Metabolomics analysis identifies different metabotypes of asthma severity

Distinct changes in serum metabolites and lipid species in the onset and progression of NAFLD in Obese Chinese

Introduction

Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese.

Methods

Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD.

Results

A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters.

Conclusion

Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.

Ephedra sinica polysaccharide regulate the anti-inflammatory immunity of intestinal microecology and bacterial metabolites in rheumatoid arthritis

Introduction

Ephedra sinica polysaccharide (ESP) exerts substantial therapeutic effects on rheumatoid arthritis (RA). However, the mechanism through which ESP intervenes in RA remains unclear. A close correlation has been observed between enzymes and derivatives in the gut microbiota and the inflammatory immune response in RA.

Methods

A type II collagen-induced arthritis (CIA) mice model was treated with Ephedra sinica polysaccharide. The therapeutic effect of ESP on collagen-induced arthritis mice was evaluated. The anti-inflammatory and cartilage-protective effects of ESP were also evaluated. Additionally, metagenomic sequencing was performed to identify changes in carbohydrate-active enzymes and resistance genes in the gut microbiota of the ESP-treated CIA mice. Liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry were performed to observe the levels of serum metabolites and short-chain fatty acids in the gut. Spearman's correlational analysis revealed a correlation among the gut microbiota, antibiotic-resistance genes, and microbiota-derived metabolites.

Results

ESP treatment significantly reduced inflammation levels and cartilage damage in the CIA mice. It also decreased the levels of pro-inflammatory cytokines interleukin (IL)-6, and IL-1-β and protected the intestinal mucosal epithelial barrier, inhibiting inflammatory cell infiltration and mucosal damage. Here, ESP reduced the TLR4, MyD88, and TRAF6 levels in the synovium, inhibited the p65 expression and pp65 phosphorylation in the NF-κB signaling pathway, and blocked histone deacetylase (HDAC1 and HDAC2) signals. ESP influenced the gut microbiota structure, microbial carbohydrate-active enzymes, and microbial resistance related to resistance genes. ESP increased the serum levels of L-tyrosine, sn-glycero-3-phosphocholine, octadecanoic acid, N-oleoyl taurine, and decreased N-palmitoyl taurine in the CIA mice.

Conclusion

ESP exhibited an inhibitory effect on RA. Its action mechanism may be related to the ability of ESP to effectively reduce pro-inflammatory cytokines levels, protect the intestinal barrier, and regulate the interaction between mucosal immune systems and abnormal local microbiota. Accordingly, immune homeostasis was maintained and the inhibition of fibroblast-like synoviocyte (FLS) proliferation through the HDAC/TLR4/NF-κB pathway was mediated, thereby contributing to its anti-inflammatory and immune-modulating effects.

Cannabinoid receptor 2 as a regulator of inflammation induced oleoylethanolamide in eosinophilic asthma

BACKGROUND

Oleoylethanolamide (OEA), an endogenously generated cannabinoid-like compound, has been reported to be increased in patients with severe asthma and aspirin-exacerbated respiratory disease. Recruitment of activated eosinophils in the airways is a hallmark of bronchial asthma.

OBJECTIVE

We explored the direct contribution of cannabinoid receptor 2 (CB2), a cognate receptor of OEA, which induces eosinophil activation in vitro and in vivo.

METHODS

We investigated OEA signaling in the eosinophilic cell line dEol-1 in peripheral blood eosinophils from people with asthma. In order to confirm whether eosinophil activation by OEA is CB2 dependent or not, CB2 small interfering RNA and the CB2 antagonist SR144528 were used. The numbers of airway inflammatory cells and the levels of cytokines were measured in bronchoalveolar lavage fluid, and airway hyperresponsiveness was examined in the BALB/c mice.

RESULTS

CB2 expression was increased after OEA treatment in both peripheral blood eosinophils and dEol-1 cells. It was also elevated after OEA-induced recruitment of eosinophils to the lungs in vivo. However, SR144528 treatment reduced the activation of peripheral blood eosinophils from asthmatic patients. Furthermore, CB2 knockdown decreased the activation of dEol-1 cells and the levels of inflammatory and type 2 cytokines. SR144528 treatment alleviated airway hyperresponsiveness and eosinophil recruitment to the lungs in vivo.

CONCLUSION

CB2 may contribute to the pathogenesis of eosinophilic asthma. Our results provide new insight into the molecular mechanism of signal transduction by OEA in eosinophilic asthma.

Inhibition of xanthine oxidase by allopurinol suppresses HMGB1 secretion and ameliorates experimental asthma

BACKGROUND

Extracellular high mobility group box 1 (HMGB1) is a key mediator in driving allergic airway inflammation and contributes to asthma. Yet, mechanism of HMGB1 secretion in asthma is poorly defined. Pulmonary metabolic dysfunction is recently recognized as a driver of respiratory pathology. However, the altered metabolic signatures and the roles of metabolic to allergic airway inflammation remain unclear.

METHODS

Male C57BL/6 J mice were sensitized and challenged with toluene diisocyanate (TDI) to generate a chemically induced asthma model. Pulmonary untargeted metabolomics was employed. According to results, mice were orally administered allopurinol, a xanthine oxidase (XO) inhibitor. Human bronchial epithelial cells (16HBE) were stimulated by TDI-human serum albumin (HSA).

RESULTS

We identified the purine metabolism was the most enriched pathway in TDI-exposed lungs, corresponding to the increase of xanthine and uric acid, products of purine degradation mediated by XO. Inhibition of XO by allopurinol ameliorates TDI-induced oxidative stress and DNA damage, mixed granulocytic airway inflammation and Th1, Th2 and Th17 immunology as well as HMGB1 acetylation and secretion. Mechanistically, HMGB1 acetylation was caused by decreased activation of the NAD+-sirtuin 1 (SIRT1) axis triggered by hyperactivation of the DNA damage sensor poly (ADP-ribose)-polymerase 1 (PARP-1). This was rescued by allopurinol, PARP-1 inhibitor or supplementation with NAD+ precursor in a SIRT1-dependent manner. Meanwhile, allopurinol attenuated Nrf2 defect due to SIRT1 inactivation to help ROS scavenge.

CONCLUSIONS

We demonstrated a novel regulation of HMGB1 acetylation and secretion by purine metabolism that is critical for asthma onset. Allopurinol may have therapeutic potential in patients with asthma.

Novel indocyanine green-loaded photothermal nanoparticles targeting TRPV1 for thermal ablation treatment of severe murine asthma induced by ovalbumin and lipopolysaccharide

To identify a replacement strategy for bronchial thermoplasty (BT) with non-invasive and free-of-severe side effect is urgently needed in the clinic for severe asthma treatment. In this study, PLGA-PEG@ICG@TRPV1 pAb (PIT) photothermal nanoparticles targeting bronchial TRPV1 were designed for photothermal therapy (PTT) against severe murine asthma induced by ovalbumin and lipopolysaccharide. PIT was formulated with a polyethylene glycol (PEG)-grafted poly (lactic-co-glycolic) acid (PLGA) coating as a skeleton structure to encapsulate indocyanine green (ICG) and was conjugated to the polyclonal antibody against transient receptor potential vanilloid 1 (TRPV1 pAb). The results revealed that PIT held good druggability due to its electronegativity and small diameter. PIT demonstrated great photothermal effects both in vivo and in vitro and exhibited good ability to target TRPV1 in vitro because of its selective cell uptake and specific cell toxicity toward TRPV1-overexpressing cells. The PIT treatment effectively reduced asthma symptoms in mice. This is evident from improvements in expiratory airflow limitation, significant decreases in inflammatory cell infiltration in the airways, and increases in goblet cell and columnar epithelial cell proliferation. In conclusion, PIT alleviates severe murine asthma symptoms through a combination of TRPV1 targeting and photothermal effects.

