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30 June 2021

Potential Metabolic Biomarkers in Adult Asthmatics

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Department of Allergy and Clinical Immunology, Ajou University School of Medicine, 164, Worldcup-ro, Yeongtong-gu, Suwon 16499, Korea
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Metabolites2021, 11(7), 430;https://doi.org/10.3390/metabo11070430
This article belongs to the Special Issue Metabolomics in the Identification of Biomarkers of Asthma
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Abstract

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

1. Introduction

Asthma is characterized by chronic airway inflammation with complex interactions among genetic, epigenetic, and environmental factors [1,2], resulting in constant attempts to understand asthma pathogenesis underlying each phenotype. Although the classification of asthma phenotypes as eosinophilic, non-eosinophilic, or paucigranulocytic phenotypes has enabled intensive treatment and improved clinical outcomes [3], attempts to develop novel approaches are needed to unveil the pathogenic mechanisms of asthma. Since the emergence of new technologies, “omics,” their application in medical research has been rapidly growing [4]. In particular, metabolomics is one of the latest approaches to detect metabolites for phenotype categorization and biomarker discovery in diverse diseases [5]. Metabolites are the intermediate or end products of cellular metabolism required for the maintenance of biological homeostasis and normal cell function [6]. Therefore, alteration in metabolites reflects physiological or pathological states [7]. With the integration of multiple omics, metabolomics is becoming a more powerful tool in clinical application for early diagnosis, prognosis, and treatment of diseases [8]. Despite an increase in metabolomic studies on asthma, it is not clear how metabolites act as key determinants for each phenotype [9]. This review highlights recent progress in the genomic, transcriptomic, proteomic, and metabolomic signatures involved in the pathogenesis of asthma, suggesting the potential for applying this approach in precision medicine.

2. Risk Factors in Asthma Pathogenesis

2.1. Genetic and Epigenetic Factors

Asthma pathogenesis is still poorly understood, as the airways are influenced by multiple environmental and genetic factors. Accumulating evidence has supported the genetic traits of asthma [10,11], suggesting specific genes involved in some phenotypes of asthma. The conventional studies on asthma-related genes were performed with linkage analysis and positional cloning. More recently, since the first introduction of genomic-wide association studies (GWAS) in asthma [12], multiple genetic variants were validated to explore disease-related regions showing differences in DNA sequences between normal and asthma groups [13]. These findings brought a huge improvement to asthma genetics by identifying novel genetic factors for asthma. However, the gene-gene interaction still remains a problem to solve in genomic analysis [14]. In addition, epigenetic studies have been highlighted focusing on genomic adaption to environmental stimuli, such as DNA methylation, histone modification, or non-coding RNAs, which are not caused by alterations in DNA sequences [15]. With the application of epigenome-wide association studies (EWAS) in asthma, DNA methylation has been suggested to mediate gene expression in immune cells, including T cell polarization [16] or monocyte differentiation [17]. In particular, methylation of cytosine at the carbon-5 position in CpG dinucleotides is regarded as a key factor for initiating a transcription and regulating cell-specific genes in inflammatory diseases [18].

2.2. Environmental Factors

Environmental exposure could impact a rapid increase in the prevalence of asthma in populations with a similar genetic background where allergen exposure is a crucial risk factor for asthma [19]. Sensitization to allergens, such as dust mites and animal dander, is related to Th2 immune response with IgE production and eosinophilia, contributing to the development and exacerbation of allergic asthma [20,21]. Other environmental factors, including smoking, air or occupational pollutants, and virus or bacterial infection, are involved in innate immunity and trigger asthma exacerbation [22]. Air pollutants, including particulate matter, nitrogen dioxide, and sulfur dioxide, are known to aggravate inflammatory response related to oxidative stress and injury in the airways, driving enhanced risk of sensitization to inhaled allergens and symptom exacerbation [23,24].

