conclusion: Our study revealed the metabolic perturbations of lung tissues from male COPD patients. The detected disorders of GPs and amino acids may provide an insight into the pathological mechanism of COPD. Phytosphingosine and l-tryptophan were two novel metabolic biomarkers for differentiating COPD patients and controls.

Comprehensive Targeted Metabolomic Study in the Lung, Plasma, and Urine of PPE/LPS-Induced COPD Mice Model

(1) Background: Progression of chronic obstructive pulmonary disease (COPD) leads to irreversible lung damage and inflammatory responses; however, biomarker discovery for monitoring of COPD progression remains challenging. (2) Methods: This study evaluated the metabolic mechanisms and potential biomarkers of COPD through the integrated analysis and receiver operating characteristic (ROC) analysis of metabolic changes in lung, plasma, and urine, and changes in morphological characteristics and pulmonary function in a model of PPE/LPS-induced COPD exacerbation. (3) Results: Metabolic changes in the lungs were evaluated as metabolic reprogramming to counteract the changes caused by the onset of COPD. In plasma, several combinations of phenylalanine, 3-methylhistidine, and polyunsaturated fatty acids have been proposed as potential biomarkers; the α-aminobutyric acid/histidine ratio has also been reported, which is a novel candidate biomarker for COPD. In urine, a combination of succinic acid, isocitric acid, and pyruvic acid has been proposed as a potential biomarker. (4) Conclusions: This study proposed potential biomarkers in plasma and urine that reflect altered lung metabolism in COPD, concurrently with the evaluation of the COPD exacerbation model induced by PPE plus LPS administration. Therefore, understanding these integrative mechanisms provides new insights into the diagnosis, treatment, and severity assessment of COPD.

Optical biosensing of markers of mucosal inflammation

We report the design and adaptation of iron/iron oxide nanoparticle-based optical nanobiosensors for enzymes or cytokine/chemokines that are established biomarkers of lung diseases. These biomarkers comprise ADAM33, granzyme B, MMP-8, neutrophil elastase, arginase, chemokine (C-C motif) ligand 20 and interleukin-6. The synthesis of nanobiosensors for these seven biomarkers, their calibration with commercially available enzymes and cytokines/chemokines, as well as their validation using bronchoalveolar lavage (BAL) obtained from a mouse model of TLR3-mediated inflammation are discussed here. Exhaled Breath Condensate (EBC) is a minimally invasive approach for sampling airway fluid in the diagnosis and management of various lung diseases in humans (e.g., asthma, COPD and viral infections). We report the proof-of-concept of using human EBC in conjunction with nanobiosensors for diagnosis/monitoring airway inflammation. These findings suggest that, with nanosensor technology, human EBC can be utilized as a liquid biopsy to monitor inflammation/remodeling in lung disease.

Ageing mechanisms that contribute to tissue remodeling in lung disease

Age is a major risk factor for chronic respiratory diseases such as idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD) and certain phenotypes of asthma. The recent COVID-19 pandemic also highlights the increased susceptibility of the elderly to acute respiratory distress syndrome (ARDS), a diffuse inflammatory lung injury with often long-term effects (ie parenchymal fibrosis). Collectively, these lung conditions are characterized by a pathogenic reparative process that, rather than restoring organ function, contributes to structural and functional tissue decline. In the ageing lung, the homeostatic control of wound healing following challenge or injury has an increased likelihood of being perturbed, increasing susceptibility to disease. This loss of fidelity is a consequence of a diverse range of underlying ageing mechanisms including senescence, mitochondrial dysfunction, proteostatic stress and diminished autophagy that occur within the lung, as well as in other tissues, organs and systems of the body. These ageing pathways are highly interconnected, involving localized and systemic increases in inflammatory mediators and damage associated molecular patterns (DAMPs); along with corresponding changes in immune cell function, metabolism and composition of the pulmonary and gut microbiomes. Here we comprehensively review the roles of ageing mechanisms in the tissue remodeling of lung disease.

Identification of Metabolism-Associated Molecular Subtypes of Chronic Obstructive Pulmonary Disease

Purpose

This study aimed to identify the COPD molecular subtypes reflecting pulmonary function damage on the basis of metabolism-related gene expression, which provided the opportunity to study the metabolic heterogeneity and the association of metabolic pathways with pulmonary function damage.

