Strong variations in urban allergenicity riskscapes due to poor knowledge of tree pollen allergenic potential.
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ABSTRACT:
SUBMITTER: Sousa-Silva R
PROVIDER: S-EPMC8119473 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Temperature gradients in cities can cause inter-neighborhood differences in the timing of pollen release. However, most epidemiological studies examining allergenic pollen utilize daily measurements from a single pollen monitoring station with the implicit assumption that the measured time series of airborne pollen concentrations applies across the study areas, and that the temporal mismatch between concentrations at the counting station and elsewhere in the study area is negligible. This assumption is tested by quantifying temperature using satellite imagery, observing flowering times of oak (Quercus) and mulberry (Morus) trees at multiple sites, and collecting airborne pollen. Epidemiological studies of allergenic pollen are reviewed and temperatures within their study areas are quantified. In this one-year study, peak oak flowering time was well explained by average February nighttime temperature (R2 = 0.94), which varied by 6 °C across Detroit. This relationship was used to predict flowering phenology across the study region. Peak flowering ranged from April 20-May 13 and predicted a substantial portion of relative airborne oak pollen concentrations in Detroit (R2 = 0.46) and at the regional pollen monitoring station (R2 = 0.61). The regional pollen monitoring station was located in a cooler outlying area where peak flowering occurred around May 12 and peak pollen concentrations were measured on May 15. This provides evidence that the timing of pollen release varies substantially within a metropolitan area and challenges the assumption that pollen measurements at a single location are representative of an entire city. Across the epidemiological studies, 50% of study areas were not within 1 °C (equal to a lag or lead of 4 days in flowering time) of temperatures at the pollen measurement location. Epidemiological studies using a single pollen station as a proxy for pollen concentrations are prone to significant measurement error if the study area is climatically variable.
| S-EPMC6402594 | biostudies-literature
Project description:The Phl p 5 allergen of the plant species Phleum pratense is considered one of the most crucial grass pollen allergenic molecules inducing respiratory allergies. In this study, we evaluated seasonal variation in the concentration of both grass pollen and Phl p 5 allergens as well as the ratio allergen/pollen (pollen potency) in the air of Bratislava during two consecutive years, 2019-2020. These 2 years differed in terms of air pollution, as COVID-19 lockdown in spring 2020 considerably improved air quality in the study area. Air samples were collected using a Hirst-type sampler for pollen detection and the cyclone sampler for aeroallergen detection. In 2020, we observed 80.3% higher seasonal pollen integral, probably associated with the longer pollen season duration, however, 43.6% lower mean daily pollen potency than in 2019. The mean daily pollen value was 37.5% higher in 2020 than in the previous year, while the mean daily allergen value was 14.9% lower in 2020. To evaluate the relationship between the amount of pollen or allergen in the air and selected meteorological factors and air pollution parameters, we used multiple regression analysis. Regarding weather factors, precipitation and relative humidity were significantly associated with pollen and/or allergen concentration, though these associations were negative. Atmospheric pollutants, especially CO, NO2 and O3 were significantly associated with pollen and/or allergen levels. The associations with CO and O3 were positive, while the association with NO2 was negative. Our results indicate that for grasses, an air pollutant that has a significant positive relationship to the ratio of allergen/pollen is nitrogen dioxide.
| S-EPMC8248954 | biostudies-literature
Project description:Many diseases are linked with climate trends and variations. In particular, climate change is expected to alter the spatiotemporal dynamics of allergenic airborne pollen and potentially increase occurrence of allergic airway disease. Understanding the spatiotemporal patterns of changes in pollen season timing and levels is thus important in assessing climate impacts on aerobiology and allergy caused by allergenic airborne pollen. Here, we describe the spatiotemporal patterns of changes in the seasonal timing and levels of allergenic airborne pollen for multiple taxa in different climate regions at a continental scale. The allergenic pollen seasons of representative trees, weeds and grass during the past decade (2001-2010) across the contiguous United States have been observed to start 3.0 [95% Confidence Interval (CI), 1.1-4.9] days earlier on average than in the 1990s (1994-2000). The average peak value and annual total of daily counted airborne pollen have increased by 42.4% (95% CI, 21.9-62.9%) and 46.0% (95% CI, 21.5-70.5%), respectively. Changes of pollen season timing and airborne levels depend on latitude, and are associated with changes of growing degree days, frost free days, and precipitation. These changes are likely due to recent climate change and particularly the enhanced warming and precipitation at higher latitudes in the contiguous United States.