3. Identification of “Omics” Markers in Asthma

3.1. Genomics

Numerous genetic studies have revealed that multiple genes are involved in the development and progress of asthma by linkage analysis and association studies. In particular, linkage analysis with positional cloning identified diverse genetic markers related to asthma in chromosomal loci [25,26,27,28,29,30,31,32]. In addition, candidate genes association studies identified asthma-related traits, focusing on different allele frequencies of a single nucleotide polymorphism in case-control studies [33]. Since the application of GWAS to asthma, large meta-analyses in European [34] and American cohorts [35] have identified variable genetic determinants (Table 1). Nevertheless, GWAS have the limitations of a small sample population and lack of significant associations [36]. Moreover, the susceptibility of genetic variants for asthma was not replicated across all relevant studies [34].
Table 1. Summary of genomic analysis in adult asthmatics.

3.2. Transcriptomics

Transcriptomics quantifies transcripts in organisms to identify differentially expressed genes under specific conditions. The main analyzing tools for transcriptomics include microarrays and RNA sequencing [147]. Transcriptomics is usually carried out in blood because of its great efficiency and convenience for analyzing gene expression [148]. Some studies have performed transcriptomic analysis in blood [149,150], bronchial tissue [151,152,153,154], sputum [155,156,157,158,159], nasal brushings [160], bronchoalveolar lavage fluid (BALF) [161], and mixed samples [162], facilitating differential phenotypes in asthma. Finally, recent studies found 90 novel genetic classifiers for asthma, which could be utilized as potential biomarkers [160]. In addition, several studies have investigated distinct gene profiles to determine the severity of asthma (Table 2).
Table 2. Summary of transcriptomic analyses in adult asthmatics.

3.3. Proteomics

Proteomic studies include protein identification, quantification or localization, post-translational modification, and protein-protein interactions [163]. Liquid chromatography is a typical analyzing tool for proteomics with coupling of mass spectrometry (MS) [164]. Several studies have performed proteomic analysis and identified different protein profiles of asthmatics in serum [165], sputum [166,167], BALF [168,169,170,171], or bronchial biopsy [172] (Table 3). Commonly, these proteins have been found to be involved in multiple biological processes, such as immune response, defense response, lipid metabolism, molecular transport, cell adhesion, and complement activation [166,168,172].
Table 3. Summary of proteomic analyses in adult asthmatics.

3.4. Metabolomics

Metabolomics is an analysis of low molecular compounds involved in biological processes [6]. For metabolic profiling, MS has been widely employed because of its simplicity and sensitivity [173]. Through its combination with chromatography, MS has become a more powerful tool with high resolution and accuracy, extending its application across biological and medical fields [174]. In addition, nuclear magnetic resonance (NMR) spectroscopy was introduced for an alternative analytic tool, using the differences in the direction and speed of nuclear spin on the magnetic field [175]. Metabolic profiling could be performed in various biospecimens according to its purpose (Table 4). Most studies have used blood [176,177,178,179,180,181,182,183,184], urine [185,186,187], or sputum samples [184], since they are easy to collect and are reflective of whole body metabolism [188]. A few studies have analyzed exhaled breath condensate [189,190,191,192,193] and BALF because of their relevance to the airway physiology [194].
Table 4. Summary of metabolomic analyses in adult asthmatics.

