Asthma phenotypes in childhood: conceptual thoughts on stability and transition

Spycher, Ben D.; Kuehni, Claudia E.

doi:10.1183/13993003.02011-2015

Cited by 16 publications

(11 citation statements)

References 14 publications

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“…Asthma in children has 2 phenotypes: 1-Transient non atopic type which start in preschool age, provoked by viral URTI, resolve by school age, inflammation not evident in this type. 2-Persistent atopy associated type which start in early preschool age ,associated with atopic manifestation ,elevated IgE, provoked by allergen sensitization may, persist into late childhood .Inflammatory reaction is evident in this type (25). Most of our patients are of non-atopic transient phenotype of asthma where chronic inflammation is not present.…”

Section: Wagdy a Elsayed And Eman Essamentioning

confidence: 83%

Iron Deficiency Anemia , Serum Iron in Children With Bronchial Asthma

ELSAYED¹,

Essa²

2017

Zagazig University Medical Journal

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Background: Asthma is a chronic inflammatory condition of the lung airways resulting in episodic airflow obstruction. iron deficiency anemia is very common public health problem in developing countries with incidence ranges from 35-90 % in developing countries and may be a risk factor for asthma in children. Objective: We investigated iron deficiency anemia, serum iron, total iron binding capacity, serum ferritin in children with bronchial asthma to study possible association of both conditions and possible role of iron deficiency anemia and iron deficiency in development of bronchial asthma and its exacerbation. Design: Case-control study. Methods: complete blood count with peripheral smear was done; C-reactive protein was determined by enzyme-linked immune-sorbent assay "high sensitive C-reactive protein". erythrocyte sedimentation rate done by Win Trobe method. Serum iron, total iron binding capacity was measured by spectrophotometer. Serum ferritin was measured by enzyme linked immune assay. Statistical analysis: Results of 40 asthmatic cases were analyzed and compared with 16 healthy controls using SPSS 20. Results: iron deficiency anemia was significantly more frequent in asthma cases compared to healthy controls. Serum iron and serum ferritin were significantly lower in asthmatic cases compared to controls .Non anemic asthmatics showed significant lower hemoglobin , serum ferritin compared with non-anemic healthy controls. Moderate cases of asthma showed significant lower hemoglobin , red cell counts , serum ferritin compared with mild cases , They did not show significant difference with severe cases in these parameters .All three groups" mild , moderate and severe" showed significant differences in these parameters. Conclusion: We conclude that iron deficiency anemia is more prevalent in asthmatic children compared to healthy controls. Asthmatic children have risk of iron deficiency even when they are not anemic. red cell counts and iron deficiency increases with severity of asthmatic attacks.

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Section: Wagdy a Elsayed And Eman Essamentioning

confidence: 83%

Iron Deficiency Anemia , Serum Iron in Children With Bronchial Asthma

ELSAYED¹,

Essa²

2017

Zagazig University Medical Journal

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“…Patients with neutrophilic and mixed asthma respond poorly to corticosteroid therapy, and increased numbers of neutrophils with persistent eosinophilia are seen in severe asthma and sudden‐onset fatal asthma . In both types of complex phenotypes, other factors such as genetics, epithelial barrier dysfunction, innate immune response, environmental exposures, viral infections, and comorbidities may further modulate inflammation, bringing the stability of dominant physiopathological mechanisms to question . Therefore, better understanding of the characteristics of each inflammatory subgroup is crucial for extensive development of personalized/precision medicine .…”

Section: Introductionmentioning

confidence: 99%

Tight junction, mucin, and inflammasome‐related molecules are differentially expressed in eosinophilic, mixed, and neutrophilic experimental asthma in mice

