Identification of lipid biomarker from serum in patients with chronic obstructive pulmonary disease

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.

Computational Analysis of Plasma Lipidomics from Mice Fed Standard Chow and Ketogenic Diet

Dietary saturated fatty acids (SFAs) are upregulated in the blood circulation following digestion. A variety of circulating lipid species have been implicated in metabolic and inflammatory diseases; however, due to the extreme variability in serum or plasma lipid concentrations found in human studies, established reference ranges are still lacking, in addition to lipid specificity and diagnostic biomarkers. Mass spectrometry is widely used for identification of lipid species in the plasma, and there are many differences in sample extraction methods within the literature. We used ultra-high performance liquid chromatography (UPLC) coupled to a high-resolution hybrid triple quadrupole-time-of-flight (QToF) mass spectrometry (MS) to compare relative peak abundance of specific lipid species within the following lipid classes: free fatty acids (FFAs), triglycerides (TAGs), phosphatidylcholines (PCs), and sphingolipids (SGs), in the plasma of mice fed a standard chow (SC; low in SFAs) or ketogenic diet (KD; high in SFAs) for two weeks. In this protocol, we used Principal Component Analysis (PCA) and R to visualize how individual mice clustered together according to their diet, and we found that KD-fed mice displayed unique blood profiles for many lipid species identified within each lipid class compared to SC-fed mice. We conclude that two weeks of KD feeding is sufficient to significantly alter circulating lipids, with PCs being the most altered lipid class, followed by SGs, TAGs, and FFAs, including palmitic acid (PA) and PA-saturated lipids. This protocol is needed to advance knowledge on the impact that SFA-enriched diets have on concentrations of specific lipids in the blood that are known to be associated with metabolic and inflammatory diseases. Key features • Analysis of relative plasma lipid concentrations from mice on different diets using R. • Lipidomics data collected via ultra-high performance liquid chromatography (UPLC) coupled to a high-resolution hybrid triple quadrupole-time-of-flight (QToF) mass spectrometry (MS). • Allows for a comprehensive comparison of diet-dependent plasma lipid profiles, including a variety of specific lipid species within several different lipid classes. • Accumulation of certain free fatty acids, phosphatidylcholines, triglycerides, and sphingolipids are associated with metabolic and inflammatory diseases, and plasma concentrations may be clinically useful.

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.

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 of asthma, COPD, and asthma-COPD overlap: an overview

The two common progressive lung diseases, asthma and chronic obstructive pulmonary disease (COPD), are the leading causes of morbidity and mortality worldwide. Asthma-COPD overlap, referred to as ACO, is another complex pulmonary disease that manifests itself with features of both asthma and COPD. The disease has no clear diagnostic or therapeutic guidelines, thereby making both diagnosis and treatment challenging. Though a number of studies on ACO have been documented, gaps in knowledge regarding the pathophysiologic mechanism of this disorder exist. Addressing this issue is an urgent need for improved diagnostic and therapeutic management of the disease. Metabolomics, an increasingly popular technique, reveals the pathogenesis of complex diseases and holds promise in biomarker discovery. This comprehensive narrative review, comprising 99 original research articles in the last five years (2017-2022), summarizes the scientific advances in terms of metabolic alterations in patients with asthma, COPD, and ACO. The analytical tools, nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS), commonly used to study the expression of the metabolome, are discussed. Challenges frequently encountered during metabolite identification and quality assessment are highlighted. Bridging the gap between phenotype and metabotype is envisioned in the future.

Applying Next-Generation Sequencing and Multi-Omics in Chronic Obstructive Pulmonary Disease

Microbiomics have significantly advanced over the last decade, driven by the widespread availability of next-generation sequencing (NGS) and multi-omic technologies. Integration of NGS and multi-omic datasets allow for a holistic assessment of endophenotypes across a range of chronic respiratory disease states, including chronic obstructive pulmonary disease (COPD). Valuable insight has been attained into the nature, function, and significance of microbial communities in disease onset, progression, prognosis, and response to treatment in COPD. Moving beyond single-biome assessment, there now exists a growing literature on functional assessment and host-microbe interaction and, in particular, their contribution to disease progression, severity, and outcome. Identifying specific microbes and/or metabolic signatures associated with COPD can open novel avenues for therapeutic intervention and prognosis-related biomarkers. Despite the promise and potential of these approaches, the large amount of data generated by such technologies can be challenging to analyze and interpret, and currently, there remains a lack of standardized methods to address this. This review outlines the current use and proposes future avenues for the application of NGS and multi-omic technologies in the endophenotyping, prognostication, and treatment of COPD.

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.

