Pollen exposure is associated with risk of respiratory symptoms during the first year of life

The association of increased pre- and postnatal NO2 and PM2.5 exposure with the infant nasal microbiome composition and respiratory symptoms

BACKGROUND

Little is known about the mediating role of nasal microbiome on the association between pre- and postnatal air pollution exposure and subsequent respiratory morbidity in infancy. We aimed to examine the impact of air pollution on microbiome and respiratory symptoms, and whether microbiome mediates the association between air pollution and symptoms.

METHODS

Nasal swabs from 270 infants in the prospective Basel-Bern Infant Lung Development cohort were analyzed by 16S ribosomal RNA gene sequencing. We investigated the association of pre- and postnatal nitrogen dioxide (NO2) and particulate matter ≤2.5 μm (PM2.5) with microbiome at 4-6 weeks and with respiratory symptoms during the first year of life. Hierarchical clustering and generalized structural equation modeling were used.

RESULTS

Mean prenatal air pollution levels were 21.54 μg/m3 (NO2) and 13.84 μg/m3 (PM2.5) (WHO guideline limits: NO2: 40 μg/m3 (2005), 10 μg/m3 (2021); PM2.5: 10 μg/m3 (2005), 5 μg/m3 (2021)). We identified two distinct microbiome clusters, characterized by high Corynebacterium/Dolosigranulum and high Staphylococcus abundance. Higher pre- and postnatal air pollution exposure was associated with Staphylococcus cluster (e.g., per 10 μg/m3 increase of prenatal NO2: odds ratio 1.58, 95% confidence interval 1.08; 2.29, padj = 0.034). Pre- and postnatal PM2.5 was associated with increased risk of severe respiratory symptoms. This association was not mediated by nasal microbiome.

CONCLUSION

Pre- and postnatal air pollution was associated with microbiome and respiratory symptoms in infancy. The microbiome did not mediate the association of air pollution with respiratory symptoms, which may indicate that other mechanisms are more relevant at this age.

The conformational epitope of Ara h 5 was crucial to the severe reactivity of peanut allergy

Conformational epitopes are associated with the development of food allergic tolerance and the severity of food allergy. Peanut can trigger severe anaphylactic reactions, however, the reason behind the severe allergic reactions caused by peanut remains unexplained. The purpose of this article was to provide an explanation for the severe allergy caused by peanut, focusing on the conformational epitopes of Ara h 5 and Ara h 8 allergens that exhibit cross-reactivity with asthma reactions. Ara h 5 and Ara h 8 proteins were prepared by an Escherichia coli expression system. IgE reactivity of 37 patients with allergy toward Ara h 5 and Ara h 8 allergens was assessed by using IgE-binding assays, dot blot and western blot. The allergenicity of Ara h 5 and Ara h 8 protein was analysed in mouse model. Conformational IgE epitopes of Ara h 5 was identified using phage peptide library and the Pepitope Server. Compared to Ara h 8, the conformational epitope of Ara h 5 protein was crucial in the process of sensitization. Ara h 5 showed a stronger IgE reactivity and the ability to induce β-hexosaminidase release. Ara h 5 caused more severe lung inflammation than Ara h 8 protein. While Ara h 8 caused more severe intestinal inflammation than Ara h 5. The results showed that the conformational epitope sequences of Ara h 5 were WETIYSR and FHWWYLK. The results provide a theoretical basis for the production of hypoallergenic peanut protein and the immunotherapy of peanut allergy.

Protective Effect of Allergen Immunotherapy in Patients With Allergic Rhinitis and Asthma Against COVID-19 Infection: Observational, Nationwide, and Multicenter Study

BACKGROUND

Allergic diseases are associated with an increased susceptibility to respiratory tract infections. Although allergen immunotherapy (AIT) alters the course of allergies, there is limited evidence from clinical practice demonstrating its ability to enhance the host defense against pathogens.

OBJECTIVE

The aim of this study was to investigate the protective effect of AIT against viral infection in patients with allergic rhinitis (AR) and allergic asthma (AS) based on clinical evidence.

METHODS

A multicenter, questionnaire-based survey was conducted during a tremendous surge in COVID-19 cases between February 10, 2023, and March 15, 2023, in 81 centers across China recruiting healthy volunteers and patients with AR and AS to investigate the clinical outcomes of COVID-19 infection.

