Global Analysis of Methylation Profiles From High Resolution CpG Data

Genetic Epidemiology

Volumn 39, Issue 2, 2015, Pages 53-64

  Zhao, Ni ^a   Bell, Douglas A ^b   Maity, Arnab ^c   Staicu, Ana Maria ^c   Joubert, Bonnie R ^b   London, Stephanie J ^b   Wu, Michael C ^a  

^a Fred Hutchinson Cancer Research Center   (United States)

^b NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES   (United States)

^c NORTH CAROLINA STATE UNIVERSITY   (United States)

Author keywords

Density approximation; Epigenome wide association study; Global testing; Spline smoothing; Variance component testing

Indexed keywords

ALCOHOL ABUSE; ARTICLE; BLOOD SAMPLING; CONTROLLED STUDY; CPG ISLAND; DNA METHYLATION; ENVIRONMENTAL FACTOR; GENETIC ASSOCIATION; GENOME; GLOBAL CHANGE; HEPATITIS C VIRUS; HUMAN; LIVER CARCINOGENESIS; MAJOR CLINICAL STUDY; RHEUMATOID ARTHRITIS; ALCOHOLISM; BIOLOGICAL MODEL; CASE CONTROL STUDY; EPIGENETICS; GENETIC EPIGENESIS; GENETICS; HEPATITIS C; INTERNET; LONG INTERSPERSED REPEAT; SOFTWARE;

HEPATITIS C VIRUS;

ALCOHOLISM; ARTHRITIS, RHEUMATOID; CASE-CONTROL STUDIES; CPG ISLANDS; DNA METHYLATION; EPIGENESIS, GENETIC; EPIGENOMICS; GENOME; HEPATITIS C; HUMANS; INTERNET; LONG INTERSPERSED NUCLEOTIDE ELEMENTS; MODELS, GENETIC; SOFTWARE;

EID: 84921023434     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.21874     Document Type: Article

References (49)

