A methylome-wide study of aging using massively parallel sequencing of the methyl-CpG-enriched genomic fraction from blood in over 700 subjects

Human Molecular Genetics

Volumn 23, Issue 5, 2014, Pages 1175-1185

  Mcclay, Joseph L ^a   Aberg, Karolina A ^a   Clark, Shaunna L ^a   Nerella, Srilaxmi ^a   Kumar, Gaurav ^a   Xie, Lin Y ^a   Hudson, Alexandra D ^a   Harada, Aki ^a   Hultman, Christina M ^b   Magnusson, Patrik K E ^b   Sullivan, Patrick F ^c   Van den oord, Edwin J C G ^a  

^a VIRGINIA COMMONWEALTH UNIVERSITY   (United States)

^b KAROLINSKA INSTITUTE   (Sweden)

^c UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; AGED, 80 AND OVER; AGING; COMPUTATIONAL BIOLOGY; CPG ISLANDS; DNA; DNA METHYLATION; DNA-BINDING PROTEINS; EPIGENESIS, GENETIC; EPIGENOMICS; FEMALE; GENE REGULATORY NETWORKS; GENOME-WIDE ASSOCIATION STUDY; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MALE; MIDDLE AGED; PROTEIN BINDING; PROTEIN INTERACTION MAPS; SEX FACTORS; SIGNAL TRANSDUCTION; TRANSCRIPTION FACTORS;

EID: 84894036364     PISSN: 09646906     EISSN: 14602083     Source Type: Journal    
DOI: 10.1093/hmg/ddt511     Document Type: Article

References (75)

