Interethnic DNA methylation difference and its implications in pharmacoepigenetics

Epigenomics

Volumn 9, Issue 11, 2017, Pages 1437-1454

  Chu, Shih Kai ^a,b,c   Yang, Hsin Chou ^a,b,c,d,e,f  

^a INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

^b INSTITUTE OF STATISTICAL SCIENCE   (Taiwan)

^c NATIONAL YANG MING UNIVERSITY   (Taiwan)

^d NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

^e NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^f NATIONAL DEFENSE MEDICAL CENTER   (Taiwan)

Author keywords

cancer epigenetics; DNA methylation; epipharmacogenomics; population differentiation

Indexed keywords

DNA; TRANSCRIPTOME; ANTINEOPLASTIC AGENT;

AFRICAN; ANCESTRY GROUP; ARTICLE; DNA METHYLATION; DRUG ABSORPTION; DRUG DISTRIBUTION; DRUG EXCRETION; DRUG METABOLISM; EPIGENETICS; ETHNIC GROUP; ETHNICITY; EUROPEAN; GENE CONTROL; HUMAN; LYMPHOBLASTOID CELL; LYMPHOBLASTOID CELL LINE; POPULATION DIFFERENTIATION; PRIMARY TUMOR; PRIORITY JOURNAL; SYSTEMATIC REVIEW; TREATMENT RESPONSE; BLACK PERSON; CAUCASIAN; CPG ISLAND; ETHNOLOGY; FEMALE; GENETIC EPIGENESIS; GENETICS; MALE; META ANALYSIS; METABOLIC CLEARANCE RATE; NEOPLASM; PHARMACOGENETICS; STANDARDS; TISSUE DISTRIBUTION; TUMOR CELL LINE;

AFRICAN CONTINENTAL ANCESTRY GROUP; ANTINEOPLASTIC AGENTS; CELL LINE, TUMOR; CPG ISLANDS; DNA METHYLATION; EPIGENESIS, GENETIC; EPIGENOMICS; EUROPEAN CONTINENTAL ANCESTRY GROUP; FEMALE; HUMANS; MALE; METABOLIC CLEARANCE RATE; NEOPLASMS; PHARMACOGENETICS; TISSUE DISTRIBUTION;

EID: 85032447890     PISSN: 17501911     EISSN: 1750192X     Source Type: Journal    
DOI: 10.2217/epi-2017-0046     Document Type: Article

References (76)

