Obesity-Associated Non-T2 Mechanisms in Obese Asthmatic Individuals

Shailesh, Harshita; Bhat, Ajaz A.; Janahi, Ibrahim A.

doi:10.3390/biomedicines11102797

Cited by 8 publications

(6 citation statements)

References 90 publications

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“…As stated before, metabolic syndrome and insulin resistance are associated with increased risk of developing asthma and asthma severity. Hyperinsulinemia may promote airway smooth muscle airway hyperreactivity [71,72]. Medications targeting the metabolic syndrome and hyperglycemia may improve asthma morbidity.…”

Section: Targeting Metabolic and Glycemic Dysfunctionmentioning

confidence: 99%

Obesity-related asthma: new insights leading to a different approach

Witte,

Türk,

Braunstahl

2024

Current Opinion in Pulmonary Medicine

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Purpose of review Obesity is a growing global health threat that significantly contributes to the burden of asthma by increasing the risk of developing asthma and exerting a distinct effect on lung function and inflammation. The treatment of obesity-related asthma is hindered by a poor response to standard asthma treatments, leading to worse asthma control. Weight loss strategies have a significant effect on asthma symptoms but are not feasible for a large proportion of patients, underscoring the need for a better understanding of the pathophysiology and the development of additional treatment options. Recent findings Recent literature focusing on pathophysiology particularly delved into nontype 2 inflammatory mechanisms, associations with the metabolic syndrome and small airway impairment. Additionally, several new treatment options are currently investigated, including biologics, weight reduction interventions, and novel antiobesity drugs. Summary Obesity-related asthma is a highly prevalent asthma phenotype for which weight loss strategies currently stand as the most specific treatment. Furthermore, novel pharmacological interventions aiming at metabolic processes are on the way.

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Section: Targeting Metabolic and Glycemic Dysfunctionmentioning

confidence: 99%

Obesity-related asthma: new insights leading to a different approach

Witte,

Türk,

Braunstahl

2024

Current Opinion in Pulmonary Medicine

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“…Body mass index (BMI, kg/m 2 ) is calculated as weight divided by height squared, while fat mass index (FMI, kg/m 2 ) is calculated as fat mass divided by height squared. The Fat-free mass index (FFMI, kg/m 2 ) is calculated by dividing the sum of total lean mass and bone mineral content by the square of height [9,14,15].…”

Section: Assessmentmentioning

confidence: 99%

Variation of all-cause mortality with Fat-free Mass Index（FFMI）and Fat Mass Index（FMI）in individuals with Asthma: results from the NHANES database prospective cohort study

Chen,

Cheng,

Yao

et al. 2024

Preprint

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Background The relationship between FFMI, FMI, and mortality in patients with asthma remains unknown. This study aimed to examine the associations between FFMI and FMI and all-cause mortality in a cohort of American adults diagnosed with asthma. Methods This study included 15200 adults from NHANES. To assess mortality, we linked participant records to the National Death Index. Survival differences across quintiles of FFMI and FMI were explored using Kaplan-Meier plots and log-rank tests. The study investigated the nonlinear relationships between FFMI, FMI, and mortality. Additionally, stratified analyses were undertaken to pinpoint subgroups of individuals who exhibited an elevated risk of mortality. Results After a median follow-up, 13360 were presumed alive and 1840 had deceased. Kaplan-Meier plots revealed significant differences in all-cause mortality in patients with asthma among the FFMI quintiles and FMI quintiles. Specifically, individuals in the lowest FFMI quintile (Q1, 10.4-16.0) exhibited a markedly increased risk of all-cause mortality (HR: 4.63; 95% CI: 1.59,13.5; p< 0.01). Similarly, increased all-cause mortality risks were observed in the upper three quintiles of FMI-Q3 (4.8-6.1) with HR: 2.9 (1.20,7.00, p<0.05), Q4 (6.2-8.3) with HR: 3.37 (1.41,8.03, p<0.01), and Q5 (8.4-22.8) with HR: 4.6 (1.31,16.2, p<0.05). Moreover, the risk of all-cause mortality increased with increasing FMI and decreasing FFMI (p for non-linearity<0.001 in both cases) respectively. Subgroup analyses further elucidated these associations across different categories. Conclusions All-cause mortality is decreased in patients with asthma when FMI is less than 5.4 kg/m2, and increased when FFMI is less than 18.6 kg/m2.

