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The nasal cellular epigenome may serve as biomarker of airway disease and environmental response. Here we collect nasal swabs from the anterior nares of 547 children (mean-age 12.9 y), and measure DNA methylation (DNAm) with the Infinium MethylationEPIC BeadChip. We perform nasal Epigenome-Wide Association analyses (EWAS) of current asthma, allergen sensitization, allergic rhinitis, fractional exhaled nitric oxide (FeNO) and lung function. We find multiple differentially methylated CpGs (FDR < 0.05) and Regions (DMRs; ≥ 5-CpGs and FDR < 0.05) for asthma (285-CpGs), FeNO (8,372-CpGs; 191-DMRs), total IgE (3-CpGs; 3-DMRs), environment IgE (17-CpGs; 4-DMRs), allergic asthma (1,235-CpGs; 7-DMRs) and bronchodilator response (130-CpGs). Discovered DMRs annotated to genes implicated in allergic asthma, Th2 activation and eosinophilia ( EPX , IL4, IL13 ) and genes previously associated with asthma and IgE in EWAS of blood ( ACOT7, SLC25A25 ). Asthma, IgE and FeNO were associated with nasal epigenetic age acceleration. The nasal epigenome is a sensitive biomarker of asthma, allergy and airway inflammation. Epigenetic differences in nasal epithelium have been proposed as a biomarker for lower airway disease and asthma. Here, in epigenome-wide association studies for asthma and other airway traits using nasal swabs, the authors identify differentially methylated CpGs that highlight genes involved in T H 2 response.

While genome-wide association studies have identified genes involved in differential treatment responses to inhaled corticosteroids (ICS) in asthma, few studies have evaluated the potential effects of age in this context. A significant proportion of asthmatics experience exacerbations (hospitalizations and emergency department visits) during ICS treatment. We evaluated the interaction of genetic variation and age on ICS response (measured by the occurrence of exacerbations) through a genome-wide interaction study (GWIS) of 1,321 adult and child asthmatic patients of European ancestry. We identified 107 genome-wide suggestive (P<10-05) age-by-genotype interactions, two of which also met genome-wide significance (P<5x10-08) (rs34631960 [OR 2.3±1.6-3.3] in thrombospondin type 1 domain-containing protein 4 (THSD4) and rs2328386 [OR 0.5±0.3-0.7] in human immunodeficiency virus type I enhancer binding protein 2 (HIVEP2)) by joint analysis of GWIS results from discovery and replication populations. In addition to THSD4 and HIVEP2, age-by-genotype interactions also prioritized genes previously identified as asthma candidate genes, including DPP10, HDAC9, TBXAS1, FBXL7, and GSDMB/ORMDL3, as pharmacogenomic loci as well. This study is the first to link these genes to a pharmacogenetic trait for asthma.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to the global coronavirus disease 2019 (COVID-19) pandemic. SARS-CoV-2 enters cells via angiotensin-Converting Enzyme 2 (ACE2) receptors, highly expressed in nasal epithelium with parallel high infectivity. 1,2 The nasal epigenome is in direct contact with the environment and could explain COVID-19 disparities by reflecting social and environmental influences on ACE2 regulation. We collected nasal swabs from anterior nares of 547 children, measured DNA methylation (DNAm), and tested differences at 15 ACE2 CpGs by sex, age, race/ethnicity and epigenetic age. ACE2 CpGs were differentially methylated by sex with 12 sites having lower DNAm (mean = 12.71%) and 3 sites greater DNAm (mean = 1.45%) among females relative to males. We observed differential DNAm at 5 CpGs for Hispanic females (mean absolute difference = 3.22%) and lower DNAm at 8 CpGs for Black males (mean absolute difference = 1.33%), relative to white participants. Longer DNAm telomere length was associated with greater ACE2 DNAm at 11 and 13 CpGs among males (mean absolute difference = 7.86%) and females (mean absolute difference = 8.21%), respectively. Nasal ACE2 DNAm differences could contribute to our understanding COVID-19 severity and disparities reflecting upstream environmental and social influences. Findings need to be confirmed among adults and patients with risk factors for COVID-19 severity.

