Dataset Information

Nasal DNA methylation profiling of asthma and rhinitis.

ABSTRACT:

Background

Epigenetic signatures in the nasal epithelium, which is a primary interface with the environment and an accessible proxy for the bronchial epithelium, might provide insights into mechanisms of allergic disease.

Objective

We aimed to identify and interpret methylation signatures in nasal epithelial brushes associated with rhinitis and asthma.

Methods

Nasal epithelial brushes were obtained from 455 children at the 16-year follow-up of the Dutch Prevention and Incidence of Asthma and Mite Allergy birth cohort study. Epigenome-wide association studies were performed on children with asthma, rhinitis, and asthma and/or rhinitis (AsRh) by using logistic regression, and the top results were replicated in 2 independent cohorts of African American and Puerto Rican children. Significant CpG sites were related to environmental exposures (pets, active and passive smoking, and molds) during secondary school and were correlated with gene expression by RNA-sequencing (n = 244).

Results

The epigenome-wide association studies identified CpG sites significantly associated with rhinitis (n = 81) and AsRh (n = 75), but not with asthma. We significantly replicated 62 of 81 CpG sites with rhinitis and 60 of 75 with AsRh, as well as 1 CpG site with asthma. Methylation of cg03565274 was negatively associated with AsRh and positively associated with exposure to pets during secondary school. DNA methylation signals associated with AsRh were mainly driven by specific IgE-positive subjects. DNA methylation related to gene transcripts that were enriched for immune pathways and expressed in immune and epithelial cells. Nasal CpG sites performed well in predicting AsRh.

Conclusions

We identified replicable DNA methylation profiles of asthma and rhinitis in nasal brushes. Exposure to pets may affect nasal epithelial methylation in relation to asthma and rhinitis.

SUBMITTER: Qi C

PROVIDER: S-EPMC7282965 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Nasal DNA methylation profiling of asthma and rhinitis.

Qi Cancan C Jiang Yale Y Yang Ivana V IV Forno Erick E Wang Ting T Vonk Judith M JM Gehring Ulrike U Smit Henriëtte A HA Milanzi Edith B EB Carpaij Orestes A OA Berg Marijn M Hesse Laura L Brouwer Sharon S Cardwell Jonathan J Vermeulen Cornelis J CJ Acosta-Pérez Edna E Canino Glorisa G Boutaoui Nadia N van den Berge Maarten M Teichmann Sarah A SA Nawijn Martijn C MC Chen Wei W Celedón Juan C JC Xu Cheng-Jian CJ Koppelman Gerard H GH

The Journal of allergy and clinical immunology 20200114 6

<h4>Background</h4>Epigenetic signatures in the nasal epithelium, which is a primary interface with the environment and an accessible proxy for the bronchial epithelium, might provide insights into mechanisms of allergic disease.<h4>Objective</h4>We aimed to identify and interpret methylation signatures in nasal epithelial brushes associated with rhinitis and asthma.<h4>Methods</h4>Nasal epithelial brushes were obtained from 455 children at the 16-year follow-up of the Dutch Prevention and Incid ...[more]

PMID: 31953105

Similar Datasets

Project description:BackgroundNasal microbiota is crucial for the pathogenesis of allergic rhinitis (AR), which has been reported to be different from that of healthy individuals. However, no study has investigated the microbiota in nasal extracellular vesicles (EVs). We aimed to compare the microbiome composition and diversity in EVs between AR patients and healthy controls (HCs) and reveal the potential metabolic mechanisms in AR.MethodsEosinophil counts and serum immunoglobulin E (IgE) levels were measured in patients with AR (n = 20) and HCs (n = 19). Nasal EVs were identified using transmission electron microscopy and flow cytometry. 16S rRNA sequencing was used to profile the microbial communities. Alpha and beta diversities were analyzed to determine microbial diversity. Taxonomic abundance was analyzed based on the linear discriminant analysis effect size (LEfSe). Microbial metabolic pathways were characterized using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUst2) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses.ResultsEosinophils, total serum IgE, and IgE specific to Dermatophagoides were increased in patients with AR. Alpha diversity in nasal EVs from patients with AR was lower than that in HCs. Beta diversity showed microbiome differences between the AR and HCs groups. The microbial abundance was distinct between AR and HCs at different taxonomic levels. Significantly higher levels of the genera Acetobacter, Mycoplasma, Escherichia, and Halomonas were observed in AR patients than in HCs. Conversely, Zoogloea, Streptococcus, Burkholderia, and Pseudomonas were more abundant in the HCs group than in the AR group. Moreover, 35 microbial metabolic pathways recognized in AR patients and HCs, and 25 pathways were more abundant in the AR group.ConclusionPatients with AR had distinct microbiota characteristics in nasal EVs compared to that in HCs. The metabolic mechanisms of the microbiota that regulate AR development were also different. These findings show that nasal fluid may reflect the specific pattern of microbiome EVs in patients with AR.