1. Portela A, Esteller M. Epigenetic modifications and human disease. Nat. Biotechnol. 28(10), 1057-1068 (2010).
2. Weber M, Schubeler D. Genomic patterns of DNA methylation: targets and function of an epigenetic mark. Curr. Opin. Cell Biol. 19(3), 273-280 (2007).
3. Lister R, Pelizzola M, Dowen RH et al. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462(7271), 315-322 (2009).
4. Jones PA. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat. Rev. Genet. 13(7), 484-492 (2012).
5. Lechner M, Boshoff C, Beck S. Cancer epigenome. Adv. Genet. 70, 247-276 (2010).
6. Gomez A, Ingelman-Sundberg M. Pharmacoepigenetics: its role in interindividual differences in drug response. Clin. Pharmacol. Ther. 85(4), 426-430 (2009).
7. Heyn H, Esteller M. DNA methylation profiling in the clinic: applications and challenges. Nat. Rev. Genet. 13(10), 679-692 (2012).
8. Winter S, Fisel P, Buttner F et al. Methylomes of renal cell lines and tumors or metastases differ significantly with impact on pharmacogenes. Sci. Rep. 6, 29930 (2016).
9. Esteller M, Garcia-Foncillas J, Andion E et al. Inactivation of the DNA-repair gene MGMT and the clinical response of gliomas to alkylating agents. N. Engl. J. Med. 343(19), 1350-1354 (2000).
10. Wiencke JK. Impact of race/ethnicity on molecular pathways in human cancer. Nat. Rev. Cancer 4(1), 79-84 (2004).
11. Kurian AK, Cardarelli KM. Racial and ethnic differences in cardiovascular disease risk factors: a systematic review. Ethn. Dis. 17(1), 143-152 (2007).
12. Caprio S, Daniels SR, Drewnowski A et al. Influence of race, ethnicity, and culture on childhood obesity: implications for prevention and treatment: a consensus statement of Shaping America's Health and the Obesity Society. Diabetes Care 31(11), 2211-2221 (2008).
13. Chung WH, Hung SI, Hong HS et al. Medical genetics: a marker for Stevens-Johnson syndrome. Nature 428(6982), 486 (2004).
14. Maisano Delser P, Fuselli S. Human loci involved in drug biotransformation: worldwide genetic variation, population structure, and pharmacogenetic implications. Hum. Genet. 132(5), 563-577 (2013).
15. Ramos E, Doumatey A, Elkahloun AG et al. Pharmacogenomics, ancestry and clinical decision-making for global populations. Pharmacogenomics J. 14(3), 217-222 (2014).
16. Fraser HB, Lam LL, Neumann SM, Kobor MS. Population-specificity of human DNA methylation. Genome Biol. 13(2), R8 (2012).
17. Moen EL, Zhang X, Mu W et al. Genome-wide variation of cytosine modifications between European and African populations and the implications for complex traits. Genetics 194(4), 987-996 (2013).
18. Xia YY, Ding YB, Liu XQ et al. Racial/ethnic disparities in human DNA methylation. Biochim. Biophys. Acta 1846(1), 258-262 (2014).
19. Conway K, Edmiston SN, Tse CK et al. Racial variation in breast tumor promoter methylation in the Carolina Breast Cancer Study. Cancer Epidemiol. Biomarkers Prev. 24(6), 921-930 (2015).
20. Lokk K, Modhukur V, Rajashekar B et al. DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns. Genome Biol. 15(4), r54 (2014).
21. Cancer Genome Atlas N. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487(7407), 330-337 (2012).
22. Cancer Genome Atlas N. Comprehensive molecular portraits of human breast tumours. Nature 490(7418), 61-70 (2012).
23. Cancer Genome Atlas Research Network, Kandoth C, Schultz N et al. Integrated genomic characterization of endometrial carcinoma. Nature 497(7447), 67-73 (2013).
24. Cancer Genome Atlas N. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517(7536), 576-582 (2015).
25. Dedeurwaerder S, Defrance M, Calonne E, Denis H, Sotiriou C, Fuks F. Evaluation of the infinium methylation 450K technology. Epigenomics 3(6), 771-784 (2011).
26. Sandoval J, Heyn H, Moran S et al. Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics 6(6), 692-702 (2011).
27. Wang K, Singh D, Zeng Z et al. MapSplice: accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Res. 38(18), e178 (2010).