Lipid network and moiety analysis for revealing enzymatic dysregulation and mechanistic alterations from lipidomics data

Lipidomics is of growing importance for clinical and biomedical research due to many associations between lipid metabolism and diseases. The discovery of these associations is facilitated by improved lipid identification and quantification. Sophisticated computational methods are advantageous for interpreting such large-scale data for understanding metabolic processes and their underlying (patho)mechanisms. To generate hypothesis about these mechanisms, the combination of metabolic networks and graph algorithms is a powerful option to pinpoint molecular disease drivers and their interactions. Here we present lipid network explorer (LINEX$^2$), a lipid network analysis framework that fuels biological interpretation of alterations in lipid compositions. By integrating lipid-metabolic reactions from public databases, we generate dataset-specific lipid interaction networks. To aid interpretation of these networks, we present an enrichment graph algorithm that infers changes in enzymatic activity in the context of their multispecificity from lipidomics data. Our inference method successfully recovered the MBOAT7 enzyme from knock-out data. Furthermore, we mechanistically interpret lipidomic alterations of adipocytes in obesity by leveraging network enrichment and lipid moieties. We address the general lack of lipidomics data mining options to elucidate potential disease mechanisms and make lipidomics more clinically relevant.

Hierarchical stratification of the factors related to exertional dyspnoea and exercise intolerance in male COPD patients

BACKGROUND

The order and extent of interactions across the factors affecting exertional dyspnoea (ED) and exercise intolerance (EI) in patients with chronic obstructive pulmonary disease (COPD) are not clear. We hypothesized that lung and non-lung variables were the primary variables, ED was the secondary variable and EI was the tertiary variable.

METHODS

Data on demographics, blood tests, cardiac imaging, lung function tests and invasive dead space fractions (V_D/V_T) during incremental exercise test of 46 male COPD subjects were obtained. These variables were categorized by factor analysis and pair-wise correlation analysis was conducted. The best factor of each category was selected and then multivariate regression was conducted.

RESULTS

Peak tidal inspiratory flow (V_T/T_Ipeak), V_D/V_Tpeak and tidal lung expansion capability, and resting diffusing capacity of the lungs (D_LCO)% predicted were the primary pulmonary factors most related to ED, whereas body mass index (BMI), haemoglobin and cholesterol levels were the primary non-pulmonary factors. In multivariate regression analysis, V_T/T_Ipeak, V_D/V_Tpeak and D_LCO% were the primary factors most related to ED (r² = 0.69); ED was most related to EI (r = -0.74 to -0.83).

CONCLUSION

Using hierarchical stratification and statistical methods may improve understanding of the pathophysiology of ED and EI in patients with COPD. KEY MESSAGESThe pathophysiology of exertional dyspnoea (ED) and exercise intolerance (EI) in chronic obstructive pulmonary disease (COPD) is complex. The order and extent of interactions across factors are not clear. In multivariate regression analysis, we found that tidal inspiratory flow, dead space fraction and resting diffusing capacity of the lungs % but not the non-pulmonary factors affected ED.Using correlation coefficients, we further found that ED was the secondary variable and EI was the tertiary variable.Hierarchical stratification of the important factors associated with ED and EI in patients with COPD clarifies their relationships and could be incorporated into management programmes and outcome studies for these patients.

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.

Regulatory roles of external cholesterol in human airway epithelial mitochondrial function through STARD3 signalling

BACKGROUND

Hypercholesterolemia is found in patients with chronic lung inflammation, during which airway epithelial cells play important roles in maintenance of inflammatory responses to pathogens. The present study aims at molecular mechanisms by which cholesterol changes airway epithelial sensitivity in response to smoking.

METHODS

Human bronchial epithelial cells (HBEs) were stimulated with cigarette smoke extract (CSE) and mice were exposed to CS/lipopolysaccharide (LPS) as models in vitro and in vivo. Severe COPD patients and healthy volunteers were also enrolled and the level of cholesterol in plasma was detected by metabolomics. Filipin III and elisa kits were used to stain free cholesterol. Mitochondrial function was detected by mitotracker green, mitotracker green, and Seahorse. Mitochondrial morphology was detected by high content screening and electron microscopy. The mRNA and protein levels of mitochondrial dynamics-related proteins were detected by RT-qPCR and Western blot,respectively. BODIPY 493/503 was used to stain lipid droplets. Lipidomics was used to detect intracellular lipid components. The mRNA level of interleukin (IL)-6 and IL-8 were detected by RT-qPCR.

