Few genetic studies that focus on moderate-to-severe asthma exist. We aimed to identity novel genetic variants associated with moderate-to-severe asthma, see whether previously identified genetic ...variants for all types of asthma contribute to moderate-to-severe asthma, and provide novel mechanistic insights using expression analyses in patients with asthma.
In this genome-wide association study, we used a two-stage case-control design. In stage 1, we genotyped patient-level data from two UK cohorts (the Genetics of Asthma Severity and Phenotypes GASP initiative and the Unbiased BIOmarkers in PREDiction of respiratory disease outcomes U-BIOPRED project) and used data from the UK Biobank to collect patient-level genomic data for cases and controls of European ancestry in a 1:5 ratio. Cases were defined as having moderate-to-severe asthma if they were taking appropriate medication or had been diagnosed by a doctor. Controls were defined as not having asthma, rhinitis, eczema, allergy, emphysema, or chronic bronchitis as diagnosed by a doctor. For stage 2, an independent cohort of cases and controls (1:5) was selected from the UK Biobank only, with no overlap with stage 1 samples. In stage 1 we undertook a genome-wide association study of moderate-to-severe asthma, and in stage 2 we followed up independent variants that reached the significance threshold of p less than 1 × 10−6 in stage 1. We set genome-wide significance at p less than 5 × 10−8. For novel signals, we investigated their effect on all types of asthma (mild, moderate, and severe). For all signals meeting genome-wide significance, we investigated their effect on gene expression in patients with asthma and controls.
We included 5135 cases and 25 675 controls for stage 1, and 5414 cases and 21 471 controls for stage 2. We identified 24 genome-wide significant signals of association with moderate-to-severe asthma, including several signals in innate or adaptive immune-response genes. Three novel signals were identified: rs10905284 in GATA3 (coded allele A, odds ratio OR 0·90, 95% CI 0·88–0·93; p=1·76 × 10−10), rs11603634 in the MUC5AC region (coded allele G, OR 1·09, 1·06–1·12; p=2·32 × 10−8), and rs560026225 near KIAA1109 (coded allele GATT, OR 1·12, 1·08–1·16; p=3·06 × 10−9). The MUC5AC signal was not associated with asthma when analyses included mild asthma. The rs11603634 G allele was associated with increased expression of MUC5AC mRNA in bronchial epithelial brush samples via proxy SNP rs11602802; (p=2·50 × 10−5) and MUC5AC mRNA was increased in bronchial epithelial samples from patients with severe asthma (in two independent analyses, p=0·039 and p=0·022).
We found substantial shared genetic architecture between mild and moderate-to-severe asthma. We also report for the first time genetic variants associated with the risk of developing moderate-to-severe asthma that regulate mucin production. Finally, we identify candidate causal genes in these loci and provide increased insight into this difficult to treat population.
Asthma UK, AirPROM, U-BIOPRED, UK Medical Research Council, and Rosetrees Trust.
Outcomes for patients with chronic respiratory diseases remain poor despite the development of novel therapies. In part, this reflects the fact that adherence to therapy is low and clinicians lack ...accurate methods to assess this issue. Digital technologies hold promise to overcome these barriers to care. For example, algorithmic analysis of large amounts of information collected on health status and treatment use, along with other disease relevant information such as environmental data, can be used to help guide personalised interventions that may have a positive health impact, such as establishing habitual and correct inhaler use. Novel approaches to data analysis also offer the possibility of statistical algorithms that are better able to predict exacerbations, thereby creating opportunities for preventive interventions that may adapt therapy as disease activity changes. To realise these possibilities, digital approaches to disease management should be supported by strong evidence, have a solid infrastructure, be designed collaboratively as clinically effective and cost-effective systems, and reflect the needs of patients and healthcare providers. Regulatory standards for digital interventions and strategies to handle the large amounts of data generated are also needed. This review highlights the opportunities provided by digital technologies for managing patients with respiratory diseases.
Clinical prediction models are widely used to guide medical advice and therapeutic interventions. Asthma is one of the most common chronic diseases globally and is characterised by acute ...deteriorations. These exacerbations are largely preventable, so there is interest in using clinical prediction models in this area. The objective of this review was to identify studies which have developed such models, determine whether consistent and appropriate methodology was used and whether statistically reliable prognostic models exist.
We searched online databases MEDLINE (1948 onwards), CINAHL Plus (1937 onwards), The Cochrane Library, Web of Science (1898 onwards) and ClinicalTrials.gov, using index terms relating to asthma and prognosis. Data was extracted and assessment of quality was based on GRADE and an early version of PROBAST (Prediction study Risk of Bias Assessment Tool). A meta-analysis of the discrimination and calibration measures was carried out to determine overall performance across models.
Ten unique prognostic models were identified. GRADE identified moderate risk of bias in two of the studies, but more detailed quality assessment via PROBAST highlighted that most models were developed using highly selected and small datasets, incompletely recorded predictors and outcomes, and incomplete methodology. None of the identified models modelled recurrent exacerbations, instead favouring either presence/absence of an event, or time to first or specified event. Preferred methodologies were logistic regression and Cox proportional hazards regression. The overall pooled c-statistic was 0.77 (95% confidence interval 0.73 to 0.80), though individually some models performed no better than chance. The meta-analysis had an I
value of 99.75% indicating a high amount of heterogeneity between studies. The majority of studies were small and did not include internal or external validation, therefore the individual performance measures are likely to be optimistic.
