Immunodominance in allergic T-cell reactivity to Japanese cedar in different geographic cohorts

Oseroff, Carla; Pham, John; Hinz, Denise; Sidney, John; Paul, Sinu; Greenbaum, Jason A.; Vita, Randi; Peters, Bjoern; Schulten, Véronique; Sette, Alessandro

doi:10.1016/j.anai.2016.10.014

Cited by 8 publications

(7 citation statements)

References 38 publications

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“…This set contained overlapping 15-mers spanning the CRJ1 and CRJ2 allergens ( 36 ). We selected 30 dominant epitopes based on average response magnitude of >100 SFC (sum of IL-5 and IFNγ) in either of two group of allergic donors: those who lived in Japan for extended periods of time and USA sensitized donors who had not lived in Japan.…”

Section: Methodsmentioning

confidence: 99%

Predicting HLA CD4 Immunogenicity in Human Populations

et al. 2018

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BackgroundPrediction of T cell immunogenicity is a topic of considerable interest, both in terms of basic understanding of the mechanisms of T cells responses and in terms of practical applications. HLA binding affinity is often used to predict T cell epitopes, since HLA binding affinity is a key requisite for human T cell immunogenicity. However, immunogenicity at the population it is complicated by the high level of variability of HLA molecules, potential other factors beyond HLA as well as the frequent lack of HLA typing data. To overcome those issues, we explored an alternative approach to identify the common characteristics able to distinguish immunogenic peptides from non-recognized peptides.MethodsSets of dominant epitopes derived from peer-reviewed published papers were used in conjunction with negative peptides from the same experiments/donors to train neural networks and generate an “immunogenicity score.” We also compared the performance of the immunogenicity score with previously described method for immunogenicity prediction based on HLA class II binding at the population level.ResultsThe immunogenicity score was validated on a series of independent datasets derived from the published literature, representing 57 independent studies where immunogenicity in human populations was assessed by testing overlapping peptides spanning different antigens. Overall, these testing datasets corresponded to over 2,000 peptides and tested in over 1,600 different human donors. The 7-allele method prediction and the immunogenicity score were associated with similar performance [average area under the ROC curve (AUC) values of 0.703 and 0.702, respectively] while the combined methods reached an average AUC of 0.725. This increase in average AUC value is significant compared with the immunogenicity score (p = 0.0135) and a strong trend toward significance is observed when compared to the 7-allele method (p = 0.0938). The new immunogenicity score method is now freely available using CD4 T cell immunogenicity prediction tool on the Immune Epitope Database website ().ConclusionThe new immunogenicity score predicts CD4 T cell immunogenicity at the population level starting from protein sequences and with no need for HLA typing. Its efficacy has been validated in the context of different antigen sources, ethnicities, and disparate techniques for epitope identification.

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Section: Methodsmentioning

confidence: 99%

Predicting HLA CD4 Immunogenicity in Human Populations

et al. 2018

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“…The literature has shown the importance of Elispot for quickly detecting the immune response to allergens such as trees, grasses, fungi, weeds, dust mites, pollen, food, and dyes [ 134 , 135 , 136 , 137 ]. Particularly, regarding medication, the literature has shown the presence of immune responses against different classes of drugs in patients presenting Hypersensibility Syndrome, Drug Reaction with eosinophilia and systemic symptoms (DRESS syndrome) [ 138 ], Stevens-Johnson Syndrome [ 139 ] (Fu et al 2012) or similarly under the use of sulfasalazine [ 140 ], cephalosporine [ 141 ], amikacin [ 138 ], B-lactams [ 142 ], and allopurinol [ 143 ], among others.…”

Section: Elispot As An Important Tool In Vaccine Allergy and Advementioning

confidence: 99%

How Can Elispot Add Information to Improve Knowledge on Tropical Diseases?

