DNA Methylation in Nasal Epithelium: Strengths and Limitations of an Emergent Biomarker for Childhood Asthma.

Asthma is one of the most widespread chronic respiratory conditions. This disease primarily develops in childhood and is influenced by different factors, mainly genetics and environmental factors. DNA methylation is an epigenetic mechanism which may represent a bridge between these two factors, providing a tool to comprehend the interaction between genetics and environment. Most epidemiological studies in this field have been conducted using blood samples, although DNA methylation marks in blood may not be reliable for drawing exhaustive conclusions about DNA methylation in the airways. Because of the role of nasal epithelium in asthma and the tissue specificity of DNA methylation, studying the relationship between DNA methylation and childhood asthma might reveal crucial information about this widespread respiratory disease. The purpose of this review is to describe current findings in this field of research. We will present a viewpoint of selected studies, consider strengths and limitations, and propose future research in this area

The effect of residential urban greenness on allergic respiratory diseases in youth: A narrative review

Background: Environmental exposures across the life course may be a contributor to the increased worldwide prevalence of respiratory and allergic diseases occurring in the last decades. Asthma and rhinoconjunctivitis especially contribute to the global burden of disease. Greenness has been suggested to have beneficial effects in terms of reduction of occurrence of allergic respiratory diseases. However, the available evidence of a relationship between urban greenness and childhood health outcomes is not yet conclusive. The current review aimed at investigating the current state of evidence, exploring the relationship between children's exposure to residential urban greenness and development of allergic respiratory diseases, jointly considering health outcomes and study design. Methods: The search strategy was designed to identify studies linking urban greenness exposure to asthma, rhinoconjunctivitis, and lung function in children and adolescents. This was a narrative review of literature following PRISMA guidelines performed using electronic search in databases of PubMed and Embase (Ovid) from the date of inception to December 2018. Results: Our search strategy identified 2315 articles; after exclusion of duplicates (n = 701), 1614 articles were screened. Following review of titles and abstracts, 162 articles were identified as potentially eligible. Of these, 148 were excluded following full-text evaluation, and 14 were included in this review. Different methods for assessing greenness exposure were found; the most used was Normalized Difference Vegetation Index. Asthma, wheezing, bronchitis, rhinoconjunctivitis, allergic symptoms, lung function, and allergic sensitization were the outcomes assessed in the identified studies; among them, asthma was the one most frequently investigated. Conclusions: The present review showed inconsistencies in the results mainly due to differences in study design, population, exposure assessment, geographic region, and ascertainment of outcome. Overall, there is a suggestion of an association between urban greenness in early life and the occurrence of allergic respiratory diseases during childhood, although the evidence is still inconsistent. It is therefore hard to draw a conclusive interpretation, so that the understanding of the impact of greenness on allergic respiratory diseases in children and adolescents remains difficult

A Methodological Framework to Discover Pharmacogenomic Interactions Based on Random Forests

The identification of genomic alterations in tumor tissues, including somatic mutations, deletions, and gene amplifications, produces large amounts of data, which can be correlated with a diversity of therapeutic responses. We aimed to provide a methodological framework to discover pharmacogenomic interactions based on Random Forests. We matched two databases from the Cancer Cell Line Encyclopaedia (CCLE) project, and the Genomics of Drug Sensitivity in Cancer (GDSC) project. For a total of 648 shared cell lines, we considered 48,270 gene alterations from CCLE as input features and the area under the dose-response curve (AUC) for 265 drugs from GDSC as the outcomes. A three-step reduction to 501 alterations was performed, selecting known driver genes and excluding very frequent/infrequent alterations and redundant ones. For each model, we used the concordance correlation coefficient (CCC) for assessing the predictive performance, and permutation importance for assessing the contribution of each alteration. In a reasonable computational time (56 min), we identified 12 compounds whose response was at least fairly sensitive (CCC > 20) to the alteration profiles. Some diversities were found in the sets of influential alterations, providing clues to discover significant drug-gene interactions. The proposed methodological framework can be helpful for mining pharmacogenomic interactions

A cross-sectional study assessing the relationship between BMI, asthma, atopy, and eNO among schoolchildren

Increased body weight may influence airway inflammatory mechanisms

Determinants of Allergic Sensitization, Asthma and Lung Function: Results from a Cross-Sectional Study in Italian Schoolchildren