| S-EPMC4356643 | biostudies-literature
Project description:BackgroundDespite the recent developments in physically and chemically based analysis of atmospheric particles, no models exist for resolving the spatial variability of pollen concentration at urban scale.ObjectivesWe developed a land use regression (LUR) approach for predicting spatial fine-scale allergenic pollen concentrations in the Helsinki metropolitan area, Finland, and evaluated the performance of the models against available empirical data.MethodsWe used grass pollen data monitored at 16 sites in an urban area during the peak pollen season and geospatial environmental data. The main statistical method was generalized linear model (GLM).ResultsGLM-based LURs explained 79% of the spatial variation in the grass pollen data based on all samples, and 47% of the variation when samples from two sites with very high concentrations were excluded. In model evaluation, prediction errors ranged from 6% to 26% of the observed range of grass pollen concentrations. Our findings support the use of geospatial data-based statistical models to predict the spatial variation of allergenic grass pollen concentrations at intra-urban scales. A remote sensing-based vegetation index was the strongest predictor of pollen concentrations for exposure assessments at local scales.ConclusionsThe LUR approach provides new opportunities to estimate the relations between environmental determinants and allergenic pollen concentration in human-modified environments at fine spatial scales. This approach could potentially be applied to estimate retrospectively pollen concentrations to be used for long-term exposure assessments.CitationHjort J, Hugg TT, Antikainen H, Rusanen J, Sofiev M, Kukkonen J, Jaakkola MS, Jaakkola JJ. 2016. Fine-scale exposure to allergenic pollen in the urban environment: evaluation of land use regression approach. Environ Health Perspect 124:619-626;?http://dx.doi.org/10.1289/ehp.1509761.
| S-EPMC4858385 | biostudies-literature
Project description:Pollen is a common allergen that causes significant health and financial impacts on up to a third of the population of the USA. Knowledge of the main pollen season can improve diagnosis and treatment of allergic diseases. Our objective in this study is to provide clear, quantitative visualizations of pollen data and make information accessible to many disciplines, in particular to allergy sufferers and those in the health field. We use data from 31 National Allergy Bureau (NAB) pollen stations in the continental USA and Canada from 2003 to 2017 to produce pollen calendars. We present pollen season metrics relevant to health and describe main pollen season start and end dates, durations, and annual pollen integrals for specific pollen taxa. In most locations, a small number of taxa constitute the bulk of the total pollen concentration. Start dates for tree and grass pollen season depend strongly on latitude, with earlier start dates at lower latitudes. Season duration is correlated with the start dates, such that locations with earlier start dates have a longer season. NAB pollen data have limited spatiotemporal coverage. Increased spatiotemporal monitoring will improve analysis and understanding of factors that govern airborne pollen concentrations.
| S-EPMC6934246 | biostudies-literature
Project description:Pollen is one of the most common causes of allergy worldwide, making the study of their molecular composition crucial for the advancement of allergy research. Despite substantial efforts in this field, it is not yet clear why some plant pollens strongly provoke allergies while others do not. However, proteases and protease inhibitors from allergen sources are known to play an important role in the development of pollen allergies. In this study, we aim to uncover differences in the transcriptional pattern of proteases and protease inhibitors in Betula verrucosa and Pinus sylvestris pollen as models for high and low allergenic potential, respectively. We applied RNA sequencing to Betula verrucosa and Pinus sylvestris pollen. After de-novo assembly we derived general functional profiles of the protein coding transcripts. By utilization of domain based functional annotation we identified potential proteases and protease inhibitors and compared their expression in the two types of pollen. Functional profiles are highly similar between Betula verrucosa and Pinus sylvestris pollen. Both pollen contain proteases and inhibitors from 53 and 7 Pfam families, respectively. Some of the members comprised within those families are implicated in facilitating allergen entry, while others are known allergens themselves. Our work revealed several candidate proteins which, with further investigation, represent exciting new leads in elucidating the process behind allergic sensitization.
