Serum periostin is not related to asthma predictive index

Early Prediction of Asthma

The clinical manifestations of asthma in children are highly variable, are associated with different molecular and cellular mechanisms, and are characterized by common symptoms that may diversify in frequency and intensity throughout life. It is a disease that generally begins in the first five years of life, and it is essential to promptly identify patients at high risk of developing asthma by using different prediction models. The aim of this review regarding the early prediction of asthma is to summarize predictive factors for the course of asthma, including lung function, allergic comorbidity, and relevant data from the patient's medical history, among other factors. This review also highlights the epigenetic factors that are involved, such as DNA methylation and asthma risk, microRNA expression, and histone modification. The different tools that have been developed in recent years for use in asthma prediction, including machine learning approaches, are presented and compared. In this review, emphasis is placed on molecular mechanisms and biomarkers that can be used as predictors of asthma in children.

Integrative Analysis Reveals a miRNA-mRNA Regulatory Network and Potential Causative Agents in the Asthmatic Airway Epithelium

Background

During asthma progression, the intricate molecular networks, including microRNA (miRNA) transcriptional regulation in airway epithelium, remain largely undefined. The abnormal expression of miRNAs in asthmatic airway epithelium is a recent and fast-growing area in developing diagnostic and therapeutic targets for asthma.

Material and Methods

Analyses were conducted to compare airway epithelial miRNAs and gene expression between patients with asthma and healthy subjects from three datasets (two for miRNAs expression profiles and one for gene expression profile). The interactions network between differentially expressed (DE)-miRNAs and mRNAs was further identified for functional analysis. To verify the involvement and functions of all the identified miRNAs in asthma, we constructed two cellular models of asthma. The most promising causal miRNA candidate, miR-1246, was examined in an in vitro system to explore its targets and roles in asthma pathophysiology.

Results

Through integrative analysis, we obtained six miRNAs with 31 validated target genes in airway epithelium associated with asthma. Next, we confirmed that these miRNAs were all associated with asthma progression by in vitro functional experiments. They may participate in eosinophilic inflammation (miR-92b-3p, miR-1246, miR-197-3p, and miR-124-5p) or remodeling (miR-197-3p, miR-193a-5p, miR-1246, and miR-92b-3p). Additionally, some other non-screened valuable miRNAs were also examined and identified (miR-21-5p and miR-19b-3p), and some detected in blood correlated with the disease status. Furthermore, we found that miR-1246 could directly target POSTN and influence epithelial-to-mesenchymal transition and fibrosis in airway epithelial cells.

Conclusion

We constructed a preliminary epithelial regulatory network in asthma based on six identified miRNAs and their valuable target genes. Candidate factors in the biological miRNA-mRNA network in airway epithelium may provide further information on the pathogenesis of asthma. Strikingly, among all screened miRNAs, miR-1246, which could interact with POSTN may have multifunctional effects in the course of asthma and be a promising agent for asthma treatment and molecular subtyping.

Association of serum periostin levels with clinical features in children with asthma

BACKGROUND

The aim of this study was to investigate the association of serum periostin levels with clinical features in children with asthma.

METHODS

Children with physician-diagnosed asthma who attended regularly to an outpatient pediatric allergy and asthma center were enrolled in the study along with control subjects. Asthma severity and control status of the patients were evaluated according to the recent GINA guidelines.

RESULTS

A total of 158 children (125 with asthma and 33 age- and sex-matched control subjects) with a median age of 10.2 years (range 5.9-17.0) were enrolled. Asthma severity was mild in 41 (32.8%), moderate in 63 (50.4%), and severe in 21 (16.8%) children. Children with asthma had significantly higher periostin levels than controls (53.1 ± 13.1 vs 43.0 ± 11.2 ng/mL, P < .001). The mean serum periostin levels in children with severe asthma (63.8 ± 10.8) were significantly higher than in children with moderate asthma (53.3 ± 12.7) and mild asthma (47.4 ± 11.1) (P < .001). Results of multivariable logistic regression analysis demonstrated an association between serum periostin levels and asthma severity in children (OR, 1.10; 95% CI, 1.04-1.15, P < .001). When analyzed for the best cut-off value with the highest combined sensitivity and specificity, a cut-off value of 52 ng/mL for serum periostin level was obtained with sensitivity, specificity, PPV, and NPV of 100%, 50%, 29%, and 100%, respectively.