Lima-Junior

Morgado

Conceição-Silva

2017

Cells

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Elispot has been used as an important tool for detecting immune cells’ products and functions and has facilitated the understanding of host-pathogen interaction. Despite the incredible diversity of possibilities, two main approaches have been developed: the immunopathogenesis and diagnosis/prognosis of infectious diseases as well as cancer research. Much has been described on the topics of allergy, autoimmune diseases, and HIV-Aids, however, Elispot can also be applied to other infectious diseases, mainly leishmaniasis, malaria, some viruses, helminths and mycosis usually classified as tropical diseases. The comprehension of the function, concentration and diversity of the immune response in the infectious disease is pointed out as crucial to the development of infection or disease in humans and animals. In this review we will describe the knowledge already obtained using Elispot as a method for accessing the profile of immune response as well as the recent advances in information about host-pathogen interaction in order to better understand the clinical outcome of a group of tropical and neglected diseases.

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“…Although allergic rhinitis is not a life-threatening disease, its main symptoms—sneezing, nasal discharge (watery), and nasal obstruction—significantly impair the quality of life (QOL) of patients, causing a major social problem [ 15 - 17 ]. According to the practical guideline for the management of allergic rhinitis in Japan 2020 [ 18 ], approximately 40% of people in Japan said they had allergic rhinitis, of which 30% had nasal allergies caused by pollen.…”

Section: Introductionmentioning

confidence: 99%

Exploring Relationships Between Tweet Numbers and Over-the-counter Drug Sales for Allergic Rhinitis: Retrospective Analysis

Wakamiya¹,

Morimoto²,

Omichi³

et al. 2022

JMIR Form Res

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Background Health-related social media data are increasingly being used in disease surveillance studies. In particular, surveillance of infectious diseases such as influenza has demonstrated high correlations between the number of social media posts mentioning the disease and the number of patients who went to the hospital and were diagnosed with the disease. However, the prevalence of some diseases, such as allergic rhinitis, cannot be estimated based on the number of patients alone. Specifically, individuals with allergic rhinitis typically self-medicate by taking over-the-counter (OTC) medications without going to the hospital. Although allergic rhinitis is not a life-threatening disease, it represents a major social problem because it reduces people’s quality of life, making it essential to understand its prevalence and people’s motives for self-medication behavior. Objective This study aims to explore the relationship between the number of social media posts mentioning the main symptoms of allergic rhinitis and the sales volume of OTC rhinitis medications in Japan. Methods We collected tweets over 4 years (from 2017 to 2020) that included keywords corresponding to the main nasal symptoms of allergic rhinitis: “sneezing,” “runny nose,” and “stuffy nose.” We also obtained the sales volume of OTC drugs, including oral medications and nasal sprays, for the same period. We then calculated the Pearson correlation coefficient between time series data on the number of tweets per week and time series data on the sales volume of OTC drugs per week. Results The results showed a much higher correlation (r=0.8432) between the time series data on the number of tweets mentioning “stuffy nose” and the time series data on the sales volume of nasal sprays than for the other two symptoms. There was also a high correlation (r=0.9317) between the seasonal components of these time series data. Conclusions We investigated the relationships between social media data and behavioral patterns, such as OTC drug sales volume. Exploring these relationships can help us understand the prevalence of allergic rhinitis and the motives for self-care treatment using social media data, which would be useful as a marketing indicator to reduce the number of out-of-stocks in stores, provide (sell) rhinitis medicines to consumers in a stable manner, and reduce the loss of sales opportunities. In the future, in-depth investigations are required to estimate sales volume using social media data, and future research could investigate other diseases and countries.

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Immunodominance in allergic T-cell reactivity to Japanese cedar in different geographic cohorts

Cited by 8 publications

References 38 publications

Predicting HLA CD4 Immunogenicity in Human Populations

Predicting HLA CD4 Immunogenicity in Human Populations

How Can Elispot Add Information to Improve Knowledge on Tropical Diseases?

Exploring Relationships Between Tweet Numbers and Over-the-counter Drug Sales for Allergic Rhinitis: Retrospective Analysis

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