DNA methylation and cancer incidence: lymphatic–hematopoietic versus solid cancers in the Strong Heart Study
EntityUAM. Departamento de Medicina Preventiva y Salud Pública y Microbiología
PublisherBioMed Central Ltd.
10.1186/s13148-021-01030-8Clinical Epigenetics 13 (2021): 43
ISSN1868-7075 (print); 1868-7083 (online)
Funded byThis work was supported by grants from the National Heart, Lung, and Blood Institute (NHLBI) (Contract Numbers 75N92019D00027, 75N92019D00028, 75N92019D00029 and 75N92019D00030) and previous Grants (R01HL090863, R01HL109315, R01HL109301, R01HL109284, R01HL109282, and R01HL109319 and Cooperative Agreements: U01HL41642, U01HL41652, U01HL41654, U01HL65520 and U01HL65521); by the National Institute of Environmental Health Sciences (Grant Numbers R01ES021367, R01ES025216, P42ES010349, P30ES009089); by the Chilean CONICYT/FONDECYT-POSTDOCTORADO Nº3180486 and by a fellowship from “la Caixa” Foundation (ID 100010434) (fellowship code “LCF/BQ/DR19/11740016”).
SubjectsAmerican Indians; DNA methylation; Epigenetics; Hematopoietic cancers; Lymphatic cancers; Medicina
Rights© The Author(s) 2021
Esta obra está bajo una Licencia Creative Commons Atribución 4.0 Internacional.
Background: Epigenetic alterations may contribute to early detection of cancer. We evaluated the association of blood DNA methylation with lymphatic–hematopoietic cancers and, for comparison, with solid cancers. We also evaluated the predictive ability of DNA methylation for lymphatic–hematopoietic cancers. Methods: Blood DNA methylation was measured using the Illumina Infinium methylationEPIC array in 2324 Strong Heart Study participants (41.4% men, mean age 56 years). 788,368 CpG sites were available for differential DNA methylation analysis for lymphatic–hematopoietic, solid and overall cancers using elastic-net and Cox regression models. We conducted replication in an independent population: the Framingham Heart Study. We also analyzed differential variability and conducted bioinformatic analyses to assess for potential biological mechanisms. Results: Over a follow-up of up to 28 years (mean 15), we identified 41 lymphatic–hematopoietic and 394 solid cancer cases. A total of 126 CpGs for lymphatic–hematopoietic cancers, 396 for solid cancers, and 414 for overall cancers were selected as predictors by the elastic-net model. For lymphatic–hematopoietic cancers, the predictive ability (C index) increased from 0.58 to 0.87 when adding these 126 CpGs to the risk factor model in the discovery set. The association was replicated with hazard ratios in the same direction in 28 CpGs in the Framingham Heart Study. When considering the association of variability, rather than mean differences, we found 432 differentially variable regions for lymphatic–hematopoietic cancers. Conclusions: This study suggests that differential methylation and differential variability in blood DNA methylation are associated with lymphatic–hematopoietic cancer risk. DNA methylation data may contribute to early detection of lymphatic–hematopoietic cancers.
Google Scholar:Domingo-Relloso, Arce - Huan, Tianxiao - Haack, Karin - Riffo-Campos, Angela L. - Levy, Daniel - Fallin, M. Daniele - Terry, Mary Beth - Zhang, Ying - Rhoades, Dorothy A. - Herreros-Martinez, Miguel - García García-Esquinas, Esther - Cole, Shelley A. - Tellez-Plaza, Maria - Navas-Acien, Ana
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