Prenatal smoking exposure and early-life respiratory infections are major determinants of asthma during childhood. We investigate the factors influencing allergic sensitization (AS), asthma, and lung function in children and the balance between individual and environmental characteristics at different life stages. 1714 children aged 7-16 years and living in southern Italy were investigated using a parental questionnaire, skin prick tests, and spirometry. We found 41.0% AS prevalence: among children without parental history of asthma, male sex, maternal smoking during pregnancy (MatSmoke), and acute respiratory diseases in the first two years of life (ARD2Y) were significant risk factors for AS. MatSmoke was associated (OR = 1.79) with ARD2Y, and this association was influenced by sex. ARD2Y was, in turn, a significant risk factor (OR = 8.53) for childhood current asthma, along with AS (OR up to 3.03) and rhinoconjuctivitis (OR = 3.59). Forced mid-expiratory flow (FEF25-75%) was negatively affected by ARD2Y, with a sex-related effect. Thus, males exposed to MatSmoke had significantly lower FEF25-75% than unexposed males. Despite the difficulty of discriminating among the complex interactions underlying the development of allergic respiratory diseases, ARD2Y appears to strongly influence both asthma and lung function during childhood. In turn, ARD2Y is influenced by prenatal exposure to tobacco smoke with a sex-dependent effect

THE VALUE OF FENO MEASUREMENT IN CHILDHOOD ASTHMA: UNCERTAINTIES AND PERSPECTIVES.

Asthma is considered an heterogeneous disease, requiring multiple biomarkers for diagnosis and management. Fractional exhaled nitric oxide in exhaled breath (FeNO) was the first useful non-invasive marker of airway inflammation in asthma and still is the most widely used. The non-invasive nature and the relatively easy use of FeNO technique make it an interesting tool to monitor airway inflammation and rationalize corticosteroid therapy in asthmatic patients, together with the traditional clinical tools (history, physical examination and lung function tests), even if some controversies have been published regarding the use of FeNO to support the management of asthma in children. The problem of multiple confounding factors and overlap between healthy and asthmatic populations preclude the routine application of FeNO reference values in clinical practice and suggest that it would be better to consider an individual "best", taking into account the context in which the measurement is obtained and the clinical history of the patient. Besides, there is still disagreement about the role of FeNO as a marker of asthma control, due to the complexity of balance among the different items involved in its determination and the ack of homogeneity in the population groups studied in the few studies conducted so far. Heterogeneity of problematic severe asthma greatly limits utility of FeNO alone as a biomarker of inflammation to optimize the disease management on an individual basis. None of the studies conducted so far demonstrated that the use of FeNO was better than current asthma guidelines in controlling asthma exacerbations. In summary, there is a large variation in FeNO levels between individuals, which may reflect the natural heterogeneity in baseline epithelial nitric oxide synthase activity and/or the contribution of other noneosinophilic factors to epithelial nitric oxide synthase activity. FeNO is a promising biomarker, but at present some limits are highlighted. We would recommend that further research can be carried out by organizing studies aimed to obtain reliable reference values of FeNO and in order to better interpret FeNO measurements in clinical settings, taking also into account the influence of genetic and environmental factor

CT Radiomic Features and Clinical Biomarkers for Predicting Coronary Artery Disease

This study was aimed to investigate the predictive value of the radiomics features extracted from pericoronaric adipose tissue & mdash; around the anterior interventricular artery (IVA) & mdash; to assess the condition of coronary arteries compared with the use of clinical characteristics alone (i.e., risk factors). Clinical and radiomic data of 118 patients were retrospectively analyzed. In total, 93 radiomics features were extracted for each ROI around the IVA, and 13 clinical features were used to build different machine learning models finalized to predict the impairment (or otherwise) of coronary arteries. Pericoronaric radiomic features improved prediction above the use of risk factors alone. In fact, with the best model (Random Forest + Mutual Information) the AUROC reached 0.820 +/- 0.076 . As a matter of fact, the combined use of both types of features (i.e., radiomic and clinical) allows for improved performance regardless of the feature selection method used. Experimental findings demonstrated that the use of radiomic features alone achieves better performance than the use of clinical features alone, while the combined use of both clinical and radiomic biomarkers further improves the predictive ability of the models. The main contribution of this work concerns: (i) the implementation of multimodal predictive models, based on both clinical and radiomic features, and (ii) a trusted system to support clinical decision-making processes by means of explainable classifiers and interpretable features

Impact of sublingual immunotherapy on seasonal asthma and skin reactivity in children allergic to Parietaria pollen treated with inhaled fluticasone propionate

Immunotherapy is a recognized treatment for allergic respiratory diseases