Viral infections and asthma: an inflammatory interface?

Genomic mosaicism: A neglected factor that promotes variability in asthma diagnosis

To elucidate the genetic architecture of asthma continues to be a challenge for molecular biologists and medical researchers. However, powerful genomic technologies are at disposal to help decipher complete human genomes; the genetic variability in asthma hinders the discovery of common molecular markers for this disease. In this context, we purpose to explore genomic mosaicism on asthma cells' biology as a strategy to discover key mechanisms, which can complement or re-define asthma diagnosis. Recent evidences showed that genomic mosaicism could be a normal event. In brains, each neuron may harbor hundreds of genetic alterations, which may contribute to neuronal diversity. Thus, can mosaicism be a natural motor of diversity in asthma? Why this genetic event is little described in scientific literature? To discuss these questions, we perform a critical review about the normality of genomic mosaicism; moreover, we examine the difficulty of current experimental approaches to detect different genotypes in cell populations of one individual.

Asthma: An Undermined State of Immunodeficiency

Asthma is a heterogeneous chronic respiratory disease characterized by an increased burden of infections. Respiratory tract infections associated with an increased risk for asthma especially when occurring in the first months of life, also represent the most common cause of asthma exacerbations. The association between asthma and the increased frequency of infections and microbiota dysbiosis might be explained by a common mechanism, such as an underlying immune system defect. Apart from the well-established association between primary immunodeficiencies and asthma, several alterations in the immune response following infection have also been observed in asthmatic patients. An impairment in lung epithelial barrier integrity exists and is associated with both an increased susceptibility to infections and the development of asthma. Asthmatic patients are also found to have a deficient interferon (IFN) response upon infection. Additionally, defects in Toll-like receptor (TLR) signaling are observed in asthma and are correlated with both recurrent infections and asthma development. In this review, we summarize the common pathophysiological background of asthma and infections, highlighting the importance of an underlying immune system defect that predispose individuals to recurrent infections and asthma.

A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data

Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-based classifier of mild/moderate asthma. 190 subjects with mild/moderate asthma and controls underwent nasal brushing and RNA sequencing of nasal samples. A machine learning-based pipeline identified an asthma classifier consisting of 90 genes interpreted via an L2-regularized logistic regression classification model. This classifier performed with strong predictive value and sensitivity across eight test sets, including (1) a test set of independent asthmatic and control subjects profiled by RNA sequencing (positive and negative predictive values of 1.00 and 0.96, respectively; AUC of 0.994), (2) two independent case-control cohorts of asthma profiled by microarray, and (3) five cohorts with other respiratory conditions (allergic rhinitis, upper respiratory infection, cystic fibrosis, smoking), where the classifier had a low to zero misclassification rate. Following validation in large, prospective cohorts, this classifier could be developed into a nasal biomarker of asthma.

Effect of enterovirus infections on asthma in young children: A national cohort study

BACKGROUND

We conducted a cohort study to determine the relationship between enterovirus (EV) infection and asthma.

MATERIALS AND METHODS

From the National Health Insurance Research Database of Taiwan, we identified patients who received a new diagnosis of asthma and concurrent treatment between January 2000 and December 2011 (EV cohort: n = 208 213; non-EV cohort: n = 208 213). Cox proportional hazards regression analysis was performed to determine and compare the adjusted hazard ratios (aHRs) of asthma between these 2 cohorts. Kaplan-Meier analysis was conducted to assess the differences in the cumulative incidence curves of asthma between the 2 cohorts.

RESULTS

The overall aHR of asthma was 1.48-fold higher in the EV cohort than in the non-EV cohort (95% confidence interval = 1.45-1.50). The aHR of asthma was higher in the EV cohort than in the non-EV cohort, comprising children aged ≤5 years, regardless of sex, sociodemographic factors (urbanization level and parental occupation) or comorbidities. The risk of asthma was higher in 1-3, 4-6, 7-9 and 10-12 months (all P < .001), particularly in those with a higher frequency of admission (>5 per year).

CONCLUSION

The incidence of asthma was higher in the EV cohort than in the non-EV cohort, comprising children aged ≤5 years, regardless of sex, urbanization level, parental occupation or season. In particular, the risk of asthma was higher in children with a higher frequency of admission, even in the absence of atopy or other respiratory infections.