1. Attar N. 2012. The allure of the epigenome. Genome Biol 13:419.
2. Beck S, Rakyan VK. 2008. The methylome: approaches for global DNA methylation profiling. Trends Genet 24(5):231-237.
3. Bellizzi D, D'Aquila P, Montesanto A, Corsonello A, Mari V, Mazzei B, Lattanzio F, Passarino G. 2012. Global DNA methylation in old subjects is correlated with frailty. Age (Dordr) 34(1):169-179.
4. Bibikova M, Barnes B, Tsan C, Ho V, Klotzle B, Le JM, Delano D, Zhang L, Schroth GP, Gunderson KL and others. 2011. High density DNA methylation array with single CpG site resolution. Genomics 98(4):288-295.
5. Bollati V, Baccarelli A, Hou L, Bonzini M, Fustinoni S, Cavallo D, Byun H-M, Jiang J, Marinelli B, Pesatori AC and others. 2007. Changes in DNA methylation patterns in subjects exposed to low-dose benzene. Cancer Res 67(3):876-880.
6. Brothman AR, Swanson G, Maxwell TM, Cui J, Murphy KJ, Herrick J, Speights VO, Isaac J, Rohr LR. 2005. Global hypomethylation is common in prostate cancer cells: a quantitative predictor for clinical outcome? Cancer Genet Cytogenet 156(1):31-36.
7. Cai T, Tonini G, Lin X. 2011. Kernel machine approach to testing the significance of multiple genetic markers for risk prediction. Biometrics 67(3):975-986.
8. Chalitchagorn K, Shuangshoti S, Hourpai N, Kongruttanachok N, Tangkijvanich P, Thong-ngam D, Voravud N, Sriuranpong V, Mutirangura A. 2004. Distinctive pattern of line-1 methylation level in normal tissues and the association with carcinogenesis. Oncogene 23(54):8841-8846.
9. Davies RB. 1973. Numerical inversion of a characteristic function. Biometrika 60(2):415-417.
10. 2 random variables. J R Stat Soc Series C 29(3):323-333.
11. Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, Fuks F. 2011. Evaluation of the infinium methylation 450 k technology. Epigenomics 3(6):771-784.
12. Edgar R, Domrachev M, Lash AE. 2002. Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30(1):207-210.
13. Eng C, Herman JG, Baylin SB. 2000. A bird's eye view of global methylation. Nat Genet 24(2):101-102.
14. Figueiredo JC, Grau MV, Wallace K, Levine AJ, Shen L, Hamdan R, Chen X, Bresalier RS, McKeown-Eyssen G, Haile RW and others. 2009. Global DNA hypomethylation (line-1) in the normal colon and lifestyle characteristics and dietary and genetic factors. Cancer Epidemiol Biomarkers Prev 18(4):1041-1049.
15. Goeman JJ, Bühlmann P. 2007. Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics 23(8):980-987.
16. Goeman JJ, A Van De Geer S, De Kort F, Van Houwelingen HC. 2004. A global test for groups of genes: testing association with a clinical outcome. Bioinformatics 20(1):93-99.
17. Heyn H, Li N, Ferreira HJ, Moran S, Pisano DG, Gomez A, Diez J, Sanchez-Mut JV, Setien F, Carmona FJ and others. 2012. Distinct DNA methylomes of newborns and centenarians. Proc Nat Acad Sci 109(26):10522-10527.
18. Heyn H, Carmona FJ, Gomez A, Ferreira HJ, Bell JT, Sayols S, Ward K, Stefansson OA, Moran S, Sandoval J and others. 2013. DNA methylation profiling in breast cancer discordant identical twins identifies dok7 as novel epigenetic biomarker. Carcinogenesis 34(1):102-108.
19. Hlady R, Tiedemann R, Puszyk W, Zendejas I, Roberts L, Jeong-Hyeon C, Liu C, Robertson K. 2014. Epigenetic signatures of alcohol abuse and hepatitis infection during human hepatocarcinogenesis. Oncotarget 5(19):9425-9443.
20. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, Wiencke JK, Kelsey KT. 2012. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 13(1):86.
21. James R, Silverman BW. 2005. Functional Data Analysis. Wiley Online Library.
22. Joubert BR, Håberg SE, Nilsen RM, Wang X, Vollset SE, Murphy SK, Huang Z, Hoyo C, Øivind M, Cupul-Uicab LA and others. 2012. 450 k epigenome-wide scan identifies differential dna methylation in newborns related to maternal smoking during pregnancy. Environ Health Perspect 120: 1425-1431.
23. Kwee LC, Liu D, Lin X, Ghosh D, Epstein MP. 2008. A powerful and flexible multilocus association test for quantitative traits. Am J Hum Genet 82(2):386-397.
24. Laird PW. 2003. The power and the promise of DNA methylation markers. Nat Rev Cancer 3:253-266.
25. Lin X. 1997. Variance component testing in generalised linear models with random effects. Biometrika 84(2):309-326.