RESULTS

We found that the cholesterol overload was associated with chronic obstructive pulmonary disease (COPD) and airway epithelia-driven inflammation, evidenced by hypercholesterolemia in patients with COPD and preclinical models, alteration of lipid metabolism-associated genes in CSE-induced airway epithelia and production of ILs. External cholesterol altered airway epithelial sensitivity of inflammation in response to CSE, through the regulation of STARD3-MFN2 pathway, cholesterol re-distribution, altered transport and accumulation of cholesterol, activities of lipid transport regulators and disorder of mitochondrial function and dynamics. MFN2 down-regulation increased airway epithelial sensitivity and production of ILs after smoking, at least partially by injuring fatty acid oxidation and activating mTOR phosphorylation.

CONCLUSIONS

Our data provide new insights for understanding molecular mechanisms of cholesterol-altered airway epithelial inflammation and for developing diagnostic biomarkers and therapeutic targets to improve patient outcomes.

Lipidomics in Understanding Pathophysiology and Pharmacologic Effects in Inflammatory Diseases: Considerations for Drug Development

The lipidome has a broad range of biological and signaling functions, including serving as a structural scaffold for membranes and initiating and resolving inflammation. To investigate the biological activity of phospholipids and their bioactive metabolites, precise analytical techniques are necessary to identify specific lipids and quantify their levels. Simultaneous quantification of a set of lipids can be achieved using high sensitivity mass spectrometry (MS) techniques, whose technological advancements have significantly improved over the last decade. This has unlocked the power of metabolomics/lipidomics allowing the dynamic characterization of metabolic systems. Lipidomics is a subset of metabolomics for multianalyte identification and quantification of endogenous lipids and their metabolites. Lipidomics-based technology has the potential to drive novel biomarker discovery and therapeutic development programs; however, appropriate standards have not been established for the field. Standardization would improve lipidomic analyses and accelerate the development of innovative therapies. This review aims to summarize considerations for lipidomic study designs including instrumentation, sample stabilization, data validation, and data analysis. In addition, this review highlights how lipidomics can be applied to biomarker discovery and drug mechanism dissection in various inflammatory diseases including cardiovascular disease, neurodegeneration, lung disease, and autoimmune disease.

Non-Exosomal and Exosome-Derived miRNAs as Promising Biomarkers in Canine Mammary Cancer

Canine mammary cancer (CMC), similar to human breast cancer (HBC) in many aspects, is the most common neoplasm associated with significant mortality in female dogs. Due to the limited therapy options, biomarkers are highly desirable for early clinical diagnosis or cancer progression monitoring. Since the discovery of microRNAs (miRNAs or miRs) as post-transcriptional gene regulators, they have become attractive biomarkers in oncological research. Except for intracellular miRNAs and cell-free miRNAs, exosome-derived miRNAs (exomiRs) have drawn much attention in recent years as biomarkers for cancer detection. Analysis of exosomes represents a non-invasive, pain-free, time- and money-saving alternative to conventional tissue biopsy. The purpose of this review is to provide a summary of miRNAs that come from non-exosomal sources (canine mammary tumor, mammary tumor cell lines or canine blood serum) and from exosomes as promising biomarkers of CMC based on the current literature. As is discussed, some of the miRNAs postulated as diagnostic or prognostic biomarkers in CMC were also altered in HBC (such as miR-21, miR-29b, miR-141, miR-429, miR-200c, miR-497, miR-210, miR-96, miR-18a, miR19b, miR-20b, miR-93, miR-101, miR-105a, miR-130a, miR-200c, miR-340, miR-486), which may be considered as potential disease-specific biomarkers in both CMC and HBC.

Human disease biomarker panels through systems biology

As more uses for biomarkers are sought after for an increasing number of disease targets, single-target biomarkers are slowly giving way for biomarker panels. These panels incorporate various sources of biomolecular and clinical data to guarantee a higher robustness and power of separation for a clinical test. Multifactorial diseases such as psychiatric disorders show great potential for clinical use, assisting medical professionals during the analysis of risk and predisposition, disease diagnosis and prognosis, and treatment applicability and efficacy. More specific tests are also being developed to assist in ruling out, distinguishing between, and confirming suspicions of multifactorial diseases, as well as to predict which therapy option may be the best option for a given patient's biochemical profile. As more complex datasets are entering the field, involving multi-omic approaches, systems biology has stepped in to facilitate the discovery and validation steps during biomarker panel generation. Filtering biomolecules and clinical data, pre-validating and cross-validating potential biomarkers, generating final biomarker panels, and testing the robustness and applicability of those panels are all beginning to rely on machine learning and systems biology and research in this area will only benefit from advances in these approaches.