| S-EPMC5486022 | biostudies-literature
Project description:Pollen allergies have been rapidly increasing over the last decades. Many allergenic proteins and non-allergenic adjuvant compounds of pollen are involved in the plant defense against environmental or microbial stress. The first aim of this study was to analyze and compare the colonizing microbes on allergenic pollen. The second aim was to investigate detectable correlations between pollen microbiota and parameters of air pollution or pollen allergenicity. To reach these aims, bacterial and fungal DNA was isolated from pollen samples of timothy grass (Phleum pratense, n = 20) and birch trees (Betula pendula, n = 55). With this isolated DNA, a terminal restriction fragment length polymorphism analysis was performed. One result was that the microbial diversity on birch tree and timothy grass pollen samples (Shannon/Simpson diversity indices) was partly significantly correlated to allergenicity parameters (Bet v 1/Phl p 5, pollen-associated lipid mediators). Furthermore, the microbial diversity on birch pollen samples was correlated to on-site air pollution (nitrogen dioxide (NO2), ammonia (NH3), and ozone (O3)). What is more, a significant negative correlation was observed between the microbial diversity on birch pollen and the measured NO2 concentrations on the corresponding trees. Our results showed that the microbial composition of pollen was correlated to environmental exposure parameters alongside with a differential expression of allergen and pollen-associated lipid mediators. This might translate into altered allergenicity of pollen due to environmental and microbial stress.
| S-EPMC4765992 | biostudies-literature
Project description:Estimates of airborne pollen concentrations at the urban scale would be useful for epidemiologists, land managers, and allergy sufferers. Mechanistic models could be well suited for this task, but their development will require data on pollen production across cities, including estimates of pollen production by individual trees. In this study, we developed predictive models for pollen production as a function of trunk size, canopy area, and height, which are commonly recorded in tree surveys or readily extracted from remote sensing data. Pollen production was estimated by measuring the number of flowers per tree, the number of anthers per flower, and the number of pollen grains per anther. Variability at each morphological scale was assessed using bootstrapping. Pollen production was estimated for the following species: Acer negundo, Acer platanoides, Acer rubrum, Acer saccharinum, Betula papyrifera, Gleditsia triacanthos, Juglans nigra, Morus alba, Platanus x acerfolia, Populus deltoides, Quercus palustris, Quercus rubra, and Ulmus americana. Basal area predicted pollen production with a mean R2 of 0.72 (range: 0.41 - 0.99), whereas canopy area predicted pollen production with a mean R2 of 0.76 (range: 0.50 - 0.99). These equations are applied to two tree datasets to estimate total municipal pollen production and the spatial distribution of street tree pollen production for the focal species. We present some of the first individual-tree based estimates of pollen production at the municipal scale; the observed spatial heterogeneity in pollen production is substantial and can feasibly be included in mechanistic models of airborne pollen at fine spatial scales.
| S-EPMC7748260 | biostudies-literature
Project description:This review summarizes the available data related to the effects of air pollution on pollen grains from different plant species. Several studies carried out either on in situ harvested pollen or on pollen exposed in different places more or less polluted are presented and discussed. The different experimental procedures used to monitor the impact of pollution on pollen grains and on various produced external or internal subparticles are listed. Physicochemical and biological effects of artificial pollution (gaseous and particulate) on pollen from different plants, in different laboratory conditions, are considered. The effects of polluted pollen grains, subparticles, and derived aeroallergens in animal models, in in vitro cell culture, on healthy human and allergic patients are described. Combined effects of atmospheric pollutants and pollen grains-derived biological material on allergic population are specifically discussed. Within the notion of "polluen," some methodological biases are underlined and research tracks in this field are proposed.
| S-EPMC4706970 | biostudies-other
Project description:Monitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.
| S-EPMC8166864 | biostudies-literature