Lipid mediators of inhalation exposure-induced pulmonary toxicity and inflammation

Many inhalation exposures induce pulmonary inflammation contributing to disease progression. Inflammatory processes are actively regulated via mediators including bioactive lipids. Bioactive lipids are potent signaling molecules involved in both pro-inflammatory and resolution processes through receptor interactions. The formation and clearance of lipid signaling mediators are controlled by multiple metabolic enzymes. An imbalance of these lipids can result in exacerbated and sustained inflammatory processes which may result in pulmonary damage and disease. Dysregulation of pulmonary bioactive lipids contribute to inflammation and pulmonary toxicity following exposures. For example, inhalation of cigarette smoke induces activation of pro-inflammatory bioactive lipids such as sphingolipids, and ceramides contributing to chronic obstructive pulmonary disease. Additionally, exposure to silver nanoparticles causes dysregulation of inflammatory resolution lipids. As inflammation is a common consequence resulting from inhaled exposures and a component of numerous diseases it represents a broadly applicable target for therapeutic intervention. With new appreciation for bioactive lipids, technological advances to reliably identify and quantify lipids have occurred. In this review, we will summarize, integrate, and discuss findings from recent studies investigating the impact of inhaled exposures on pro-inflammatory and resolution lipids within the lung and their contribution to disease. Throughout the review current knowledge gaps in our understanding of bioactive lipids and their contribution to pulmonary effects of inhaled exposures will be presented. New methods being employed to detect and quantify disruption of pulmonary lipid levels following inhalation exposures will be highlighted. Lastly, we will describe how lipid dysregulation could potentially be addressed by therapeutic strategies to address inflammation.

Untargeted metabolomic profiling in children identifies novel pathways in asthma and atopy

BACKGROUND

Asthma and other atopic disorders can present with varying clinical phenotypes marked by differential metabolomic manifestations and enriched biological pathways.

OBJECTIVE

We sought to identify these unique metabolomic profiles in atopy and asthma.

METHODS

We analyzed baseline nonfasted plasma samples from a large multisite pediatric population of 470 children aged <13 years from 3 different sites in the United States and France. Atopy positivity (At+) was defined as skin prick test result of ≥3 mm and/or specific IgE ≥ 0.35 IU/mL and/or total IgE ≥ 173 IU/mL. Asthma positivity (As+) was based on physician diagnosis. The cohort was divided into 4 groups of varying combinations of asthma and atopy, and 6 pairwise analyses were conducted to best assess the differential metabolomic profiles between groups.

RESULTS

Two hundred ten children were classified as At-As-, 42 as At+As-, 74 as At-As+, and 144 as At+As+. Untargeted global metabolomic profiles were generated through ultra-high-performance liquid chromatography-tandem mass spectroscopy. We applied 2 independent machine learning classifiers and short-listed 362 metabolites as discriminant features. Our analysis showed the most diverse metabolomic profile in the At+As+/At-As- comparison, followed by the At-As+/At-As- comparison, indicating that asthma is the most discriminant condition associated with metabolomic changes. At+As+ metabolomic profiles were characterized by higher levels of bile acids, sphingolipids, and phospholipids, and lower levels of polyamine, tryptophan, and gamma-glutamyl amino acids.

CONCLUSION

The At+As+ phenotype displays a distinct metabolomic profile suggesting underlying mechanisms such as modulation of host-pathogen and gut microbiota interactions, epigenetic changes in T-cell differentiation, and lower antioxidant properties of the airway epithelium.

New Therapeutic Options in Pulmonal Diseases: Sphingolipids and Modulation of Sphingolipid Metabolism

Sphingolipids are crucial molecules in the respiratory airways. As in most other tissues and organs, in the lung sphingolipids play an essential role as structural constituents as they regulate barrier function and fluidity of cell membranes. A lung-specific feature is the occurrence of sphingolipids as minor structural components in the surfactant. However, sphingolipids are also key signaling molecules involved in airway cell signaling and their dynamical formation and metabolism are important for normal lung physiology. Dysregulation of sphingolipid metabolism and signaling is involved in altering lung tissue and initiates inflammatory processes promoting the pathogenesis of pulmonal diseases including cystic fibrosis (CF), chronic obstructive pulmonary disease (COPD), and asthma.In the present review, the important role of specific sphingolipid species in pulmonal diseases will be discussed. Only such an understanding opens up the possibility of developing new therapeutic strategies with the aim of correcting the imbalance in sphingolipid metabolism and signaling. Such delivery strategies have already been studied in animal models of these lung diseases, demonstrating that targeting the sphingolipid profile represents new therapeutic opportunities for lung disorders.

Metabolomics in Animal Models of Bronchial Asthma and Its Translational Importance for Clinics

Bronchial asthma is an extremely heterogenous chronic respiratory disorder with several distinct endotypes and phenotypes. These subtypes differ not only in the pathophysiological changes and/or clinical features but also in their response to the treatment. Therefore, precise diagnostics represent a fundamental condition for effective therapy. In the diagnostic process, metabolomic approaches have been increasingly used, providing detailed information on the metabolic alterations associated with human asthma. Further information is brought by metabolomic analysis of samples obtained from animal models. This article summarizes the current knowledge on metabolomic changes in human and animal studies of asthma and reveals that alterations in lipid metabolism, amino acid metabolism, purine metabolism, glycolysis and the tricarboxylic acid cycle found in the animal studies resemble, to a large extent, the changes found in human patients with asthma. The findings indicate that, despite the limitations of animal modeling in asthma, pre-clinical testing and metabolomic analysis of animal samples may, together with metabolomic analysis of human samples, contribute to a novel way of personalized treatment of asthma patients.

Maternal vitamin D-related metabolome and offspring risk of asthma outcomes

BACKGROUND

Gestational vitamin D deficiency is implicated in development of respiratory diseases in offspring, but the mechanism underlying this relationship is unknown.

OBJECTIVE

We sought to study the link between gestational vitamin D exposure and childhood asthma phenotypes using maternal blood metabolomics profiling.

METHODS

Untargeted blood metabolic profiles were acquired using liquid chromatography-mass spectrometry at 1 week postpartum from 672 women in the Copenhagen Prospective Studies on Asthma in Childhood2010 (COPSAC2010) mother-child cohort and at pregnancy weeks 32 to 38 from 779 women in the Vitamin D Antenatal Asthma Reduction Trial (VDAART) mother-child cohort. In COPSAC2010, we employed multivariate models and pathway enrichment analysis to identify metabolites and pathways associated with gestational vitamin D blood levels and investigated their relationship with development of asthma phenotypes in early childhood. The findings were validated in VDAART and in cellular models.

RESULTS

In COPSAC2010, higher vitamin D blood levels at 1 week postpartum were associated with distinct maternal metabolome perturbations with significant enrichment of the sphingomyelin pathway (P < .01). This vitamin D-related maternal metabolic profile at 1 week postpartum containing 46 metabolites was associated with decreased risk of recurrent wheeze (hazard ratio [HR] = 0.92 [95% CI 0.86-0.98], P = .01) and wheeze exacerbations (HR = 0.90 [95% CI 0.84-0.97], P = .01) at ages 0 to 3 years. The same metabolic profile was similarly associated with decreased risk of asthma/wheeze at ages 0 to 3 in VDAART (odds ratio = 0.92 [95% CI 0.85-0.99], P = .04). Human bronchial epithelial cells treated with high-dose vitamin D3 showed an increased cytoplasmic sphingolipid level (P < .01).

CONCLUSIONS

This exploratory metabolomics study in 2 independent birth cohorts demonstrates that the beneficial effect of higher gestational vitamin D exposure on offspring respiratory health is characterized by specific maternal metabolic alterations during pregnancy, which involves the sphingomyelin pathway.