Current prognostic models for asthma exacerbations are heterogeneous in methodology, but reported c-statistics suggest a clinically useful model could be created. Studies were consistent in lacking robust validation and in not modelling serial events. Further research is required with respect to incorporating recurrent events, and to externally validate tools in large representative populations to demonstrate the generalizability of published results.
Asthma is a complex disease with multiple phenotypes that may differ in disease pathobiology and treatment response. IL33 single nucleotide polymorphisms (SNPs) have been reproducibly associated with ...asthma. IL33 levels are elevated in sputum and bronchial biopsies of patients with asthma. The functional consequences of IL33 asthma SNPs remain unknown.
This study sought to determine whether IL33 SNPs associate with asthma-related phenotypes and with IL33 expression in lung or bronchial epithelium. This study investigated the effect of increased IL33 expression on human bronchial epithelial cell (HBEC) function.
Association between IL33 SNPs (Chr9: 5,815,786-6,657,983) and asthma phenotypes (Lifelines/DAG Dutch Asthma GWAS/GASP Genetics of Asthma Severity & Phenotypes cohorts) and between SNPs and expression (lung tissue, bronchial brushes, HBECs) was done using regression modeling. Lentiviral overexpression was used to study IL33 effects on HBECs.
We found that 161 SNPs spanning the IL33 region associated with 1 or more asthma phenotypes after correction for multiple testing. We report a main independent signal tagged by rs992969 associating with blood eosinophil levels, asthma, and eosinophilic asthma. A second, independent signal tagged by rs4008366 presented modest association with eosinophilic asthma. Neither signal associated with FEV1, FEV1/forced vital capacity, atopy, and age of asthma onset. The 2 IL33 signals are expression quantitative loci in bronchial brushes and cultured HBECs, but not in lung tissue. IL33 overexpression in vitro resulted in reduced viability and reactive oxygen species–capturing of HBECs, without influencing epithelial cell count, metabolic activity, or barrier function.
We identify IL33 as an epithelial susceptibility gene for eosinophilia and asthma, provide mechanistic insight, and implicate targeting of the IL33 pathway specifically in eosinophilic asthma.
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The "weekend effect" describes an increase in adverse outcomes for patients admitted at the weekend. Critical care units have moved to higher intensity working patterns to address this with some ...improved outcomes. However, support services have persisted with traditional working patterns. Blood cultures are an essential diagnostic tool for patients with sepsis but yield is dependent on sampling technique and processing. We therefore used blood culture yield as a surrogate for the quality of support service provision. We hypothesized that blood culture yields would be lower over the weekend as a consequence of reduced support services.
We performed a retrospective observational study examining 1575 blood culture samples in a university hospital critical care unit over a one-year period.
Patients with positive cultures had, on average, higher APACHE II scores (p = 0.015), longer durations of stay (p = 0.03), required more renal replacement therapy (p<0.001) and had higher mortality (p = 0.024). Blood culture yield decreased with repeated sampling with an increased proportion of contaminants. Blood cultures were 26.7% less likely to be positive if taken at the weekend (p = 0.0402). This effect size is the equivalent to the impact of sampling before and after antibiotic administration.
Our study demonstrates that blood culture yield is lower at the weekend. This is likely caused by delays or errors in incubation and processing, reflecting the reduced provision of support services at the weekend. Reorganization of services to address the "weekend effect" should acknowledge the interdependent nature of healthcare service delivery.
ABSTRACT
Asthma and pneumonia are common respiratory conditions globally, affecting individuals of all ages. Streptococcus pneumoniae is the predominant bacterial cause of pneumonia, with ...nasopharyngeal carriage an important step towards invasive and pulmonary disease. Vaccines provide individual protection, and also prevent nasopharyngeal carriage, providing herd immunity. Asthma is associated with an increased risk of pneumonia, but there is limited information on the underlying mechanism of this predisposition. Both asthma and its treatment may conceivably alter propensity to, and density of, carriage through an altered epithelial microenvironment driven by disease‐related inflammation or treatment‐related immunomodulation, for example with inhaled corticosteroids. The relative importance of these factors could impact the efficacy of vaccines in this vulnerable patient population. In this review, we summarize the evidence for an increased risk of pneumonia in asthma, and discuss factors affecting nasopharyngeal carriage in the context of current guidelines for pneumococcal vaccination.
Asthma and chronic obstructive pulmonary disease (COPD) are highly prevalent worldwide, and major sources of morbidity. Key barriers to reduce the harm from these conditions are the widespread and ...related issues of low use of prescribed inhaled therapy, use of medicines differently from that prescribed, suboptimal inhaler technique, and lack of adherence are the action plans. Connected smart inhalers show great potential to improve these issues, and thus outcomes from airways disease. In this mini-review, we considered the published evidence that the use of smart inhalers leads to more doses of preventative treatment being taken on time and with appropriate techniques. We found multiple trials across a variety of settings and age groups where smart inhalers were used with audio-visual reminders and healthcare professional feedback, which substantially improved the number of doses of preventative treatment taken. Trial evidence also supports the use of feedback from smart inhalers in improving true concordance (doses taken correctly and on time), though only for a single type of smart device. The relative lack of study is in contrast with the potential impact of smart inhalers. Major research questions remain unresolved, as who might fund future large-scale studies, how guideline committees may consider them, and how to implement effective solutions.
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