Genetic and Environmental Causes of Variation in the Difference Between Biological Age Based on DNA Methylation and Chronological Age for Middle-Aged Women

Twin Research and Human Genetics

Volumn 18, Issue 6, 2015, Pages 720-726

  Li, Shuai ^a   Wong, Ee Ming ^b   Joo, JiHoon E ^b   Jung, Chol Hee ^b   Chung, Jessica ^b   Apicella, Carmel ^a   Stone, Jennifer ^c   Dite, Gillian S ^a   Giles, Graham G ^a,d   Southey, Melissa C ^b   Hopper, John L ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b UNIVERSITY OF MELBOURNE   (Australia)

^c UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^d CANCER EPIDEMIOLOGY CENTRE   (Australia)

Author keywords

age; DNA methylation; familial correlation; heritability; twin family study

Indexed keywords

DNA;

ADULT; AGED; AGING; ARTICLE; BLOOD SAMPLING; CONTROLLED STUDY; DIZYGOTIC TWINS; DNA METHYLATION; FAMILY STUDY; FEMALE; GENETIC ANALYSIS; GENETIC VARIABILITY; GENOTYPE ENVIRONMENT INTERACTION; HERITABILITY; HUMAN; MIDDLE AGED; MONOZYGOTIC TWINS; MORBIDITY; MORTALITY; PEDIGREE ANALYSIS; PRIORITY JOURNAL; RELATIVE; SIBLING; AGE; COMPARATIVE STUDY; TWINS;

AGE FACTORS; DNA METHYLATION; FEMALE; GENE-ENVIRONMENT INTERACTION; HUMANS; MIDDLE AGED;

EID: 84952875887     PISSN: 18324274     EISSN: 18392628     Source Type: Journal    
DOI: 10.1017/thg.2015.75     Document Type: Article

References (31)