Nasal Transcriptome and Epigenome Analysis Identifies the Pathogenic Features of Aspirin-Exacerbated Respiratory Disease

Dysregulation of the arachidonic acid metabolic pathway is the most widely known pathomechanism of aspirin-exacerbated respiratory disease (AERD). This study aimed to perform integrative analysis of transcriptomic and epigenomic profiling with network analysis to determine the novel pathogenic features of AERD. Ten patients with asthma including 5 patients with AERD and another 5 patients with aspirin tolerant asthma (ATA) were enrolled. Nasal scraping was performed and nasal mucosa was used in omics profiling. Peripheral eosinophil counts, sputum eosinophil counts, fractional exhaled nitric oxide levels, and pulmonary function test results were evaluated. Differentially expressed genes (DEGs), differentially methylated probes (DMPs) and differentially correlated genes (DCGs) between patients with AERD and those with ATA were analyzed. Network analysis using ingenuity pathway analysis (IPA) was performed to determine the gene connection network and signaling pathways. In total, 1,736 DEGs, 1,401 DMPs, and 19 pairs for DCGs were identified. Among DCGs, genes related to vesicle transport (e.g., RAB3B and STX2) and sphingolipid dysregulation (e.g., SMPD3) were found to be hypo-methylated and up-regulated in AERD. Using the canonical pathway analysis of IPA with 78 asthma-related DEGs, signaling pathways of T helper cell differentiation/activation and Fcε receptor I were generated. Up-regulation of RORγt and FcER1A were noted in AERD. Gene expression levels of RAB3B, SYNE1, STX2, SMPD3 and RORγt were significantly associated with sputum eosinophil counts. Quantitative real-time polymerase chain reaction was performed and mRNA expression levels of STX2, SMPD3, RORγt, and FcER1A were significantly higher in AERD compared to ATA. Distinct pathogenic features were identified by using integrative multi-omics data analysis in patients with AERD.

An epidemiological introduction to human metabolomic investigations

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

Proline is increased in allergic asthma and promotes airway remodeling

Proline and its synthesis enzyme pyrroline-5-carboxylate reductase 1 (PYCR1) are implicated in epithelial-mesenchymal transition (EMT), yet how proline and PYCR1 function in allergic asthmatic airway remodeling via EMT has not yet been addressed to our knowledge. In the present study, increased levels of plasma proline and PYCR1 were observed in patients with asthma. Similarly, proline and PYCR1 in lung tissues were high in a murine allergic asthma model induced by house dust mites (HDMs). Pycr1 knockout decreased proline in lung tissues, with reduced airway remodeling and EMT. Mechanistically, loss of Pycr1 restrained HDM-induced EMT by modulating mitochondrial fission, metabolic reprogramming, and the AKT/mTORC1 and WNT3a/β-catenin signaling pathways in airway epithelial cells. Therapeutic inhibition of PYCR1 in wild-type mice disrupted HDM-induced airway inflammation and remodeling. Deprivation of exogenous proline relieved HDM-induced airway remodeling to some extent. Collectively, this study illuminates that proline and PYCR1 involved with airway remodeling in allergic asthma could be viable targets for asthma treatment.

Metabolomics identifies disturbances in arginine, phenylalanine, and glycine metabolism as differentiating features of exacerbating atopic asthma in children

Background

Asthma exacerbations are highly prevalent in children, but only a few studies have examined the biologic mechanisms underlying exacerbations in this population.

Objective

High-resolution metabolomics analyses were performed to understand the differences in metabolites in children with exacerbating asthma who were hospitalized in a pediatric intensive care unit for status asthmaticus. We hypothesized that compared with a similar population of stable outpatients with asthma, children with exacerbating asthma would have differing metabolite abundance patterns with distinct clustering profiles.

Methods

A total of 98 children aged 6 through 17 years with exacerbating asthma (n = 69) and stable asthma (n = 29) underwent clinical characterization procedures and submitted plasma samples for metabolomic analyses. High-confidence metabolites were retained and utilized for pathway enrichment analyses to identify the most relevant metabolic pathways that discriminated between groups.

Results

In all, 118 and 131 high-confidence metabolites were identified in positive and negative ionization mode, respectively. A total of 103 unique metabolites differed significantly between children with exacerbating asthma and children with stable asthma. In all, 8 significantly enriched pathways that were largely associated with alterations in arginine, phenylalanine, and glycine metabolism were identified. However, other metabolites and pathways of interest were also identified.

Conclusion

Metabolomic analyses identified multiple perturbed metabolites and pathways that discriminated children with exacerbating asthma who were hospitalized for status asthmaticus. These results highlight the complex biology of inflammation in children with exacerbating asthma and argue for additional studies of the metabolic determinants of asthma exacerbations in children because many of the identified metabolites of interest may be amenable to targeted interventions.

Identification of diurnal rhythmic blood markers in bronchial asthma

Rationale

Asthma is a rhythmic inflammatory disease of the airway, regulated by the circadian clock. "Spill-over" of airway inflammation into the systemic circulation occurs in asthma and is reflected in circulating immune cell repertoire. The objective of the present study was to determine how asthma impacts peripheral blood diurnal rhythmicity.

Methods

10 healthy and 10 mild/moderate asthma participants were recruited to an overnight study. Blood was drawn every 6 h for 24 h.

Main results

The molecular clock in blood cells in asthma is altered; PER3 is significantly more rhythmic in asthma compared to healthy controls. Blood immune cell numbers oscillate throughout the day, in health and asthma. Peripheral blood mononucleocytes from asthma patients show significantly enhanced responses to immune stimulation and steroid suppression at 16:00 h, compared to at 04:00 h. Serum ceramides show complex changes in asthma: some losing and others gaining rhythmicity.

Conclusions

This is the first report showing that asthma is associated with a gain in peripheral blood molecular clock rhythmicity. Whether the blood clock is responding to rhythmic signals received from the lung or driving rhythmic pathology within the lung itself is not clear. Dynamic changes occur in serum ceramides in asthma, probably reflecting systemic inflammatory action. The enhanced responses of asthma blood immune cells to glucocorticoid at 16:00 h may explain why steroid administration is more effective at this time.

Metabolite-disease interaction prediction based on logistic matrix factorization and local neighborhood constraints

Background

Increasing evidence indicates that metabolites are closely related to human diseases. Identifying disease-related metabolites is especially important for the diagnosis and treatment of disease. Previous works have mainly focused on the global topological information of metabolite and disease similarity networks. However, the local tiny structure of metabolites and diseases may have been ignored, leading to insufficiency and inaccuracy in the latent metabolite-disease interaction mining.

Methods

To solve the aforementioned problem, we propose a novel metabolite-disease interaction prediction method with logical matrix factorization and local nearest neighbor constraints (LMFLNC). First, the algorithm constructs metabolite-metabolite and disease-disease similarity networks by integrating multi-source heterogeneous microbiome data. Then, the local spectral matrices based on these two networks are established and used as the input of the model, together with the known metabolite-disease interaction network. Finally, the probability of metabolite-disease interaction is calculated according to the learned latent representations of metabolites and diseases.

Results

Extensive experiments on the metabolite-disease interaction data were conducted. The results show that the proposed LMFLNC method outperformed the second-best algorithm by 5.28 and 5.61% in the AUPR and F1, respectively. The LMFLNC method also exhibited several potential metabolite-disease interactions, such as "Cortisol" (HMDB0000063), relating to "21-Hydroxylase deficiency," and "3-Hydroxybutyric acid" (HMDB0000011) and "Acetoacetic acid" (HMDB0000060), both relating to "3-Hydroxy-3-methylglutaryl-CoA lyase deficiency."

Conclusion

The proposed LMFLNC method can well preserve the geometrical structure of original data and can thus effectively predict the underlying associations between metabolites and diseases. The experimental results show its effectiveness in metabolite-disease interaction prediction.

