A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease

Proteomic networks and related genetic variants associated with smoking and chronic obstructive pulmonary disease

BACKGROUND

Studies have identified individual blood biomarkers associated with chronic obstructive pulmonary disease (COPD) and related phenotypes. However, complex diseases such as COPD typically involve changes in multiple molecules with interconnections that may not be captured when considering single molecular features.

METHODS

Leveraging proteomic data from 3,173 COPDGene Non-Hispanic White (NHW) and African American (AA) participants, we applied sparse multiple canonical correlation network analysis (SmCCNet) to 4,776 proteins assayed on the SomaScan v4.0 platform to derive sparse networks of proteins associated with current vs. former smoking status, airflow obstruction, and emphysema quantitated from high-resolution computed tomography scans. We then used NetSHy, a dimension reduction technique leveraging network topology, to produce summary scores of each proteomic network, referred to as NetSHy scores. We next performed a genome-wide association study (GWAS) to identify variants associated with the NetSHy scores, or network quantitative trait loci (nQTLs). Finally, we evaluated the replicability of the networks in an independent cohort, SPIROMICS.

RESULTS

We identified networks of 13 to 104 proteins for each phenotype and exposure in NHW and AA, and the derived NetSHy scores significantly associated with the variable of interests. Networks included known (sRAGE, ALPP, MIP1) and novel molecules (CA10, CPB1, HIS3, PXDN) and interactions involved in COPD pathogenesis. We observed 7 nQTL loci associated with NetSHy scores, 4 of which remained after conditional analysis. Networks for smoking status and emphysema, but not airflow obstruction, demonstrated a high degree of replicability across race groups and cohorts.

CONCLUSIONS

In this work, we apply state-of-the-art molecular network generation and summarization approaches to proteomic data from COPDGene participants to uncover protein networks associated with COPD phenotypes. We further identify genetic associations with networks. This work discovers protein networks containing known and novel proteins and protein interactions associated with clinically relevant COPD phenotypes across race groups and cohorts.

Genetic association of inflammatory marker GlycA with lung function and respiratory diseases

Association of circulating glycoprotein acetyls (GlycA), a systemic inflammation biomarker, with lung function and respiratory diseases remain to be investigated. We examined the genetic correlation, shared genetics, and potential causality of GlycA (N = 115,078) with lung function and respiratory diseases (N = 497,000). GlycA showed significant genetic correlation with FEV1 (rg = -0.14), FVC (rg = -0.18), asthma (rg = 0.21) and COPD (rg = 0.31). We consistently identified ten shared loci (including chr3p21.31 and chr8p23.1) at both SNP and gene level revealing potential shared biological mechanisms involving ubiquitination, immune response, Wnt/β-catenin signaling, cell growth and differentiation in tissues or cells including blood, epithelium, fibroblast, fetal thymus, and fetal intestine. Genetically elevated GlycA was significantly correlated with lung function and asthma susceptibility (354.13 ml decrement of FEV1, 442.28 ml decrement of FVC, and 144% increased risk of asthma per SD increment of GlycA) from MR analyses. Our findings provide insights into biological mechanisms of GlycA in relating to lung function, asthma, and COPD.

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.

Proteomic Networks and Related Genetic Variants Associated with Smoking and Chronic Obstructive Pulmonary Disease

Background

Studies have identified individual blood biomarkers associated with chronic obstructive pulmonary disease (COPD) and related phenotypes. However, complex diseases such as COPD typically involve changes in multiple molecules with interconnections that may not be captured when considering single molecular features.

Methods

Leveraging proteomic data from 3,173 COPDGene Non-Hispanic White (NHW) and African American (AA) participants, we applied sparse multiple canonical correlation network analysis (SmCCNet) to 4,776 proteins assayed on the SomaScan v4.0 platform to derive sparse networks of proteins associated with current vs. former smoking status, airflow obstruction, and emphysema quantitated from high-resolution computed tomography scans. We then used NetSHy, a dimension reduction technique leveraging network topology, to produce summary scores of each proteomic network, referred to as NetSHy scores. We next performed genome-wide association study (GWAS) to identify variants associated with the NetSHy scores, or network quantitative trait loci (nQTLs). Finally, we evaluated the replicability of the networks in an independent cohort, SPIROMICS.

Results

We identified networks of 13 to 104 proteins for each phenotype and exposure in NHW and AA, and the derived NetSHy scores significantly associated with the variable of interests. Networks included known (sRAGE, ALPP, MIP1) and novel molecules (CA10, CPB1, HIS3, PXDN) and interactions involved in COPD pathogenesis. We observed 7 nQTL loci associated with NetSHy scores, 4 of which remained after conditional analysis. Networks for smoking status and emphysema, but not airflow obstruction, demonstrated a high degree of replicability across race groups and cohorts.

Conclusions

In this work, we apply state-of-the-art molecular network generation and summarization approaches to proteomic data from COPDGene participants to uncover protein networks associated with COPD phenotypes. We further identify genetic associations with networks. This work discovers protein networks containing known and novel proteins and protein interactions associated with clinically relevant COPD phenotypes across race groups and cohorts.

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.

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.

Systematic Review of NMR-Based Metabolomics Practices in Human Disease Research

Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.

Air pollution, metabolites and respiratory health across the life-course

Previous studies have explored the relationships of air pollution and metabolic profiles with lung function. However, the metabolites linking air pollution and lung function and the associated mechanisms have not been reviewed from a life-course perspective. Here, we provide a narrative review summarising recent evidence on the associations of metabolic profiles with air pollution exposure and lung function in children and adults. Twenty-six studies identified through a systematic PubMed search were included with 10 studies analysing air pollution-related metabolic profiles and 16 studies analysing lung function-related metabolic profiles. A wide range of metabolites were associated with short- and long-term exposure, partly overlapping with those linked to lung function in the general population and with respiratory diseases such as asthma and COPD. The existing studies show that metabolomics offers the potential to identify biomarkers linked to both environmental exposures and respiratory outcomes, but many studies suffer from small sample sizes, cross-sectional designs, a preponderance on adult lung function, heterogeneity in exposure assessment, lack of confounding control and omics integration. The ongoing EXposome Powered tools for healthy living in urbAN Settings (EXPANSE) project aims to address some of these shortcomings by combining biospecimens from large European cohorts and harmonised air pollution exposure and exposome data.

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.

Vaccination and modern management of chronic obstructive pulmonary disease - a narrative review

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) carries a tremendous societal and individual burden, posing significant challenges for public health systems worldwide due to its high morbidity and mortality. Due to aging and multimorbidity but also in the wake of important progress in deciphering the heterogeneous disease endotypes, an individualized approach to the prevention and management of COPD is necessary.

AREAS COVERED

This article tackles relevant immunization strategies that are available or still under development with a focus on the latest evidence but also controversies around different regional immunization approaches. Further, we present the crossover between chronic lung inflammation and lung microbiome disturbance as well as its role in delineating COPD endotypes. Moreover, the article attempts to underline endotype-specific treatment approaches. Lastly, we highlight non-pharmacologic prevention and management programs in view of the challenges and opportunities of the COVID-19 era.

EXPERT OPINION

Despite the remaining challenges, personalized medicine has the potential to offer tailored approaches to prevention and therapy and promises to improve the care of patients living with COPD.

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.