Expression quantitative trait methylation analysis reveals methylomic associations with gene expression in childhood asthma

Nasal airway epithelial methylation profiles have been associated with asthma, but the effects of such profiles on expression of distant cis-genes are largely unknown. We identified 16,867 significant methylation-gene expression pairs in nasal epithelium from Puerto Rican children and adolescents (with and without asthma) in an expression quantitative trait methylation (eQTM) analysis of cis-genes located within 1 Mb of the methylation probes tested. Most eQTM methylation probes were distant from their target genes, and more likely located in enhancer regions of their target genes in lung tissue than control probes. The top 500 eQTM genes were enriched in pathways for immune processes and epithelial integrity, and also more likely to be differentially expressed in atopic asthma. Moreover, we identified 5,934 paths through which methylation probes could affect atopic asthma through gene expression. Our findings suggest that distant epigenetic regulation of gene expression in airway epithelium plays a role in atopic asthma.

[1]  X. Cui,et al.  Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer , 2020, Scientific Reports.

[2]  D. Weeks,et al.  Transcriptome-wide and differential expression network analyses of childhood asthma in nasal epithelium. , 2020, The Journal of allergy and clinical immunology.

[3]  G. Canino,et al.  SNPs identified by GWAS affect asthma risk through DNA methylation and expression of cis-genes in airway epithelium , 2019, European Respiratory Journal.

[4]  Ivana V. Yang,et al.  Epigenome-wide meta-analysis of DNA methylation and childhood asthma. , 2019, The Journal of allergy and clinical immunology.

[5]  D. Weeks,et al.  DNA methylation in nasal epithelium, atopy, and atopic asthma in children: a genome-wide study. , 2019, The Lancet. Respiratory medicine.

[6]  X. Cui,et al.  Leveraging collective regulatory effects of long-range DNA methylations to predict gene expressions and estimate their effects on phenotypes in cancer , 2018, bioRxiv.

[7]  J. Vonk,et al.  From blood to lung tissue: effect of cigarette smoke on DNA methylation and lung function , 2018, Respiratory Research.

[8]  Lauren S. Mogil,et al.  Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function , 2018, Nature Communications.

[9]  F. Piferrer,et al.  Consistent inverse correlation between DNA methylation of the first intron and gene expression across tissues and species , 2018, Epigenetics & Chromatin.

[10]  Ching Ngar Wong,et al.  MICMIC: identification of DNA methylation of distal regulatory regions with causal effects on tumorigenesis , 2018, Genome Biology.

[11]  F. Grassmann,et al.  A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver , 2018, Scientific Reports.

[12]  V. Rakyan,et al.  DNA methylation profiles between airway epithelium and proxy tissues in children , 2017, Acta paediatrica.

[13]  Manuel A. R. Ferreira,et al.  Multiancestry association study identifies new asthma risk loci that colocalize with immune cell enhancer marks , 2017, Nature Genetics.

[14]  D. Posthuma,et al.  Functional mapping and annotation of genetic associations with FUMA , 2017, Nature Communications.

[15]  Limsoon Wong,et al.  Why Batch Effects Matter in Omics Data, and How to Avoid Them. , 2017, Trends in biotechnology.

[16]  Brent S. Pedersen,et al.  The nasal methylome and childhood atopic asthma , 2017, The Journal of allergy and clinical immunology.

[17]  Bing He,et al.  EnhancerAtlas: a resource for enhancer annotation and analysis in 105 human cell/tissue types , 2016, Bioinform..

[18]  Yuping Zhang,et al.  Targeted inhibition of GATA-6 attenuates airway inflammation and remodeling by regulating caveolin-1 through TLR2/MyD88/NF-κB in murine model of asthma. , 2016, Molecular immunology.

[19]  J. Taipale,et al.  The role of enhancers in cancer , 2016, Nature Reviews Cancer.

[20]  Geir Kjetil Sandve,et al.  In the loop: promoter–enhancer interactions and bioinformatics , 2015, Briefings Bioinform..

[21]  Lixin Liu,et al.  Leukocyte-specific protein 1 regulates neutrophil recruitment in acute lung inflammation. , 2015, American journal of physiology. Lung cellular and molecular physiology.

[22]  E. Hovig,et al.  Methods that remove batch effects while retaining group differences may lead to exaggerated confidence in downstream analyses , 2015, Biostatistics.

[23]  E. Dermitzakis,et al.  Tissue-Specific Effects of Genetic and Epigenetic Variation on Gene Regulation and Splicing , 2015, PLoS genetics.

[24]  Sukjoon Yoon,et al.  Somatic Mutaome Profile in Human Cancer Tissues , 2013, Genomics & informatics.

[25]  John M. Greally,et al.  Differential epigenome-wide DNA methylation patterns in childhood obesity-associated asthma , 2013, Scientific Reports.

[26]  E. Dermitzakis,et al.  Passive and active DNA methylation and the interplay with genetic variation in gene regulation , 2013, eLife.

[27]  W. Teague,et al.  ALOX5 Polymorphism associates with increased leukotriene production and reduced lung function and asthma control in children with poorly controlled asthma , 2013, Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology.

[28]  O. Boucherat,et al.  The loss of Hoxa5 function promotes Notch-dependent goblet cell metaplasia in lung airways , 2012, Biology Open.

[29]  Andrew E. Jaffe,et al.  Bioinformatics Applications Note Gene Expression the Sva Package for Removing Batch Effects and Other Unwanted Variation in High-throughput Experiments , 2022 .

[30]  A. Litonjua,et al.  A polymorphism in the thyroid hormone receptor gene is associated with bronchodilator response in asthmatics , 2011, The Pharmacogenomics Journal.

[31]  Andrey A. Shabalin,et al.  Matrix eQTL: ultra fast eQTL analysis via large matrix operations , 2011, Bioinform..

[32]  D. Zilberman,et al.  Genome-Wide Evolutionary Analysis of Eukaryotic DNA Methylation , 2010, Science.

[33]  I. Simon,et al.  DNA methylation and gene expression , 2010, Wiley interdisciplinary reviews. Systems biology and medicine.

[34]  Y. Nakagami,et al.  Distinct roles of FOXA2 and FOXA3 in allergic airway disease and asthma. , 2009, American journal of respiratory and critical care medicine.

[35]  A. Aghamohammadi,et al.  Association of HLA class II alleles with childhood asthma and Total IgE levels. , 2008, Iranian journal of allergy, asthma, and immunology.

[36]  Alexander E. Kel,et al.  MATCHTM: a tool for searching transcription factor binding sites in DNA sequences , 2003, Nucleic Acids Res..

[37]  A. Sousa,et al.  Glucocorticoid resistance in asthma is associated with elevated in vivo expression of the glucocorticoid receptor β-isoform , 2000 .

[38]  A. Razin,et al.  DNA methylation and gene expression , 1991, Microbiological reviews.

[39]  Holger Karas,et al.  TRANSFAC: a database on transcription factors and their DNA binding sites , 1996, Nucleic Acids Res..

[40]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[41]  M. Sobel.  Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .