C Christiansen1, J E Castillo-Fernandez1, A Domingo-Relloso2,3,4, W Zhao5, J S El-Sayed Moustafa1, P-C Tsai1,6,7, J Maddock8, K Haack9, S A Cole9, S L R Kardia5, M Molokhia10, M Suderman11, C Power12, C Relton11,12, A Wong8, D Kuh8, A Goodman13, K S Small1, J A Smith5, M Tellez-Plaza3, A Navas-Acien2, G B Ploubidis13, R Hardy8, J T Bell14. 1. Department of Twin Research and Genetic Epidemiology, King's College London, London, UK. 2. Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA. 3. Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain. 4. Department of Statistics and Operative Research, University of Valencia, Valencia, Spain. 5. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA. 6. Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan. 7. Genomic Medicine Research Core Laboratory, Chang Gung Memorial Hospital, Linkou, Taiwan. 8. MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK. 9. Population Health Program, Texas Biomedical Research Institute, San Antonio, USA. 10. School of Population Health and Environmental Sciences, King's College London, London, UK. 11. MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK. 12. Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK. 13. Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK. 14. Department of Twin Research and Genetic Epidemiology, King's College London, London, UK. jordana.bell@kcl.ac.uk.
Abstract
BACKGROUND: Smoking remains one of the leading preventable causes of death. Smoking leaves a strong signature on the blood methylome as shown in multiple studies using the Infinium HumanMethylation450 BeadChip. Here, we explore novel blood methylation smoking signals on the Illumina MethylationEPIC BeadChip (EPIC) array, which also targets novel CpG-sites in enhancers. METHOD: A smoking-methylation meta-analysis was carried out using EPIC DNA methylation profiles in 1407 blood samples from four UK population-based cohorts, including the MRC National Survey for Health and Development (NSHD) or 1946 British birth cohort, the National Child Development Study (NCDS) or 1958 birth cohort, the 1970 British Cohort Study (BCS70), and the TwinsUK cohort (TwinsUK). The overall discovery sample included 269 current, 497 former, and 643 never smokers. Replication was pursued in 3425 trans-ethnic samples, including 2325 American Indian individuals participating in the Strong Heart Study (SHS) in 1989-1991 and 1100 African-American participants in the Genetic Epidemiology Network of Arteriopathy Study (GENOA). RESULTS: Altogether 952 CpG-sites in 500 genes were differentially methylated between smokers and never smokers after Bonferroni correction. There were 526 novel smoking-associated CpG-sites only profiled by the EPIC array, of which 486 (92%) replicated in a meta-analysis of the American Indian and African-American samples. Novel CpG sites mapped both to genes containing previously identified smoking-methylation signals and to 80 novel genes not previously linked to smoking, with the strongest novel signal in SLAMF7. Comparison of former versus never smokers identified that 37 of these sites were persistently differentially methylated after cessation, where 16 represented novel signals only profiled by the EPIC array. We observed a depletion of smoking-associated signals in CpG islands and an enrichment in enhancer regions, consistent with previous results. CONCLUSION: This study identified novel smoking-associated signals as possible biomarkers of exposure to smoking and may help improve our understanding of smoking-related disease risk.
BACKGROUND: Smoking remains one of the leading preventable causes of death. Smoking leaves a strong signature on the blood methylome as shown in multiple studies using the Infinium HumanMethylation450 BeadChip. Here, we explore novel blood methylation smoking signals on the Illumina MethylationEPIC BeadChip (EPIC) array, which also targets novel CpG-sites in enhancers. METHOD: A smoking-methylation meta-analysis was carried out using EPIC DNA methylation profiles in 1407 blood samples from four UK population-based cohorts, including the MRC National Survey for Health and Development (NSHD) or 1946 British birth cohort, the National Child Development Study (NCDS) or 1958 birth cohort, the 1970 British Cohort Study (BCS70), and the TwinsUK cohort (TwinsUK). The overall discovery sample included 269 current, 497 former, and 643 never smokers. Replication was pursued in 3425 trans-ethnic samples, including 2325 American Indian individuals participating in the Strong Heart Study (SHS) in 1989-1991 and 1100 African-American participants in the Genetic Epidemiology Network of Arteriopathy Study (GENOA). RESULTS: Altogether 952 CpG-sites in 500 genes were differentially methylated between smokers and never smokers after Bonferroni correction. There were 526 novel smoking-associated CpG-sites only profiled by the EPIC array, of which 486 (92%) replicated in a meta-analysis of the American Indian and African-American samples. Novel CpG sites mapped both to genes containing previously identified smoking-methylation signals and to 80 novel genes not previously linked to smoking, with the strongest novel signal in SLAMF7. Comparison of former versus never smokers identified that 37 of these sites were persistently differentially methylated after cessation, where 16 represented novel signals only profiled by the EPIC array. We observed a depletion of smoking-associated signals in CpG islands and an enrichment in enhancer regions, consistent with previous results. CONCLUSION: This study identified novel smoking-associated signals as possible biomarkers of exposure to smoking and may help improve our understanding of smoking-related disease risk.
Entities:
Keywords:
DNA methylation; Environment; Epigenetics; Lifestyle; SLAMF7; Smoking
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