Obese Asthma Phenotype Is Associated with hsa-miR-26a-1-3p and hsa-miR-376a-3p Modulating the IGF Axis.

Clarifying inflammatory processes and categorising asthma into phenotypes and endotypes improves asthma management. Obesity worsens severe asthma and reduces quality of life, although its specific molecular impact remains unclear. We previously demonstrated that hsa-miR-26a-1-3p and hsa-miR-376a-3p, biomarkers related to an inflammatory profile, discriminate eosinophilic from non-eosinophilic asthmatics. We aimed to study hsa-miR-26a-1-3p, hsa-miR-376a-3p, and their target genes in asthmatic subjects with or without obesity to find biomarkers and comprehend obese asthma mechanisms. Lung tissue samples were obtained from asthmatic patients (n = 16) and healthy subjects (n = 20). We measured miRNA expression using RT-qPCR and protein levels (IGF axis) by ELISA in confirmation samples from eosinophilic (n = 38) and non-eosinophilic (n = 39) obese (n = 26) and non-obese (n = 51) asthma patients. Asthmatic lungs showed higher hsa-miR-26a-1-3p and hsa-miR-376a-3p expression than healthy lungs. A study of seven genes regulated by these miRNAs revealed differential expression of IGFBP3 between asthma patients and healthy individuals. In obese asthma patients, we found higher hsa-miR-26a-1-3p and IGF-1R values and lower values for hsa-miR-376a-3p and IGFBP-3. Hsa-miR-26a-1-3p and IGFBP-3 were directly and inversely correlated with body mass index, respectively. Hsa-miR-26a-1-3p and hsa-miR-376a-3p could be used as biomarkers to phenotype patients with eosinophilic and non-eosinophilic asthma in relation to comorbid obesity.

Identification of Asthma Phenotypes in the Spanish MEGA Cohort Study Using Cluster Analysis

Introduction: The definition of asthma phenotypes has not been fully established, neither there are cluster studies showing homogeneous results to solidly establish clear phenotypes. The purpose of this study was to develop a classification algorithm based on unsupervised cluster analysis, identifying clusters that represent clinically relevant asthma phenotypes that may share asthma-related outcomes. Methods: We performed a multicentre prospective cohort study, including adult patients with asthma (N=512) from the MEGA study (Mechanisms underlying the Genesis and evolution of Asthma). A standardised clinical history was completed for each patient. Cluster analysis was performed using the kernel k-groups algorithm. Results: Four clusters were identified. Cluster 1 (31.5% of subjects) includes adult-onset atopic patients with better lung function, lower BMI, good asthma control, low ICS dose, and few exacerbations. Cluster 2 (23.6%) is made of adolescent-onset atopic asthma patients with normal lung function, but low adherence to treatment (59% well-controlled) and smokers (48%). Cluster 3 (17.1%) includes adult-onset patients, mostly severe non-atopic, with overweight, the worse lung function and asthma control, and receiving combination of treatments. Cluster 4 (26.7%) consists of the elderly-onset patients, mostly female, atopic (64%), with high BMI and normal lung function, prevalence of smokers and comorbidities. Conclusion: We defined four phenotypes of asthma using unsupervised cluster analysis. These clusters are clinically relevant and differ from each other as regards FEV1, age of onset, age, BMI, atopy, asthma severity, exacerbations, control, social class, smoking and nasal polyps. (AU)

Identification of Asthma Phenotypes in the Spanish MEGA Cohort Study Using Cluster Analysis.

INTRODUCTION: The definition of asthma phenotypes has not been fully established, neither there are cluster studies showing homogeneous results to solidly establish clear phenotypes. The purpose of this study was to develop a classification algorithm based on unsupervised cluster analysis, identifying clusters that represent clinically relevant asthma phenotypes that may share asthma-related outcomes. METHODS: We performed a multicentre prospective cohort study, including adult patients with asthma (N=512) from the MEGA study (Mechanisms underlying the Genesis and evolution of Asthma). A standardised clinical history was completed for each patient. Cluster analysis was performed using the kernel k-groups algorithm. RESULTS: Four clusters were identified. Cluster 1 (31.5% of subjects) includes adult-onset atopic patients with better lung function, lower BMI, good asthma control, low ICS dose, and few exacerbations. Cluster 2 (23.6%) is made of adolescent-onset atopic asthma patients with normal lung function, but low adherence to treatment (59% well-controlled) and smokers (48%). Cluster 3 (17.1%) includes adult-onset patients, mostly severe non-atopic, with overweight, the worse lung function and asthma control, and receiving combination of treatments. Cluster 4 (26.7%) consists of the elderly-onset patients, mostly female, atopic (64%), with high BMI and normal lung function, prevalence of smokers and comorbidities. CONCLUSION: We defined four phenotypes of asthma using unsupervised cluster analysis. These clusters are clinically relevant and differ from each other as regards FEV1, age of onset, age, BMI, atopy, asthma severity, exacerbations, control, social class, smoking and nasal polyps.

Analysis of Differentially Expressed MicroRNAs in Serum and Lung Tissues from Individuals with Severe Asthma Treated with Oral Glucocorticoids.

