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| Home > Publications database > Association of leukocyte DNA methylation changes with dietary folate and alcohol intake in the EPIC study. > print |
| 001 | 143520 | ||
| 005 | 20240229112556.0 | ||
| 024 | 7 | _ | |a 10.1186/s13148-019-0637-x |2 doi |
| 024 | 7 | _ | |a pmid:30940212 |2 pmid |
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| 037 | _ | _ | |a DKFZ-2019-01104 |
| 041 | _ | _ | |a eng |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Perrier, F. |b 0 |
| 245 | _ | _ | |a Association of leukocyte DNA methylation changes with dietary folate and alcohol intake in the EPIC study. |
| 260 | _ | _ | |a [S.l.] |c 2019 |b BioMed Central |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1556109743_27237 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a There is increasing evidence that folate, an important component of one-carbon metabolism, modulates the epigenome. Alcohol, which can disrupt folate absorption, is also known to affect the epigenome. We investigated the association of dietary folate and alcohol intake on leukocyte DNA methylation levels in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Leukocyte genome-wide DNA methylation profiles on approximately 450,000 CpG sites were acquired with Illumina HumanMethylation 450K BeadChip measured among 450 women control participants of a case-control study on breast cancer nested within the EPIC cohort. After data preprocessing using surrogate variable analysis to reduce systematic variation, associations of DNA methylation with dietary folate and alcohol intake, assessed with dietary questionnaires, were investigated using CpG site-specific linear models. Specific regions of the methylome were explored using differentially methylated region (DMR) analysis and fused lasso (FL) regressions. The DMR analysis combined results from the feature-specific analysis for a specific chromosome and using distances between features as weights whereas FL regression combined two penalties to encourage sparsity of single features and the difference between two consecutive features.After correction for multiple testing, intake of dietary folate was not associated with methylation level at any DNA methylation site, while weak associations were observed between alcohol intake and methylation level at CpG sites cg03199996 and cg07382687, with qval = 0.029 and qval = 0.048, respectively. Interestingly, the DMR analysis revealed a total of 24 and 90 regions associated with dietary folate and alcohol, respectively. For alcohol intake, 6 of the 15 most significant DMRs were identified through FL.Alcohol intake was associated with methylation levels at two CpG sites. Evidence from DMR and FL analyses indicated that dietary folate and alcohol intake may be associated with genomic regions with tumor suppressor activity such as the GSDMD and HOXA5 genes. These results were in line with the hypothesis that epigenetic mechanisms play a role in the association between folate and alcohol, although further studies are warranted to clarify the importance of these mechanisms in cancer. |
| 536 | _ | _ | |a 313 - Cancer risk factors and prevention (POF3-313) |0 G:(DE-HGF)POF3-313 |c POF3-313 |f POF III |x 0 |
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| 700 | 1 | _ | |a Viallon, V. |b 1 |
| 700 | 1 | _ | |a Ambatipudi, S. |b 2 |
| 700 | 1 | _ | |a Ghantous, A. |b 3 |
| 700 | 1 | _ | |a Cuenin, C. |b 4 |
| 700 | 1 | _ | |a Hernandez-Vargas, H. |b 5 |
| 700 | 1 | _ | |a Chajès, V. |b 6 |
| 700 | 1 | _ | |a Baglietto, L. |b 7 |
| 700 | 1 | _ | |a Matejcic, M. |b 8 |
| 700 | 1 | _ | |a Moreno-Macias, H. |b 9 |
| 700 | 1 | _ | |a Kühn, T. |0 P:(DE-He78)0907a10ba1dc8f53f04907f54f6fdcfe |b 10 |u dkfz |
| 700 | 1 | _ | |a Boeing, H. |b 11 |
| 700 | 1 | _ | |a Karakatsani, A. |b 12 |
| 700 | 1 | _ | |a Kotanidou, A. |b 13 |
| 700 | 1 | _ | |a Trichopoulou, A. |b 14 |
| 700 | 1 | _ | |a Sieri, S. |b 15 |
| 700 | 1 | _ | |a Panico, S. |b 16 |
| 700 | 1 | _ | |a Fasanelli, F. |b 17 |
| 700 | 1 | _ | |a Dolle, M. |b 18 |
| 700 | 1 | _ | |a Onland-Moret, C. |b 19 |
| 700 | 1 | _ | |a Sluijs, I. |b 20 |
| 700 | 1 | _ | |a Weiderpass, E. |b 21 |
| 700 | 1 | _ | |a Quirós, J. R. |b 22 |
| 700 | 1 | _ | |a Agudo, A. |b 23 |
| 700 | 1 | _ | |a Huerta, J. M. |b 24 |
| 700 | 1 | _ | |a Ardanaz, E. |b 25 |
| 700 | 1 | _ | |a Dorronsoro, M. |b 26 |
| 700 | 1 | _ | |a Tong, T. Y. N. |b 27 |
| 700 | 1 | _ | |a Tsilidis, K. |b 28 |
| 700 | 1 | _ | |a Riboli, E. |b 29 |
| 700 | 1 | _ | |a Gunter, M. J. |b 30 |
| 700 | 1 | _ | |a Herceg, Z. |b 31 |
| 700 | 1 | _ | |a Ferrari, P. |b 32 |
| 700 | 1 | _ | |a Romieu, I. |b 33 |
| 773 | _ | _ | |a 10.1186/s13148-019-0637-x |g Vol. 11, no. 1, p. 57 |0 PERI:(DE-600)2553921-8 |n 1 |p 57 |t Clinical epigenetics |v 11 |y 2019 |x 1868-7083 |
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