Variability in response to short-acting β 2 -agonists (e.g., albuterol) among patients with asthma from diverse racial/ethnic groups may contribute to asthma disparities. We sought to identify genetic variants associated with bronchodilator response (BDR) to identify potential mechanisms of drug response and risk factors for worse asthma outcomes. Genome-wide association studies of bronchodilator response (BDR) were performed using TOPMed Whole Genome Sequencing data of the Asthma Translational Genomic Collaboration (ATGC), which corresponded to 1136 Puerto Rican, 656 Mexican and 4337 African American patients with asthma. With the population-specific GWAS results, a trans-ethnic meta-analysis was performed to identify BDR-associated variants shared across the three populations. Replication analysis was carried out in three pediatric asthma cohorts, including CAMP (Childhood Asthma Management Program; n = 560), GACRS (Genetics of Asthma in Costa Rica Study; n = 967) and HPR (Hartford-Puerto Rico; n = 417). A genome-wide significant locus (rs35661809; P  = 3.61 × 10 –8 ) in LINC02220 , a non-coding RNA gene, was identified in Puerto Ricans. While this region was devoid of protein-coding genes, capture Hi-C data showed a distal interaction with the promoter of the DNAH5 gene in lung tissue. In replication analysis, the GACRS cohort yielded a nominal association (1-tailed P  < 0.05). No genetic variant was associated with BDR at the genome-wide significant threshold in Mexicans and African Americans. Our findings help inform genetic underpinnings of BDR for understudied minority patients with asthma, but the limited availability of genetic data for racial/ethnic minority children with asthma remains a paramount challenge.

Prenatal exposures may be critical for immune system development, with consequences for allergic disease susceptibility. We examined associations of prenatal exposures (nutrient intakes and air pollutants) with allergic disease biomarkers in adolescence. We used data from 857 mother-child pairs in Project Viva, a Massachusetts-based pre-birth cohort. Outcomes of interest at follow-up (median age 12.9 years) were fractional exhaled nitric oxide (FeNO) and total serum IgE. We applied Bayesian Kernel Machine Regression analyses to estimate multivariate exposure-response functions, allowing for exposure interactions. Exposures were expressed as z-scores of log-transformed data and we report effects in % change in FeNO or IgE z-score per increase in exposure from the 25 th to 75 th percentile. FeNO levels were lower with higher intakes of prenatal vitamin D (−16.15%, 95% CI: −20.38 to −2.88%), folate from foods (−3.86%, 95% CI: −8.33 to 0.83%) and n-3 PUFAs (−9.21%, 95% CI −16.81 to −0.92%). Prenatal air pollutants were associated with higher FeNO and IgE, with the strongest associations detected for PM 2.5 with IgE (25.6% increase, 95% CI 9.34% to 44.29%). We identified a potential synergistic interaction (p = 0.02) between vitamin E (food + supplements) and PM 2.5 ; this exposure combination was associated with further increases in FeNO levels.

Background Global gene expression levels are known to be highly dependent upon gross demographic features including age, yet identification of age-related genomic indicators has yet to be comprehensively undertaken in a disease and treatment-specific context. Methods We used gene expression data from CD4+ lymphocytes in the Asthma BioRepository for Integrative Genomic Exploration (Asthma BRIDGE), an open-access collection of subjects participating in genetic studies of asthma with available gene expression data. Replication population participants were Puerto Rico islanders recruited as part of the ongoing Genes environments & Admixture in Latino Americans (GALA II), who provided nasal brushings for transcript sequencing. The main outcome measure was chronic asthma control as derived by questionnaires. Genomic associations were performed using regression of chronic asthma control score on gene expression with age in years as a covariate, including a multiplicative interaction term for gene expression times age. Results The SMARCD1 gene (SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily D member 1) interacted with age to influence chronic asthma control on inhaled corticosteroids, with a doubling of expression leading to an increase of 1.3 units of chronic asthma control per year (95% CI [0.86, 1.74], p  = 6 × 10 − 9 ), suggesting worsening asthma control with increasing age. This result replicated in GALA II ( p  = 3.8 × 10 − 8 ). Cellular assays confirmed the role of SMARCD1 in glucocorticoid response in airway epithelial cells. Conclusion Focusing on age-dependent factors may help identify novel indicators of asthma medication response. Age appears to modulate the effect of SMARCD1 on asthma control with inhaled corticosteroids.

