DNA methylation in lung cells is associated with asthma endotypes and genetic risk

JCI Insight

Volumn 1, Issue 20, 2016, Pages

  Nicodemus Johnson, Jessie ^a   Myers, Rachel A ^a   Sakabe, Noburu J ^a   Sobreira, Debora R ^a   Hogarth, Douglas K ^b   Naureckas, Edward T ^b   Sperling, Anne I ^b   Solway, Julian ^b   White, Steven R ^b   Nobrega, Marcelo A ^a   Nicolae, Dan L ^a,b,c   Gilad, Yoav ^a,b   Ober, Carole ^a  

^a UNIVERSITY OF CHICAGO   (United States)

^b UNIVERSITY OF CHICAGO   (United States)

^c University of Chicago   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85055604048     PISSN: None     EISSN: 23793708     Source Type: Journal    
DOI: 10.1172/jci.insight.90151     Document Type: Article

References (56)

1. Asthma Fact Sheet. World Health Organization. http://www.who.int/mediacentre/factsheets/fs307/en/. Accessed October 28, 2016.
2. Bisgaard H, Szefler S. Prevalence of asthma-like symptoms in young children. Pediatr Pulmonol. 2007;42(8):723–728.
3. Polderman TJ, et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet. 2015;47(7):702–709.
4. Wesolowska-Andersen A, Seibold MA. Airway molecular endotypes of asthma: dissecting the heterogeneity. Curr Opin Allergy Clin Immunol. 2015;15(2):163–168.
5. Bønnelykke K, Ober C. Leveraging gene-environment interactions and endotypes for asthma gene discovery. J Allergy Clin Immunol. 2016;137(3):667–679.
6. Ober C, Vercelli D. Gene-environment interactions in human disease: nuisance or opportunity? Trends Genet. 2011;27(3):107–115.
7. Furlong LI. Human diseases through the lens of network biology. Trends Genet. 2013;29(3):150–159.
8. Lovinsky-Desir S, Miller RL. Epigenetics, asthma, and allergic diseases: a review of the latest advancements. Curr Allergy Asthma Rep. 2012;12(3):211–220.
9. North ML, Ellis AK. The role of epigenetics in the developmental origins of allergic disease. Ann Allergy Asthma Immunol. 2011;106(5):355–61; quiz 362.
10. Liang L, et al. An epigenome-wide association study of total serum immunoglobulin E concentration. Nature. 2015;520(7549):670–674.
11. Smyth GK. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004;3:Article3.
12. Bell JT, et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 2011;12(1):R10.
13. Banovich NE, et al. Methylation QTLs are associated with coordinated changes in transcription factor binding, histone modifications, and gene expression levels. PLoS Genet. 2014;10(9):e1004663.
14. Shabalin AA. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics. 2012;28(10):1353–1358.
15. Flutre T, Wen X, Pritchard J, Stephens M. A statistical framework for joint eQTL analysis in multiple tissues. PLoS Genet. 2013;9(5):e1003486.
16. Torgerson DG, et al. Meta-analysis of genome-wide association studies of asthma in ethnically diverse North American populations. Nat Genet. 2011;43(9):887–892.
17. Moffatt MF, et al. A large-scale, consortium-based genomewide association study of asthma. N Engl J Med. 2010;363(13):1211–1221.
18. Nicolae DL, Gamazon E, Zhang W, Duan S, Dolan ME, Cox NJ. Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet. 2010;6(4):e1000888.
19. GTEx Consortium. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348(6235):648–660.
20. Zhang X, et al. Genetic associations with expression for genes implicated in GWAS studies for atherosclerotic cardiovascular disease and blood phenotypes. Hum Mol Genet. 2014;23(3):782–795.
21. Zhong H, et al. Liver and adipose expression associated SNPs are enriched for association to type 2 diabetes. PLoS Genet. 2010;6(5):e1000932.
22. Gamazon ER, et al. Enrichment of cis-regulatory gene expression SNPs and methylation quantitative trait loci among bipolar disorder susceptibility variants. Mol Psychiatry. 2013;18(3):340–346.
23. Calışkan M, et al. Rhinovirus wheezing illness and genetic risk of childhood-onset asthma. N Engl J Med. 2013;368(15):1398–1407.
24. Murphy A, et al. Mapping of numerous disease-associated expression polymorphisms in primary peripheral blood CD4+ lymphocytes. Hum Mol Genet. 2010;19(23):4745–4757.
