RESUMEN
Allergic rhinitis is an inflammation in the nose caused by overreaction of the immune system to allergens in the air. Managing allergic rhinitis symptoms is challenging and requires timely intervention. The following are major questions often posed by those with allergic rhinitis: How should I prepare for the forthcoming season? How will the season's severity develop over the years? No country yet provides clear guidance addressing these questions. We propose two previously unexplored approaches for forecasting the severity of the grass pollen season on the basis of statistical and mechanistic models. The results suggest annual severity is largely governed by preseasonal meteorological conditions. The mechanistic model suggests climate change will increase the season severity by up to 60%, in line with experimental chamber studies. These models can be used as forecasting tools for advising individuals with hay fever and health care professionals how to prepare for the grass pollen season.
RESUMEN
Grass (Poaceae) pollen is the most important outdoor aeroallergen,1 exacerbating a range of respiratory conditions, including allergic asthma and rhinitis ("hay fever").2-5 Understanding the relationships between respiratory diseases and airborne grass pollen with a view to improving forecasting has broad public health and socioeconomic relevance. It is estimated that there are over 400 million people with allergic rhinitis6 and over 300 million with asthma, globally,7 often comorbidly.8 In the UK, allergic asthma has an annual cost of around US$ 2.8 billion (2017).9 The relative contributions of the >11,000 (worldwide) grass species (C. Osborne et al., 2011, Botany Conference, abstract) to respiratory health have been unresolved,10 as grass pollen cannot be readily discriminated using standard microscopy.11 Instead, here we used novel environmental DNA (eDNA) sampling and qPCR12-15 to measure the relative abundances of airborne pollen from common grass species during two grass pollen seasons (2016 and 2017) across the UK. We quantitatively demonstrate discrete spatiotemporal patterns in airborne grass pollen assemblages. Using a series of generalized additive models (GAMs), we explore the relationship between the incidences of airborne pollen and severe asthma exacerbations (sub-weekly) and prescribing rates of drugs for respiratory allergies (monthly). Our results indicate that a subset of grass species may have disproportionate influence on these population-scale respiratory health responses during peak grass pollen concentrations. The work demonstrates the need for sensitive and detailed biomonitoring of harmful aeroallergens in order to investigate and mitigate their impacts on human health.
Asunto(s)
Asma , ADN Ambiental , Rinitis Alérgica Estacional , Alérgenos , Asma/epidemiología , Asma/genética , Humanos , Poaceae , Polen , Rinitis Alérgica Estacional/epidemiologíaRESUMEN
Grass pollen is the world's most harmful outdoor aeroallergen. However, it is unknown how airborne pollen assemblages change across time and space. Human sensitivity varies between different species of grass that flower at different times, but it is not known whether temporal turnover in species composition match terrestrial flowering or whether species richness steadily accumulates over the grass pollen season. Here, using targeted, high-throughput sequencing, we demonstrate that all grass genera displayed discrete, temporally restricted peaks of incidence, which varied with latitude and longitude throughout Great Britain, revealing that the taxonomic composition of grass pollen exposure changes substantially across the grass pollen season.