Tan

Hagner

Ruchti

et al. 2018

Allergy

128

131

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Background: Asthma is a chronic respiratory disease with marked clinical and pathophysiological heterogeneity. Specific pathways are thought to be involved in the pathomechanisms of different inflammatory phenotypes of asthma; however, direct in vivo comparison has not been performed. Methods:We developed mouse models representing three different phenotypes of allergic airway inflammation-eosinophilic, mixed, and neutrophilic asthma via different methods of house dust mite sensitization and challenge. Transcriptomic analysis of the lungs, followed by the RT-PCR, western blot, and confocal microscopy, was performed. Primary human bronchial epithelial cells cultured in air-liquid interface were used to study the mechanisms revealed in the in vivo models.Results: By whole-genome transcriptome profiling of the lung, we found that airway tight junction (TJ), mucin, and inflammasome-related genes are differentially expressed in these distinct phenotypes. Further analysis of proteins from these families revealed that Zo-1 and Cldn18 were downregulated in all phenotypes, while increased Cldn4 expression was characteristic for neutrophilic airway inflammation.Mucins Clca1 (Gob5) and Muc5ac were upregulated in eosinophilic and even more in neutrophilic phenotype. Increased expression of inflammasome-related molecules such as Nlrp3, Nlrc4, Casp-1, and IL-1β was characteristic for neutrophilic asthma. In addition, we showed that inflammasome/Th17/neutrophilic axis cytokine-IL-1βmay transiently impair epithelial barrier function, while IL-1β and IL-17 increase mucin expressions in primary human bronchial epithelial cells.Conclusion: Our findings suggest that differential expression of TJ, mucin, and inflammasome-related molecules in distinct inflammatory phenotypes of asthma may be linked to pathophysiology and might reflect the differences observed in the clinic. K E Y W O R D Sendotype, epithelial barrier, house dust mite, phenotype, precision medicine Tan and Hagner equal first-author contribution.

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“…We and others have shown that different phenotypes of childhood wheezing have different environmental associations. 2 , 8 , 32 , 33 , 34 , 35 , 36 , 37 , 38 Similarly, different subtypes of atopic sensitization differ in their environmental risk factors; for example, endotoxin exposure is protective for multiple early but not multiple late sensitizations. 39 It is likely that the effect of most environmental factors varies across subjects with different genetic predispositions, but the precise nature of most gene-environment interactions remains unclear.…”

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confidence: 99%

Disaggregating asthma: Big investigation versus big data

Belgrave

Henderson

Simpson

et al. 2017

Journal of Allergy and Clinical Immunology

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We are facing a major challenge in bridging the gap between identifying subtypes of asthma to understand causal mechanisms and translating this knowledge into personalized prevention and management strategies. In recent years, “big data” has been sold as a panacea for generating hypotheses and driving new frontiers of health care; the idea that the data must and will speak for themselves is fast becoming a new dogma. One of the dangers of ready accessibility of health care data and computational tools for data analysis is that the process of data mining can become uncoupled from the scientific process of clinical interpretation, understanding the provenance of the data, and external validation. Although advances in computational methods can be valuable for using unexpected structure in data to generate hypotheses, there remains a need for testing hypotheses and interpreting results with scientific rigor. We argue for combining data- and hypothesis-driven methods in a careful synergy, and the importance of carefully characterized birth and patient cohorts with genetic, phenotypic, biological, and molecular data in this process cannot be overemphasized. The main challenge on the road ahead is to harness bigger health care data in ways that produce meaningful clinical interpretation and to translate this into better diagnoses and properly personalized prevention and treatment plans. There is a pressing need for cross-disciplinary research with an integrative approach to data science, whereby basic scientists, clinicians, data analysts, and epidemiologists work together to understand the heterogeneity of asthma.

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Asthma phenotypes in childhood: conceptual thoughts on stability and transition

Cited by 16 publications

References 14 publications

Iron Deficiency Anemia , Serum Iron in Children With Bronchial Asthma

Iron Deficiency Anemia , Serum Iron in Children With Bronchial Asthma

Tight junction, mucin, and inflammasome‐related molecules are differentially expressed in eosinophilic, mixed, and neutrophilic experimental asthma in mice

Disaggregating asthma: Big investigation versus big data

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