期刊论文详细信息
Clinical Epigenetics
Association of DNA methylation with age, gender, and smoking in an Arab population
Karsten Suhre2  Mario Falchi1  Pankaj Kumar5  Wadha A Al Muftah3  Mashael Al-Shafai3  Shaza B Zaghlool4 
[1] Department of Genomics of Common Disease, Imperial College London, London, UK;Helmholtz Zentrum München, Germany, Research Center for Environmental Health, Neuherberg, 85764, Germany;Research Division, Qatar Science Leadership Program, Qatar Foundation, Doha, Qatar;Computer Engineering Department, Virginia Tech, Blacksburg 24060, VA, USA;Bioinformatics Core, Weill Cornell Medical College in Qatar, Education City, Doha, Qatar
关键词: Epigenetics;    Association study;    Smoking;    Gender;    Age;    DNA methylation;   
Others  :  1148149
DOI  :  10.1186/s13148-014-0040-6
 received in 2014-10-23, accepted in 2014-12-22,  发布年份 2015
PDF
【 摘 要 】

Background

Modification of DNA by methylation of cytosines at CpG dinucleotides is a widespread phenomenon that leads to changes in gene expression, thereby influencing and regulating many biological processes. Recent technical advances in the genome-wide determination of single-base DNA-methylation enabled epigenome-wide association studies (EWASs). Early EWASs established robust associations between age and gender with the degree of CpG methylation at specific sites. Other studies uncovered associations with cigarette smoking. However, so far these studies were mainly conducted in Caucasians, raising the question of whether these findings can also be extrapolated to other populations.

Results

Here, we present an EWAS with age, gender, and smoking status in a family study of 123 individuals of Arab descent. We determined DNA methylation at over 450,000 CpG sites using the Illumina Infinium HumanMethylation450 BeadChip, applied state-of-the-art data processing protocols, including correction for blood cell type heterogeneity and hidden confounders, and eliminated probes containing SNPs at the targeted CpG site using 40× whole-genome sequencing data. Using this approach, we could replicate the leading published EWAS associations with age, gender and smoking, and recovered hallmarks of gender-specific epigenetic changes. Interestingly, we could even replicate the recently reported precise prediction of chronological age based on the methylation of only a few selected CpG sites.

Conclusion

Our study supports the view that when applied with state-of-the art protocols to account for all potential confounders, DNA methylation arrays represent powerful tools for EWAS with more complex phenotypes that can also be successfully applied to non-Caucasian populations.

【 授权许可】

   
2015 Zaghlool et al.; licensee Biomed Central.

【 预 览 】
附件列表
Files Size Format View
20150404094543210.pdf 1173KB PDF download
Figure 4. 24KB Image download
Figure 3. 74KB Image download
Figure 2. 35KB Image download
Figure 1. 28KB Image download
【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