1. Alisch, R. S., Barwick, B.G., Chopra, P., Myrick, L. K., Satten, G. A., Conneely, K. N., & Warren, S. T. (2012). Ageassociated DNA methylation in pediatric populations. Genome Research, 22, 623-632.
2. Aryee, M. J., Jaffe, A. E., Corrada-Bravo, H., Ladd-Acosta, C., Feinberg, A. P., Hansen, K. D., & Irizarry, R. A. (2014). Minfi: A flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics, 30, 1363-1369.
3. Bell, J. T., Tsai, P. C., Yang, T. P., Pidsley, R., Nisbet, J., Glass, D., ⋯ Deloukas, P. (2012). Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS Genetics, 8(4), e1002629.
4. Bocklandt, S., Lin, W., Sehl, M. E., Sanchez, F. J., Sinsheimer, J. S., Horvath, S., & Vilain, E. (2011). Epigenetic predictor of age. PLoS One, 6, e14821.
5. Florath, I., Butterbach, K., Muller, H., Bewerunge-Hudler, M., & Brenner, H. (2014). Cross-sectional and longitudinal changes in DNA methylation with age: An epigenome-wide analysis revealing over 60 novel age-associated CpG sites. Human Molecular Genetics, 23, 1186-1201.
6. Fraga, M. F., Ballestar, E., Paz, M. F., Ropero, S., Setien, F., Ballestar, M. L., ⋯ Esteller, M. (2005). Epigenetic differences arise during the lifetime of monozygotic twins. Proceedings of the National Academy of Sciences of the USA, 102, 10604-10609.
7. Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., ⋯ Zhang, K. (2013). Genome-wide methylation profiles reveal quantitative views of human aging rates. Molecular Cell, 49, 359-367.
8. Hopper, J. L., & Mathews, J. D. (1982). Extensions tomultivariate normal models for pedigree analysis. Annals of Human Genetics, 46, 373-383.
9. Hopper, J. L., & Mathews, J. D. (1994). A multivariate normal model for pedigree and longitudinal data and the software 'FISHER'. Australian Journal of Statistics, 36, 153-176.
10. Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome Biology, 14, R115.
11. Horvath, S., Erhart, W., Brosch, M., Ammerpohl, O., von Schonfels, W., Ahrens, M., ⋯ Hampe, J. (2014). Obesity accelerates epigenetic aging of human liver. Proceedings of the National Academy of Sciences of the USA, 111, 15538-15543.
12. Horvath, S., Garagnani, P., Bacalini, M. G., Pirazzini, C., Salvioli, S., Gentilini, D., ⋯ Franceschi, C. (2015). Accelerated epigenetic aging in Down syndrome. Aging Cell, 14, 491-495.
13. Houseman, E. A., Accomando, W. P., Koestler, D. C., Christensen, B. C., Marsit, C. J., Nelson, H. H., ⋯ Kelsey, K. T. (2012). DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics, 13, 86.
14. Jaffe, A. E., & Irizarry, R. A. (2014). Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biology, 15, R31.
15. Johansson, A., Enroth, S., & Gyllensten, U. (2013). Continuous aging of the human DNA methylome throughout the human lifespan. PLoS One, 8, e67378.
16. Johnson, W. E., Li, C., & Rabinovic, A. (2007). Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics, 8, 118-127.
17. Joo, J. E., Wong, E.M., Baglietto, L., Jung, C.-H., Tsimiklis, H., Park, D. J., ⋯ Severi, G. (2013). The use of DNA from archival dried blood spots with the Infinium Human Methylation 450 array. BMC Biotechnology, 13, 23.
18. Koch, C. M., & Wagner, W. (2011). Epigenetic-aging-signature to determine age in different tissues. Aging, 3, 1018-1027.
19. Lange, K., Boehnke, M., & Opitz, J. M. (1983). Extensions to pedigree analysis. IV. Covariance components models for multivariate traits. American Journal of Medical Genetics, 14, 513-524.
20. Lange, K., Boehnke, M., & Weeks, D. (1987). Programs for pedigree analysis. Los Angeles, CA: Department of Biomathematics, University of California.
21. Maksimovic, J., Gordon, L., & Oshlack, A. (2012). SWAN: Subset-quantile within array normalization for illumina infinium Human Methylation 450 BeadChips. Genome Biology, 13, R44.
22. Marioni, R. E., Shah, S., McRae, A. F., Chen, B. H., Colicino, E., Harris, S. E., ⋯ Cox, S. R. (2015). DNA methylation age of blood predicts all-cause mortality in later life. Genome Biology, 16, 25.
23. Martino, D., Loke, Y. J., Gordon, L., Ollikainen, M., Cruickshank, M. N., Saffery, R., & Craig, J. M. (2013). Longitudinal, genome-scale analysis of DNA methylation in twins frombirth to 18 months of age reveals rapid epigenetic change in early life and pair-specific effects of discordance. Genome Biology, 14, R42.
24. Odefrey, F., Stone, J., Gurrin, L. C., Byrnes, G. B., Apicella, C., Dite, G. S., ⋯ Southey, M. C. (2010). Common genetic variants associated with breast cancer and mammographic density measures that predict disease. Cancer Research, 70, 1449-1458.
25. Rakyan, V.K., Down, T.A., Maslau, S., Andrew, T., Yang, T.-P., Beyan, H., ⋯ Valdes, A. M. (2010). Human agingassociated DNA hypermethylation occurs preferentially at bivalent chromatin domains. Genome Research, 20, 434-439.
26. Sandoval, J., Heyn, H., Moran, S., Serra-Musach, J., Pujana, M. A., Bibikova, M., & Esteller, M. (2011). Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics, 6, 692-702.
27. Stone, J., Gurrin, L.C., Byrnes, G. B., Schroen, C. J., Treloar, S. A., Padilla, E. J., ⋯ Hopper, J. L. (2007). Mammographic density and candidate gene variants: A twins and sisters study. Cancer Epidemiology, Biomarkers & Prevention, 16, 1479-1484.
28. Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36, 1-48.
29. Weidner, C. I., Lin, Q., Koch, C. M., Eisele, L., Beier, F., Ziegler, P., ⋯ Wagner, W. (2014). Aging of blood can be tracked by DNA methylation changes at just three CpG sites. Genome Biology, 15, R24.
30. Wong, C. C., Caspi, A., Williams, B., Craig, I.W., Houts, R., Ambler, A., ⋯ Mill, J. (2010). A longitudinal study of epigenetic variation in twins. Epigenetics, 5, 516-526.
31. Wong, E.M., Joo, J. H. E., McLean, C. A., Baglietto, L., English, D. R., Severi, G., ⋯ Southey, M. C. (2015). Tools for translational epigenetic studies involving formalin-fixed paraffin-embedded human tissue: Applying the Infinium Human Methyation 450 Beadchip assay to large populationbased studies. BMC Research Notes, 8(1), 543.