Methods

Univariate linear regression and the Boruta algorithm were used to select metabolism-related genes associated with forced expiratory volume in the first second (FEV1) and FEV1/forced vital capacity (FVC) in the Evaluation of COPD to Longitudinally Identify Predictive Surrogate Endpoints (ECLIPSE) cohort. COPD subtypes were further identified by consensus clustering with best-fit. Then, we analyzed the differences in the clinical characteristics, metabolic pathways, immune cell characteristics, and transcription features among the subtypes.

Results

This study identified two subtypes (C1 and C2). C1 exhibited higher levels of lower pulmonary function and innate immunity than C2. Ten metabolic pathways were confirmed as key metabolic pathways. The pathways related to N-glycan, hexosamine, purine, alanine, aspartate and glutamate tended to be positively associated with the abundance of adaptive immune cells and negatively associated with the abundance of innate immune cells. In addition, other pathways had opposite trends. All results were verified in Genetic Epidemiology of COPD (COPDGene) datasets.

Conclusion

The two subtypes reflect the pulmonary function damage and help to further understand the metabolic mechanism of pulmonary function in COPD. Further studies are needed to prove the prognostic and therapeutic value of the subtypes.

Histidine ameliorates elastase- and lipopolysaccharide-induced lung inflammation by inhibiting the activation of the NLRP3 inflammasome

Histidine treatment has anti-inflammatory effects on several diseases such as colitis and obesity. We revealed that histidine levels were decreased in the serum of patients with chronic obstructive pulmonary disease (COPD) in our previous study. However, whether histidine confers protection against COPD is unclear. In the present study, we evaluated the protective effects of histidine in a porcine pancreatic elastase- and lipopolysaccharide-induced COPD mouse model. We found that the serum histidine concentration was decreased in COPD mice. Histidine supplementation improved the COPD mouse lung function and reduced the inflammatory cell counts and production of cytokines in bronchoalveolar lavage fluid. In addition, histidine treatment ameliorated lung inflammation by inhibiting the nucleotide-binding oligomerization domain-like receptor (NLR) family pyrin domain-containing 3 inflammasome activation both in vivo and in vitro. Furthermore, we found that the potential anti-inflammatory mechanism involved the upregulation of silent information regulator factor 2-related enzyme 1. These results suggest that histidine may be a valuable therapeutic target for COPD.

The Ability of Metabolomics to Discriminate Non-Small-Cell Lung Cancer Subtypes Depends on the Stage of the Disease and the Type of Material Studied

Identification of the NSCLC subtype at an early stage is still quite sophisticated. Metabolomics analysis of tissue and plasma of NSCLC patients may indicate new, and yet unknown, metabolic pathways active in the NSCLC. Our research characterized the metabolomics profile of tissue and plasma of patients with early and advanced NSCLC stage. Samples were subjected to thorough metabolomics analyses using liquid chromatography-mass spectrometry (LC-MS) technique. Tissue and/or plasma samples from 137 NSCLC patients were analyzed. Based on the early stage tissue analysis, more than 200 metabolites differentiating adenocarcinoma (ADC) and squamous cell lung carcinoma (SCC) subtypes as well as normal tissue, were identified. Most of the identified metabolites were amino acids, fatty acids, carnitines, lysoglycerophospholipids, sphingomyelins, plasmalogens and glycerophospholipids. Moreover, metabolites related to N-acyl ethanolamine (NAE) biosynthesis, namely glycerophospho (N-acyl) ethanolamines (GP-NAE), which discriminated early-stage SCC from ADC, have also been identified. On the other hand, the analysis of plasma of chronic obstructive pulmonary disease (COPD) and NSCLC patients allowed exclusion of the metabolites related to the inflammatory state in lungs and the identification of compounds (lysoglycerophospholipids, glycerophospholipids and sphingomyelins) truly characteristic to cancer. Our results, among already known, showed novel, thus far not described, metabolites discriminating NSCLC subtypes, especially in the early stage of cancer. Moreover, the presented results also indicated the activity of new metabolic pathways in NSCLC. Further investigations on the role of NAE biosynthesis pathways in the early stage of NSCLC may reveal new prognostic and diagnostic targets.

