WHO/IUIS Allergen Nomenclature: Providing a common language

A systematic nomenclature for allergens originated in the early 1980s, when few protein allergens had been described. A group of scientists led by Dr. David G. Marsh developed a nomenclature based on the Linnaean taxonomy, and further established the World Health Organization/International Union of Immunological Societies (WHO/IUIS) Allergen Nomenclature Sub-Committee in 1986. Its stated aim was to standardize the names given to the antigens (allergens) that caused IgE-mediated allergies in humans. The Sub-Committee first published a revised list of allergen names in 1986, which continued to grow with rare publications until 1994. Between 1994 and 2007 the database was a text table online, then converted to a more readily updated website. The allergen list became the Allergen Nomenclature database (www.allergen.org), which currently includes approximately 880 proteins from a wide variety of sources. The Sub-Committee includes experts on clinical and molecular allergology. They review submissions of allergen candidates, using evidence-based criteria developed by the Sub-Committee. The review process assesses the biochemical analysis and the proof of allergenicity submitted, and aims to assign allergen names prior to publication. The Sub-Committee maintains and revises the database, and addresses continuous challenges as new “omics” technologies provide increasing data about potential new allergens. Most journals publishing information on new allergens require an official allergen name, which involves submission of confidential data to the WHO/IUIS Allergen Nomenclature Sub-Committee, sufficient to demonstrate binding of IgE from allergic subjects to the purified protein

IgE Recognition Patterns of Profilin, PR-10, and Tropomyosin Panallergens Tested in 3,113 Allergic Patients by Allergen Microarray-Based Technology

BACKGROUND: IgE recognition of panallergens having highly conserved sequence regions, structure, and function and shared by inhalant and food allergen sources is often observed. METHODS: We evaluated the IgE recognition profile of profilins (Bet v 2, Cyn d 12, Hel a 2, Hev b 8, Mer a 1, Ole e 2, Par j 3, Phl p 12, Pho d 2), PR-10 proteins (Aln g 1, Api g 1, Bet v 1.0101, Bet v 1.0401, Cor a 1, Dau c 1 and Mal d 1.0108) and tropomyosins (Ani s 3, Der p 10, Hel as 1, Pen i 1, Pen m 1, Per a 7) using the Immuno-Solid phase Allergen Chip (ISAC) microarray system. The three panallergen groups were well represented among the allergenic molecules immobilized on the ISAC. Moreover, they are distributed in several taxonomical allergenic sources, either close or distant, and have a route of exposure being either inhalation or ingestion. RESULTS: 3,113 individuals (49.9% female) were selected on the basis of their reactivity to profilins, PR-10 or tropomyosins. 1,521 (48.8%) patients were reactive to profilins (77.6% Mer a 1 IgE(+)), 1,420 (45.6%) to PR-10 (92.5% Bet v 1 IgE(+)) and 632 (20.3%) to tropomyosins (68% Der p 10 IgE(+)). A significant direct relationship between different representative molecules within each group of panallergens was found. 2,688 patients (86.4%) recognized only one out of the three distinct groups of molecules as confirmed also by hierarchical clustering analysis. CONCLUSIONS: Unless exposed to most of the allergens in the same or related allergenic sources, a preferential IgE response to distinct panallergens has been recorded. Allergen microarray IgE testing increases our knowledge of the IgE immune response and related epidemiological features within and between homologous molecules better describing the patients' immunological phenotypes

The chlL ( frxC ) gene: Phylogenetic distribution in vascular plants and DNA sequence from Polystichum acrostichoides ( Pteridophyta ) and Synechococcus sp. 7002 ( Cyanobacteria )

We examined chlL ( frxC ) gene evolution using several approaches. Sequences from the chloroplast genome of the fern Polystichum acrostichoides and from the cyanobacterium Synechococcus sp. 7002 were determined and found to be highly conserved. A complete physical map of the fern chloroplast genome and partial maps of other vascular plant taxa show that chlL is located primarily in the small single copy region as in Marchantia polymorpha. A survey of a wide variety of non-angiospermous vascular plant DNAs shows that chlL is widely distributed but has been lost in the pteridophyte Psilotum and (presumably independently) within the Gnetalean gymnosperms.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41636/1/606_2004_Article_BF00994092.pd

A European-Japanese study on peach allergy: IgE to Pru p 7 associates with severity

Background: Pru p 3 and Pru p 7 have been implicated as risk factors for severe peach allergy. This study aimed to establish sensitization patterns to five peach components across Europe and in Japan, to explore their relation to pollen and foods and to predict symptom severity. Methods: In twelve European (EuroPrevall project) and one Japanese outpatient clinic, a standardized clinical evaluation was conducted in 1231 patients who reported symptoms to peach and/or were sensitized to peach. Specific IgE against Pru p 1, 2, 3, 4 and 7 and against Cup s 7 was measured in 474 of them. Univariable and multivariable Lasso regression was applied to identify combinations of parameters predicting severity. Results: Sensitization to Pru p 3 dominated in Southern Europe but was also quite common in Northern and Central Europe. Sensitization to Pru p 7 was low and variable in the European centers but very dominant in Japan. Severity could be predicted by a model combining age of onset of peach allergy, probable mugwort, Parietaria pollen and latex allergy, and sensitization to Japanese cedar pollen, Pru p 4 and Pru p 7 which resulted in an AUC of 0.73 (95% CI 0.73–0.74). Pru p 3 tended to be a risk factor in South Europe only. Conclusions: Pru p 7 was confirmed as a significant risk factor for severe peach allergy in Europe and Japan. Combining outcomes from clinical and demographic background with serology resulted in a model that could better predict severity than CRD alone