28. UNC Bioinformatics Utilities. https://github.com/mozack/ubu
29. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).
30. Lappalainen T, Sammeth M, Friedlander MR et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501(7468), 506-511 (2013).
31. T Hoen PA, Friedlander MR, Almlof J et al. Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories. Nat. Biotechnol. 31(11), 1015-1022 (2013).
32. Marco-Sola S, Sammeth M, Guigo R, Ribeca P. The GEM mapper: fast, accurate and versatile alignment by filtration. Nat. Methods 9(12), 1185-1188 (2012).
33. Griebel T, Zacher B, Ribeca P et al. Modelling and simulating generic RNA-Seq experiments with the flux simulator. Nucleic Acids Res. 40(20), 10073-10083 (2012).
34. Teschendorff AE, Marabita F, Lechner M et al. A beta-mixture quantile normalization method for correcting probe design bias in illumina infinium 450 k DNA methylation data. Bioinformatics 29(2), 189-196 (2013).
35. Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes' methods. Biostatistics 8(1), 118-127 (2007).
36. Leek JT, Storey JD. Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genetics 3(9), 1724-1735 (2007).
37. Du P, Zhang X, Huang CC et al. Comparison of beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics 11, 587 (2010).
38. Miller RG. Simultaneous Statistical Inference (2nd Edition). Springer-Verlag, NY, USA (1981).
39. Hartmann O, Spyratos F, Harbeck N et al. DNA methylation markers predict outcome in node-positive, estrogen receptor-positive breast cancer with adjuvant anthracycline-based chemotherapy. Clin. Cancer Res. 15(1), 315-323 (2009).
40. Veeck J, Ropero S, Setien F et al. BRCA1 CpG island hypermethylation predicts sensitivity to poly(adenosine diphosphate)-ribose polymerase inhibitors. J. Clin. Oncol. 28(29), e563-e564; author reply e565-e566 (2010).
41. Wright JL, Reis IM, Zhao W et al. Racial disparity in estrogen receptor positive breast cancer patients receiving trimodality therapy. Breast 21(3), 276-283 (2012).
42. Tichy JR, Deal AM, Anders CK, Reeder-Hayes K, Carey LA. Race, response to chemotherapy and outcome within clinical breast cancer subtypes. Breast Cancer Res. Treat 150(3), 667-674 (2015).
43. Mihaly Z, Kormos M, Lanczky A et al. A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer. Breast Cancer Res. Tr. 140(2), 219-232 (2013).
44. Eltayeb AE, Demas DM, Clarke R, Shajahan-Haq AN. The unfolded protein response may contribute to racial disparity in endocrine responsiveness in breast cancer. Cancer Res. 1(3), 640-644 (2015).
45. Dombroski BA, Nayak RR, Ewens KG, Ankener W, Cheung VG, Spielman RS. Gene expression and genetic variation in response to endoplasmic reticulum stress in human cells. Am. J. Hum. Genet. 86(5), 719-729 (2010).
46. Li Q, Su Z, Xu X et al. AS1DHRS4, a head-to-head natural antisense transcript, silences the DHRS4 gene cluster in cis and trans. Proc. Natl Acad. Sci. USA 109(35), 14110-14115 (2012).
47. Korkola JE, Blaveri E, Devries S et al. Identification of a robust gene signature that predicts breast cancer outcome in independent data sets. BMC Cancer 7, 61 (2007).
48. Subramanian A, Tamayo P, Mootha VK et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102(43), 15545-15550 (2005).
49. Schlattner U, Tokarska-Schlattner M, Wallimann T. Mitochondrial creatine kinase in human health and disease. BBA Mol. Basis Dis. 1762(2), 164-180 (2006).
50. Brewster LM, Coronel CMD, Sluiter W, Clark JF, Van Montfrans GA. Ethnic differences in tissue creatine kinase activity: an observational study. PLoS ONE 7(3), e32471 (2012).
51. Danforth DN. Disparities in breast cancer outcomes between Caucasian and African American women: a model for describing the relationship of biological and nonbiological factors. Breast Cancer Res. 15(3), 208 (2013).
52. Grafodatskaya D, Choufani S, Ferreira JC et al. EBV transformation and cell culturing destabilizes DNA methylation in human lymphoblastoid cell lines. Genomics 95(2), 73-83 (2010).