Metabolic Fingerprinting Uncovers the Distinction Between the Phenotypes of Tuberculosis Associated COPD and Smoking-Induced COPD

Background: Although smoking is considered the main cause of chronic obstructive pulmonary disease (COPD), several other risk factors, including pulmonary tuberculosis (TB), contribute significantly to disease causation, particularly in developing countries. However, the underlying pathogenesis of TB-associated COPD (T-COPD) is unclear. Moreover, the need for prompt diagnosis and treatment of T-COPD to decrease the future burden of inflammation is underestimated. This study aimed to identify distinctive endogenous metabotypes of T-COPD, compared to smoking-associated COPD (S-COPD). Methods: Cross-sectional metabolomic analyses and clinical examinations of serum samples were performed for three groups of 168 male subjects: T-COPD (n = 59), S-COPD (n = 70), and healthy normal controls (n = 39). To retain a broad spectrum of metabolites, we performed technically distinct analyses (global metabolomic profiling using LC-QTOFMS and targeted analyses using LC-MS/MS). Results: Higher levels of IL-6 and C-reactive protein and St. George Respiratory Questionnaire scores were seen in the T-COPD group, compared to those in the S-COPD group. Global metabolomic profiling showed elevated metabolites, including arachidonic and eicosanoic acids, in the T-COPD group. Typical changes in tryptophan catabolism were observed through targeted profiling. Additionally, in the T-COPD group, kynurenine was elevated, and serotonin levels were reduced; therefore, indoleamine dioxygenase (IDO)/tryptophan hydroxylase (TPH) activities were dysregulated. Correlation analyses showed that changes in oxylipins were positively correlated with serum levels of IL-6 and C-reactive protein. Conclusion: Patients with TB-related COPD have enhanced inflammatory responses that may be linked to fatty acid pathways and tryptophan catabolism, which could be novel therapeutic targets for T-COPD.

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.

Metabolic reprogramming: A driver of cigarette smoke-induced inflammatory lung diseases

Cigarette smoking is a well-known risk factor for pulmonary diseases, including chronic obstructive pulmonary disease (COPD), asthma and pulmonary fibrosis. Despite major progress in dissecting the mechanisms associated with disease development and progression, findings only represent one aspect of multifaceted disease. A crucial consequence of this approach is that many therapeutic treatments often fail to improve or reverse the disease state as other conditions and variables are insufficiently considered. To expand our understanding of pulmonary diseases, omics approaches, particularly metabolomics, has been emerging in the field. This strategy has been applied to identify putative biomarkers and novel mechanistic insights. In this review, we discuss metabolic profiles of patients with COPD, asthma, and idiopathic pulmonary fibrosis (IPF) with a focus on the direct effects of cigarette smoking in altering metabolic regulation. We next present cell- and animal-based experiments and point out the therapeutic potential of targeting metabolic reprogramming in inflammatory lung diseases. In addition, the obstacles in translating these findings into clinical practice, including potential adverse effects and limited pharmacological efficacy, are also addressed.

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.

Induced sputum metabolomic profiles and oxidative stress are associated with chronic obstructive pulmonary disease (COPD) severity: potential use for predictive, preventive, and personalized medicine

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous disease, and metabolomics plays a hub role in predictive, preventive, and personalized medicine (PPPM) related to COPD. This study thus aimed to reveal the role of induced sputum metabolomics in predicting COPD severity. In this pilot study, a total of 20 COPD patients were included. The induced sputum metabolites were assayed using a liquid chromatography-mass spectrometry (LC-MS/MS) system. Five oxidative stress products (myeloperoxidase (MPO), superoxide dismutase (SOD), glutathione (GSH), neutrophil elastase (NE), and 8-iso-PGF2α) in induced sputum were measured by ELISA, and the metabolomic profiles were distinguished by principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA). The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for pathway enrichment analysis, and a significant difference in induced sputum metabolomics was observed between moderate and severe COPD. The KEGG analysis revealed that the glycerophospholipid metabolism pathway was downregulated in severe COPD. Due to the critical role of glycerophospholipid metabolism in oxidative stress, significant negative correlations were discovered between glycerophospholipid metabolites and three oxidative stress products (SOD, MPO, and 8-iso-PGF2α). The diagnostic values of SOD, MPO, and 8-iso-PGF2α in induced sputum were found to exhibit high sensitivities and specificities in the prediction of COPD severity. Collectively, this study provides the first identification of the association between induced sputum metabolomic profiles and COPD severity, indicating the potential value of metabolomics in PPPM for COPD management. The study also reveals the correlation between glycerophospholipid metabolites and oxidative stress products and their value for predicting COPD severity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-020-00227-w.