Short‐acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative “omics” approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC‐MS), ­ using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome‐wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over‐representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites—monoHETE_0863 and sphingosine‐1‐phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine‐related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.

Early growth is associated with future metabolic risk; however, little is known of the underlying biological pathways. In this prospective study of 249 boys and 227 girls, we sought to identify sex-specific metabolite profiles that mark the relationship between age and magnitude of the infancy body mass index (BMI) peak, and the childhood BMI rebound with a metabolic syndrome z-score (MetS z-score) during early adolescence (median age 12.8 years). Thirteen consensus metabolite networks were generated between male and female adolescents using weighted correlation network analysis. In girls, none of the networks were related to BMI milestones after false discovery rate (FDR) correction at 5%. In boys, age and/or magnitude of BMI at rebound were associated with three metabolite eigenvector (ME) networks comprising androgen hormones (ME7), lysophospholipids (ME8), and diacylglycerols (ME11) after FDR correction. These networks were also associated with MetS z-score in boys after accounting for age and race/ethnicity: ME7 (1.43 [95% CI: 0.52, 2.34] units higher MetS z-score per 1 unit of ME7), ME8 (−1.01 [95% CI: −1.96, −0.07]), and ME11 (2.88 [95% CI: 2.06, 3.70]). These findings suggest that alterations in sex steroid hormone and lipid metabolism are involved in the relationship of early growth with future metabolic risk in males.

The role of metabolism in modifying age-related differential responses to asthma medications is insufficiently understood. The objective of this study was to determine the role of the metabolome in modifying the effect of age on bronchodilator response (BDR) in individuals with asthma. We used longitudinal measures of BDR and plasma metabolomic profiling in 565 children with asthma from the Childhood Asthma Management Program (CAMP) to identify age by metabolite interactions on BDR. The mean ages at the three studied time-points across 16 years of follow-up in CAMP were 8.8, 12.8, and 16.8 years; the mean BDRs were 11%, 9% and 8%, respectively. Of 501 identified metabolites, 39 (7.8%) demonstrated a significant interaction with age on BDR (p-value < 0.05). We were able to validate two significant interactions in 320 children with asthma from the Genetics of Asthma in Costa Rica Study; 2-hydroxyglutarate, a compound involved in butanoate metabolism (interaction; CAMP: β = −0.004, p = 1.8 × 10−4; GACRS: β = −0.015, p = 0.018), and a cholesterol ester; CE C18:1 (CAMP: β = 0.005, p = 0.006; GACRS: β = 0.023, p = 0.041) Five additional metabolites had a p-value < 0.1 in GACRS, including Gammaminobutyric acid (GABA), C16:0 CE, C20:4 CE, C18.0 CE and ribothymidine. These findings suggest Cholesterol esters and GABA may modify the estimated effect of age on bronchodilator response.

Asthma is known to display different phenotypes across the life-course, suggesting that age related changes are particularly relevant to understanding asthma pathogenesis and remission. We have previously demonstrated that a lung function phenotype associated with asthma, bronchodilator response, is reduced with age, at rate of 0.24 percent per year. In this study, we interrogated the serum metabolome, to determine whether circulating metabolites mediate age-related changes in bronchodilator response (BDR) for individuals with asthma. We used data on 295 participants from the follow-up phase of the CAMP clinical trial (age 12.2-25.9 years; mean BDR of 8%, standard deviation 7%). Using a counterfactual framework, we analyzed over 500 pareto-scaled metabolites using mediation analysis to identify indirect effects of age through potential metabolite mediators. There was a significant indirect effect of age on BDR through 4 plasmalogens (C36:1 PC and related metabolites) (Indirect Effect Beta = -0.001, = 0.006). Our findings suggest that plasmalogens may contribute to age-related asthma phenotypes, and may also serve as potential pharmacologic targets for enhancement of lung function in individuals with asthma. This work uses data from the previous clinical trial of asthma, the Childhood Asthma Management Program (CAMP), registered at ClinicalTrials.gov, # NCT00000575.