26. Lin X, Cai T, Wu MC, Zhou Q, Liu G, Christiani DC, Lin X. 2011. Kernel machine SNP-set analysis for censored survival outcomes in genome-wide association studies. Genet Epidemiol 35(7):620-631.
27. Lisanti S, Omar WA, Tomaszewski B, De Prins S, Jacobs G, Koppen G, Mathers JC, Langie SA. 2013. Comparison of methods for quantification of global DNA methylation in human cells and tissues. PLoS ONE 8(11):e79044.
28. Liu D, Lin X, Ghosh D. 2007. Semiparametric regression of multidimensional genetic pathway data: least-squares kernel machines and linear mixed models. Biometrics 63(4):1079-1088.
29. Liu D, Ghosh D, Lin X. 2008. Estimation and testing for the effect of a genetic pathway on a disease outcome using logistic kernel machine regression via logistic mixed models. BMC Bioinformatics 9(1):292.
30. Liu H, Tang Y, Zhang HH. 2009. A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables. Comput Stat Data Anal 53(4):853-856.
31. Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, Reinius L, Acevedo N, Taub M, Ronninger M and others. 2013. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol 31(2):142-147.
32. Maity A, Sullivan PF, Tzeng JY. 2012. Multivariate phenotype association analysis by marker-set kernel machine regression. Genet Epidemiol 36: 686-695.
33. Meissner A, Gnirke A, Bell GW, Ramsahoye B, Lander ES, Jaenisch R. 2005. Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res 33(18):5868-5877.
34. Nakano K, Whitaker JW, Boyle DL, Wang W, Firestein GS. 2013. DNA methylome signature in rheumatoid arthritis. Ann Rheum Dis 72(1):110-117.
35. Okada N, Hamada M, Ogiwara I, Ohshima K. 1997. Sines and lines share common 39 sequences: a review. Gene 205: 229-243.
36. Pierre D, Micheaux PLD. 2010. Computing the distribution of quadratic forms: further comparisons between the liu-tang-zhang approximation and exact methods. Comput Stat Data Anal 54(4):858-862.
37. Rakyan VK, Down TA, Balding DJ, Beck Stephan. 2011. Epigenome-wide association studies for common human diseases. Nat Rev Genet 12(8):529-541.
38. Rodić N, Burns KH. 2013. Long interspersed element-1 (LINE-1): passenger or driver in human neoplasms? PLoS Genet 9(3):e1003402.
39. Sandoval J, Heyn H, Moran S, Serra-Musach J, Pujana MA, Bibikova M, Esteller M. 2011. Validation of a DNA methylation microarray for 450, 000 CpG sites in the human genome. Epigenetics 6(6):692-702.
40. Sharma P, Kumar J, Garg G, Kumar A, Patowary A, Karthikeyan G, Ramakrishnan L, Brahmachari V, Shantanu S. 2008. Detection of altered global DNA methylation in coronary artery disease patients. DNA Cell Biol 27(7):357-365.
41. Shen J, Wang S, Yu-Jing Z, Hui-Chen Wu, Kibriya MG, Jasmine F, Ahsan H, Wu DPH, Siegel AB, Remotti H and others. 2013. Exploring genome-wide DNA methylation profiles altered in hepatocellular carcinoma using Infinium HumanMethylation 450 beadchips. Epigenetics 8(1):34-43.
42. Song L, James SR, Kazim L, Karpf AR. 2005. Specific method for the determination of genomic DNA methylation by liquid chromatography-electrospray ionization tandem mass spectrometry. Anal Chem 77(2):504-510.
43. Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, Beck S. 2013. A beta-mixture quantile normalization method for correcting probe design bias in illumina infinium 450 k DNA methylation data. Bioinformatics 29(2):189-196.
44. Wand R, Carroll RJ. 2003. Semiparametric Regression. Cambridge University Press, Cambridge.
45. Wei W, Gilbert N, Ooi SL, Lawler JF, Ostertag EM, Kazazian HH, Boeke JD, Moran JV. 2001. Human L1 retrotransposition: cis preference versus trans complementation. Mol Cell Biol 21(4):1429-1439.
46. Wu MC, Kraft P, Epstein MP, Taylor DM, Chanock SJ, Hunter DJ, Lin X. 2010. Powerful SNP-set analysis for case-control genome-wide association studies. Am J Hum Genet 86(6):929-942.
47. Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X. 2011. Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet 89(1):82-93.
48. Yang AS, Estécio MRH, Doshi K, Kondo Y, Tajara EH, Issa JP. 2004. A simple method for estimating global DNA methylation using bisulfite PCR of repetitive DNA elements. Nucleic Acids Res 32(3):e38.
49. Young-In K, Giuliano A, Hatch KD, Schneider A, Nour MA, Dallal GE, Selhub J, Mason JB. 2006. Global DNA hypomethylation increases progressively in cervical dysplasia and carcinoma. Cancer 74(3):893-899.