1. Riley, J. (2001) Rising Life Expectancy: A Global History. Cambridge University Press, Cambridge.
2. Duron, E. and Hanon, O. (2008) Hypertension, cognitive decline and dementia. Arch Cardiovasc. Dis., 101, 181-189.
3. Barzilai, N., Huffman, D.M., Muzumdar, R.H. and Bartke, A. (2012) The critical role of metabolic pathways in aging. Diabetes, 61, 1315-1322.
4. Issa, J.P. (2002) Epigenetic variation and human disease. J. Nutr., 132, 2388S-2392S.
5. Sahin, E. and Depinho, R.A. (2010) Linking functional decline of telomeres, mitochondria and stem cells during ageing. Nature, 464, 520-528.
6. Gonzalo, S. (2010) Epigenetic alterations in aging. J. Appl. Physiol., 109, 586-597.
7. Laird, P.W. (2010) Principles and challenges of genome-wide DNA methylation analysis. Nat. Rev. Genet., 11, 191-203.
8. Calvanese, V., Lara, E., Kahn, A. and Fraga, M.F. (2009) The role of epigenetics in aging and age-related diseases. Ageing Res. Rev., 8, 268-276.
9. Fuke, C., Shimabukuro, M., Petronis, A., Sugimoto, J., Oda, T., Miura, K., Miyazaki, T., Ogura, C., Okazaki, Y. and Jinno, Y. (2004) Age related changes in 5-methylcytosine content in human peripheral leukocytes and placentas: an HPLC-based study. Ann. Hum. Genet., 68, 196-204.
10. Fraga, M.F. (2009) Genetic and epigenetic regulation of aging. Curr. Opin. Immunol., 21, 446-453.
11. Fraga, M.F. and Esteller,M. (2007) Epigenetics and aging: the targets and the marks. Trends Genet., 23, 413-418.
12. So, K., Tamura, G., Honda, T., Homma, N., Endoh, M., Togawa, N., Nishizuka, S. and Motoyama, T. (2006) Quantitative assessment of RUNX3 methylation in neoplastic and non-neoplastic gastric epithelia using a DNA microarray. Pathol. Int., 56, 571-575.
13. Choi, E.K., Uyeno, S., Nishida, N., Okumoto, T., Fujimura, S., Aoki, Y., Nata, M., Sagisaka, K., Fukuda, Y., Nakao, K. et al. (1996) Alterations of c-fos gene methylation in the processes of aging and tumorigenesis in human liver. Mutat. Res., 354, 123-128.
14. Bornman, D.M., Mathew, S., Alsruhe, J., Herman, J.G. and Gabrielson, E. (2001) Methylation of the E-cadherin gene in bladder neoplasia and in normal urothelial epithelium from elderly individuals. Am. J. Pathol., 159, 831-835.
15. Gronniger, E., Weber, B., Heil, O., Peters, N., Stab, F., Wenck, H., Korn, B., Winnefeld, M. and Lyko, F. (2010) Aging and chronic sun exposure cause distinct epigenetic changes in human skin. PLoS Genet., 6, e1000971.
16. Bork, S., Pfister, S., Witt, H., Horn, P., Korn, B., Ho, A.D. and Wagner, W. (2010) DNA Methylation pattern changes upon long-term culture and aging of human mesenchymal stromal cells. Aging Cell, 9, 54-63.
17. Bocklandt, S., Lin, W., Sehl, M.E., Sanchez, F.J., Sinsheimer, J.S., Horvath, S. and Vilain, E. (2011) Epigenetic predictor of age. PLoS One, 6, e14821.
18. Teschendorff, A.E., Menon, U., Gentry-Maharaj, A., Ramus, S.J., Weisenberger, D.J., Shen, H., Campan, M., Noushmehr, H., Bell, C.G., Maxwell, A.P. et al. (2010) Age-dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer. Genome Res., 20, 440-446.
19. Bell, J.T., Tsai, P.C., Yang, T.P., Pidsley, R., Nisbet, J., Glass, D., Mangino, M., Zhai, G., Zhang, F., Valdes, A. et al. (2012) Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS Genet., 8, e1002629.
20. Rakyan, V.K., Down, T.A., Maslau, S., Andrew, T., Yang, T.P., Beyan, H., Whittaker, P., McCann, O.T., Finer, S., Valdes, A.M. et al. (2010) Human aging-associated DNA hypermethylation occurs preferentially at bivalent chromatin domains. Genome Res., 20, 434-439.
21. Alisch, R.S., Barwick, B.G., Chopra, P., Myrick, L.K., Satten, G.A., Conneely, K.N. and Warren, S.T. (2012) Age-associated DNA methylation in pediatric populations. Genome Res., 22, 623-632.
