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Volume 8 Epidemiology: Open Access
ISSN: 2161-1165 Epidemiology 2018
September 17-19, 2018
September 17-19, 2018 | Rome, Italy
8th International Conference on
Epidemiology & Public Health
Genome-wide interaction study of alcohol consumption on blood pressure: The Korean genome and
epidemiology study (koges)_Ansan and Ansung study
Youngjun Kim1,3, Jihye Kim1 , Bermseok Oh2 and Mi Kyung Kim1
1Hanyang University, Korea
2Kyung Hee University, Korea
3Cheil General Hospital and Women’s Healthcare Center, Korea
Background: Heavy alcohol drinking is a known risk factor for hypertension, however, little is known about the interaction
of gene-alcohol consumption on the blood pressure. We carried out the Genome-wide gene-environment interaction (GEI)
analysis in order to find significant SNPs that interacted alcohol consumption on blood pressure.
Methods: The data were from the Ansan-Ansung community-based cohort in Korean genome and epidemiology study
(KoGES) consisting of epidemiologic data and genome-wide SNPs data among 10,030 study participants aged 40-69 years
old. Gene-alcohol interaction analysis on blood pressure was analyzed by multiple linear regression in PLINK in men study
participants. The blood pressure was represented by two traits of systolic blood pressure (SBP), diastolic blood pressure (DBP).
10% False Discovery Rate (FDR) was considered to determine significant SNPs in this analysis.
Results: The 15 index SNPs showed significant interaction (10% FDR, P< 9.07e-07) with alcohol consumption on DBP in men
participants.
Conclusion and Discussion: Among the 15 findings in this analysis, two index SNPs, rs1297184 (LGR5) and rs78333128
(RSPO3) were known to be involved Renin-angiotensin system on blood pressure regulation. However, there have been no
reports about its interaction with alcohol consumption on blood pressure. Thus, this finding could contribute to explain blood
pressure regulation by interaction of gene-alcohol consumption.
Recent Publications:
1. Marmot, M.G., et al. (1994), Alcohol and blood pressure: the INTERSALT study. Bmj, 308(6939): p. 1263-1267.
2. Cho, Y.S., et al. (2009), A large-scale genome-wide association study of Asian populations uncovers genetic factors
influencing eight quantitative traits. Nature genetics 41: 527–534.
3. Benjamini, Y. and Y. Hochberg (1995), Controlling the false discovery rate: a practical and powerful approach to
multiple testing. Journal of the royal statistical society. Series B (Methodological): p. 289-300.
4. Shaikh, L.H., et al. (2015), LGR5 activates noncanonical Wnt signaling and inhibits aldosterone production in the
human adrenal. The Journal of Clinical Endocrinology & Metabolism 100(6): E836-E844.
5. Tomaschitz, A., et al. (2010), Aldosterone and arterial hypertension. Nature Reviews Endocrinology, 6(2): p. 83.
Biography
Youngjun Kim has his expertise in evaluation and passion in improving the public health and wellbeing. He works in Cheil General Hospital & Women's Healthcare
Center as a researcher and studies epidemiology in doctoral course.
Youngjun Kim et al., Epidemiology (Sunnyvale) 2018, Volume 8
DOI: 10.4172/2161-1165-C1-021