Abstract
Epidemiological studies of DNA methylation (DNAm) profiles may hold substantial promise for identifying mechanisms through which genetic and environmental factors jointly contribute to disease risk. Different cell types are likely to have different DNAm patterns. We investigate the DNAm differences between two types of biospecimens available in many genetic epidemiology studies. We compared DNAm patterns in two different DNA samples from each of 34 participants in the Genetic Epidemiology Network of Arteriopathy study (20 Caucasians and 14 African-Americans). One was extracted from peripheral blood cells (PBC) and the other from transformed B-lymphocytes (TBL). The genome-wide DNAm profiles were compared at over 27,000 genome-wide methylation sites. We found that 26 out of the 34 participants had correlation coefficients higher than 0.9 between methylation profiles of PBC and TBL. Although a high correlation was observed in the DNAm profile between PBC and TBL, we also observed variation across samples from different DNA resources and donors. Using principal component analysis of the DNAm profiles, the two sources of the DNA samples could be accurately predicted. We also identified 3,723 autosomal DNAm sites that had significantly different methylation statuses in PBC compared to TBL (Bonferroni corrected p value <0.05). Both PBC and TBL provide a rich resource for understanding the DNAm profiles in humans participating in epidemiologic studies. While the majority of DNAm findings in PBC and TBL may be consistent, caution must be used when interpreting results because of the possibility of cell type-specific methylation modification.
Similar content being viewed by others
References
Bird A (2007) Perceptions of epigenetics. Nature 447:396–398
Bjornsson HT, Sigurdsson MI, Fallin MD, Irizarry RA, Aspelund T, Cui H, Yu W, Rongione MA, Ekstrom TJ, Harris TB, Launer LJ, Eiriksdottir G, Leppert MF, Sapienza C, Gudnason V, Feinberg AP (2008) Intra-individual change over time in DNA methylation with familial clustering. JAMA 299:2877–2883
Brennan EP, Ehrich M, Brazil DP, Crean JK, Murphy M, Sadlier DM, Martin F, Godson C, McKnight AJ, van den Boom D, Maxwell AP, Savage DA (2009) Comparative analysis of DNA methylation profiles in peripheral blood leukocytes versus lymphoblastoid cell lines. Epigenetics 4:159–164
Bruniquel D, Schwartz RH (2003) Selective, stable demethylation of the interleukin-2 gene enhances transcription by an active process. Nat Immunol 4:235–240
Christensen BC, Houseman EA, Godleski JJ, Marsit CJ, Longacker JL, Roelofs CR, Karagas MR, Wrensch MR, Yeh RF, Nelson HH, Wiemels JL, Zheng S, Wiencke JK, Bueno R, Sugarbaker DJ, Kelsey KT (2009) Epigenetic profiles distinguish pleural mesothelioma from normal pleura and predict lung asbestos burden and clinical outcome. Cancer Res 69:227–234
Chu MW, Siegmund KD, Eckstam CL, Kim JY, Yang AS, Kanel GC, Tavare S, Shibata D (2007) Lack of increases in methylation at three CpG-rich genomic loci in non-mitotic adult tissues during aging. BMC Med Genet 8:50
Chu M, Siegmund KD, Hao QL, Crooks GM, Tavare S, Shibata D (2008) Inferring relative numbers of human leucocyte genome replications. Br J Haematol 141:862–871
Cotran RS, Kumar V, Collins T, Robbins SL (1999) Pathologic basis of disease. WB Saunders, Philadelphia
Daniels PR, Kardia SL, Hanis CL, Brown CA, Hutchinson R, Boerwinkle E, Turner ST, Genetic Epidemiology Network of Arteriopathy study (2004) Familial aggregation of hypertension treatment and control in the Genetic Epidemiology Network of Arteriopathy (GENOA) Study. Am J Med 116:676–681
Davis CD, Ross SA (2007) Dietary components impact histone modifications and cancer risk. Nutr Rev 65:88–94
Dong C, Yoon W, Goldschmidt-Clermont PJ (2002) DNA methylation and atherosclerosis. J Nutr 132:2406S–2409S
Ehrlich M (2003) Expression of various genes is controlled by DNA methylation during mammalian development. J Cell Biochem 88:899–910
FBPP Investigators (2002) Multi-center genetic study of hypertension: the family blood pressure program (FBPP). Hypertension 39:3–9
Fitzpatrick DR, Wilson CB (2003) Methylation and demethylation in the regulation of genes, cells, and responses in the immune system. Clin Immunol 109:37–45