22. Koch, C.M. and Wagner, W. (2011) Epigenetic-aging-signature to determine age in different tissues. Aging, 3, 1018-1027.
23. Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J.B., Gao, Y. et al. (2013) Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol. Cell, 49, 359-367.
24. Heyn, H., Li, N., Ferreira, H.J., Moran, S., Pisano, D.G., Gomez, A., Diez, J., Sanchez-Mut, J.V., Setien, F., Carmona, F.J. et al. (2012) Distinct DNA methylomes of newborns and centenarians. Proc. Natl. Acad. Sci. USA, 109, 10522-10527.
25. Bibikova, M., Le, J., Barnes, B., Saedinia-Melnyk, S., Zhou, L., Shen, R. and Gunderson, K.L. (2009) Genome-wide DNA methylation profiling using infinium(R) assay. Epigenomics, 1, 177-200.
26. Irizarry, R.A., Ladd-Acosta, C., Wen, B., Wu, Z., Montano, C., Onyango, P., Cui, H., Gabo, K., Rongione, M., Webster, M. et al. (2009) The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat. Genet., 41, 178-186.
27. Metzker, M.L. (2010) Sequencing technologies-the next generation. Nat. Rev. Genet., 11, 31-46.
28. Rakyan, V.K., Down, T.A., Balding, D.J. and Beck, S. (2011) Epigenome-wide association studies for common human diseases. Nat. Rev. Genet., 12, 529-541.
29. Frommer, M., McDonald, L.E., Millar, D.S., Collis, C.M., Watt, F., Grigg, G.W., Molloy, P.L. and Paul, C.L. (1992) A genomic sequencing protocol that yields a positive display of 5-methylcytosine residues in individualDNA strands. Proc. Natl. Acad. Sci. USA, 89, 1827-1831.
30. Serre, D., Lee, B.H. and Ting, A.H. (2010) MBD-isolated genome sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome. Nucleic Acids Res., 38, 391-399.
31. Mohn, F., Weber, M., Schubeler, D. and Roloff, T.C. (2009) Methylated DNA immunoprecipitation (MeDIP). Methods Mol. Biol., 507, 55-64.
32. Nair, S.S., Coolen, M.W., Stirzaker, C., Song, J.Z., Statham, A.L., Strbenac, D., Robinson, M.D. and Clark, S.J. (2011) Comparison of methyl-DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain (MBD) protein capture for genome-wide DNA methylation analysis reveal CpG sequence coverage bias. Epigenetics, 6, 34-44.
33. Harris, R.A., Wang, T., Coarfa, C., Nagarajan, R.P., Hong, C., Downey, S.L., Johnson, B.E., Fouse, S.D., Delaney, A., Zhao, Y. et al. (2010) Comparison of sequencing-based methods to profileDNAmethylation and identification of monoallelic epigenetic modifications. Nat. Biotechnol., 28, 1097-1105.
34. Salpea, P., Russanova, V.R., Hirai, T.H., Sourlingas, T.G., Sekeri-Pataryas, K.E., Romero, R., Epstein, J. and Howard, B.H. (2012) Postnatal development- and age-related changes in DNA-methylation patterns in the human genome. Nucleic Acids Res., 40, 6477-6494.
35. Aberg, K.A., McClay, J.L., Nerella, S., Xie, L.Y., Clark, S.L., Hudson, A.D., Bukszar, J., Adkins, D., Consortium, S.S., Hultman, C.M. et al. (2012) MBD-seq as a cost-effective approach for methylome-wide association studies: demonstration in 1500 case-control samples. Epigenomics, 4, 605-621.
36. Chen, W., Gao, G., Nerella, S., Hultman, C.M., Magnusson, P.K., Sullivan, P.F., Aberg, K.A. and van den Oord, E.J. (2013) MethylPCA: a toolkit to control for confounders in methylome-wide association studies. BMC Bioinformatics, 14, 74.
37. van den Oord, E.J., Bukszar, J., Rudolf, G., Nerella, S., McClay, J.L., Xie, L.Y. and Aberg, K.A. (2013) Estimation of CpG coverage in whole methylome next-generation sequencing studies. BMC Bioinformatics, 14, 50.
38. Aberg, K., Khachane, A.N., Rudolf, G., Nerella, S., Fugman, D.A., Tischfield, J.A. and van den Oord, E.J. (2012) Methylome-wide comparison of human genomic DNA extracted from whole blood and from EBV-transformed lymphocyte cell lines. Eur. J. Hum. Genet., 20, 953-955.
