Mental resilience, perceived immune functioning, and health

Marith Van Schrojenstein Lantman,1 Marlou Mackus,1 Leila S Otten,1 Deborah de Kruijff,1 Aurora JAE van de Loo,1,2 Aletta D Kraneveld,1,2 Johan Garssen,1,3 Joris C Verster1,2,4 1Division of Pharmacology, Utrecht University, Utrecht, the Netherlands; 2Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands; 3Nutricia Research, Utrecht, the Netherlands; 4Centre for Human Psychopharmacology, Swinburne University, Melbourne, Australia Background: Mental resilience can be seen as a trait that enables an individual to recover from stress and to face the next stressor with optimism. People with resilient traits are considered to have a better mental and physical health. However, there are limited data available assessing the relationship between resilient individuals and their perspective of their health and immune status. Therefore, this study was conducted to examine the relationship between mental resilience, perceived health, and perceived immune status. Methods: A total of 779 participants recruited at Utrecht University completed a questionnaire consisting of demographic characteristics, the brief resilience scale for the assessment of mental resilience, the immune function questionnaire (IFQ), and questions regarding their perceived health and immune status. Results: When correcting for gender, age, height, weight, smoker status, amount of cigarettes smoked per week, alcohol consumption status, amount of drinks consumed per week, drug use, and frequency of past year drug use, mental resilience was significantly correlated with perceived health (r=0.233, p=0.0001), perceived immune functioning (r=0.124, p=0.002), and IFQ score (r=−0.185, p=0.0001). Conclusion: A significant, albeit modest, relationship was found between mental resilience and perceived immune functioning and health. Keywords: mental resilience, immune functioning, health, vitality, quality of lif

eNose breath prints as a surrogate biomarker for classifying patients with asthma by atopy

BACKGROUND: Electronic noses (eNoses) are emerging point-of-care tools that may help in the subphenotyping of chronic respiratory diseases such as asthma. OBJECTIVE: We aimed to investigate whether eNoses can classify atopy in pediatric and adult patients with asthma. METHODS: Participants with asthma and/or wheezing from 4 independent cohorts were included; BreathCloud participants (n = 429), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adults (n = 96), Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes pediatric participants (n = 100), and Pharmacogenetics of Asthma Medication in Children: Medication with Anti-Inflammatory Effects 2 participants (n = 30). Atopy was defined as a positive skin prick test result (≥3 mm) and/or a positive specific IgE level (≥0.35 kU/L) for common allergens. Exhaled breath profiles were measured by using either an integrated eNose platform or the SpiroNose. Data were divided into 2 training and 2 validation sets according to the technology used. Supervised data analysis involved the use of 3 different machine learning algorithms to classify patients with atopic versus nonatopic asthma with reporting of areas under the receiver operating characteristic curves as a measure of model performance. In addition, an unsupervised approach was performed by using a bayesian network to reveal data-driven relationships between eNose volatile organic compound profiles and asthma characteristics. RESULTS: Breath profiles of 655 participants (n = 601 adults and school-aged children with asthma and 54 preschool children with wheezing [68.2% of whom were atopic]) were included in this study. Machine learning models utilizing volatile organic compound profiles discriminated between atopic and nonatopic participants with areas under the receiver operating characteristic curves of at least 0.84 and 0.72 in the training and validation sets, respectively. The unsupervised approach revealed that breath profiles classifying atopy are not confounded by other patient characteristics. CONCLUSION: eNoses accurately detect atopy in individuals with asthma and wheezing in cohorts with different age groups and could be used in asthma phenotyping

Ovalbumin-sensitized mice are good models for airway hyperresponsiveness but not acute physiological responses to allergen inhalation

Background: Asthma is a chronic inflammatory disease that is characterized clinically by airway hyperresponsiveness (AHR) to bronchoconstricting agents. The physiological response of the asthmatic lung to inhaled allergen is often characterized by two distinct phases: an early-phase response (EPR) within the first hour following exposure that subsides and a late-phase response (LPR) that is more prolonged and may occur several hours later. Mouse models of asthma have become increasingly popular and should be designed to exhibit an EPR, LPR and AHR. Objective: To determine whether a common model of asthma is capable of demonstrating an EPR, LPR and AHR. Methods: BALB/c mice were sensitized to ovalbumin (OVA) and challenged with one or three OVA aerosols. Changes in lung mechanics in response to allergen inhalation were assessed using a modification of the low-frequency forced oscillation technique (LFOT). In order to assess AHR, changes in lung mechanics in response to aerosolized methacholine were assessed using LFOT. Inflammatory cell infiltration into the lung was measured via bronchoalveolar lavage (BAL). ELISAs were used to measure inflammatory cytokines in the BAL and levels of IgE in the serum. Results: An EPR was only detectable after three OVA aerosols in approximately half of the mice studied. There was no evidence of an LPR despite a clear increase in cellular infiltration 6 h post-allergen challenge. AHR was present after a single OVA aerosol but not after three OVA aerosols. Conclusions: The lack of an LPR, limited EPR and the absence of a link between the LPR and AHR highlight the limitations of this mouse model as a complete model of the lung dysfunction associated with asthma