Tackling the enemy of allergies

A novel method for rapid pollen characterisation in allergic disease research

ALLERGIC diseases are now the most frequent reason for patients to seek medical care1. Worldwide, it is estimated that more than 500 million people have allergic rhinitis, and over 300 million are affected by asthma2.

Although linked to differences in affluence and lifestyle, exact causal factors of the increase in allergic disease remain uncertain. This article focuses on allergies to pollen and examines a novel analytical method (Morphologi G3, Malvern Instruments) that is contributing to pollen characterisation, essential both in fundamental research and to ensure the integrity of starting materials for immunotherapy and diagnostic products.

Allergies occur when common environmental substances, which normally present no health risk, trigger allergen-specific immunoglobulin E (IgE) production. Many developed countries have seen an epidemic rise in allergic disease, particularly over the last four decades. The reasons for this increase are unclear, but hypotheses include: increased pollution; a consequence of improved hygiene standards; or a side effect of success in the fight against infectious disease. Climate change may also be playing a role, causing subtle changes to the extent of plant species and modifying pollen production.

Patients with asthma and allergic rhinitis have a reduced quality of life and, in terms of disability-adjusted life-years, asthma is 22nd among diseases worldwide3. Furthermore, the financial cost associated with allergic disease is immense. For example, one estimate of the cost of rhinitis to the US economy is around $7.9 billion per year, which includes a substantial proportion of indirect costs such as lost productivity4.

Pollen-induced rhinitis is the most characteristic IgE-mediated allergic disease2. Treatment is helped by effective diagnostic testing to identify the allergen concerned. Many trees and plants produce pollens known to cause allergic reactions, including for example ryegrass, nettle, birch and willow. Following diagnosis, the next steps are to examine the feasibility of allergen avoidance and consider the use of drugs to alleviate allergic symptoms.

Figure 1: CE diameter distribution for the three pollen samples on a volume basis

Immunotherapy is an increasingly popular method for the treatment of certain types of allergic disease. The technique has been shown to work well for grass pollen allergies. A patient undergoing immunotherapy receives progressively larger doses of an allergen. This controlled exposure allows the body to gradually build tolerance to an allergen and reduces the strength of the associated IgE response.

The clinical efficacy of allergy diagnostic products is highly dependent on the composition of the active allergen source material chosen. Therefore, it is important to effectively characterise source material during the manufacturing process. Traditionally, manual microscopy methods have been used to control the purity of products and to identify foreign particles such as spores and unwanted pollen types.

Figure 2: HS circularity distribution for the three samples

Immunotherapy in particular is more effective when specific allergens have been isolated. Treatment of patients with multiple sensitivities with mixtures of unrelated allergens is less effective, thus only proven mixtures containing known amounts of each component should be used5,6. Furthermore, the possibility of triggering adverse reactions may be increased with inappropriate allergen dosage.

The importance of purified international standards for allergens was underlined in a recent report by the European Union’s CREATE consortium, which comprised 28 organisations from nine European countries, including research laboratories, clinical research groups, allergen manufacturers and biotech companies7. The CREATE project compared purified natural and recombinant allergens and analyzed the IgE reactivity, providing a major step forward in allergen standardisation.

The following section focuses on a novel method for the fully automated characterisation of pollen. This technique offers major advantages over conventional microscopy approaches for obtaining pure pollen samples.

Figure 3: Convexity distribution for the three samples

Materials and method
Three pollen types were analysed, two from single species Parietaria Judaica (PJ) and Avena Fatua (AF); and the third containing a mixture of Taraxacum Officinale and Chrysanthemum Leucanthemum (TF and CL).

An automated particle characterisation system (Morphologi G3, Malvern Instruments) was used to analyse the samples. Pollen samples were dry dispersed using the integrated Sample Dispersion Unit via an instantaneous pulse of compressed air, and measured using Standard Operating Procedures (SOPs) which define the instrument’s software and hardware settings. Measurements were made in an enclosed sample carrier, minimising environmental exposure.

The analysis generated high quality images from thousands of particles. Filters were applied to all analyses to remove images with a low pixel area (and therefore limited shape information) and also images of touching particles. Three repeat measurements were performed on each sample.

Figure 4: Elongation distribution for the three samples

To ensure data integrity the image analysis system automatically calibrates before and after every particle analysis using a multi-pitch grating traceable to the National Physical Laboratory. The system also conforms to 21CFR part 11 requirements.

Results
The automated particle characterisation system records an image of every particle analysed. Example images from pollen samples and the resulting size distributions of the three different pollen sample types in terms of Circular Equivalent (CE) diameter on a number basis are shown in Figure 1.

Figures 2, 3 and 4 show the shape distributions for the same samples in terms of High Sensitivity (HS) circularity (Figure 2); convexity - a measure of surface roughness (Figure 3); and elongation, a measure of overall form (Figure 4).

Discussion
Comparison of results shows that differences in size and shape are apparent between the three pollen samples. The images indicate that in terms of CE diameter, sample AF is the largest and PJ is the smallest, while the mixed sample is bi-modal.

AF is the most circular of the three samples. The mixed sample presents much lower circularity than the other two and is also bi-modal in terms of the distribution.

In terms of convexity, samples PJ and AV are very similar with high convexity and thus have relatively smooth edges. The mixed sample has much lower convexity, indicating that the particles have rougher edges.

Sample PJ shows the highest elongation, while the mixed sample shows the lowest. This means that the mixed sample particles have a length that is similar to their width.

A scatter plot for the results of the three repeat measurements for each sample, comparing mean CD diameter against mean HS circularity, showed that the three measurements for each sample type cluster together well. This type of plot allows the subsequent assessment of unknown pollen samples by comparison with the clusters on the graph, potentially enabling identification. In addition, post-measurement classifications were applied to the mixed sample results to distinguish the proportions of the different particle types in the samples, with particle images being described as either ‘spiky’ or ‘spherical’.

Advancing knowledge in the field of allergic diseases is vitally important in order to address this growing public health issue. As such, methods that allow rapid, highly detailed and reliable characterisation of allergens will prove invaluable.

The data presented here demonstrate that an automated particle characterisation system allows the rapid characterisation of pollen samples in terms of size and shape. The results enable distinction between different types of pollen and, along with the particle images, allow samples to be checked to ensure that only the desired pollen type is present. Mixed samples can be further characterized to determine the proportion of each pollen type present.

The automated particle characterisation system combines high quality imaging with statistically significant particle shape and particle size measurements. Hundreds of thousands of particles can be analysed rapidly, with little or no user intervention, delivering results with statistical significance and saving substantial amounts of time and labour compared to conventional manual microscopy techniques.