Instrumental Drift in Untargeted Metabolomics: Optimizing Data Quality with Intrastudy QC Samples

Untargeted metabolomics is an important tool in studying health and disease and is employed in fields such as biomarker discovery and drug development, as well as precision medicine. Although significant technical advances were made in the field of mass-spectrometry driven metabolomics, instrumental drifts, such as fluctuations in retention time and signal intensity, remain a challenge, particularly in large untargeted metabolomics studies. Therefore, it is crucial to consider these variations during data processing to ensure high-quality data. Here, we will provide recommendations for an optimal data processing workflow using intrastudy quality control (QC) samples that identifies errors resulting from instrumental drifts, such as shifts in retention time and metabolite intensities. Furthermore, we provide an in-depth comparison of the performance of three popular batch-effect correction methods of different complexity. By using different evaluation metrics based on QC samples and a machine learning approach based on biological samples, the performance of the batch-effect correction methods were evaluated. Here, the method TIGER demonstrated the overall best performance by reducing the relative standard deviation of the QCs and dispersion-ratio the most, as well as demonstrating the highest area under the receiver operating characteristic with three different probabilistic classifiers (Logistic regression, Random Forest, and Support Vector Machine). In summary, our recommendations will help to generate high-quality data that are suitable for further downstream processing, leading to more accurate and meaningful insights into the underlying biological processes.

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.

Application of Metabolomics in Obesity-Related Childhood Asthma Subtyping: A Narrative Scoping Review

Obesity-related asthma is a heterogeneous childhood asthma phenotype with rising prevalence. Observational studies identify early-life obesity or weight gain as risk factors for childhood asthma development. The reverse association is also described, children with asthma have a higher risk of being obese. Obese children with asthma have poor symptom control and an increased number of asthma attacks compared to non-obese children with asthma. Clinical trials have also identified that a proportion of obese children with asthma do not respond as well to usual treatment (e.g., inhaled corticosteroids). The heterogeneity of obesity-related asthma phenotypes may be attributable to different underlying pathogenetic mechanisms. Although few childhood obesity-related asthma endotypes have been described, our knowledge in this field is incomplete. An evolving analytical profiling technique, metabolomics, has the potential to link individuals' genetic backgrounds and environmental exposures (e.g., diet) to disease endotypes. This will ultimately help define clinically relevant obesity-related childhood asthma subtypes that respond better to targeted treatment. However, there are challenges related to this approach. The current narrative scoping review summarizes the evidence for metabolomics contributing to asthma subtyping in obese children, highlights the challenges associated with the implementation of this approach, and identifies gaps in research.

Blood-Based Biomarkers for Eosinophilic Esophagitis and Concomitant Atopic Diseases: A Look into the Potential of Extracellular Vesicles

Eosinophilic esophagitis (EoE) is a chronic, Th2-inflammatory disease of the esophagus that can severely affect food intake. Currently, diagnosis and assessing response to treatment of EoE is highly invasive and requires endoscopy with esophageal biopsies. Finding non-invasive and accurate biomarkers is important for improving patient well-being. Unfortunately, EoE is usually accompanied by other atopies, which make it difficult to identify specific biomarkers. Providing an update of circulating EoE biomarkers and concomitant atopies is therefore timely. This review summarizes the current knowledge in EoE blood biomarkers and two of its most common comorbidities, bronchial asthma (BA) and atopic dermatitis (AD), focusing on dysregulated proteins, metabolites, and RNAs. It also revises the current knowledge on extracellular vesicles (EVs) as non-invasive biomarkers for BA and AD, and concludes with the potential use of EVs as biomarkers in EoE.

Phospholipid remodeling and its derivatives are associated with COVID-19 severity

BACKGROUND

Timely medical intervention in severe cases of coronavirus disease 2019 (COVID-19) and better understanding of the disease's pathogenesis are essential for reducing mortality, but early classification of severe cases and its progression is challenging.

OBJECTIVE

We investigated the levels of circulating phospholipid metabolites and their relationship with COVID-19 severity, as well as the potential role of phospholipids in disease progression.

METHODS

We performed nontargeted lipidomic analysis of plasma samples (n = 150) collected from COVID-19 patients (n = 46) with 3 levels of disease severity, healthy individuals, and subjects with metabolic disease.

RESULTS

Phospholipid metabolism was significantly altered in COVID-19 patients. Results of a panel of phosphatidylcholine (PC) and lysophosphatidylcholine (LPC) and of phosphatidylethanolamine and lysophosphatidylethanolamine (LPE) ratios were significantly correlated with COVID-19 severity, in which 16 phospholipid ratios were shown to distinguish between patients with severe disease, mild disease, and healthy controls, 9 of which were at variance with those in subjects with metabolic disease. In particular, relatively lower ratios of circulating (PC16:1/22:6)/LPC 16:1 and (PE18:1/22:6)/LPE 18:1 were the most indicative of severe COVID-19. The elevation of levels of LPC 16:1 and LPE 18:1 contributed to the changes of related lipid ratios. An exploratory functional study of LPC 16:1 and LPE 18:1 demonstrated their ability in causing membrane perturbation, increased intracellular calcium, cytokines, and apoptosis in cellular models.

CONCLUSION

Significant Lands cycle remodeling is present in patients with severe COVID-19, suggesting a potential utility of selective phospholipids with functional consequences in evaluating COVID-19's severity and pathogenesis.

Pharmacometabolomics of Asthma as a Road Map to Precision Medicine

Pharmacometabolomics applies the principles of metabolomics to therapeutics in order to elucidate the biological mechanisms underlying the variation in responses to drugs between groups and individuals. Asthma is associated with broad systemic effects and heterogeneity in treatment response and as such is ideally suited to pharmacometabolomics. In this chapter, we discuss the state of the emerging field of asthma pharmacometabolomics, with a particular focus on studies of steroids, bronchodilators, and leukotriene inhibitors. We also consider those studies concerned with subtyping cases to better understand the pharmacology of those groups and those looking to leverage pharmacometabolomics for asthma prevention. We finish with a discussion of the challenges and opportunities of asthma pharmacometabolomics and reflect upon where this field must go next in order to realize its precision medicine potential.

Metabolomics of Respiratory Diseases

Metabolomics is an expanding field of systems biology that is gaining significant attention in respiratory research. As a unique approach to understanding and diagnosing diseases, metabolomics provides a snapshot of all metabolites present in biological samples such as exhaled breath condensate, bronchoalveolar lavage, plasma, serum, urine, and other specimens that may be obtained from patients with respiratory diseases. In this article, we review the rapidly expanding field of metabolomics in its application to respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), pneumonia, and acute lung injury, along with its more severe form, adult respiratory disease syndrome. We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized occupational and environmental materials. With the latest advances in our understanding of the microbiome, we discuss microbiome-derived metabolites that arise from the gut and lung in asthma and COPD that have mechanistic implications for these diseases. Recent literature has suggested that metabolomics analysis using nuclear magnetic resonance (NMR) and mass spectrometry (MS) approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe diseases which may be fatal for many patients each year.

Precision Medicine in Asthma Therapy

Asthma is a complex, heterogeneous disease that necessitates a proper patient evaluation to decide the correct treatment and optimize disease control. The recent introduction of new target therapies for the most severe form of the disease has heralded a new era of treatment options, intending to treat and control specific molecular pathways in asthma pathophysiology. Precision medicine, using omics sciences, investigates biological and molecular mechanisms to find novel biomarkers that can be used to guide treatment selection and predict response. The identification of reliable biomarkers indicative of the pathological mechanisms in asthma is essential to unravel new potential treatment targets. In this chapter, we provide a general description of the currently available -omics techniques, focusing on their implications in asthma therapy.

Deciphering the role of platelets in severe allergy by an integrative omics approach

BACKGROUND

Mechanisms causing the onset and perpetuation of inflammation in severe allergic patients remain unknown. Our previous studies suggested that severe allergic inflammation is linked to platelet dysfunction.

METHODS

Platelet-rich plasma (PRP) and platelet-poor plasma (PPP) samples were obtained by platelet-apheresis from severe (n = 7) and mild (n = 10) allergic patients and nonallergic subjects (n = 9) to perform platelet lipidomics by liquid chromatography coupled to mass spectrometry (LC-MS) and RNA-seq analysis. Significant metabolites and transcripts were used to identify compromised biological pathways in the severe phenotype. Platelet and inflammation-related proteins were quantified by Luminex.