53. Caliskan M, Cusanovich DA, Ober C, Gilad Y. The effects of EBV transformation on gene expression levels and methylation profiles. Hum. Mol. Genet. 20(8), 1643-1652 (2011).
54. Heyn H, Moran S, Hernando-Herraez I et al. DNA methylation contributes to natural human variation. Genome Res. 23(9), 1363-1372 (2013).
55. Yi X, Hong M, Gui B et al. RNA Processing and modification protein, carbon catabolite Repression 4 (Ccr4), arrests the cell cycle through p21-dependent and p53-independent pathway. J. Biol. Chem. 287(25), 21045-21057 (2012).
56. Wilkinson S, Paterson HF, Marshall CJ. Cdc42-MRCK and Rho-ROCK signalling cooperate in myosin phosphorylation and cell invasion. Nat. Cell Biol. 7(3), U255-U245 (2005).
57. Liu YJ, Wang F, Liu YS et al. RNF135, RING finger protein, promotes the proliferation of human glioblastoma cells in vivo and in vitro via the ERK pathway. Sci. Rep. 6, 20642 (2016).
58. Li M, Zhang YQ, Liu ZJ et al. Aberrant expression of zinc transporter ZIP4 (SLC39A4) significantly contributes to human pancreatic cancer pathogenesis and progression. Proc. Natl Acad. Sci. USA 104(47), 18636-18641 (2007).
59. Lapenna S, Giordano A. Cell cycle kinases as therapeutic targets for cancer. Nat. Rev. Drug Discov. 8(7), 547-566 (2009).
60. Malumbres M, Barbacid M. Cell cycle, CDKs and cancer: a changing paradigm. Nat. Rev. Cancer 9(3), 153-166 (2009).
61. Wilkinson S, Croft DR, O'prey J et al. The cyclin-dependent kinase PITSLRE/CDK11 is required for successful autophagy. Autophagy 7(11), 1295-1301 (2011).
62. Murase D, Hachiya A, Takano K et al. Autophagy has a significant role in determining skin color by regulating melanosome degradation in keratinocytes. J. Invest. Dermatol. 133(10), 2416-2424 (2013).
63. Zhang X, Moen EL, Liu C et al. Linking the genetic architecture of cytosine modifications with human complex traits. Hum. Mol. Genet. 23(22), 5893-5905 (2014).
64. Barrow TM, Michels KB. Epigenetic epidemiology of cancer. Biochem. Biophys. Res. Commun. 455(1-2), 70-83 (2014).
65. Suzuki H, Yamamoto E, Maruyama R, Niinuma T, Kai M. Biological significance of the CpG island methylator phenotype. Biochem. Biophys. Res. Commun. 455(1-2), 35-42 (2014).
66. Weisenberger DJ, Levine AJ, Long TI et al. Association of the colorectal CpG island methylator phenotype with molecular features, risk factors, and family history. Cancer Epidemiol. Biomarkers Prev. 24(3), 512-519 (2015).
67. Fang F, Turcan S, Rimner A et al. Breast cancer methylomes establish an epigenomic foundation for metastasis. Sci. Transl. Med. 3(75), 75ra25 (2011).
68. Hinoue T, Weisenberger DJ, Lange CP et al. Genome-scale analysis of aberrant DNA methylation in colorectal cancer. Genome Res. 22(2), 271-282 (2012).
69. Ogino S, Chan AT, Fuchs CS, Giovannucci E. Molecular pathological epidemiology of colorectal neoplasia: an emerging transdisciplinary and interdisciplinary field. Gut 60(3), 397-411 (2011).
70. Ogino S, Lochhead P, Chan AT et al. Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease. Mod. Pathol. 26(4), 465-484 (2013).
71. Ogino S, Nishihara R, Vanderweele TJ et al. The role of molecular pathological epidemiology in the study of neoplastic and non-neoplastic diseases in the era of precision medicine. Epidemiology 27(4), 602-611 (2016).
72. Anisimov VN, Sikora E, Pawelec G. Relationships between cancer and aging: a multilevel approach. Biogerontology 10(4), 323-338 (2009).
73. De Magalhaes JP. How ageing processes influence cancer. Nat. Rev. Cancer 13(5), 357-365 (2013).
74. Mangoni AA, Jackson SH. Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. Br. J. Clin. Pharmacol. 57(1), 6-14 (2004).
75. Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 14(10), R115 (2013).
76. Horvath S, Gurven M, Levine ME et al. An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biol. 17(1), 171 (2016).