Continued post-retraction citation of a fraudulent clinical trial report, 11 years after it was retracted for falsifying data

This paper presents a case study of long-term post-retraction citation to falsified clinical trial data (Matsuyama et al. in Chest 128(6):3817–3827, 2005. 10.1378/chest.128.6.3817), demonstrating problems with how the current digital library environment communicates retraction status. Eleven years after its retraction, the paper continues to be cited positively and uncritically to support a medical nutrition intervention, without mention of its 2008 retraction for falsifying data. To date no high quality clinical trials reporting on the efficacy of omega-3 fatty acids on reducing inflammatory markers have been published. Our paper uses network analysis, citation context analysis, and retraction status visibility analysis to illustrate the potential for extended propagation of misinformation over a citation network, updating and extending a case study of the first 6 years of post-retraction citation (Fulton et al. in Publications 3(1):7–26, 2015. 10.3390/publications3010017). The current study covers 148 direct citations from 2006 through 2019 and their 2542 second-generation citations and assesses retraction status visibility of the case study paper and its retraction notice on 12 digital platforms as of 2020. The retraction is not mentioned in 96% (107/112) of direct post-retraction citations for which we were able to conduct citation context analysis. Over 41% (44/107) of direct post-retraction citations that do not mention the retraction describe the case study paper in detail, giving a risk of diffusing misinformation from the case paper. We analyze 152 second-generation citations to the most recent 35 direct citations (2010–2019) that do not mention the retraction but do mention methods or results of the case paper, finding 23 possible diffusions of misinformation from these non-direct citations to the case paper. Link resolving errors from databases show a significant challenge in a reader reaching the retraction notice via a database search. Only 1/8 databases (and 1/9 database records) consistently resolved the retraction notice to its full-text correctly in our tests. Although limited to evaluation of a single case (N = 1), this work demonstrates how retracted research can continue to spread and how the current information environment contributes to this problem.

Association between Metabolites and the Risk of Lung Cancer: A Systematic Literature Review and Meta-Analysis of Observational Studies

Globally, lung cancer is the most prevalent cancer type. However, screening and early detection is challenging. Previous studies have identified metabolites as promising lung cancer biomarkers. This systematic literature review and meta-analysis aimed to identify metabolites associated with lung cancer risk in observational studies. The literature search was performed in PubMed and EMBASE databases, up to 31 December 2019, for observational studies on the association between metabolites and lung cancer risk. Heterogeneity was assessed using the I2 statistic and Cochran's Q test. Meta-analyses were performed using either a fixed-effects or random-effects model, depending on study heterogeneity. Fifty-three studies with 297 metabolites were included. Most identified metabolites (252 metabolites) were reported in individual studies. Meta-analyses were conducted on 45 metabolites. Five metabolites (cotinine, creatinine riboside, N-acetylneuraminic acid, proline and r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene) and five metabolite groups (total 3-hydroxycotinine, total cotinine, total nicotine, total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (sum of concentrations of the metabolite and its glucuronides), and total nicotine equivalent (sum of total 3-hydroxycotinine, total cotinine and total nicotine)) were associated with higher lung cancer risk, while three others (folate, methionine and tryptophan) were associated with lower lung cancer risk. Significant heterogeneity was detected across most studies. These significant metabolites should be further evaluated as potential biomarkers for lung cancer.

Integrative clinical, genomics and metabolomics data analysis for mainstream precision medicine to investigate COVID-19

Despite significant scientific and medical discoveries, the genetics of novel infectious diseases like COVID-19 remains far from understanding. SARS-CoV-2 is a single-stranded RNA respiratory virus that causes COVID-19 by binding to the ACE2 receptor in the lung and other organs. Understanding its clinical presentation and metabolomic and genetic profile will lead to the discovery of diagnostic, prognostic and predictive biomarkers, which may lead to more effective medical therapy. It is important to investigate correlations and overlap between reported diagnoses of a patient with COVID-19 in clinical data with identified germline and somatic mutations, and highly expressed genes from genomics data analysis. Timely model clinical, genomics and metabolomics data to find statistical patterns across millions of features to identify underlying biological pathways, modifiable risk factors and actionable information that supports early detection and prevention of COVID-19, and development of new therapies for better patient care. Next, ensuring security reconcile noise, need to build and train machine learning prognostic models to find actionable information that supports early detection and prevention of COVID-19. Based on the myriad data, applying appropriate machine learning algorithms to stratify patients, understand scenarios, optimise decision-making, identify high-risk rare variants (including ACE2, TMPRSS2) and making medically relevant predictions. Innovative and intelligent solutions are required to improve the traditional symptom-driven practice, and allow earlier interventions using predictive diagnostics and tailor better personalised treatments, when confronted with the challenges of pandemic situations.

