Background
There is an association between persistent preschool wheezing phenotypes and school‐age asthma. These wheezing/asthma phenotypes likely represent clinical entities having specific genetic ...risk factors. The SERPINA1 gene encodes α
1‐antitrypsin (AAT), and mutations in the gene are important in the pathophysiology of pulmonary diseases. We hypothesized that there might be an association between SERPINA1 gene polymorphisms and the risk of developing wheezing/school age asthma.
Objective
To examine 10 single nucleotide polymorphisms (SNPs) of SERPINA1 (rs6647, rs11832, rs17580, rs709932, rs1243160, rs2854254, rs8004738, rs17751769, rs28929470, and rs28929474) and relate them to childhood wheezing phenotypes and doctor‐diagnosed asthma in the population‐based Avon Longitudinal Study of Parents and Children (ALSPAC) cohort.
Methods
Wheeze data, reports of physician‐diagnosed asthma and data on the SERPINA1 gene SNPs, were available for 7964 children. Binary logistic regression was used to assess the associations between allele prevalence and wheezing and asthma phenotypes. P values were adjusted to account for multiple hypotheses using the Benjamini‐Hochberg false discovery rate.
Results
Only within a subgroup of children with asthma who had no prior diagnosis of preschool wheeze was there a trend for association between rs28929474 (Glu342Lys, Pi*Z causing AAT deficiency; P = .0058, adjusted P = .058). No SNP was associated with wheezing and asthma in those with preschool wheeze.
Conclusion
Analyzed SNPs in SERPINA1 are not associated with wheezing/asthma phenotypes. Only rs28929474, the most common pathologic SNP (Pi*Z) in the SERPINA1 gene, might be associated with a risk of developing school‐age asthma without exhibiting preschool wheeze.
Tobacco has long been known to be one of the greatest causes of morbidity and mortality in the adults, but the effects on the foetus and young children, which are lifelong, have been less well ...appreciated. Developing from this are electronic nicotine delivery systems or vapes, promulgated as being less harmful than tobacco. Nicotine itself is toxic to the foetus, with permanent effects on lung structure and function. Most vapes contain nicotine, but they also contain many other compounds which are inhaled and for which there are no toxicity studies. They also contain known toxic substances, whose use is banned by European Union legislation. Accelerating numbers of young people are vaping, and this does not reflect an exchange of vapes for cigarettes. The acute toxicity of e-cigarettes is greater than that of tobacco, and includes acute lung injury, pulmonary haemorrhage and eosinophilic and lipoid pneumonia. Given the worse acute toxicity, it should be impossible to be complacent about medium and long term effects of vaping. Laboratory studies have demonstrated changes in lung proteomics and the innate immune system with vaping, some but not all of which overlap with tobacco. It would be wrong to consider vapes as a weaker form of tobacco, they have their own toxicity. Children and young people are being targeted by the vaping industry (which is largely the same as the tobacco industry), including on-line, and unless an efficient legislative program is put in place, a whole new generation of nicotine addicts will result.
Abstract
Eight million Ukrainians have taken refuge in the European Union. Many have asthma and/or allergic rhinitis and/or urticaria, and around 100,000 may have a severe disease. Cultural and ...language barriers are a major obstacle to appropriate management. Two widely available mHealth apps, MASK‐air® (Mobile Airways Sentinel NetworK) for the management of rhinitis and asthma and CRUSE® (Chronic Urticaria Self Evaluation) for patients with chronic spontaneous urticaria, were updated to include Ukrainian versions that make the documented information available to treating physicians in their own language. The Ukrainian patients fill in the questionnaires and daily symptom‐medication scores for asthma, rhinitis (MASK‐air) or urticaria (CRUSE) in Ukrainian. Then, following the GDPR, patients grant their physician access to the app by scanning a QR code displayed on the physician's computer enabling the physician to read the app contents in his/her own language. This service is available freely. It takes less than a minute to show patient data to the physician in the physician's web browser. UCRAID—developed by ARIA (Allergic Rhinitis and its Impact on Asthma) and UCARE (Urticaria Centers of Reference and Excellence)—is under the auspices of the Ukraine Ministry of Health as well as European (European Academy of Allergy and Clinical immunology, EAACI, European Respiratory Society, ERS, European Society of Dermatologic Research, ESDR) and national societies.