3.5. Limitation of “Omics” in Biomaker Identification for Asthma

“Omics” enabled the comprehensive evaluation of holistic molecules in an organism. This advantage leads to the advances in biomarker discovery in medical fields [195]. Genomics is the first study of the omics and aims to search for genetic variants associated with specific diseases [4]. Although it has provided a comprehensive understanding for asthma, it could not explain a mild to moderate asthmatic state [196]. Moreover, the number of samples or replication tests was not sufficient [33]. In contrast, transcriptomics focuses on the differential gene expression and activity of functional genes in patients [197]. Nevertheless, DNA or mRNA expression may not represent the biological function of genes at the protein levels due to translational regulation or post-translational modification [198]. Proteomics reflects pathological changes at the time because cytokines or chemokines are important protein related to the severity of inflammatory diseases [199]. In asthma, transcriptomics and proteomics could be applicable to a wide range of cell types and biological samples including blood, BALF, sputum, and bronchial or nasal brushings [200]. However, they could not provide overall information underlying diseases due to a large variability in sample types or disease states [201]. To overcome these limitations, metabolomics was suggested as one of the latest omics technologies. In particular, its application is rapidly increasing in asthma for the detection of volatile organic compounds in EBC with a noninvasive way [202]. However, the lack of replication or standards of metabolic profiling in different biospecimens is still challenging [9]. Despite the outstanding achievements of omics studies, they are still considered insufficient to mainly be utilized in clinical practices. Therefore, the integration of multiple omics could complement the limitation of each technology.

4. Metabolic Pathways Involved in Asthma

4.1. Amino Acid Metabolism

Amino acids are involved in multiple biological functions including growth, maintenance or development, regulation of gene expression/cell signaling, and synthesis of nitrogen/protein/energy substrates for homeostasis in organisms [203]. Moreover, they are known as crucial regulators of metabolic pathways for immune responses and anti-oxidant activities [204]. In particular, arginine has been suggested to affect the development of asthma. It synthesizes nitric oxide (NO) by NO synthase (NOS) composed of 3 isoforms, neuronal NOS (nNOS), inducible NOS (iNOS), and endothelial NOS (eNOS) [205]. In asthmatic patients, expression of iNOS and arginase-1/2 were upregulated in the serum or epithelium and immune cells of the airways, leading to higher levels of exhaled NO and more severe symptoms [206,207,208]. Furthermore, arginase metabolism is involved in the regulation of T-cell function, driving Th2 airway inflammation [208]. However, suppressive roles of arginase-2 have been reported in severe eosinophilic and neutrophilic inflammation in asthma [209]. In addition to arginine, higher levels of β-alanine [185] and lysine [190] were detected in patients with severe asthma. However, another study showed conflicting results with decreased levels of arginine, alanine, leucine, valine, and histidine in asthmatics [177]. Therefore, further studies on various phenotypes of asthma are needed to clarify with this pathway.

4.2. Lipid Metabolism

The importance of lipid mediators in respiratory diseases is highlighted due to their involvement in various biological functions, such as cell structural components, energy sources/metabolism, signal transduction, and material transport [210]. Among several types of lipids, fatty acids are known to be relevant to diverse mechanisms of inflammatory response in chronic airway diseases [211]. Moreover, arachidonic acids have been identified to contribute to asthma pathogenesis as precursors of eicosanoids including leukotrienes, prostaglandins, thromboxane, lipoxins, and hydroxyeicosatetraenoic acids [212]. In particular, urinary leukotriene E4 (LTE4) has been widely used for a diagnosis of a distinct phenotype of severe eosinophilic asthma, referred as aspirin-exacerbated respiratory disease (AERD) [213]. In addition to fatty acids, several studies reported that sphingosine-1-phosphate (S1P) levels were increased in asthmatics and correlated with asthma severity [214,215,216]. Furthermore, increased levels of S1P (derived from various inflammatory cells) were found in patients with AERD [217]. Despite the controversial functions of lipids, it is certain that they are key mediators in asthma pathogenesis. Therefore, lipids might be potent biomarkers for specific phenotypes of asthma and promising candidates for new therapeutic targets.

5. Changes in Metabolite Profiles According to the Phenotype of Asthma

5.1. Mild-to-Moderate Asthma

Asthma has been classified as mild, moderate, or severe types according to the severity of symptoms and frequency of asthma exacerbation. Mild-to-moderate asthma can be defined as a controlled one by step 1-4 treatments [218]. Several studies have performed metabolic analyses to identify metabolic determinants related to the severity of asthma. As a result, increased 8 (α-linolenic acid, linoleic acid, oleic acid, linoleoyl ethanolamide, dodecanedioic acid, linoleates, methylcysteine, and theobromine) and decreased 6 metabolites (indole-3-acetate, lysine, lyso-platelet activating factor C16:0, methionine, phenylalanine, and phenylacetyl glutamine) were identified in metabolic profiles of mild asthmatics compared to healthy controls [179]. In addition, lipidomic analysis found lipid metabolism dysregulation in moderate asthma positively correlated with asthma severity, but not in mild asthma when compared to healthy controls [183].