Nowadays, microRNAs (miRNAs) are increasingly used as biomarkers due to their potential contribution to the diagnosis and targeted treatment of a range of diseases. The aim of the study was to analyze the miRNA expression profiles in serum and lung tissue from patients with severe asthma treated with oral corticosteroids (OCS) and those without OCS treatment. For this purpose, serum and lung tissue miRNAs of OCS and non-OCS asthmatic individuals were evaluated by miRNAs-Seq, and subsequently miRNA validation was performed using RT-qPCR. Additionally, pathway enrichment analysis of deregulated miRNAs was conducted. We observed altered expression by the next-generation sequencing (NGS) of 11 miRNAs in serum, of which five (hsa-miR-148b-3p, hsa-miR-221-5p, hsa-miR-618, hsa-miR-941, and hsa-miR-769-5p) were validated by RT-qPCR, and three miRNAs in lung tissue (hsa-miR-144-3p, hsa-miR-144-5p, and hsa-miR-451a). The best multivariate logistic regression model to differentiate individuals with severe asthma, treated and untreated with OCS, was to combine the serum miRNAs hsa-miR-221-5p and hsa-miR-769-5p. Expression of hsa-miR-148b-3p and hsa-miR-221-5p correlated with FEV1/FVC (%) and these altered miRNAs act in key signaling pathways for asthma disease and the regulated expression of some genes (FOXO3, PTEN, and MAPK3) involved in these pathways. In conclusion, there are miRNA profiles differentially expressed in OCS-treated individuals with asthma and could be used as biomarkers of OCS treatment.

Hyperacute Incidental Late Myocardial Enhancement in Ischemic Stroke Using Chest Spectral CT: Relationship with Etiology.

BACKGROUND: Hyperacute cardiac imaging of patients with acute ischemic stroke (AIS), though desirable, is impractical. Using delayed-enhancement, low-dose, non-gated, chest spectral computed tomography scans (DESCT), we explored the prevalence and patterns of incidental myocardial late iodine enhancement (LIE) and embolic sources, and their relationship with stroke etiology. METHODS: Since July 2020, DESCT was performed after cerebrovascular CT angiography (CTA) among patients with suspected AIS undergoing CT using a dual-layer spectral scanner, without additional contrast administration. Images were analyzed using monoenergetic reconstructions and iodine density maps, and the myocardial extracellular volume fraction (ECV, %) was calculated. RESULTS: Eighty patients with AIS were included. DESCT identified a cardiac thrombi in 6 patients (7.5%), and a complex aortic plaque in 4 (5%) cases; reclassifying 5 embolic strokes of uncertain source (28% of ESUS) to cardioembolic (CE, n = 3) and non-CE (n = 2) etiologies. LIE was identified in 38 (48%) patients, most commonly (82%) of ischemic pattern. We did not identify significant relationships between AIS etiology and the presence, pattern, and extent of LIE (p > 0.05); ECV (p = 0.56), severe aortic (p = 0.25) or valvular (p = 0.26) disease, or the extent of coronary calcification (p = 0.39). Patients with evidence of major cardiovascular DESCT findings had higher rates of all-cause death at 90 days (42% vs. 19%, p = 0.037). CONCLUSIONS: In this study, hyperacute cardiac imaging of AIS with DESCT identified a high prevalence of incidental cardiac disease predominantly involving LIE of ischemic etiology and mostly not related to the stroke etiology.

Clinical and inflammatory characteristics of patients with asthma in the Spanish MEGA project cohort.

INTRODUCTION: The MEGA (MEchanism underlying the Genesis and evolution of Asthma) project is a multicenter cohort study carried out in eight Spanish hospitals, gathering clinical, physiological, and molecular data from patients with asthma and multimorbidities in order to gain insight into the different physiopathological mechanisms involved in this disorder. MATERIAL AND METHODS: We report the baseline clinical and physiological characteristics and biomarker measures of adult participants in the project with the aim of better understanding the natural history and underlying mechanisms of asthma as well as the associated multimorbidities across different levels of severity. We carried out a detailed clinical examination, pulmonary function testing, measurement of fractional exhaled nitric oxide (FeNO), blood counts, induced sputum, skin prick tests, chest computed tomography scan, asthma questionnaires, and multimorbidity assessment in 512 asthmatic patients. RESULTS: When compared to patients with milder disease, severe asthmatic patients showed greater presence of symptoms, more exacerbations, lower asthma control, increased airflow obstruction, and higher frequency of chronic rhinosinusitis with nasal polyps, severe rhinitis, anxiety and depression, gastroesophageal reflux, and bronchiectasis. CONCLUSION: The MEGA project succeeded in recruiting a high number of asthma patients, especially those with severe disease, who showed lower control and higher frequency of multimorbidities.

Cardiovascular thrombotic complications in acute ischemic stroke assessed by chest spectral computed tomography during COVID-19.

During the pandemic context, diagnostic algorithms had to be adapted considering the decimated medical personnel, local technical resources, and the likelihood of contamination. Given the higher probability of thrombotic complications related to COVID-19 and the availability of a dual-layer spectral computed tomography (CT) scanner, we have recently adopted the use of low-dose, non-gated, chest CT scans performed five minutes after contrast administration among patients admitted with acute ischemic stroke (AIS) undergoing cerebrovascular CT angiography. Dual-layer spectral CT comprises a single X-ray source and two-layer detector with different photon-absorption capabilities. In addition to conventional images, the two distinct energy datasets obtained enable multiparametric spectral analysis without need to change the original scanning protocol. The two spectral features that emerge as most useful for patients with AIS are virtual monoenergetic imaging and iodine-based results. Aside from the evaluation of lung parenchyma, this novel strategy enables ruling out cardioembolic sources and simultaneously providing evidence of pulmonary and myocardial injury in a single session and immediately after CT cerebrovascular angiography. Furthermore, it involves a non-invasive, seemingly accurate, unsophisticated, safer (very low radiation dose and no contrast administration), and cheaper tool for ruling out cardioembolic sources compared to transesophageal echocardiogram and cardiac CT. Accordingly, we sought to standardize the technical aspects and overview the usefulness of delayed-phase, low-dose chest spectral CT in patients admitted with AIS.