Background
In allergic rhinitis and asthma, adolescents and young adult patients are likely to differ from older patients. We compared adolescents, young adults and adults on symptoms, control ...levels, and medication adherence.
Methods
In a cross‐sectional study (2015–2022), we assessed European users of the MASK‐air mHealth app of three age groups: adolescents (13–18 years), young adults (18–26 years), and adults (>26 years). We compared them on their reported rhinitis and asthma symptoms, use and adherence to rhinitis and asthma treatment and app adherence. Allergy symptoms and control were assessed by means of visual analogue scales (VASs) on rhinitis or asthma, the combined symptom‐medication score (CSMS), and the electronic daily control score for asthma (e‐DASTHMA). We built multivariable regression models to compare symptoms or medication accounting for potential differences in demographic characteristics and baseline severity.
Results
We assessed 965 adolescent users (15,252 days), 4595 young adults (58,161 days), and 15,154 adult users (258,796 days). Users of all three age groups displayed similar app adherence. In multivariable models, age groups were not found to significantly differ in their adherence to rhinitis or asthma medication. These models also found that adolescents reported lower VAS on global allergy, ocular, and asthma symptoms (as well as lower CSMS) than young adults and adults.
Conclusions
Adolescents reported a better rhinitis and asthma control than young adults and adults, even though similar medication adherence levels were observed across age groups. These results pave the way for future studies on understanding how adolescents control their allergic diseases.
Smart devices and Internet-based applications (apps) are largely used in allergic rhinitis and may help to address some unmet needs. However, these new tools need to first of all be tested for ...privacy rules, acceptability, usability, and cost-effectiveness. Second, they should be evaluated in the frame of the digital transformation of health, their impact on health care delivery, and health outcomes. This review (1) summarizes some existing mobile health apps for allergic rhinitis and reviews those in which testing has been published, (2) discusses apps that include risk factors of allergic rhinitis, (3) examines the impact of mobile health apps in phenotype discovery, (4) provides real-world evidence for care pathways, and finally (5) discusses mobile health tools enabling the digital transformation of health and care, empowering citizens, and building a healthier society.
IntroductionData from mHealth apps can provide valuable information on rhinitis control and treatment patterns. However, in MASK‐air®, these data have only been analyzed cross‐sectionally, without ...considering the changes of symptoms over time. We analyzed data from MASK‐air® longitudinally, clustering weeks according to reported rhinitis symptoms.MethodsWe analyzed MASK‐air® data, assessing the weeks for which patients had answered a rhinitis daily questionnaire on all 7 days. We firstly used k‐means clustering algorithms for longitudinal data to define clusters of weeks according to the trajectories of reported daily rhinitis symptoms. Clustering was applied separately for weeks when medication was reported or not. We compared obtained clusters on symptoms and rhinitis medication patterns. We then used the latent class mixture model to assess the robustness of results.ResultsWe analyzed 113,239 days (16,177 complete weeks) from 2590 patients (mean age ± SD = 39.1 ± 13.7 years). The first clustering algorithm identified ten clusters among weeks with medication use: seven with low variability in rhinitis control during the week and three with highly‐variable control. Clusters with poorly‐controlled rhinitis displayed a higher frequency of rhinitis co‐medication, a more frequent change of medication schemes and more pronounced seasonal patterns. Six clusters were identified in weeks when no rhinitis medication was used, displaying similar control patterns. The second clustering method provided similar results. Moreover, patients displayed consistent levels of rhinitis control, reporting several weeks with similar levels of control.ConclusionsWe identified 16 patterns of weekly rhinitis control. Co‐medication and medication change schemes were common in uncontrolled weeks, reinforcing the hypothesis that patients treat themselves according to their symptoms.
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