Fitzpatrick DR, Shirley KM, McDonald LE, Bielefeldt-Ohmann H, Kay GF, Kelso A (1998) Distinct methylation of the interferon gamma (IFN-Gamma) and Interleukin 3 (IL-3) genes in newly activated primary CD8+ T lymphocytes: regional IFN-Gamma promoter demethylation and mRNA expression are heritable in CD44(High)CD8+ T cells. J Exp Med 188:103–117
Foley DL, Craig JM, Morley R, Olsson CA, Dwyer T, Smith K, Saffery R (2009) Prospects for epigenetic epidemiology. Am J Epidemiol 169:389–400
Fridman AL, Tainsky MA (2008) Critical pathways in cellular senescence and immortalization revealed by gene expression profiling. Oncogene 27:5975–5987
Herceg Z (2007) Epigenetics and cancer: towards an evaluation of the impact of environmental and dietary factors. Mutagenesis 22:91–103
Illumina (2009) Illumina GenomeStudio methylation module v1.0 user guide, Part # 11319130
Irizarry RA, Ladd-Acosta C, Wen B, Wu Z, Montano C, Onyango P, Cui H, Gabo K, Rongione M, Webster M, Ji H, Potash JB, Sabunciyan S, Feinberg AP (2009) The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat Genet 41:178–186
Kauermann G, Carroll RJ (2001) A note on the efficiency of sandwich covariance matrix estimation. J Am Stat Assoc 96:1387–1396
Kochanek S, Radbruch A, Tesch H, Renz D, Doerfler W (1991) DNA methylation profiles in the human genes for tumor necrosis factors alpha and beta in subpopulations of leukocytes and in leukemias. Proc Natl Acad Sci USA 88:5759–5763
Ladd-Acosta C, Pevsner J, Sabunciyan S, Yolken RH, Webster MJ, Dinkins T, Callinan PA, Fan JB, Potash JB, Feinberg AP (2007) DNA methylation signatures within the human brain. Am J Hum Genet 81:1304–1315
Liang KY, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrika 73:13–22
Lu B, Preisser JS, Qaqish BF, Suchindran C, Bangdiwala SI, Wolfson M (2007) A comparison of two bias-corrected covariance estimators for generalized estimating equations. Biometrics 63:935–941
Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, Sivachenko A, Zhang X, Bernstein BE, Nusbaum C, Jaffe DB, Gnirke A, Jaenisch R, Lander ES (2008) Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 454:766–770
Metivier R, Gallais R, Tiffoche C, Le Peron C, Jurkowska RZ, Carmouche RP, Ibberson D, Barath P, Demay F, Reid G, Benes V, Jeltsch A, Gannon F, Salbert G (2008) Cyclical DNA methylation of a transcriptionally active promoter. Nature 452:45–50
Moverare-Skrtic S, Mellstrom D, Vandenput L, Ehrich M, Ohlsson C (2009) Peripheral blood leukocyte distribution and body mass index are associated with the methylation pattern of the androgen receptor promoter. Endocrine 35:204–210
Namihira M, Kohyama J, Abematsu M, Nakashima K (2008) Epigenetic mechanisms regulating fate specification of neural stem cells. Philos Trans R Soc Lond B Biol Sci 363:2099–2109
Northrop JK, Thomas RM, Wells AD, Shen H (2006) Epigenetic remodeling of the IL-2 and IFN-Gamma loci in memory CD8 T cells is influenced by CD4 T cells. J Immunol 177:1062–1069
O’Brien LM, Fitzmaurice GM (2004) Analysis of longitudinal multiple-source binary data using generalized estimating equations. J R Stat Soc Ser C Appl Stat 53:177–193
Pearce EL, Shen H (2006) Making sense of inflammation, epigenetics, and memory CD8+ T-cell differentiation in the context of infection. Immunol Rev 211:197–202
Reimand J, Kull M, Peterson H, Hansen J, Vilo J (2007) g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Res 35:W193–W200
Richards EJ (2006) Inherited epigenetic variation—revisiting soft inheritance. Nat Rev Genet 7:395–401
Suzuki MM, Bird A (2008) DNA methylation landscapes: provocative insights from epigenomics. Nat Rev Genet 9:465–476
Wilson AG (2008) Epigenetic regulation of gene expression in the inflammatory response and relevance to common diseases. J Periodontol 79:1514–1519
Acknowledgments
This work was supported by National Institute of Health grant NS041558 and HL100185.
Conflict of interest statement
The authors declare that they have no competing interests.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Sun, Y.V., Turner, S.T., Smith, J.A. et al. Comparison of the DNA methylation profiles of human peripheral blood cells and transformed B-lymphocytes. Hum Genet 127, 651–658 (2010). https://doi.org/10.1007/s00439-010-0810-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00439-010-0810-y