【 参考文献 】
  • [1]Okano M, Bell DW, Haber DA, Li E: DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell 1999, 99(3):247-57.
  • [2]Smith ZD, Meissner A: DNA methylation: roles in mammalian development. Nat Rev Genet 2013, 14(3):204-20.
  • [3]Holliday R, Pugh JE: DNA modification mechanisms and gene activity during development. Science 1975, 187(4173):226-32.
  • [4]Radford EJ, Ito M, Shi H, Corish JA, Yamazawa K, Isganaitis E, et al.: In utero effects. In utero undernourishment perturbs the adult sperm methylome and intergenerational metabolism. Science 2014, 345(6198):1255903.
  • [5]Callaway E: Epigenomics starts to make its mark. Nature 2014, 508(7494):22.
  • [6]Ng SF, Lin RC, Laybutt DR, Barres R, Owens JA, Morris MJ: Chronic high-fat diet in fathers programs beta-cell dysfunction in female rat offspring. Nature 2010, 467(7318):963-6.
  • [7]Bird A: DNA methylation patterns and epigenetic memory. Genes Dev 2002, 16(1):6-21.
  • [8]Hackett JA, Surani MA: DNA methylation dynamics during the mammalian life cycle. Philos Trans R Soc Lond B Biol Sci 2013, 368(1609):20110328.
  • [9]Wu H, Zhang Y: Early embryos reprogram DNA methylation in two steps. Cell Stem Cell 2012, 10(5):487-9.
  • [10]Li E, Beard C, Jaenisch R: Role for DNA methylation in genomic imprinting. Nature 1993, 366(6453):362-5.
  • [11]Chaligne R, Heard E: X-chromosome inactivation in development and cancer. FEBS Lett 2014, 588(15):2514-22.
  • [12]Smith ZD, Chan MM, Humm KC, Karnik R, Mekhoubad S, Regev A, et al.: DNA methylation dynamics of the human preimplantation embryo. Nature 2014, 511(7511):611-5.
  • [13]Guo H, Zhu P, Yan L, Li R, Hu B, Lian Y, et al.: The DNA methylation landscape of human early embryos. Nature 2014, 511(7511):606-10.
  • [14]Paul DS, Beck S: Advances in epigenome-wide association studies for common diseases. Trends Mol Med 2014, 20(10):541-3.
  • [15]Xu X, Su S, Barnes VA, De Miguel C, Pollock J, Ownby D, et al.: A genome-wide methylation study on obesity: differential variability and differential methylation. Epigenetics 2013, 8(5):522-33.
  • [16]Dick KJ, Nelson CP, Tsaprouni L, Sandling JK, Aïssi D, Wahl S, et al.: DNA methylation and body-mass index: a genome-wide analysis. Lancet 2014, 383(9933):1990-8.
  • [17]Na YK, Hong HS, Lee DH, Lee WK, Kim DS, et al.: Effect of body mass index on global DNA methylation in healthy Korean women. Mol Cells 2014, 37(6):467-72.
  • [18]Hidalgo B, Irvin MR, Sha J, Zhi D, Aslibekyan S, Absher D, et al.: Epigenome-wide association study of fasting measures of glucose, insulin, and HOMA-IR in the Genetics of Lipid Lowering Drugs and Diet Network study. Diabetes 2014, 63(2):801-7.
  • [19]Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, et al.: Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol 2013, 31(2):142-7.
  • [20]Petersen AK, Zeilinger S, Kastenmüller G, Römisch-Margl W, Brugger M, Peters A, et al.: Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits. Hum Mol Genet 2014, 23(2):534-45.
  • [21]Zeilinger S, et al.: Tobacco smoking leads to extensive genome-wide changes in DNA methylation. PLoS One 2013, 8(5):e63812.
  • [22]Breitling LP, Kühnel B, Klopp N, Baurecht H, Kleinschmidt A, Gieger C, et al.: Tobacco-smoking-related differential DNA methylation: 27 K discovery and replication. Am J Hum Genet 2011, 88(4):450-7.
  • [23]Joubert BR, Håberg SE, Nilsen RM, Wang X, Vollset SE, Murphy SK, et al.: 450 K epigenome-wide scan identifies differential DNA methylation in newborns related to maternal smoking during pregnancy. Environ Health Perspect 2012, 120(10):1425-31.
  • [24]Monick MM, Beach SR, Plume J, Sears R, Gerrard M, Brody GH, et al.: Coordinated changes in AHRR methylation in lymphoblasts and pulmonary macrophages from smokers. Am J Med Genet B Neuropsychiatr Genet 2012, 159B(2):141-51.
  • [25]Langevin SM, Houseman EA, Christensen BC, Wiencke JK, Nelson HH, Karagas MR, et al.: The influence of aging, environmental exposures and local sequence features on the variation of DNA methylation in blood. Epigenetics 2011, 6(7):908-19.
  • [26]Bell JT, Tsai PC, Yang TP, Pidsley R, Nisbet J, Glass D, et al.: Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLoS Genet 2012, 8(4):e1002629.