RESULTS

Platelets from severe allergic patients were characterized by high levels of ceramides, phosphoinositols, phosphocholines, and sphingomyelins. In contrast, they showed a decrease in eicosanoid precursor levels. Biological pathway analysis performed with the significant lipids revealed the alteration of phospholipases, calcium-dependent events, and linolenic metabolism. RNAseq confirmed mRNA overexpression of genes related to platelet activation and arachidonic acid metabolism in the severe phenotypes. Pathway analysis indicated the alteration of NOD, MAPK, TLR, TNF, and IL-17 pathways in the severe phenotype. P-Selectin and IL-17AF proteins were increased in the severe phenotype.

CONCLUSIONS

This study demonstrates that platelet lipid, mRNA, and protein content is different according to allergy severity. These findings suggest that platelet load is a potential source of biomarkers and a new chance for therapeutic targets in severe inflammatory pathologies.

Integrated Exposomics/Metabolomics for Rapid Exposure and Effect Analyses

The totality of environmental exposures and lifestyle factors, commonly referred to as the exposome, is poorly understood. Measuring the myriad of chemicals that humans are exposed to is immensely challenging, and identifying disrupted metabolic pathways is even more complex. Here, we present a novel technological approach for the comprehensive, rapid, and integrated analysis of the endogenous human metabolome and the chemical exposome. By combining reverse-phase and hydrophilic interaction liquid chromatography (HILIC) and fast polarity-switching, molecules with highly diverse chemical structures can be analyzed in 15 min with a single analytical run as both column's effluents are combined before analysis. Standard reference materials and authentic standards were evaluated to critically benchmark performance. Highly sensitive median limits of detection (LODs) with 0.04 μM for >140 quantitatively assessed endogenous metabolites and 0.08 ng/mL for the >100 model xenobiotics and human estrogens in solvent were obtained. In matrix, the median LOD values were higher with 0.7 ng/mL (urine) and 0.5 ng/mL (plasma) for exogenous chemicals. To prove the dual-column approach's applicability, real-life urine samples from sub-Saharan Africa (high-exposure scenario) and Europe (low-exposure scenario) were assessed in a targeted and nontargeted manner. Our liquid chromatography high-resolution mass spectrometry (LC-HRMS) approach demonstrates the feasibility of quantitatively and simultaneously assessing the endogenous metabolome and the chemical exposome for the high-throughput measurement of environmental drivers of diseases.

The Role of Systems Biology in Deciphering Asthma Heterogeneity

Asthma is one of the most common and lifelong and chronic inflammatory diseases characterized by inflammation, bronchial hyperresponsiveness, and airway obstruction episodes. It is a heterogeneous disease of varying and overlapping phenotypes with many confounding factors playing a role in disease susceptibility and management. Such multifactorial disorders will benefit from using systems biology as a strategy to elucidate molecular insights from complex, quantitative, massive clinical, and biological data that will help to understand the underlying disease mechanism, early detection, and treatment planning. Systems biology is an approach that uses the comprehensive understanding of living systems through bioinformatics, mathematical, and computational techniques to model diverse high-throughput molecular, cellular, and the physiologic profiling of healthy and diseased populations to define biological processes. The use of systems biology has helped understand and enrich our knowledge of asthma heterogeneity and molecular basis; however, such methods have their limitations. The translational benefits of these studies are few, and it is recommended to reanalyze the different studies and omics in conjugation with one another which may help understand the reasons for this variation and help overcome the limitations of understanding the heterogeneity in asthma pathology. In this review, we aim to show the different factors that play a role in asthma heterogeneity and how systems biology may aid in understanding and deciphering the molecular basis of asthma.

Omics technologies in allergy and asthma research: An EAACI position paper

Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force "Omics technologies in allergic research" broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients' stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Metabolomic changes related to airway inflammation, asthma pathogenesis and systemic activity following inhaled fluticasone furoate/vilanterol: a randomized controlled trial

BACKGROUND

Fluticasone furoate/vilanterol trifenatate (FF/VI) is an inhaled therapy for the treatment of asthma, with a prolonged duration of anti-inflammatory and bronchodilatory action. This study investigated the global metabolomic and lipidomic profile following treatment with FF/VI or placebo and assessed whether changes correlated with exhaled nitric oxide levels as a measure of airway inflammation.

METHODS

This was a single-center, randomized, double-blind, placebo-controlled, two-period, crossover, repeat-dose study. Adults with asthma (forced expiratory volume in 1 s ≥ 60% predicted; fraction of exhaled nitric oxide [FeNO] > 40 parts per billion) received once-daily FF/VI 100 µg/25 µg or placebo for 14 days, followed by a 21-day washout period. Serum samples were taken at pre-dose (T1), and 15 and 21 days (T2 and T3, respectively) post dose in each period. The metabolomic and lipidomic profiles were analyzed by liquid chromatography with tandem mass spectrometry and polar liquid chromatography platforms, and ions were matched to a library of standards for metabolite identification and quantification. FeNO values at each timepoint were evaluated for correlations with the biochemical data.

RESULTS

Of 27 randomized participants (mean age 24.5 years, 63% male), 26 provided serum samples for metabolomic analysis. A total of 1969 metabolites were identified, 1634 of which corresponded to a named structure in a reference library. Treatment-related changes in the metabolome were generally subtle, with a modest increase in metabolite perturbations across timepoints. The percentage of metabolites with significant changes (p < 0.05 for all) (increases↑/decreases↓) versus placebo were: 2.1% (1.1%↑/1.0%↓), 6.7% (0.46%↑/6.2%↓) and 11.8% (0.86%↑/10.9%↓) at T1, T2 and T3, respectively. Treatment with FF/VI reduced FeNO levels by 60%, whereas the systemic intermediates involved in NO biosynthesis remained unaffected. Evidence of systemic anti-inflammatory activity was seen in complex lipid pathways, suggesting reduced phospholipase-A2 activity, but without downstream impact on free fatty acids or inflammatory mediators. Consistent with the pathogenesis of asthma, there was evidence of higher fatty acid β-oxidation and lower glycolysis in the placebo arm; this pattern was reversed in the treatment arm.

CONCLUSIONS

Despite the prolonged airway anti-inflammatory action of FF/VI, this was accompanied by only subtle systemic metabolomic and lipidomic changes. Trial registration Prospectively registered on ClinicalTrials.gov registry number NCT02712047.

Metabolomic Profiling of Samples from Pediatric Asthma Patients Unveils Deficient Nutrients in African Americans

Plasma metabolomics represents a potentially powerful approach to understand the biochemical mechanisms of nutrition and metabolism in asthma. This study aims to acquire knowledge on plasma metabolites in asthma, which may provide avenues for nutrition therapy, as well as explanations for the observed effects in existing therapies. This study investigated 249 metabolites from 18 metabolite groups in a large cohort of African American population, including 602 pediatric patients with asthma and 593 controls, using a nuclear magnetic resonance (NMR) metabolomics platform. Decreased levels of citrate, ketone bodies, and two amino acids histidine (His) and glutamine (Gln), were observed in asthma cases compared to controls. Metabolites for lipid metabolism lost significance after controlling for comorbid obesity. For the first time, this study depicts a broad panorama of lipid metabolism and nutrition in asthma. Supplementation or augmentation of nutrients that are deficient may be beneficial for asthma care.

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Asthma is a major health issue in African Americans

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Metabolomics represents a powerful approach to understand the metabolism in asthma

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We observed decreased citrate, ketone bodies, and amino acids in the plasma

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Supplementation of nutrients that are deficient may be beneficial for asthma care

Understanding uncontrolled severe allergic asthma by integration of omic and clinical data

BACKGROUND

Asthma is a complex, multifactorial disease often linked with sensitization to house dust mites (HDM). There is a subset of patients that does not respond to available treatments, who present a higher number of exacerbations and a worse quality of life. To understand the mechanisms of poor asthma control and disease severity, we aim to elucidate the metabolic and immunologic routes underlying this specific phenotype and the associated clinical features.