25. Li X, et al. eQTL of bronchial epithelial cells and bronchial alveolar lavage deciphers GWAS-identified asthma genes. Allergy. 2015;70(10):1309–1318.
26. Smith GD. Mendelian Randomization for Strengthening Causal Inference in Observational Studies: Application to Gene × Environment Interactions. Perspect Psychol Sci. 2010;5(5):527–545.
27. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57–74.
28. Creyghton MP, et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc Natl Acad Sci USA. 2010;107(50):21931–21936.
29. Wang Z, et al. Combinatorial patterns of histone acetylations and methylations in the human genome. Nat Genet. 2008;40(7):897–903.
30. Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9:559.
31. Nicodemus-Johnson J, et al. Genome-Wide Methylation Study Identifies an IL-13-induced Epigenetic Signature in Asthmatic Airways. Am J Respir Crit Care Med. 2016;193(4):376–385.
32. Gagliardo R, et al. The role of transforming growth factor-β1 in airway inflammation of childhood asthma. Int J Immunopathol Pharmacol. 2013;26(3):725–738.
33. Makinde T, Murphy RF, Agrawal DK. Immunomodulatory role of vascular endothelial growth factor and angiopoietin-1 in airway remodeling. Curr Mol Med. 2006;6(8):831–841.
34. Michail S, Mezoff E, Abernathy F. Role of selectins in the intestinal epithelial migration of eosinophils. Pediatr Res. 2005;58(4):644–647.
35. Zheng S, et al. Impaired innate host defense causes susceptibility to respiratory virus infections in cystic fibrosis. Immunity. 2003;18(5):619–630.
36. Roadmap Epigenomics Consortium, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518(7539):317–330.
37. Nicodemus-Johnson J, et al. Maternal asthma and microRNA regulation of soluble HLA-G in the airway. J Allergy Clin Immunol. 2013;131(6):1496–1503.
38. Nicodemus-Johnson J, et al. Genome-Wide Methylation Study Identifies an IL-13-induced Epigenetic Signature in Asthmatic Airways. Am J Respir Crit Care Med. 2016;193(4):376–385.
39. Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, Fuks F. Evaluation of the Infinium Methylation 450K technology. Epigenomics. 2011;3(6):771–784.
40. Aryee MJ, et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics. 2014;30(10):1363–1369.
41. Maksimovic J, Gordon L, Oshlack A. SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips. Genome Biol. 2012;13(6):R44.
42. Lee KW, Pausova Z. Cigarette smoking and DNA methylation. Front Genet. 2013;4:132.
43. Li H. Exploring single-sample SNP and INDEL calling with whole-genome de novo assembly. Bioinformatics. 2012;28(14):1838–1844.
44. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–842.
45. Risso D, Ngai J, Speed TP, Dudoit S. Normalization of RNA-seq data using factor analysis of control genes or samples. Nat Biotechnol. 2014;32(9):896–902.
46. Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet Epidemiol. 2010;34(8):816–834.
47. Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nat Genet. 2012;44(8):955–959.
48. Zhang B, Horvath S. A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol. 2005;4:Article17.
49. Tandon A, Patterson N, Reich D. Ancestry informative marker panels for African Americans based on subsets of commercially available SNP arrays. Genet Epidemiol. 2011;35(1):80–83.
50. Hartung J, Knapp G. On tests of the overall treatment effect in meta-analysis with normally distributed responses. Stat Med. 2001;20(12):1771–1782.
51. Rao SS, et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell. 2014;159(7):1665–1680.
52. Battle A, et al. Genomic variation. Impact of regulatory variation from RNA to protein. Science. 2015;347(6222):664–667.
53. Gnirke A, et al. Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing. Nat Biotechnol. 2009;27(2):182–189.
54. Kent WJ, et al. The human genome browser at UCSC. Genome Res. 2002;12(6):996–1006.
55. Heinz S, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38(4):576–589.
56. O’Leary NA, et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 2016;44(D1):D733–D745.