Characteristics and Mechanisms of a Sphingolipid-associated Childhood Asthma Endotype

Rago, Daniela; Pedersen, Casper-Emil Tingskov; Huang, Mengna; Kelly, Rachel S.; Gürdeniz, Gözde; Brustad, Nicklas; Knihtilä, Hanna; Lee-Sarwar, Kathleen; Morin, Andréanne; Rasmussen, Morten Arendt; Stokholm, Jakob; Bønnelykke, Klaus; Litonjua, Augusto A.; Wheelock, Craig E.; Weiss, Scott T.; Lasky‐Su, Jessica; Bisgaard, Hans; Chawes, Bo

doi:10.1164/rccm.202008-3206oc

Cited by 42 publications

(44 citation statements)

References 45 publications

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“…Metabolomic studies can be either untargeted metabolic profiling or targeted studies of a single class of metabolites, both of which have been applied to the study of metabolites in asthma patients. Untargeted metabolomic profiling has been performed using MS on plasma, urine, stool, and exhaled breath samples from children with asthma [118][119][120][121][122]. In a study using untargeted LC-MS analysis of plasma metabolomes, children with severe asthma were distinguished by metabolic pathways associated with oxidative stress [121], in agreement with observations of increased oxidative stress in asthma exacerbations [123].…”

Section: Metabolomics Of Asthmasupporting

confidence: 52%

Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Gautam

Johansson

Mersha

2022

JPM

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Asthma is a complex multifactorial and heterogeneous respiratory disease. Although genetics is a strong risk factor of asthma, external and internal exposures and their interactions with genetic factors also play important roles in the pathophysiology of asthma. Over the past decades, the application of high-throughput omics approaches has emerged and been applied to the field of asthma research for screening biomarkers such as genes, transcript, proteins, and metabolites in an unbiased fashion. Leveraging large-scale studies representative of diverse population-based omics data and integrating with clinical data has led to better profiling of asthma risk. Yet, to date, no omic-driven endotypes have been translated into clinical practice and management of asthma. In this article, we provide an overview of the current status of omics studies of asthma, namely, genomics, transcriptomics, epigenomics, proteomics, exposomics, and metabolomics. The current development of the multi-omics integrations of asthma is also briefly discussed. Biomarker discovery following multi-omics profiling could be challenging but useful for better disease phenotyping and endotyping that can translate into advances in asthma management and clinical care, ultimately leading to successful precision medicine approaches.

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Section: Metabolomics Of Asthmasupporting

confidence: 52%

Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Gautam

Johansson

Mersha

2022

JPM

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“…Thus, sphingolipid-related changes may be associated with inflammatory changes induced by aeroallergen-induced bronchial hyperreactivity. Furthermore, an exploratory study in children, using untargeted metabolomics by LC–MS, showed that lower concentrations of ceramides (d:16:1/24:1 and d19:1/18:0) and sphingomyelins (and reduced concentrations of serine palmitoyl-CoA transferase, the rate-limiting enzyme in de novo sphingolipid synthesis) at the age of 6 months were associated with an increased risk of developing asthma before 3 years of age [ 110 ]. This study may be relevant because such low levels of these sphingolipids are associated with increased airway resistance, and the authors suggest that this may indicate a childhood asthma endotype with early onset and increased airway resistance, linked to reduced sphingolipid concentrations.…”

Section: Assessment Of Metabolic Changes In Inflammatory Asthma Phenotypesmentioning

confidence: 99%

Metabolic Phenotypes in Asthmatic Adults: Relationship with Inflammatory and Clinical Phenotypes and Prognostic Implications

et al. 2021

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Bronchial asthma is a chronic disease that affects individuals of all ages. It has a high prevalence and is associated with high morbidity and considerable levels of mortality. However, asthma is not a single disease, and multiple subtypes or phenotypes (clinical, inflammatory or combinations thereof) can be detected, namely in aggregated clusters. Most studies have characterised asthma phenotypes and clusters of phenotypes using mainly clinical and inflammatory parameters. These studies are important because they may have clinical and prognostic implications and may also help to tailor personalised treatment approaches. In addition, various metabolomics studies have helped to further define the metabolic features of asthma, using electronic noses or targeted and untargeted approaches. Besides discriminating between asthma and a healthy state, metabolomics can detect the metabolic signatures associated with some asthma subtypes, namely eosinophilic and non-eosinophilic phenotypes or the obese asthma phenotype, and this may prove very useful in point-of-care application. Furthermore, metabolomics also discriminates between asthma and other “phenotypes” of chronic obstructive airway diseases, such as chronic obstructive pulmonary disease (COPD) or Asthma–COPD Overlap (ACO). However, there are still various aspects that need to be more thoroughly investigated in the context of asthma phenotypes in adequately designed, homogeneous, multicentre studies, using adequate tools and integrating metabolomics into a multiple-level approach.

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“…As an example, a recent study in childhood asthma using metabolomics suggests the existence of an endotype with early onset and increased airway resistance that is characterized by reduced sphingolipid concentrations, which are associated with 17q21 genetic variants and expression of the serine palmitoyl-CoA transferase (SPT) enzyme [12].…”

Section: Metabolomicsmentioning

confidence: 99%