Anti-Inflammatory Function of Fatty Acids and Involvement of Their Metabolites in the Resolution of Inflammation in Chronic Obstructive Pulmonary Disease

Lipid metabolism plays an important role in many lung functions. Disorders of lipid metabolism are part of the pathogenesis of chronic obstructive pulmonary disease (COPD). Lipids are involved in numerous cross-linkages with inflammation. Recent studies strongly support the involvement of fatty acids as participants in inflammation. They are involved in the initiation and resolution of inflammation, including acting as a substrate for the formation of lipid mediators of inflammation resolution. Specialized pro-inflammatory mediators (SPMs) belonging to the classes of lipoxins, resolvins, maresins, and protectins, which are formed enzymatically from unsaturated fatty acids, are now described. Disorders of their production and function are part of the pathogenesis of COPD. SPMs are currently the subject of active research in order to find new drugs. Short-chain fatty acids are another important participant in metabolic and immune processes, and their role in the pathogenesis of COPD is of great clinical interest.

The Role of ABC Transporters in Lipid Metabolism and the Comorbid Course of Chronic Obstructive Pulmonary Disease and Atherosclerosis

Chronic obstructive pulmonary disease (COPD) ranks among the leading causes of morbidity and mortality worldwide. COPD rarely occurs in isolation and is often combined with various diseases. It is considered that systemic inflammation underlies the comorbid course of COPD. The data obtained in recent years have shown the importance of violations of the cross-links of lipid metabolism and the immune response, which are links in the pathogenesis of both COPD and atherosclerosis. The role of lipid metabolism disorders in the pathogenesis of the comorbid course of COPD and atherosclerosis and the participation of ATP-binding cassette (ABC) transporters in these processes is discussed in this article. It is known that about 20 representatives of a large family of ABC transporters provide lipid homeostasis of cells by moving lipids inside the cell and in its plasma membrane, as well as removing lipids from the cell. It was shown that some representatives of the ABC-transporter family are involved in various links of the pathogenesis of COPD and atherosclerosis, which can determine their comorbid course.

Dysregulated Metabolites Serve as Novel Biomarkers for Metabolic Diseases Caused by E-Cigarette Vaping and Cigarette Smoking

Metabolites are essential intermediate products in metabolism, and metabolism dysregulation indicates different types of diseases. Previous studies have shown that cigarette smoke dysregulated metabolites; however, limited information is available with electronic cigarette (e-cig) vaping. We hypothesized that e-cig vaping and cigarette smoking alters systemic metabolites, and we propose to understand the specific metabolic signature between e-cig users and cigarette smokers. Plasma from non-smoker controls, cigarette smokers, and e-cig users was collected, and metabolites were identified by UPLC-MS (ultra-performance liquid chromatography mass spectrometer). Nicotine degradation was activated by e-cig vaping and cigarette smoking with increased concentrations of cotinine, cotinine N-oxide, (S)-nicotine, and (R)-6-hydroxynicotine. Additionally, we found significantly decreased concentrations in metabolites associated with tricarboxylic acid (TCA) cycle pathways in e-cig users versus cigarette smokers, such as d-glucose, (2R,3S)-2,3-dimethylmalate, (R)-2-hydroxyglutarate, O-phosphoethanolamine, malathion, d-threo-isocitrate, malic acid, and 4-acetamidobutanoic acid. Cigarette smoking significant upregulated sphingolipid metabolites, such as d-sphingosine, ceramide, N-(octadecanoyl)-sphing-4-enine, N-(9Z-octadecenoyl)-sphing-4-enine, and N-[(13Z)-docosenoyl]-sphingosine, versus e-cig vaping. Overall, e-cig vaping dysregulated TCA cycle-related metabolites while cigarette smoking altered sphingolipid metabolites. Both e-cig and cigarette smoke increased nicotinic metabolites. Therefore, specific metabolic signatures altered by e-cig vaping and cigarette smoking could serve as potential systemic biomarkers for early pathogenesis of cardiopulmonary diseases.

Characterization of the COPD Salivary Fingerprint through Surface Enhanced Raman Spectroscopy: A Pilot Study

Chronic Obstructive Pulmonary Disease (COPD) is a debilitating pathology characterized by reduced lung function, breathlessness and rapid and unrelenting decrease in quality of life. The severity rate and the therapy selection are strictly dependent on various parameters verifiable after years of clinical observations, missing a direct biomarker associated with COPD. In this work, we report the methodological application of Surface Enhanced Raman Spectroscopy combined with Multivariate statistics for the analysis of saliva samples collected from 15 patients affected by COPD and 15 related healthy subjects in a pilot study. The comparative Raman analysis allowed to determine a specific signature of the pathological saliva, highlighting differences in determined biological species, already studied and characterized in COPD onset, compared to the Raman signature of healthy samples. The unsupervised principal component analysis and hierarchical clustering revealed a sharp data dispersion between the two experimental groups. Using the linear discriminant analysis, we created a classification model able to discriminate the collected signals with accuracies, specificities, and sensitivities of more than 98%. The results of this preliminary study are promising for further applications of Raman spectroscopy in the COPD clinical field.