METHODS

Eighty-seven patients with a clinical history of asthma were recruited and stratified in 4 groups according to their response to treatment: corticosteroid-controlled (ICS), immunotherapy-controlled (IT), biologicals-controlled (BIO) or uncontrolled (UC). Serum samples were analysed by metabolomics and proteomics; and classifiers were built using machine-learning algorithms.

RESULTS

Metabolomic analysis showed that ICS and UC groups cluster separately from one another and display the highest number of significantly different metabolites among all comparisons. Metabolite identification and pathway enrichment analysis highlighted increased levels of lysophospholipids related to inflammatory pathways in the UC patients. Likewise, 8 proteins were either upregulated (CCL13, ARG1, IL15 and TNFRSF12A) or downregulated (sCD4, CCL19 and IFNγ) in UC patients compared to ICS, suggesting a significant activation of T cells in these patients. Finally, the machine-learning model built including metabolomic and clinical data was able to classify the patients with an 87.5% accuracy.

CONCLUSIONS

UC patients display a unique fingerprint characterized by inflammatory-related metabolites and proteins, suggesting a pro-inflammatory environment. Moreover, the integration of clinical and experimental data led to a deeper understanding of the mechanisms underlying UC phenotype.

Metabolomics in pulmonary medicine - extracting the most from your data

The metabolome enables unprecedented insight into biochemistry, providing an integrated signature of the genome, transcriptome, proteome and exposome. Measurement requires rigorous protocols combined with specialised data analysis to achieve its promise.https://bit.ly/3yPiYkQ

Prediction of clinical efficacy of subcutaneous immunotherapy for Artemisia sieversiana pollen allergic rhinitis by serum metabolomics

BACKGROUND/PURPOSE

Specific immunotherapy is the only effective etiological treatment for allergic rhinitis, but subcutaneous immunotherapy has a slow onset and poor compliance. Predicting the clinical efficacy of subcutaneous immunotherapy in advance can reduce unnecessary medical costs and resource waste. This study aimed to identify metabolites that could predict the efficacy of subcutaneous immunotherapy on seasonal allergic rhinitis by serum metabolomics.

METHODS

Patients (n = 43) with Artemisia sieversiana pollen allergic rhinitis were enrolled and treated with subcutaneous immunotherapy for one year. Patients were divided into the ineffective group (n = 10) and effective group (n = 33) according to the therapeutic index. Serum samples were collected before treatment. Metabolomics was determined by liquid chromatography-mass spectrometry combined with gas chromatography-mass spectrometry and analyzed differential compounds and related metabolic pathways.

RESULTS

A total of 129 differential metabolites (P < 0.05) were identified and 4 metabolic pathways, namely taurine and hypotaurine metabolism, pentose and glucuronate interconversions, pentose phosphate pathway, and alanine, aspartate, and glutamate metabolism, were involved.

CONCLUSION

Some metabolites, such as hypotaurine, taurine, and l-alanine, have the potential to become predictive biomarkers for effective subcutaneous immunotherapy.

The impact of maternal asthma on the preterm infants' gut metabolome and microbiome (MAP study)

Preterm infants are at a greater risk for the development of asthma and atopic disease, which can lead to lifelong negative health consequences. This may be due, in part, to alterations that occur in the gut microbiome and metabolome during their stay in the Neonatal Intensive Care Unit (NICU). To explore the differential roles of family history (i.e., predisposition due to maternal asthma diagnosis) and hospital-related environmental and clinical factors that alter microbial exposures early in life, we considered a unique cohort of preterm infants born ≤ 34 weeks gestational age from two local level III NICUs, as part of the MAP (Microbiome, Atopic disease, and Prematurity) Study. From MAP participants, we chose a sub-cohort of infants whose mothers had a history of asthma and matched gestational age and sex to infants of mothers without a history of asthma diagnosis (control). We performed a prospective, paired metagenomic and metabolomic analysis of stool and milk feed samples collected at birth, 2 weeks, and 6 weeks postnatal age. Although there were clinical factors associated with shifts in the diversity and composition of stool-associated bacterial communities, maternal asthma diagnosis did not play an observable role in shaping the infant gut microbiome during the study period. There were significant differences, however, in the metabolite profile between the maternal asthma and control groups at 6 weeks postnatal age. The most notable changes occurred in the linoleic acid spectral network, which plays a role in inflammatory and immune pathways, suggesting early metabolomic changes in the gut of preterm infants born to mothers with a history of asthma. Our pilot study suggests that a history of maternal asthma alters a preterm infants’ metabolomic pathways in the gut, as early as the first 6 weeks of life.

Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma

The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.

Gut Microbiome and Metabolomics Profiles of Allergic and Non-Allergic Childhood Asthma

Purpose

This study aimed to investigate the characteristics of gut bacteria and the derived metabolites among allergic asthmatic children, non-allergic asthmatic children and healthy children without asthma.

Methods

Fecal samples were collected from 57 participants, including 20 healthy children, 27 allergic asthmatic children, and 10 non-allergic asthmatic children. 16S rRNA gene sequencing was conducted for analyzing gut bacterial compositions and untargeted metabolomics was used to analyze the alterations of gut microbe-derived metabolites. The associations between gut bacterial compositions and metabolites were analyzed by the method of Spearman correlation.

Results

The results showed that the compositions and metabolites of gut microbiome were altered both in allergic and non-allergic asthmatics compared with healthy controls. Chao1 (p = 0.025) index reflected a higher bacterial richness and Simpson (p = 0.024) index showed a lower diversity in asthma group. PERMANOVA analysis showed significant differences among the three groups based on unweighted UniFrac distance (p = 0.001). Both allergic and non-allergic asthmatics showed a higher relative abundance of Proteobacteria and a lower relative abundance of genera from Clostridia. More bacteria were altered in non-allergic asthmatics compared with allergic asthmatics. Metabolomics analysis identified that 42 metabolites were significantly associated with allergic asthma, and 58 metabolites were significantly associated with non-allergic asthma (multiple linear regression, p < 0.05). Histamine was 4 folds up-regulated only in the non-allergic asthma group. The relative abundance of Candidatus Accumulib was significantly correlated with the upregulation of histamine. The relative abundance of genera from Clostridia was significantly correlated with the downregulation of lipid and tryptophan metabolism.

Conclusion

The altered gut microbes was associated with the mechanism of asthma attack through metabolites in allergic and non-allergic asthma group, respectively. The result suggested that gut microbiome had an impact on the development of both allergic and non-allergic asthma. The distinct gut microbiome and microbiome-derived metabolites in non-allergic asthma children suggested that gut microbiome might play a critical role in modulation of asthma phenotype.

Metabo-Endotypes of Asthma Reveal Differences in Lung Function: Discovery and Validation in Two TOPMed Cohorts

Rationale: Current guidelines do not sufficiently capture the heterogeneous nature of asthma; a more detailed molecular classification is needed. Metabolomics represents a novel and compelling approach to derive asthma endotypes (i.e., subtypes defined by functional and/or pathobiological mechanisms). Objectives: To validate metabolomic-driven endotypes of asthma and explore their underlying biology. Methods: In the Genetics of Asthma in Costa Rica Study (GACRS), untargeted metabolomic profiling, similarity network fusion, and spectral clustering was used to identify metabo-endotypes of asthma, and differences in asthma-relevant phenotypes across these metabo-endotypes were explored. The metabo-endotypes were recapitulated in the Childhood Asthma Management Program (CAMP), and clinical differences were determined. Metabolomic drivers of metabo-endotype membership were investigated by meta-analyzing findings from GACRS and CAMP. Measurements and Main Results: Five metabo-endotypes were identified in GACRS with significant differences in asthma-relevant phenotypes, including prebronchodilator (p-ANOVA = 8.3 × 10^-5) and postbronchodilator (p-ANOVA = 1.8 × 10^-5) FEV₁/FVC. These differences were validated in the recapitulated metabo-endotypes in CAMP. Cholesterol esters, trigylcerides, and fatty acids were among the most important drivers of metabo-endotype membership. The findings suggest dysregulation of pulmonary surfactant homeostasis may play a role in asthma severity. Conclusions: Clinically meaningful endotypes may be derived and validated using metabolomic data. Interrogating the drivers of these metabo-endotypes has the potential to help understand their pathophysiology.