39. van den Oord, E.J. and Sullivan, P.F. (2003) False discoveries and models for gene discovery. Trends Genet., 19, 537-542.
40. Brown,B.W. and Russell, K. (1997) Methods correcting for multiple testing: operating characteristics. Stat. Med., 16, 2511-2528.
41. Fernando, R.L., Nettleton, D., Southey, B.R., Dekkers, J.C., Rothschild, M.F. and Soller, M. (2004) Controlling the proportion of false positives in multiple dependent tests. Genetics, 166, 611-619.
42. Korn, E.L., Troendle, J.F., McShane, L.M. and Simon, R. (2004) Controlling the number of false discoveries: application to high-dimensional genomic data. J. Stat. Plan. Infer., 124, 379-398.
43. Sabatti, C., Service, S. and Freimer, N. (2003) False discovery rate in linkage and association genome screens for complex disorders. Genetics, 164, 829- 833.
44. Tsai, C.A., Hsueh, H.M. and Chen, J.J. (2003) Estimation of false discovery rates in multiple testing: application to gene microarray data. Biometrics, 59, 1071-1081.
45. Reed, K., Poulin, M.L., Yan, L. and Parissenti, A.M. (2010) Comparison of bisulfite sequencing PCR with pyrosequencing for measuring differences in DNA methylation. Anal Biochem., 397, 96-106.
46. Kamburov, A., Pentchev, K., Galicka, H., Wierling, C., Lehrach, H. and Herwig, R. (2011) ConsensusPathDB: toward a more complete picture of cell biology. Nucleic Acids Res., 39, D712-D717.
47. Friedman, R.C., Farh, K.K., Burge, C.B. and Bartel, D.P. (2009) Most mammalianmRNAsare conserved targets of microRNAs. Genome Res., 19, 92-105.
48. Wang, C., Deng, L., Hong, M., Akkaraju, G.R., Inoue, J. and Chen, Z.J. (2001) TAK1 Is a ubiquitin-dependent kinase of MKK and IKK. Nature, 412, 346-351.
49. Koch, C.M., Reck, K., Shao, K., Lin, Q., Joussen, S., Ziegler, P., Walenda, G., Drescher, W., Opalka, B., May, T. et al. (2012) Pluripotent stem cells escape from senescence-associated DNA methylation changes. Genome Res., 23, 248-259.
50. Azuara, V., Perry, P., Sauer, S., Spivakov, M., Jorgensen, H.F., John, R.M., Gouti, M., Casanova, M., Warnes, G., Merkenschlager, M. et al. (2006) Chromatin signatures of pluripotent cell lines. Nat. Cell Biol., 8, 532-538.
51. Han, S. and Brunet, A. (2012) Histone methylation makes its mark on longevity. Trends Cell Biol., 22, 42-49.
52. Hirayama, T. and Yagi, T. (2006) The role and expression of the protocadherin-alpha clusters in the CNS. Curr. Opin. Neurobiol., 16, 336- 342.
53. Kawaguchi, M., Toyama, T., Kaneko, R., Hirayama, T., Kawamura, Y. and Yagi, T. (2008) Relationship between DNA methylation states and transcription of individual isoforms encoded by the protocadherin-alpha gene cluster. J. Biol. Chem., 283, 12064-12075.
54. Medina, A., Swain, R.K., Kuerner, K.M. and Steinbeisser, H. (2004) Xenopus paraxial protocadherin has signaling functions and is involved in tissue separation. EMBO. J., 23, 3249-3258.
55. Walter, S., Atzmon, G., Demerath, E.W., Garcia, M.E., Kaplan, R.C., Kumari, M., Lunetta, K.L., Milaneschi, Y., Tanaka, T., Tranah, G.J. et al. (2011) A genome-wide association study of aging. Neurobiol Aging, 32, 2109.e15-2109.e28.
56. Nair, K.S. (2005) Aging muscle. Am. J. Clin. Nutr., 81, 953-963.
57. Takeda, K., Noguchi, T., Naguro, I. and Ichijo, H. (2008) Apoptosis signal-regulating kinase 1 in stress and immune response. Annu. Rev. Pharmacol. Toxicol., 48, 199-225.
58. Maruyama, J., Naguro, I., Takeda, K. and Ichijo, H. (2009) Stress-activated MAP kinase cascades in cellular senescence. Curr. Med. Chem., 16, 1229- 1235.
59. Mattson, M.P. (2010) ERcalcium and Alzheimer's disease: in a state of flux. Sci. Signal, 3, pe10.