  • [27]Horvath S, Zhang Y, Langfelder P, Kahn RS, Boks MP, van Eijk K, et al.: Aging effects on DNA methylation modules in human brain and blood tissue. Genome Biol 2012, 13(10):R97. BioMed Central Full Text
  • [28]Fraga MF, Esteller M: Epigenetics and aging: the targets and the marks. Trends Genet 2007, 23(8):413-8.
  • [29]Bollati V, Schwartz J, Wright R, Litonjua A, Tarantini L, Suh H, et al.: Decline in genomic DNA methylation through aging in a cohort of elderly subjects. Mech Ageing Dev 2009, 130(4):234-9.
  • [30]Florath I, Butterbach K, Müller H, Bewerunge-Hudler M, Brenner H: Cross-sectional and longitudinal changes in DNA methylation with age: an epigenome-wide analysis revealing over 60 novel age-associated CpG sites. Hum Mol Genet 2014, 23(5):1186-201.
  • [31]Liu J, Morgan M, Hutchison K, Calhoun VD, et al.: A study of the influence of sex on genome wide methylation. PLoS One 2010, 5(4):e10028.
  • [32]Boks MP, Derks EM, Weisenberger DJ, Strengman E, Janson E, Sommer IE, et al.: The relationship of DNA methylation with age, gender and genotype in twins and healthy controls. PLoS One 2009, 4(8):e6767.
  • [33]Zhang FF, Cardarelli R, Carroll J, Fulda KG, Kaur M, Gonzalez K, et al.: Significant differences in global genomic DNA methylation by gender and race/ethnicity in peripheral blood. Epigenetics 2011, 6(5):623-9.
  • [34]Horvath S: DNA methylation age of human tissues and cell types. Genome Biology 2013, 14(10):R115. BioMed Central Full Text
  • [35]Weidner CI, Lin Q, Koch CM, Eisele L, Beier F, Ziegler P, et al.: Aging of blood can be tracked by DNA methylation changes at just three CpG sites. Genome Biol 2014, 15(2):R24. BioMed Central Full Text
  • [36]Marabita F, Almgren M, Lindholm ME, Ruhrmann S, Fagerström-Billai F, Jagodic M, et al.: An evaluation of analysis pipelines for DNA methylation profiling using the Illumina HumanMethylation450 BeadChip platform. Epigenetics 2013, 8(3):333-46.
  • [37]Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, et al.: DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics. 2012, 13:86. BioMed Central Full Text
  • [38]Chen W, Gao G, Nerella S, Hultman CM, Magnusson PK, Sullivan PF, et al.: MethylPCA: a toolkit to control for confounders in methylome-wide association studies. BMC Bioinformatics. 2013, 14:74. BioMed Central Full Text
  • [39]Reynolds LM, Taylor JR, Ding J, Lohman K, Johnson C, Siscovick D, et al.: Age-related variations in the methylome associated with gene expression in human monocytes and T cells. Nat Commun. 2014, 5:5366.
  • [40]Bocklandt S, Lin W, Sehl ME, Sánchez FJ, Sinsheimer JS, Horvath S, et al.: Epigenetic predictor of age. Plos One 2011, 6(6):e14821.
  • [41]Michels KB, Binder AM, Dedeurwaerder S, Epstein CB, Greally JM, Gut I, et al.: Recommendations for the design and analysis of epigenome-wide association studies. Nat Methods 2013, 10(10):949-55.
  • [42]Tadmouri GO, Nair P, Obeid T, Al Ali MT, Al Khaja N, Hamamy HA: Consanguinity and reproductive health among Arabs. Reprod Health. 2009, 6:17. BioMed Central Full Text
  • [43]Therneau T. 2009;coxme: mixed effects cox models. Available online at: http://cran.r-project.org/web/packages/coxme/coxme.pdf.
  • [44]Infinium HumanMethylation 450 K BeadChip, Datasheet: Epigenetics. 2012.
  • [45]Zudaire E, Cuesta N, Murty V, Woodson K, Adams L, Gonzalez N, et al.: The aryl hydrocarbon receptor repressor is a putative tumor suppressor gene in multiple human cancers. J Clin Invest 2008, 118(2):640-50.
  • [46]Rahman MM, Laher I: Structural and functional alteration of blood vessels caused by cigarette smoking: an overview of molecular mechanisms. Curr Vasc Pharmacol 2007, 5(4):276-92.
  • [47]Bibikova M, Barnes B, Tsan C, Ho V, Klotzle B, Le JM, et al.: High density DNA methylation array with single CpG site resolution. Genomics 2011, 98(4):288-95.
  • [48]Du P, Zhang X, Huang CC, Jafari N, Kibbe WA, Hou L, et al.: Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis. BMC Bioinformatics. 2010, 11:587. BioMed Central Full Text
  • [49]Du P, Kibbe WA, Lin SM: lumi: a pipeline for processing Illumina microarray. Bioinformatics 2008, 24(13):1547-8.
  • [50]Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, et al.: A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics 2013, 29(2):189-96.
  文献评价指标  
  下载次数:26次 浏览次数:19次