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3 "Gene-environment interaction"
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Perspective
Necessity of Epigenetic Epidemiology Studies on the Carcinogenesis of Lung Cancer in Never Smokers
Jong-Myon Bae
J Prev Med Public Health. 2018;51(5):263-264.   Published online July 8, 2018
DOI: https://doi.org/10.3961/jpmph.18.076
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AbstractAbstract PDFSupplementary Material
Based on epidemiological and genomic characteristics, lung cancer in never smokers (LCNS) is a different disease from lung cancer in smokers. Based on current research, the main risk factor for LCNS may be air pollution. A recent case-control study in Koreans reported that nitrogen dioxide (NO2) may be a risk factor for LCNS. Additionally, a cohort study showed that exposure to NO2 was associated with significant hypomethylation. Thus, epigenetic epidemiology studies are needed in the near future to evaluate the carcinogenesis of LCNS according to chronic exposure to air pollution and/or viral infections.
Summary
Original Article
Replication of Early B-cell Factor 1 (EBF1) Gene-by-psychosocial Stress Interaction Effects on Central Adiposity in a Korean Population
Hyun-Jin Kim, Jin-Young Min, Kyoung-Bok Min
J Prev Med Public Health. 2016;49(5):253-259.   Published online July 10, 2016
DOI: https://doi.org/10.3961/jpmph.16.028
  • 9,864 View
  • 157 Download
  • 2 Crossref
AbstractAbstract PDF
Objectives
Central obesity plays a major role in the development of many chronic diseases, including cardiovascular disease and cancer. Chronic stress may be involved in the pathophysiology of central obesity. Although several large-scale genome-wide association studies have reported susceptibility genes for central adiposity, the effects of interactions between genes and psychosocial stress on central adiposity have rarely been examined. A recent study focusing on Caucasians discovered the novel gene , which was associated with central obesity-related traits via interactions with stress levels. We aimed to evaluate EBF1 gene-by-stress interaction effects on central adiposity traits, including visceral adipose tissue (VAT), in Korean adults.
Methods
A total of 1467 Korean adults were included in this study. We selected 22 single-nucleotide polymorphisms (SNPs) in the EBF1 gene and analyzed their interactions with stress on central adiposity using additive, dominant, and recessive genetic modeling.
Results
The four SNPs that had strong linkage disequilibrium relationships (rs10061900, rs10070743, rs4704967, and rs10056564) demonstrated significant interactions with the waist-hip ratio in the dominant model (pint<0.007). In addition, two other SNPs (rs6556377 and rs13180086) were associated with VAT by interactions with stress levels, especially in the recessive genetic model (pint<0.007). As stress levels increased, the mean values of central adiposity traits according to SNP genotypes exhibited gradual but significant changes (p<0.05).
Conclusions
These results suggest that the common genetic variants for EBF1 are associated with central adiposity through interactions with stress levels, emphasizing the importance of managing stress in the prevention of central obesity.
Summary

Citations

Citations to this article as recorded by  
  • Nipping Adipocyte Inflammation in the Bud
    Michael J. Griffin
    Immunometabolism.2021;[Epub]     CrossRef
  • The Emerging Role of Zfp217 in Adipogenesis
    Hong Xiang, Zhu-Xia Zhong, Yong-Dong Peng, Si-Wen Jiang
    International Journal of Molecular Sciences.2017; 18(7): 1367.     CrossRef
English Abstract
Statistical Issues in Genomic Cohort Studies.
Sohee Park
J Prev Med Public Health. 2007;40(2):108-113.
DOI: https://doi.org/10.3961/jpmph.2007.40.2.108
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  • 26 Download
AbstractAbstract PDF
When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.
Summary

JPMPH : Journal of Preventive Medicine and Public Health