RESULTS

Of 10,151 participants recruited in the survey, 3654 patients and 2192 healthy volunteers who tested positive for COVID-19 were included in this analysis after screening. Overall, no significant differences in COVID-19 outcomes were observed between patients and healthy volunteers. An additional 451 patients were excluded due to their use of biologics as the sole add-on treatment, leaving 3203 patients in the further analysis. Of them, 1752 were undergoing routine medication treatment (RMT; the RMT group), whereas 1057 and 394 were receiving AIT and a combination of AIT and omalizumab (OMA) as adjunct therapies to RMT, respectively (AIT+RMT and AIT+OMA+RMT groups). The AIT group showed milder COVID-19 symptoms, shorter recovery periods, and a lower likelihood of hospitalization or emergency department visits than the RMT group (all P<.05). After adjusting for confounding factors, including demographic characteristics and COVID-19 vaccination, AIT remained a significant protective factor associated with shorter recovery time (adjusted odds ratio [OR] 0.62, 95% CI 0.52-0.75; adjusted P<.001) and a lower incidence of hospitalization or emergency department visits (adjusted OR 0.73, 95% CI 0.54-0.98; adjusted P=.03). Furthermore, the AIT+OMA+RMT group showed greater protection with a shorter recovery time (adjusted OR 0.51, 95% CI 0.34-0.74; adjusted P<.001) than the AIT+RMT group.

CONCLUSIONS

Our multicenter observational study provides valuable clinical evidence supporting the protective effect of AIT against COVID-19 infection in patients with AR and AS.

Early life exposure to pollens and increased risks of childhood asthma: a prospective cohort study in Ontario children

Asthma is a disease characterised by wheeze, cough and shortness of breath, and constitutes the most prevalent chronic disease among children [1]. Various phenotypes have been specifically identified in the paediatric population, and include early transient wheeze, current wheeze/asthma, and mild or moderate asthma [2]. Lifestyle behaviours, genetics, maternal and paternal factors, and environment exposures have been identified as risk factors in the multifactorial aetiology of childhood asthma [3].

Increased exposure to tree canopy around the place of residence at birth prevented the risk of childhood asthma development, but this protective effect can be reduced when exposure to weed and tree pollen increases https://bit.ly/3Tboabo

Estimation of historical daily airborne pollen concentrations across Switzerland using a spatio temporal random forest model

High concentrations of airborne pollen trigger seasonal allergies and possibly more severe adverse respiratory and cardiovascular health events. Predicting pollen concentration accurately is valuable for epidemiological studies, in order to study the effects of pollen exposure. We aimed to develop a spatiotemporal machine learning model predicting daily pollen concentrations at a spatial resolution of 1 × 1 km across Switzerland between 2000 and 2019. Daily pollen concentrations for five common, highly allergenic pollen types (hazel, alder, birch ash, and grasses) were available from fourteen measurement sites across Switzerland. We considered several predictors such as elevation, species distribution, wind speed, wind direction, temperature, precipitation, relative humidity, satellite-observed Normalized Difference Vegetation Index, and land-use (CORINE, Landsat satellite) to explain variation in pollen concentration. We employed feature engineering techniques to encode categorical variables and fill in missing values. We applied a random forest machine learning model with 5-fold cross-validation. The 5th-99th percentiles for concentrations of hazel, alder, birch, ash, and grass pollen at the pollen monitoring stations were 0-298, 0-306, 0-1153, 0-800, and 0-290 pollen grains/m3, respectively. The results of a predictive model for these concentrations yielded overall R2 values of 0.87, 0.84, 0.89, 0.88, and 0.91, and temporal root mean squared errors (RMSEs) of 16.07, 16.72, 69.04, 41.50, and 22.45 pollen grains/m3. An analysis of predictor variable importance indicates that the average national daily pollen concentration is the most important predictor of pollen concentrations for all pollen types. Furthermore, meteorological variables including temperature, total precipitation, humidity, boundary layer height, wind speed, and wind direction, as well as date and satellite features, are important factors in pollen concentration prediction. These spatiotemporal pollen models will serve to estimate individual residential pollen exposure for epidemiological studies. Resulting estimates will enable us to study respiratory and cardiovascular mortality and hospital admissions in Switzerland.

Effect of altered human exposome on the skin and mucosal epithelial barrier integrity

Pollution in the world and exposure of humans and nature to toxic substances is continuously worsening at a rapid pace. In the last 60 years, human and domestic animal health has been challenged by continuous exposure to toxic substances and pollutants because of uncontrolled growth, modernization, and industrialization. More than 350,000 new chemicals have been introduced to our lives, mostly without any reasonable control of their health effects and toxicity. A plethora of studies show exposure to these harmful substances during this period with their implications on the skin and mucosal epithelial barrier and increasing prevalence of allergic and autoimmune diseases in the context of the "epithelial barrier hypothesis". Exposure to these substances causes an epithelial injury with peri-epithelial inflammation, microbial dysbiosis and bacterial translocation to sub-epithelial areas, and immune response to dysbiotic bacteria. Here, we provide scientific evidence on the altered human exposome and its impact on epithelial barriers.