Metabolic profiling of organic and fatty acids in chronic and autoimmune diseases

Metabolomics is a powerful tool of omics that permits the simultaneous identification of metabolic perturbations in several autoimmune and chronic diseases. Several parameters can affect a metabolic profile, from the population characteristics to the selection of the analytical method. In the current chapter, we summarize the main analytical methods and results of the metabolic profiling of fatty and organic acids performed in human metabolomic studies for asthma, COPD, psoriasis and Hashimoto's thyroiditis. We discuss the most significant metabolic alterations associated with these diseases, after comparison of either a single patient's group with healthy controls or several patient's subgroups of different disease severity and phenotype with healthy controls or of a patient's group before and after treatment. Finally, we present critical metabolic patterns that are associated with each disease and their potency for the unraveling of disease pathogenesis, prediction, diagnosis, patient stratification and treatment selection.

Comprehensive metabolic flux analysis to explain skeletal muscle weakness in COPD

BACKGROUND & AIMS

Metabolic characterization of a well-defined group of patients could be a powerful tool in revealing metabolic signatures to explain limb muscle weakness in chronic diseases. Studies are currently limited in Chronic Obstructive Pulmonary Disease (COPD) to the identification of differential amino acid concentrations but lack comprehensive analysis of the flux through relevant muscle function related metabolic pathways.

METHODS

In 23 stable patients with moderate to very severe COPD and 19 healthy controls, a comprehensive metabolic flux analysis was conducted by administering an intravenous pulse and primed constant infusion of multiple stable tracers of amino acids known to play a role in muscle health. Blood samples were obtained to calculate production (WBP) and interconversion rates, and plasma concentrations of these amino acids. Lower and upper limb muscle strength, muscle mass, lung function, physical activity level, and disease history and characteristics were assessed.

RESULTS

The COPD group was characterized by lower and upper limb muscle weakness (P < 0.01) despite preserved muscle mass. Higher values were found in COPD for plasma glutamine, WBP of leucine (P < 0.001), 3-methylhistidine (P < 0.01) (marker of enhanced myofibrillar protein breakdown), citrulline (P < 0.05), and arginine to citrulline conversion (P < 0.05) (reflecting enhanced nitric oxide synthesis). Plasma concentration of β-hydroxy β-methylbutyrate (HMB with anticatabolic, anabolic and contractile properties), WBP of glycine (precursor of creatine and glutathione), and transcutaneous O₂ saturation explained up to 79% and 65% of the variation in strength of the lower and upper limb muscles, respectively, in COPD.

CONCLUSIONS

Comprehensive metabolic flux analysis revealed a homogenous metabolic signature in stable patients with COPD and a specific metabolic profile in those with skeletal muscle weakness.

CLINICAL TRIAL REGISTRY

ClinicalTrials.gov; No. NCT01787682; URL: www.clinicaltrials.gov.

Plasma Metabolomics and Lipidomics Reveal Perturbed Metabolites in Different Disease Stages of Chronic Obstructive Pulmonary Disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a common disease characterized by persistent respiratory symptoms and airflow restriction. It is usually manifested as airway and/or alveolar abnormalities caused by significant exposure to harmful particulates or gases.

OBJECTIVE

We aim to explore plasma metabolomic changes in the acute exacerbation stage of COPD (AECOPD) and stable stage of COPD (Stable COPD) to identify potential biomarkers for diagnosis or prognosis in clinical practice.

METHODS

Untargeted metabolomics and lipidomics analyses were performed to investigate dysregulated molecules in blood plasma of AECOPD patients (n=48) and Stable COPD (n=48), and a cohort of healthy people were included as a control group (n=48). Statistical analysis and bioinformatics analysis were performed to reveal dysregulated metabolites and perturbed metabolic pathways. SVM-based multivariate ROC analysis was used for candidate biomarker screening.

RESULTS

A total of 142 metabolites and 688 lipids were dysregulated in COPD patients. Pathway enrichment analysis showed that several metabolic pathways were perturbed after COPD onset. Several biomarker panels were proposed for diagnosis of COPD vs healthy control and AECOPD vs Stable COPD with AUC greater than 0.9.

CONCLUSION

Numerous plasma metabolites and several metabolic pathways were detected relevant to COPD disease onset or progression. These metabolites may be considered as candidate biomarkers for diagnosis or prognosis of COPD. The perturbed pathways involved in COPD provide clues for further pathological mechanism studies of COPD.

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.