CONCLUSION

Although serum periostin levels are higher in children with asthma, its diagnostic role in identifying children with severe asthma is limited.

Asthma predictive index as a useful diagnostic tool in preschool children: a cross-sectional study in Korea

BACKGROUND

It is challenging to diagnose asthma in preschool children. The asthma predictive index (API) has been used to predict asthma and decide whether to initiate treatment in preschool children.

PURPOSE

This study aimed to investigate the association between questionnaire-based current asthma with API, pulmonary function, airway hyperreactivity (AHR), fractional expiratory nitric oxide (FeNO), and atopic sensitization in preschool children.

METHODS

We performed a population-based cross-sectional study in 916 preschool children aged 4-6 years. We defined current asthma as the presence of both physician-diagnosed asthma and at least one wheezing episode within the previous 12 months using a modified International Study of Asthma and Allergies in Childhood questionnaire. Clinical and laboratory parameters were compared between groups according to the presence of current asthma.

RESULTS

The prevalence of current asthma was 3.9% in the study population. Children with current asthma showed a higher rate of positive bronchodilator response and loose and stringent API scores than children without current asthma. The stringent API was associated with current asthma with 72.2% sensitivity and 82.0% specificity. The diagnostic accuracy of the stringent API for current asthma was 0.771. However, no intergroup differences in spirometry results, methacholine provocation test results, FeNO level, or atopic sensitization rate were observed.

CONCLUSION

The questionnaire-based diagnosis of current asthma is associated with API, but not with spirometry, AHR, FeNO, or atopic sensitization in preschool children.

Periostin concentration in exhaled breath condensate in children with mild asthma

OBJECTIVE

Periostin is considered to be a marker of eosinophilic inflammation in patients with asthma. However, there are no literature data on exhaled breath condensate (EBC) periostin level in pediatric patients with asthma. The aim of this study was to analyze EBC periostin concentration in children with mild asthma and to evaluate the potential usefulness of EBC periostin level as a biomarker for the disease.

METHODS

EBC and serum periostin concentrations were measured by enzyme-linked immunosorbent assay in 23 children with asthma and 23 healthy controls.

RESULTS

EBC periostin concentration was 250- to 780-fold lower than that found in serum. No significant differences between serum nor EBC periostin concentration in asthmatics and the control group were showed. The comparison between children with Th2 and non-Th2 type of asthma did not show significant differences in periostin concentration, both in serum and EBC. Serum periostin concentration inversely correlated with BMI and age not only in asthma patients but also in controls.

CONCLUSIONS

In children with mild asthma, periostin may be measured not only in serum but also in EBC. The low periostin level in patients with mild asthma and lack of difference between asthmatic subjects and controls indicate that EBC periostin may not be useful as an asthma biomarker in this group.

Predicting Asthma Using Clinical Indexes

Asthma is no longer considered a single disease, but a common label for a set of heterogeneous conditions with shared clinical symptoms but associated with different cellular and molecular mechanisms. Several wheezing phenotypes coexist at preschool age but not all preschoolers with recurrent wheezing develop asthma at school-age; and since at the present no accurate single screening test using genetic or biochemical markers has been developed to determine which preschooler with recurrent wheezing will have asthma at school age, the asthma diagnosis still needs to be based on clinical predicted models or scores. The purpose of this review is to summarize the existing and most frequently used asthma predicting models, to discuss their advantages/disadvantages, and their accomplishment on all the necessary consecutive steps for any predictive model. Seven most popular asthma predictive models were reviewed (original API, Isle of Wight, PIAMA, modified API, ucAPI, APT Leicestersher, and ademAPI). Among these, the original API has a good positive LR~7.4 (increases the probability of a prediction of asthma by 2-7 times), and it is also simple: it only requires four clinical parameters and a peripheral blood sample for eosinophil count. It is thus an easy model to use in any rural or urban health care system. However, because its negative LR is not good, it cannot be used to rule out the development of asthma.