5.2. Severe Asthma

According to the GINA guidelines, severe asthma (SA) is characterized by uncontrolled or partially controlled symptoms, despite consistent demands for high-dose inhaled corticosteroids (ICSs) with an additional controller or oral corticosteroids (OCSs) [218]. Metabolic analysis in SA found significant differences of metabolites, especially in amino acid metabolism with higher levels of β-alanine [182] or lysine [190]. Moreover, a lipidomic analysis revealed that 22 metabolites are changed in SA. Several lipid mediators, including sphingolipids (sphingomyelin, ceramide, and S1P), free fatty acids, and eicosanoids (LTE4) are positively correlated with asthma severity [179,186]. In addition, the resistance to steroids is one of the clinical characteristics in SA [219]. In particular, distinct metabolic profiles are noted in severe asthmatics using ICSs or OCSs with decreased steroid metabolites. Moreover, linoleic acids from polyunsaturated fatty acids drive steroid refractory response and contribute to asthma severity with airway epithelial injury [220,221].

5.3. Obese Asthma

Obese asthma is classified as a distinct phenotype of asthma with persistent symptoms and resistance to conventional medication [222]. With the increasing of the obese population, obesity now accounts for 11% of adult asthmatics [223]. Although obesity is one of the risk factors for asthma, the mechanisms are poorly understood and needed to be clarified [224]. Several studies have suggested that the metabolic dysregulation is related to development and progress of asthma [225,226]. With omics technologies, distinct metabolic changes have been identified in obese subjects [227]. In particular, high-fat diets tend to increase the concentrations of ceramide, sphingomyelin, and S1P in multiple tissue and organs [228]. Among them, ceramide could contribute to airway hyperresponsiveness, suggesting a possible correlation with asthma severity [229]. Moreover, elevated levels of C18:0 and C:20 were found in the sera of obese asthmatics [230]. Although the exact mechanisms are not comprehended yet, clinical and experimental research have suggested the specific metabolic changes in obese asthma.

6. Clinical Implications and Perspectives of Various Metabolites

Due to the sensitivity to biological alterations, metabolites can serve to search for novel biomarkers and pathological mechanisms for asthma phenotypes (Table 5). The application of metabolomic analysis provides new insights into the classification of asthma phenotypes in terms of the dynamic network between genetic and environmental factors [6]. In addition, the integrated omics has been used from early diagnosis to monitoring treatment response in diseases [231]. Therefore, metabolomics may lead to a precise discrimination of asthmatic patients, but also improvement in a search for new therapeutic targets in asthma as well [232]. Furthermore, the metabolic therapy is a novel concept comprising restrictive diet control or nutritional supplements with relatively easy and safe interventions. Although metabolomics is highlighted for biomarker identification for asthma, the efficacy and safety of metabolic signatures should be validated for their practical uses in clinical courses. Based on integrative omics studies in asthma, metabolites may realize the implementation of personalized medication and expand treatment options for asthmatics in a combination with current medications.
Table 5. Metabolic signatures for asthma and its phenotypes.

Author Contributions

S.S. wrote the paper and created the tables. Y.C. revised the manuscript. H.-S.P. provided overall supervision for the entire study. All authors have read and agreed to the published version of the manuscript.

Funding

The work was supported by the Korean Health Technology R & D Project through the Korea Health Industry Development Institute (KHIDI) grant funded by the Ministry of Health and Welfare, Republic of Korea (HR16C0001). This research received no external funding.

Conflicts of Interest

The authors declare no competing financial interest.

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