Obesity Is Associated with Sustained Symptomatology and Unique Inflammatory Features in Children with Asthma

Fitzpatrick, Anne M.; Mutic, Abby; Mohammad, Ahmad F.; Stephenson, Susan; Grunwell, Jocelyn R.

doi:10.1016/j.jaip.2021.10.020

Cited by 20 publications

(13 citation statements)

References 80 publications

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“…Moreover, our study showed that obesity played an important role in assessing risk of school‐age asthma. This evidence about obesity and asthma is consistent with the existing studies 29–31 . Although none of any single variable yet is specifically definitive with certainty in the asthma prediction of preschool children, the associated variables in conjunction may be useful adjuncts, 2,11,13 which has been supported by our study.…”

Section: Discussionsupporting

confidence: 90%

Development and validation of a prediction model to predict school‐age asthma in preschool children

Zhao

Patel

et al. 2023

Pediatric Pulmonology

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Objective To develop and validate a clinical prediction model to identify school‐age asthma in preschool asthmatic children. Study Design In this retrospective prognosis cohort study, asthmatic children aged 3–5 years were enrolled with at least 2 years of follow‐up, and their potential variables at baseline and the prognosis of school‐age asthma were collected from medical records. A clinical prediction model was developed using Logistic regression. The performance of prediction model was assessed and quantified by discrimination of the area under the receiver operating characteristic curve (AUC) and calibration of Brier score. The model was validated by the temporal‐validation method. Results In the development dataset, 2748 preschool asthmatic children were included for model development, and 883 (32.13%) children were translated to school‐age asthma. The independent prognostic variables with an increased risk for school‐age asthma were used to develop the prediction model, including: age, parental asthma, early frequent wheezing, allergic rhinitis, eczema, allergic conjunctivitis, obesity, and aeroallergen of dust mite. While assessing model performance, the discrimination power of AUC was moderate [0.788 (0.770–0.805)] with sensitivity (81.5%) and specificity (60.9%), and the calibration of Brier score was 0.169, supporting the calibration ability. In the temporal‐validation dataset of 583 preschool asthmatic children, our model showed satisfactory discrimination (AUC 0.818) and calibration (Brier score 0.150). The prediction model was presented by the web‐based calculator (https://casthma.shinyapps.io/dynnomapp/) and a nomogram for clinical application. Conclusion In preschool asthmatic children, our prediction model could be used to predict the risk of school‐age asthma.

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Section: Discussionsupporting

confidence: 90%

Development and validation of a prediction model to predict school‐age asthma in preschool children

Zhao

Patel

et al. 2023

Pediatric Pulmonology

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“…Plasma was stored at − 80 °C and analyzed in a single batch on a Luminex MAGPIX system (Millipore) according to the manufacturer’s protocol. A 21-plex human T cell Panel array (HSTCMAG 28SK, T cell Panel, Millipore) was used to quantify fraktaline; granulocyte–macrophage colony-stimulating factor (GMCSF); interferon gamma (IFNG); interleukins (IL) 1b, 2, 4, 5, 6, 7, 8, 10, 12 (p70), 13, 17, 21, 23; interferon–inducible T cell alpha chemoattractant (ITAC); macrophage inflammatory protein (MIP) 1A, 1B, 3A; and tumor necrosis factor alpha (TNFa) as previously published by our group comparing obese to non-obese children with asthma who were not having an exacerbation 18 .…”

Section: Methodsmentioning

confidence: 90%

“…We measured differential gene expression of 579 genes of interest from purified neutrophils using the Human Immunology v2 NanoString nCounter Gene Expression CodeSet (NanoString, Seattle, WA). All NanoString-based measurements were conducted at the Emory University Integrated Genomics Core facility using an amplification step for low abundant RNA applied to all samples as previously described 18 . The raw data are available at Gene Expression Omnibus ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE208220 ).…”

Section: Methodsmentioning

confidence: 99%

Cluster analysis of plasma cytokines identifies two unique endotypes of children with asthma in the pediatric intensive care unit

Cottrill

Rad

Ripple

et al. 2023

Sci Rep

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Children with life-threatening asthma exacerbations who are admitted to a pediatric intensive care unit (PICU) are a heterogeneous group with poorly studied inflammatory features. We hypothesized that distinct clusters of children with asthma in a PICU would be identified based on differences in plasma cytokine levels and that these clusters would have differing underlying inflammation and asthma outcomes within 1 year. Plasma cytokines and differential gene expression were measured in neutrophils isolated from children admitted to a PICU for asthma. Participants were clustered by differential plasma cytokine abundance. Gene expression differences were compared by cluster and pathway over-representation analysis was performed. We identified two clusters in 69 children with no clinical differences. Cluster 1 (n = 41) had higher cytokines compared to Cluster 2 (n = 28). Cluster 2 had a hazard ratio of 2.71 (95% CI 1.11–6.64) compared to Cluster 1 for time to subsequent exacerbation. Gene expression pathways that differed by cluster included interleukin-10 signaling; nucleotide-binding domain, leucine rich repeat containing receptor (NLR signaling); and toll-like receptor (TLR) signaling. These observations suggest that a subset of children may have a unique pattern of inflammation during PICU hospitalization that might require alternative treatment approaches.

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“…Oxidative stress is a central pathogenetic process in obesity-related childhood asthma and is considered to drive other metabolic processes, including dysregulation of fatty acids, peripheral blood ketones, amino acid metabolism, and insulin resistance [ 24 , 25 , 41 , 65 , 75 ].…”

Section: Relevant Sectionsmentioning

confidence: 99%

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

et al. 2023

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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.

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Obesity Is Associated with Sustained Symptomatology and Unique Inflammatory Features in Children with Asthma

Cited by 20 publications

References 80 publications

Development and validation of a prediction model to predict school‐age asthma in preschool children

Development and validation of a prediction model to predict school‐age asthma in preschool children

Cluster analysis of plasma cytokines identifies two unique endotypes of children with asthma in the pediatric intensive care unit

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

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