60. Park, S.J., Ahmad, F., Philp, A., Baar, K., Williams, T., Luo, H., Ke, H., Rehmann, H., Taussig, R., Brown, A.L. et al. (2012) Resveratrol ameliorates aging-related metabolic phenotypes by inhibiting cAMP phosphodiesterases. Cell, 148, 421-433.
61. Schizophrenia Psychiatric Genome-Wide Association Study Consortium (2011)Genome-wide association study of schizophrenia identifiesfive novel loci. Nat. Genet., 43, 969-976.
62. International Schizophrenia Consortium (2009) Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature, 460, 748-752.
63. Bergen, S.E., O'Dushlaine, C.T., Ripke, S., Lee, P.H., Ruderfer, D.M., Akterin, S., Moran, J.L., Chambert, K.D., Handsaker, R.E., Backlund, L. et al. (2012) Genome-wide association study in a Swedish population yields support for greater CNV and MHCinvolvement in schizophrenia compared with bipolar disorder. Mol. Psychiatry, 17, 880-886.
64. Bock, C., Tomazou, E.M., Brinkman, A.B., Muller, F., Simmer, F., Gu, H., Jager, N., Gnirke, A., Stunnenberg, H.G. and Meissner, A. (2010) Quantitative comparison of genome-wide DNA methylation mapping technologies. Nat. Biotechnol., 28, 1106-1114.
65. Chavez, L., Jozefczuk, J., Grimm, C., Dietrich, J., Timmermann, B., Lehrach, H., Herwig, R. and Adjaye, J. (2010) Computational analysis of genome-wide DNA methylation during the differentiation of human embryonic stem cells along the endodermal lineage. Genome Res., 20, 1441-1450.
66. McKernan, K.J., Peckham, H.E., Costa, G.L., McLaughlin, S.F., Fu, Y., Tsung, E.F., Clouser, C.R., Duncan, C., Ichikawa, J.K., Lee, C.C. et al. (2009) Sequence and structural variation in a human genome uncovered by short-read, massively parallel ligation sequencing using two-base encoding. Genome Res., 19, 1527-1541.
67. Liu, Y.,Aryee,M.J., Padyukov, L.,Fallin, M.D.,Hesselberg, E.,Runarsson,A., Reinius, L., Acevedo, N., Taub,M., Ronninger, M. et al. (2013) Epigenomewide association data implicateDNAmethylation as an intermediary of genetic risk in rheumatoid arthritis. Nat. Biotechnol., 31, 142-147.
68. Houseman, E.A., Accomando, W.P., Koestler, D.C., Christensen, B.C., Marsit, C.J., Nelson, H.H., Wiencke, J.K. and Kelsey, K.T. (2012) DNA Methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics, 13, 86.
69. Sun, Y.V., Turner, S.T., Smith, J.A., Hammond, P.I., Lazarus, A., Van De Rostyne, J.L., Cunningham, J.M. and Kardia, S.L. (2010) Comparison of the DNA methylation profiles of human peripheral blood cells and transformed B-lymphocytes. Hum. Genet., 127, 651-658.
70. Bell, J.T., Pai, A.A., Pickrell, J.K., Gaffney, D.J., Pique-Regi, R., Degner, J.F., Gilad, Y. and Pritchard, J.K. (2011) DNA Methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol., 12, R10.
71. Benjamini, Y. and Hochberg,Y. (1995) Controlling the false discovery rate-a practical and powerful approach to multiple testing. J. Roy. Stat. Soc. B Met., 57, 289-300.
72. Storey, J.D. (2003) The positive false discovery rate: A Bayesian interpretation and the q-value. Ann. Stat., 31, 2013-2035.
73. Storey, J.D. and Tibshirani, R. (2003) Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. USA, 100, 9440-9445.
74. Ram, O., Goren, A., Amit, I., Shoresh, N., Yosef, N., Ernst, J., Kellis, M., Gymrek, M., Issner, R., Coyne, M. et al. (2011) Combinatorial patterning of chromatin regulators uncovered by genome-wide location analysis in human cells. Cell, 147, 1628-1639.
75. Ernst, J., Kheradpour, P., Mikkelsen, T.S., Shoresh, N., Ward, L.D., Epstein, C.B., Zhang, X., Wang, L., Issner, R., Coyne, M. et al. (2011) Mapping and analysis of chromatin state dynamics in nine human cell types. Nature, 473, 43-49.