Association between Genetic Variations Affecting Mean Telomere Length and the Prevalence of Hypertension and Coronary Heart Disease in Koreans.
Jean Kyung PaikRyungwoo KangYoonsu ChoMin-Jeong ShinPublished in: Clinical nutrition research (2016)
In this study, we investigated whether the single nucleotide polymorphisms (SNPs) associated with telomere length (TL) were associated with the incidence of hypertension (HTN)/coronary heart disease (CHD) and cardiovascular risk factors in the Korean population. Data from 5,705 (ages 39-70) participants in the Korean Genome Epidemiology Study (rural Ansung and urban Ansan cohorts) were studied. Twelve SNPs known to be associated with telomere biology were tested for an association with HTN/CHD. As results, no significant associations were found between the selected TL-related SNPs and prevalence of HTN and CHD. Among non-alcohol users, subjects with minor alleles in rs1269304 and rs10936601 (TERC and LRRC34, respectively) exhibited a higher rate of CHD occurrence (odds ratio [OR], 1.862; 95% confidence intervals [CIs], 1.137, 3.049; OR, 1.855; 95% CIs, 1.111, 2.985; respectively). However, alcohol users with minor alleles in rs398652 (PELI2) were significantly associated with higher HTN prevalence (OR, 1.179; 95% CIs, 1.040, 1.336). Of the 3 SNPs related to disease outcomes, rs1296304 was significantly associated with increased levels of diastolic blood pressure (β estimate, 0.470; 95% CIs, 0.013, 0.926). The minor allele in rs398652 was significantly associated with higher levels of body mass index (OR, 0.128; 95% CIs, 0.010, 0.246) and γ-glutamyl transpeptidase (OR, 0.013; 95% CIs, 0.001, 0.024). In conclusion, there were no significant associations between the selected TL-related SNPs and the occurrence of HTN/CHD in Koreans. However, the results suggest the presence of a possible interaction between related SNPs and alcohol behavior associated with HTN/CHD occurrence.
Keyphrases
- blood pressure
- genome wide
- risk factors
- body mass index
- cardiovascular risk factors
- risk assessment
- cardiovascular disease
- gene expression
- physical activity
- type diabetes
- big data
- heart failure
- left ventricular
- mass spectrometry
- alcohol consumption
- machine learning
- blood glucose
- copy number
- drug induced
- atomic force microscopy
- ejection fraction
- weight gain