Multiple factors interact to trigger allergic diseases, including individual genetic background and factors related to the environment such as exposure to allergens, air pollution and respiratory infections. The FOXP3 transcription factor is constitutively expressed in CD4+CD25+FOXP3+ regulatory T cells (Tregs) and is critical for the maintenance of immune homeostasis. For example, FOXP3 is responsible for the suppression of the Th2 response following exposure to allergens. Studies have shown that expression of the FOXP3 gene is reduced in patients with asthma and allergies compared to healthy controls. Therefore, the impairment of FOXP3 function caused by genetic polymorphisms and/or epigenetic mechanisms may be involved in the etiology of asthma and other allergic diseases. This review discusses some aspects of the role of FOXP3 in the development of asthma and allergy, with a particular emphasis on genetic and epigenetic factors.

Atopic asthma is a chronic inflammatory disease in airways resulting from genetic and environmental factors, characterized by production of the Th2 cytokines interleukin-4 (IL-4), interleukin-5 (IL-5) and interleukin-13 (IL-13). Interleukin-33 (IL-33) appears to be a potent inducer of Th2 immune response. This occurs when IL-33 binds and activates its receptor, the membrane ST2 (ST2L) in mast cells, dendritic cells, basophils, eosinophils, innate lymphoids and Th2 cells, leading to the release of these cytokines and intensifying allergic inflammation. Polymorphisms in the IL33 and IL1RL1 can act as protective or risk factors for asthma and/or allergy in humans. No study was conducted to replicate such findings in a European and African descendent mixed population. DNA was extracted from peripheral blood from 1223 subjects, and the samples were genotyped using Illumina 2.5 Human Omni Beadchip. We tested for possible associations between SNPs in the IL33 and ST2 with asthma and allergy markers such as specific IgE (sIgE), IL-5 and IL-13 production and skin prick test (SPT). Logistics regressions were performed using PLINK software 1.07. The analyses were adjusted for sex, age, helminth infection and ancestry markers. The G allele of IL33 SNP rs12551256 was negatively associated with asthma (OR 0.71, 95% CI: 0.53-0.94, P = 0.017). In contrast, the A allele of IL1RL1 rs1041973 was positively associated with IL-5 production (OR 1.36, 95% CI: 1.09-1.84, P = 0.044), sIgE levels (OR 1.40, 95% CI: 1.07-1.84, P = 0.013) and positive SPT (OR 1.48, 95% CI: 1.08-2.03, P = 0.014), for Blomia tropicalis mite. The same allele, in atopic subjects, was associated with decreased production of soluble ST2 (sST2) (P < 0.05). Moreover, expression quantitative trait loci (eQTL) analysis suggests that rs1041973 and rs873022 regulate the expression of IL1RL1 gene. This latest SNP, rs873022, the T allele, was also associated with a lower production of sST2 in plasma of Brazilians. The genetic risk score for rs1041973 and rs16924161 demonstrated a higher risk for SPT positivity against B. tropicalis, the greater the number of risk alleles for both SNPs. Our findings demonstrate a robust association of genetic variants in IL1RL1 and IL33 SNPs with allergy markers and asthma.

EPIGEN-Brazil is one of the largest Latin American initiatives at the interface of human genomics, public health, and computational biology. Here, we present two resources to address two challenges to the global dissemination of precision medicine and the development of the bioinformatics know-how to support it. To address the underrepresentation of non-European individuals in human genome diversity studies, we present the EPIGEN-5M+1KGP imputation panel-the fusion of the public 1000 Genomes Project (1KGP) Phase 3 imputation panel with haplotypes derived from the EPIGEN-5M data set (a product of the genotyping of 4.3 million SNPs in 265 admixed individuals from the EPIGEN-Brazil Initiative). When we imputed a target SNPs data set (6487 admixed individuals genotyped for 2.2 million SNPs from the EPIGEN-Brazil project) with the EPIGEN-5M+1KGP panel, we gained 140,452 more SNPs in total than when using the 1KGP Phase 3 panel alone and 788,873 additional high confidence SNPs ( ≥ 0.8). Thus, the major effect of the inclusion of the EPIGEN-5M data set in this new imputation panel is not only to gain more SNPs but also to improve the quality of imputation. To address the lack of transparency and reproducibility of bioinformatics protocols, we present a conceptual Scientific Workflow in the form of a website that models the scientific process (by including publications, flowcharts, masterscripts, documents, and bioinformatics protocols), making it accessible and interactive. Its applicability is shown in the context of the development of our EPIGEN-5M+1KGP imputation panel. The Scientific Workflow also serves as a repository of bioinformatics resources.