Project description:BackgroundEpigenetic mechanisms could alter the airway epithelial barrier and ultimately lead to atopic diseases such as asthma. We aimed to identify DNA methylation profiles that are associated with-and could accurately classify-atopy and atopic asthma in school-aged children.MethodsWe did a genome-wide study of DNA methylation in nasal epithelium and atopy or atopic asthma in 483 Puerto Rican children aged 9-20 years, recruited using multistage probability sampling. Atopy was defined as at least one positive IgE (≥0·35 IU/mL) to common aeroallergens, and asthma was defined as a physician's diagnosis plus wheeze in the previous year. Significant (false discovery rate p<0·01) methylation signals were correlated with gene expression, and top CpGs were validated by pyrosequencing. We then replicated our top methylation findings in a cohort of 72 predominantly African American children, and in 432 children from a European birth cohort. Next, we tested classification models based on nasal methylation for atopy or atopic asthma in all cohorts.FindingsDNA methylation profiles were markedly different between children with (n=312) and without (n=171) atopy in the Puerto Rico discovery cohort, recruited from Feb 12, 2014, until May 8, 2017. After adjustment for covariates and multiple testing, we found 8664 differentially methylated CpGs by atopy, with false discovery rate-adjusted p values ranging from 9·58 × 10-17 to 2·18 × 10-22 for the top 30 CpGs. These CpGs were in or near genes relevant to epithelial barrier function, including CDHR3 and CDH26, and in other genes related to airway epithelial integrity and immune regulation, such as FBXL7, NTRK1, and SLC9A3. Moreover, 28 of the top 30 CpGs replicated in the same direction in both independent cohorts. Classification models of atopy based on nasal methylation performed well in the Puerto Rico cohort (area under the curve [AUC] 0·93-0·94 and accuracy 85-88%) and in both replication cohorts (AUC 0·74-0·92, accuracy 68-82%). The models also performed well for atopic asthma in the Puerto Rico cohort (AUC 0·95-1·00, accuracy 88%) and the replication cohorts (AUC 0·82-0·88, accuracy 86%).InterpretationWe identified specific methylation profiles in airway epithelium that are associated with atopy and atopic asthma in children, and a nasal methylation panel that could classify children by atopy or atopic asthma. Our findings support the feasibility of using the nasal methylome for future clinical applications, such as predicting the development of asthma among wheezing infants.FundingUS National Institutes of Health.

Project description:Perturbation of the microbiome has numerous associations with the phenotypes and progression in chronic airways disease. However, the differences in the nasal microbiome in asthma and allergic rhinitis (AR) have not been defined. We examined whether the nasal microbiome would vary among different comorbidities in asthma and AR and that those differences may be associated with the severity of asthma. Nasal lavage fluid was collected from 110 participants, including 20 healthy controls, 30 subjects with AR, 30 subjects with asthma and 30 subjects with combined asthma + AR. The Asthma Control Questionnaire (ACQ-7) was used to evaluate asthma control status. Using 16S rRNA bacterial gene sequencing, we analyzed nasal microbiome in patients with asthma, AR, combined asthma + AR, and healthy controls. Bacterial diversity was analyzed in corresponding with α diversity indices (Chao and Shannon index). Compared with healthy controls, the Chao index tended to be lower in subjects with AR (P = 0.001), asthma (P = 0.001), and combined asthma + AR (P = 0.001) when compared with healthy controls. Furthermore, the Shannon index was significantly lower in subjects with asthma (P = 0.013) and comorbid asthma with AR (P = 0.004) than the control subjects. Disparity in the structure and composition of nasal bacteria were also observed among the four groups. Furthermore, patients with combined asthma + AR and isolated asthma were divided into two groups according to the level of disease control: partially or well-controlled and uncontrolled asthma. The mean relative abundance observed in the groups mentioned the genera of Pseudoflavonifractor were dominated in patients with well and partially controlled disease, in both isolated asthma and combined asthma + AR. In subjects with uncontrolled asthma and combined asthma + AR, a lower evenness and richness (Shannon index, P = 0.040) was observed in nasal microbiome composition. Importantly, lower evenness and richness in the nasal microbiome may be associated with poor disease control in combined asthma + AR. This study showed the upper airway microbiome is associated with airway inflammation disorders and the level of asthma control.

Dataset Information

Nasal DNA methylation profiling of asthma and rhinitis.

Background

Objective

Methods

Results

Conclusions

Publications

Nasal DNA methylation profiling of asthma and rhinitis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets