Thunderstorm allergy and asthma: state of the art

Temporal variation of allergenic potential in urban parks during the vegetation period: a case study from Bratislava, Slovakia

Park greenery represents an oasis for urban residents; however, during the flowering period of trees that produce allergenic pollen grains, these areas threaten individuals suffering from seasonal allergic respiratory diseases. In this study, we evaluated the temporal distribution of the allergenic potential of three most important urban parks in Bratislava over the vegetation period, using a modification of the Urban Green Zone Allergenicity Index (IUGZA) and Individual-Specific Allergenic Potential Index (IISA) designed as a running index - rIUGZA and rIISA. We found that rIUGZA gives better information for park management and revitalization, since it considers the potential size of woody plants, while rIISA, considering the actual size of the vegetation, provides more relevant information for pollen-allergy sufferers. Based on rIISA, the allergenic potential was highest in May for the Grassalkovich Garden (formal baroque garden) and Janko Kráľ Park (English landscape park) and in April for the Medic Garden (repurposed baroque garden). We also found differences in the duration of the period of increased allergenic potential in these parks, ranging from 1 to 3 months. Based on the total annual sums of rIISA, we found the highest allergenic potential in the Medic Garden and lowest in the Janko Kráľ Park. This variance is caused mainly by the different density of trees and percentage of allergenic species. The biggest contributors to the allergenic potential were Platanus, Acer and Tilia. Based on the information on temporal variation of the allergenic potential during the vegetation period provided by the running indices, it is possible to improve the planning of park revitalization based on the flowering period of allergenic species and provide better information to the pollen-allergy sufferers for minimizing the allergenic effect of urban green areas on their health during a particular month.

[Unmet Needs in Severe Allergic Asthma]

Severe asthma affects 3%-10% of the world's population, according to estimates by the Global Initiative for ASTHMA (GINA). Allergic asthma is one of the most common phenotypes of severe asthma and it is characterized by allergen-induced type 2 inflammation in which immunoglobulin E (IgE) is a key mediator, making it an important therapeutic target. The introduction of targeted biological therapies or treatments has entered the management for severe asthma in the era of precision medicine, and the goal of treatment is clinical remission of the disease. There is a significant percentage of patients with severe allergic asthma who do not respond to treatments and whose symptoms are not controlled. In this paper, a group of experts in the management of severe allergic asthma reviewed and evaluated the most relevant evidence regarding the pathophysiology and phenotypes of severe allergic asthma, the role of IgE in allergic inflammation, allergen identification, techniques, biomarkers and diagnostic challenges, available treatments and strategies for disease management, with a special focus on biological treatments. From this review, recommendations were developed and validated through a Delphi consensus process with the aim of offering improvements in the management of severe allergic asthma to the professionals involved and identifying the unmet needs in the management of this pathology.

Thunder storm mortality: Issues of medicolegal concern

Thunderstorms refer to atmospheric disturbances that are associated with electrical discharges in the form of lightning, with acoustic effects from thunder. They involve the rapid upward movement of warm, moist air which then cools and condenses creating typical cumulonimbus clouds with precipitation. Thunderstorms range in severity but are usually associated with heavy rains, winds and sometimes sleet, hail and snow. If the intensity of a storm increases there may be tornadoes or cyclones. In cases with lightning strikes and minimal or no rain there is an associated risk for the development of quite devastating wild (bush) fires. Lightning strikes may also be associated with the development, or an exacerbation, of potentially lethal natural cardiac or respiratory diseases.

Relationship between Aspergillus and asthma

Fungal sensitization is highly prevalent in severe asthma. The relationship between fungus and asthma, especially Aspergillus fumigatus, has been the subject of extensive research. The ubiquitous presence of A. fumigatus, its thermotolerant nature, the respirable size of its conidia, and its ability to produce potent allergens are pivotal in worsening asthma control. Due to the diverse clinical manifestations of fungal asthma and the lack of specific biomarkers, its diagnosis remains intricate. Diagnosing fungal asthma requires carefully assessing the patient's clinical history, immunological tests, and imaging. Depending on the severity, patients with fungal asthma require personalized treatment plans, including inhaled corticosteroids and bronchodilators, and antifungal therapy. This review provides a comprehensive overview of the association between Aspergillus and asthma by reviewing the relevant literature and highlighting key findings. We discuss the diagnosis of various entities included in fungal asthma. We also debate whether newer definitions, including allergic fungal airway disease, offer any additional advantages over the existing ones. Finally, we provide the current treatment options for the individual entities, including A. fumigatus-associated asthma, severe asthma with fungal sensitization, and allergic bronchopulmonary mycoses.

Association of asthma exacerbations with paper mulberry (Broussenetia papyrifera) pollen in Islamabad: An observational study

Background

Although the role of airborne plant pollen in causing allergic rhinitis has been established, the association of concentrations of paper mulberry (Broussenetia papyrifera) pollens in the air and incidence of asthma exacerbations has not, despite an observed increase in the number of asthma patients attending physician clinics and hospital Accident and Emergency (A&E) Departments during the paper mulberry pollen season. We aimed to assess the association between paper mulberry pollen concentrations (typically peaking in March each year) and asthma exacerbations in the city of Islamabad.

Methods

We used three approaches to investigate the correlation of paper mulberry pollen concentration with asthma exacerbations: A retrospective analysis of historical records (2000-2019) of asthma exacerbations of patients from the Allergy and Asthma Institute, Pakistan (n = 284), an analysis of daily nebulisations in patients attending the A&E Department of the Pakistan Institute of Medical Sciences (March 2020 to July 2021), a prospective peak expiratory flow rate (PEFR) diary from participants (n = 40) with or without asthma and with or without paper mulberry sensitisation. We examined associations between pollen data and asthma exacerbations using Pearson correlation.

Results

We found a strong positive correlation between mean paper mulberry pollen counts and clinical records of asthma exacerbations in patients sensitised to paper mulberry (Pearson correlation coefficient (r) = 0.86; P < 0.001), but not in non-sensitised patients (r = 0.32; P = 0.3). There was a moderate positive correlation between monthly nebulisation counts and pollen counts (r = 0.56; P = 0.03), and a strong negative correlation between percent predicted PEFR and pollen counts in sensitised asthma patients (r = -0.72, P < 0.001). However, these correlations were of low magnitude in the non-sensitised asthma (r = -0.16; P < 0.001) and sensitised non-asthma (r = -0.28; P < 0.001) groups.

Conclusions

Our three approaches to analysis all showed an association between high paper mulberry pollen concentration in Islamabad and asthma exacerbations. Predicting pollen peaks could enable alerts and mobilise strategies to proactively manage these peaks of asthma exacerbations.

Impact of meteorological parameters and air pollutants on airborne concentration of Betula pollen and Bet v 1 allergen

The intensity of birch pollen season is expressed by seasonal pollen integral (SPIn, the sum of the mean daily pollen concentration during the birch pollination period) and the amount of Bet v 1 allergen released per birch pollen grain expressed by pollen allergen potency (PAP). Betula pollen and Bet v 1 allergen were simultaneously measured in the air of Bratislava from 2019 to 2022 by using two Burkard traps (Hirst-type and cyclone) in order to evaluate the causes of the seasonal variation in the SPIn and PAP levels. The highest SPIn (19,975 pollen/m3) was observed in 2022 and the lowest one (1484 pollen/m3) in 2021. The average daily PAP level (4.0 pg Bet v 1/pollen) was highest in 2019 and lowest (2.5 pg Bet v 1/pollen) in 2020. We found that seasonal variation in SPIn was associated mainly with the changes in environmental conditions during the pre-season period, whereas the year-to-year variation in PAP levels was attributed to environmental conditions during both pre- and in-season periods. Our results indicate that rainy weather in June 2020 and cold overcast weather in January‒February 2021 resulted in low SPIn in 2021. On the other hand, dry weather in June 2021 and warm weather in January‒February 2022 resulted in high SPIn in 2022. The low average daily PAP level in 2020 was associated with (1) low levels of gaseous air pollutants in March, when the ripening of pollen takes place; (2) an earlier start of the birch main pollen season (MPS); and (3) dry weather during the MPS. On the other hand, high PAP level in 2019 was associated with higher levels of air pollutants in March and during the MPS.

EAACI guidelines on environmental science in allergic diseases and asthma - Leveraging artificial intelligence and machine learning to develop a causality model in exposomics

Allergic diseases and asthma are intrinsically linked to the environment we live in and to patterns of exposure. The integrated approach to understanding the effects of exposures on the immune system includes the ongoing collection of large-scale and complex data. This requires sophisticated methods to take full advantage of what this data can offer. Here we discuss the progress and further promise of applying artificial intelligence and machine-learning approaches to help unlock the power of complex environmental data sets toward providing causality models of exposure and intervention. We discuss a range of relevant machine-learning paradigms and models including the way such models are trained and validated together with examples of machine learning applied to allergic disease in the context of specific environmental exposures as well as attempts to tie these environmental data streams to the full representative exposome. We also discuss the promise of artificial intelligence in personalized medicine and the methodological approaches to healthcare with the final AI to improve public health.

Climate change, airborne allergens, and three translational mitigation approaches

One of the important adverse impacts of climate change on human health is increases in allergic respiratory diseases such as allergic rhinitis and asthma. This impact is via the effects of increases in atmospheric carbon dioxide concentration and air temperature on sources of airborne allergens such as pollen and fungal spores. This review describes these effects and then explores three translational mitigation approaches that may lead to improved health outcomes, with recent examples and developments highlighted. Impacts have already been observed on the seasonality, production and atmospheric concentration, allergenicity, and geographic distribution of airborne allergens, and these are projected to continue into the future. A technological revolution is underway that has the potential to advance patient management by better avoiding associated increased exposures, including automated real-time airborne allergen monitoring, airborne allergen forecasting and modelling, and smartphone apps for mitigating the health impacts of airborne allergens.