Erick Forno1, Ting Wang1, Cancan Qi2, Qi Yan1, Cheng-Jian Xu2, Nadia Boutaoui1, Yueh-Ying Han1, Daniel E Weeks3, Yale Jiang4, Franziska Rosser1, Judith M Vonk5, Sharon Brouwer6, Edna Acosta-Perez7, Angel Colón-Semidey8, María Alvarez8, Glorisa Canino7, Gerard H Koppelman2, Wei Chen1, Juan C Celedón9. 1. Division of Pulmonary Medicine, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, PA, USA; Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. 2. Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, Groningen, Netherlands; GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, Netherlands. 3. Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA. 4. Division of Pulmonary Medicine, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, PA, USA; Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; School of Medicine, Tsinghua University, Beijing, China. 5. GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, Netherlands; Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands. 6. GRIAC Research Institute, University of Groningen, University Medical Center Groningen, Groningen, Netherlands; Department of Pathology and Medical Biology, Experimental Pulmonology and Inflammation Research, University of Groningen, University Medical Center Groningen, Groningen, Netherlands. 7. Behavioral Sciences Research Institute of Puerto Rico, Medical Science Campus, University of Puerto Rico, San Juan, Puerto Rico. 8. Department of Pediatrics, Medical Science Campus, University of Puerto Rico, San Juan, Puerto Rico. 9. Division of Pulmonary Medicine, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, PA, USA; Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Electronic address: juan.celedon@chp.edu.
Abstract
BACKGROUND: Epigenetic 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. METHODS: We 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. FINDINGS: DNA 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%). INTERPRETATION: We 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. FUNDING: US National Institutes of Health.
BACKGROUND: Epigenetic 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. METHODS: We 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. FINDINGS: DNA 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%). INTERPRETATION: We 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 wheezinginfants. FUNDING: US National Institutes of Health.
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