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“…One review reported a 20% increase and a twofold increase in asthma's prevalence in overweight and obese children, respectively [4], while another review reported a 20% and a 40% risk increment in overweight and obese children, respectively [5]. Obesity-related factors such as altered lung mechanics, hyperinsulinemia, increased inflammation, metabolic dysregulation, and microbiome dysbiosis are implicated in the pathogenesis of asthma [9,10].…”

Section: Introductionmentioning

confidence: 99%

Sphingolipids in Childhood Asthma and Obesity (SOAP Study): A Protocol of a Cross-Sectional Study

Antonisamy,

Shailesh,

Hani

et al. 2023

Metabolites

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Asthma and obesity are two of the most common chronic conditions in children and adolescents. There is increasing evidence that sphingolipid metabolism is altered in childhood asthma and is linked to airway hyperreactivity. Dysregulated sphingolipid metabolism is also reported in obesity. However, the functional link between sphingolipid metabolism, asthma, and obesity is not completely understood. This paper describes the protocol of an ongoing study on sphingolipids that aims to examine the pathophysiology of sphingolipids in childhood asthma and obesity. In addition, this study aims to explore the novel biomarkers through a comprehensive multi-omics approach including genomics, genome-wide DNA methylation, RNA-Seq, microRNA (miRNA) profiling, lipidomics, metabolomics, and cytokine profiling. This is a cross-sectional study aiming to recruit 440 children from different groups: children with asthma and normal weight (n = 100), asthma with overweight or obesity (n = 100), overweight or obesity (n = 100), normal weight (n = 70), and siblings of asthmatic children with normal weight, overweight, or obesity (n = 70). These participants will be recruited from the pediatric pulmonology, pediatric endocrinology, and general pediatric outpatient clinics at Sidra Medicine, Doha, Qatar. Information will be obtained from self-reported questionnaires on asthma, quality of life, food frequency (FFQ), and a 3-day food diary that are completed by the children and their parents. Clinical measurements will include anthropometry, blood pressure, biochemistry, bioelectrical impedance, and pulmonary function tests. Blood samples will be obtained for sphingolipid analysis, serine palmitoyltransferase (SPT) assay, whole-genome sequencing (WGS), genome-wide DNA methylation study, RNA-Seq, miRNA profiling, metabolomics, lipidomics, and cytokine analysis. Group comparisons of continuous outcome variables will be carried out by a one-way analysis of variance or the Kruskal–Wallis test using an appropriate pairwise multiple comparison test. The chi-squared test or a Fisher’s exact test will be used to test the associations between categorical variables. Finally, multivariate analysis will be carried out to integrate the clinical data with multi-omics data. This study will help us to understand the role of dysregulated sphingolipid metabolism in obesity and asthma. In addition, the multi-omics data from the study will help to identify novel genetic and epigenetic signatures, inflammatory markers, and mechanistic pathways that link asthma and obesity in children. Furthermore, the integration of clinical and multi-omics data will help us to uncover the potential interactions between these diseases and to offer a new paradigm for the treatment of pediatric obesity-associated asthma.

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Obesity-Associated Non-T2 Mechanisms in Obese Asthmatic Individuals

Cited by 8 publications

References 90 publications

Obesity-related asthma: new insights leading to a different approach

Obesity-related asthma: new insights leading to a different approach

Variation of all-cause mortality with Fat-free Mass Index（FFMI）and Fat Mass Index（FMI）in individuals with Asthma: results from the NHANES database prospective cohort study

Sphingolipids in Childhood Asthma and Obesity (SOAP Study): A Protocol of a Cross-Sectional Study

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