Revealing the Mysteries of Acute Myeloid Leukemia: From Quantitative PCR through Next-Generation Sequencing and Systemic Metabolomic Profiling

The efforts made in the last decade regarding the molecular landscape of acute myeloid leukemia (AML) have created the possibility of obtaining patients’ personalized treatment. Indeed, the improvement of accurate diagnosis and precise assessment of minimal residual disease (MRD) increased the number of new markers suitable for novel and targeted therapies. This progress was obtained thanks to the development of molecular techniques starting with real-time quantitative PCR (Rt-qPCR) passing through digital droplet PCR (ddPCR) and next-generation sequencing (NGS) up to the new attractive metabolomic approach. The objective of this surge in technological advances is a better delineation of AML clonal heterogeneity, monitoring patients without disease-specific mutation and designing customized post-remission strategies based on MRD assessment. In this context, metabolomics, which pertains to overall small molecules profiling, emerged as relevant access for risk stratification and targeted therapies improvement. In this review, we performed a detailed overview of the most popular modern methods used in hematological laboratories, pointing out their vital importance for MRD monitoring in order to improve overall survival, early detection of possible relapses and treatment efficacy.

A roadmap for multi-omics data integration using deep learning

High-throughput next-generation sequencing now makes it possible to generate a vast amount of multi-omics data for various applications. These data have revolutionized biomedical research by providing a more comprehensive understanding of the biological systems and molecular mechanisms of disease development. Recently, deep learning (DL) algorithms have become one of the most promising methods in multi-omics data analysis, due to their predictive performance and capability of capturing nonlinear and hierarchical features. While integrating and translating multi-omics data into useful functional insights remain the biggest bottleneck, there is a clear trend towards incorporating multi-omics analysis in biomedical research to help explain the complex relationships between molecular layers. Multi-omics data have a role to improve prevention, early detection and prediction; monitor progression; interpret patterns and endotyping; and design personalized treatments. In this review, we outline a roadmap of multi-omics integration using DL and offer a practical perspective into the advantages, challenges and barriers to the implementation of DL in multi-omics data.

The preliminary investigation of potential response biomarkers to PAHs exposure on childhood asthma

BACKGROUND

Exposure to polycyclic aromatic hydrocarbons (PAHs) is a potential risk factor for asthma prevalence. This study aims to explore whether PAHs exposure is associated with childhood asthma by altering microbial diversity and metabolic profiles.

METHODS

Thirty children with asthma and 30 children as control in Nanjing, China were recruited. Urinary 1-hydroxypyrene (1-OHPyr) level was determined by UPLC-Orbitrap-MS as a PAHs exposure biomarker. Logistic regression was conducted to investigate the association between 1-OHPyr and childhood asthma. Microbial diversity was analyzed by 16S rRNA gene sequencing. Metabolic profiles were obtained by UPLC-Orbitrap-MS methods. Differential microbiota and metabolites were screened and selected as response biomarkers or intermediates. Mediation analysis was conducted to assess the association between PAHs and asthma mediated by intermediates.

RESULTS

Participating children with and without asthma aged 6.43 ± 2.23 years. The urinary 1-OHPyr level ranged from 0.10 to 1.51 μmol/mol (creatinine corrected) in the participants. The urinary 1-OHPyr level was associated with childhood asthma (OR = 7.21, 95% CI: 1.03-50.42 per 1 μmol/mol unit). Microbial diversity was decreased in the group with asthma and there was a significant shift in the abundance of Proteobacteria (at the phylum level), Veillonella and Prevotella (at the genus level). The enrichment pathway analysis showed that differentially expressed metabolites were involved in purine metabolism, amino acid metabolism, and lipid and fatty acid metabolism. The urinary 1-OHPyr level was associated with the abundance of Actinomyces sp. oral clone IO076 and 7-methylguanine that showed a mediation effect on the association between urinary 1-OHPyr levels and childhood asthma by mediation analysis.

CONCLUSIONS

Urinary 1-OHPyr exposure was associated with childhood asthma, microbial diversity, and metabolic profiles. Microbial diversity and metabolic profiles may be intermediates as response biomarkers to PAHs exposure in childhood asthma. Further research is needed to confirm these study results and determine the underlying mechanism.

Metabolome subtyping of severe bronchiolitis in infancy and risk of childhood asthma

BACKGROUND

Infants with bronchiolitis are at increased risk for developing asthma. Growing evidence suggests bronchiolitis is a heterogeneous condition.

OBJECTIVES

We sought to identify biologically distinct subgroups based on the metabolome signatures (metabotypes) in infants with severe bronchiolitis and to examine the longitudinal relationships of metabotypes with asthma development.

METHODS

In a multicenter prospective cohort study of infants (age, <12 months) hospitalized for bronchiolitis, the nasopharyngeal airway metabolome was profiled at hospitalization. Using a clustering approach, this study identified mutually exclusive metabotypes. This study also examined their longitudinal association with the risk of developing asthma by 5 years of age.

RESULTS

Of 918 infants hospitalized for bronchiolitis (median age, 3 months), this study identified 5 distinct metabotypes-characterized by their nasopharyngeal metabolome profile: A, glycerophosphocholine-high; B, amino acid-high, polyunsaturated fatty acid-low; C, amino acid-high, glycerophospholipid-low; D, glycerophospholipid-high; and E, mixed. Compared with infants with metabotype A (who clinically resembled "classic" bronchiolitis), infants with metabotype B had a significantly higher risk for developing asthma (23% vs 41%; adjusted odds ratio, 2.22; 95% CI, 1.07-4.69). The pathway analysis showed that metabotype B had enriched amino acid (eg, methionine, histidine, glutathione) and α-linolenic/linoleic acid metabolism pathways (false discovery rate, <5 × 10-14 for all). Finally, the transcriptome analysis revealed that infants with metabotype B had upregulated IFN-α and IL-6/JAK/STAT3 pathways and downregulated fatty acid metabolism pathways (false discovery rate, <0.05 for both).

CONCLUSIONS

In this multicenter prospective cohort study of infants with severe bronchiolitis, the clustering analysis of metabolome data identified biologically distinct metabotypes, including a metabotype characterized by high inflammatory amino acids and low polyunsaturated fatty acids that is at significantly increased risk for developing asthma.

Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma

Asthma is a multifactorial inflammatory disorder of the respiratory system characterized by high diversity in clinical manifestations, underlying pathological mechanisms and response to treatment. It is generally established that human microbiota plays an essential role in shaping a healthy immune response, while its perturbation can cause chronic inflammation related to a wide range of diseases, including asthma. Systems biology approaches encompassing microbiome analysis can offer valuable platforms towards a global understanding of asthma complexity and improving patients' classification, status monitoring and therapeutic choices. In the present review, we summarize recent studies exploring the contribution of microbiota dysbiosis to asthma pathogenesis and heterogeneity in the context of asthma phenotypes-endotypes and administered medication. We subsequently focus on emerging efforts to gain deeper insights into microbiota-host interactions driving asthma complexity by integrating microbiome and host multi-omics data. One of the most prominent achievements of these research efforts is the association of refractory neutrophilic asthma with certain microbial signatures, including predominant pathogenic bacterial taxa (such as Proteobacteria phyla, Gammaproteobacteria class, especially species from Haemophilus and Moraxella genera). Overall, despite existing challenges, large-scale multi-omics endeavors may provide promising biomarkers and therapeutic targets for future development of novel microbe-based personalized strategies for diagnosis, prevention and/or treatment of uncontrollable asthma.

