Lack of allergy to timothy grass pollen is not a passive phenomenon but associated with allergen specific modulation of immune reactivity - GSE70050

Timothy grass (TG) pollen is a common seasonal airborne allergen associated with symptoms ranging from mild rhinitis to severe asthma. The aim of this study was to characterize changes in TG-specific T cell responses as a function of seasonality. Peripheral blood mononuclear cells (PBMC) obtained either during the pollen season or out of season, from allergic individuals and non-allergic controls were stimulated either with TG extract or a pool of previously identified immunodominant antigenic regions. PBMC from in season allergic subjects exhibit higher IL-5 and IL-10 responses compared to out of season donors. In the case of non-allergic subjects, as expected we observed lower IL-5 responses and robust production of IFN? compared to allergic individuals. Strikingly, non-atopic donors exhibited an opposing pattern with decreased immune reactivity in-season. The broad downregulation in non-allergic donors indicates that healthy individuals are not oblivious to allergen exposure but rather react with an active modulation of the responses following the antigenic stimulus provided during the pollen season. Transcriptomic analysis of allergen-specific T cells defined genes modulated in concomitance with allergen exposure and inhibition of responses in non-allergic donors. Magnitude and functionality of T-helper cell responses differ substantially for in season versus out of season in allergic and non-allergic subjects. The results indicate specific and opposing modulation of immune responses following the antigenic stimulation during the pollen season. This seasonal modulation reflects the enactment of specific molecular programs associated with health and allergic disease.

11 allergen-specific T cell RNA samples were analyzed: 5 isolated from PBMC of allergic individuals and 6 from non-allergic individuals (considered as the control group).

Allergy

6 non-allergic individuals.

Illumina filteringAlignment with TopHatDUST scores were calculated with PRINSEQ Lite (v 0.20.3)Low-complexity reads (DUST > 4) were removed from the BAM filesGeneration of SAM files with SAMtoolsObtention of read counts with htseq-count using "union" optionRemoving absent features (zero counts in all samples)Raw counts were imported to R/Bioconductor package DESeq2 to identify differentially expressed genes among samplesDESeq2 normalizes counts by dividing each column of the count table (samples) by the size factor of this column. The size factor is calculated by dividing the samples by geometric means of the genes.P-values for differential expression are calculated using binomial test for differences between the base means of two conditions.These p-values are then adjusted for multiple test correction using Benjamini Hochberg algorithm to control the false discovery rate.We considered genes differentially expressed between two groups of samples when the DESeq2 analysis resulted in an adjusted P-value of <0.05 and the fold-change in gene expression was 2-fold.Genome_build: UCSC hg19

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70050