Urinary metabotype of severe asthma evidences decreased carnitine metabolism independent of oral corticosteroid treatment in the U-BIOPRED study

INTRODUCTION

Asthma is a heterogeneous disease with poorly defined phenotypes. Severe asthmatics often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication.

METHODS

Baseline urine was collected prospectively from healthy participants (n=100), mild-to-moderate asthmatics (n=87) and severe asthmatics (n=418) in the cross-sectional U-BIOPRED cohort; 12-18-month longitudinal samples were collected from severe asthmatics (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods.

RESULTS

Ninety metabolites were identified, with 40 significantly altered (p<0.05, FDR<0.05) in severe asthma and 23 by OCS use. Multivariate modelling showed that observed metabotypes in healthy participants and mild-to-moderate asthmatics differed significantly from severe asthmatics (p=2.6×10^-20), OCS-treated asthmatics differed significantly from non-treated (p=9.5×10^-4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings.

CONCLUSIONS

This is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the necessity to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma.

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation

Rationale

Asthma phenotyping requires novel biomarker discovery.

Objectives

To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs).

Methods

An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED.

Results

In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation.

Conclusions

The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.

Application of new proteomic panel in two established European asthma cohorts identifies plasma proteins associated with disease severity independently of Type-2 inflammation, suggesting potentially useful novel biomarkers and therapeutic targets.https://bit.ly/3jtTq5m

Childhood asthma- pathogenesis and phenotypes

In the pathogenesis of asthma in children there is a pivotal role for a type 2 inflammatory response to early life exposures or events. Interactions between infections, atopy, genetic susceptibility, and environmental exposures (such as farmyard environment, air pollution, tobacco smoke exposure) influence the development of wheezing illness and the risk for progression to asthma. The immune system, lung function and the microbiome in gut and airways develop in parallel and dysbiosis of the microbiome may be a critical factor in asthma development. Increased infant weight gain and preterm birth are other risk factors for development of asthma and reduced lung function. The complex interplay between these factors explains the heterogeneity of asthma in children. Subgroups of patients can be identified as phenotypes based on clinical parameters, or endotypes, based on a specific pathophysiological mechanism. Paediatric asthma phenotypes and endotypes may ultimately help to improve diagnosis of asthma, prediction of asthma development and treatment of individual children, based on clinical, temporal, developmental or inflammatory characteristics. Unbiased, data-driven clustering, using a multidimensional or systems biology approach may be needed to better define phenotypes. The present knowledge on inflammatory phenotypes of childhood asthma has now been successfully applied in the treatment with biologicals of children with severe therapy resistant asthma, and it is to be expected that more personalized treatment options may become available.

Severity of COVID-19 Patients Predicted by Serum Sphingolipids Signature

The reason behind the high inter-individual variability in response to SARS-CoV-2 infection and patient’s outcome is poorly understood. The present study targets the sphingolipid profile of twenty-four healthy controls and fifty-nine COVID-19 patients with different disease severity. Sera were analyzed by untargeted and targeted mass spectrometry and ELISA. Results indicated a progressive increase in dihydrosphingosine, dihydroceramides, ceramides, sphingosine, and a decrease in sphingosine-1-phosphate. These changes are associated with a serine palmitoyltransferase long chain base subunit 1 (SPTLC1) increase in relation to COVID-19 severity. Severe patients showed a decrease in sphingomyelins and a high level of acid sphingomyelinase (aSMase) that influences monosialodihexosyl ganglioside (GM3) C16:0 levels. Critical patients are characterized by high levels of dihydrosphingosine and dihydroceramide but not of glycosphingolipids. In severe and critical patients, unbalanced lipid metabolism induces lipid raft remodeling, leads to cell apoptosis and immunoescape, suggesting active sphingolipid participation in viral infection. Furthermore, results indicated that the sphingolipid and glycosphingolipid metabolic rewiring promoted by aSMase and GM3 is age-dependent but also characteristic of severe and critical patients influencing prognosis and increasing viral load. AUCs calculated from ROC curves indicated ceramides C16:0, C18:0, C24:1, sphingosine and SPTLC1 as putative biomarkers of disease evolution.

Reproducibility of mass spectrometry based metabolomics data

BACKGROUND

Assessing the reproducibility of measurements is an important first step for improving the reliability of downstream analyses of high-throughput metabolomics experiments. We define a metabolite to be reproducible when it demonstrates consistency across replicate experiments. Similarly, metabolites which are not consistent across replicates can be labeled as irreproducible. In this work, we introduce and evaluate the use (Ma)ximum (R)ank (R)eproducibility (MaRR) to examine reproducibility in mass spectrometry-based metabolomics experiments. We examine reproducibility across technical or biological samples in three different mass spectrometry metabolomics (MS-Metabolomics) data sets.

RESULTS

We apply MaRR, a nonparametric approach that detects the change from reproducible to irreproducible signals using a maximal rank statistic. The advantage of using MaRR over model-based methods that it does not make parametric assumptions on the underlying distributions or dependence structures of reproducible metabolites. Using three MS Metabolomics data sets generated in the multi-center Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPD) study, we applied the MaRR procedure after data processing to explore reproducibility across technical or biological samples. Under realistic settings of MS-Metabolomics data, the MaRR procedure effectively controls the False Discovery Rate (FDR) when there was a gradual reduction in correlation between replicate pairs for less highly ranked signals. Simulation studies also show that the MaRR procedure tends to have high power for detecting reproducible metabolites in most situations except for smaller values of proportion of reproducible metabolites. Bias (i.e., the difference between the estimated and the true value of reproducible signal proportions) values for simulations are also close to zero. The results reported from the real data show a higher level of reproducibility for technical replicates compared to biological replicates across all the three different datasets. In summary, we demonstrate that the MaRR procedure application can be adapted to various experimental designs, and that the nonparametric approach performs consistently well.

CONCLUSIONS

This research was motivated by reproducibility, which has proven to be a major obstacle in the use of genomic findings to advance clinical practice. In this paper, we developed a data-driven approach to assess the reproducibility of MS-Metabolomics data sets. The methods described in this paper are implemented in the open-source R package marr, which is freely available from Bioconductor at http://bioconductor.org/packages/marr .

Metabolomics in Parkinson's disease

Parkinson's disease (PD) is a multifactorial neurodegenerative disorder in which environmental (lifestyle, dietary, infectious disease) factors as well as genetic make-up play a role. Metabolomics, an evolving research field combining biomarker discovery and pathogenetics, is particularly useful in studying complex pathophysiology in general and Parkinson's disease (PD) specifically. PD, the second most frequent neurodegenerative disorder, is characterized by the loss of dopaminergic neurons in the substantia nigra and the presence of intraneural inclusions of α-synuclein aggregates. Although considered a predominantly movement disorder, PD is also associated with number of non-motor features. Metabolomics has provided useful information regarding this neurodegenerative process with the aim of identifying a disease-specific fingerprint. Unfortunately, many disease variables such as clinical presentation, motor system involvement, disease stage and duration substantially affect biomarker relevance. As such, metabolomics provides a unique approach to studying this multifactorial neurodegenerative disorder.

ABC Transporters in T Cell-Mediated Physiological and Pathological Immune Responses

ATP-binding cassette (ABC) transporters represent a heterogeneous group of ATP-dependent transport proteins, which facilitate the import and/or export of various substrates, including lipids, sugars, amino acids and peptides, ions, and drugs. ABC transporters are involved in a variety of physiological processes in different human tissues. More recent studies have demonstrated that ABC transporters also regulate the development and function of different T cell populations, such as thymocytes, Natural Killer T cells, CD8⁺ T cells, and CD4⁺ T helper cells, including regulatory T cells. Here, we review the current knowledge on ABC transporters in these T cell populations by summarizing how ABC transporters regulate the function of the individual cell types and how this affects the immunity to viruses and tumors, and the course of autoimmune diseases. Furthermore, we provide a perspective on how a better understanding of the function of ABC transporters in T cells might provide promising novel avenues for the therapy of autoimmunity and to improve immunity to infection and cancer.