Abstract:Background and aims:The APOE ε4 genotype has a higher risk for developing coronary artery disease (CAD), but there is preliminary evidence that antioxidative lifestyle factors interact with APOE genotype on CAD risk. Here, we assessed the effect modification of physical activity, oily fish and polyunsaturated fatty acid (PUFA) intake with APOE genotype on risk of incident CAD. Methods: The present study comprised 345,659 white European participants from UK Biobank (mean age: 56.5 years, 45.7% men) without a hi… Show more
“…The locus surrounding rs5117 near the APOE / APOC cluster was the most pleiotropic, associated with the variance of nine biomarkers (including lipids [TC, LDL-C, HDL-C, TG], lipoproteins [ApoA, ApoB, LipA], liver enzymes [ALT], and hsCRP). This locus has strong main effects on the same biomarkers and is known to interact with lifestyle factors in determining cardiovascular disease risk 19 . Fig.…”
Gene-environment interactions represent the modification of genetic effects by environmental exposures and are critical for understanding disease and informing personalized medicine. These often induce differential phenotypic variance across genotypes; these variance-quantitative trait loci can be prioritized in a two-stage interaction detection strategy to greatly reduce the computational and statistical burden and enable testing of a broader range of exposures. We perform genome-wide variance-quantitative trait locus analysis for 20 serum cardiometabolic biomarkers by multi-ancestry meta-analysis of 350,016 unrelated participants in the UK Biobank, identifying 182 independent locus-biomarker pairs (p < 4.5×10−9). Most are concentrated in a small subset (4%) of loci with genome-wide significant main effects, and 44% replicate (p < 0.05) in the Women’s Genome Health Study (N = 23,294). Next, we test each locus-biomarker pair for interaction across 2380 exposures, identifying 847 significant interactions (p < 2.4×10−7), of which 132 are independent (p < 0.05) after accounting for correlation between exposures. Specific examples demonstrate interaction of triglyceride-associated variants with distinct body mass- versus body fat-related exposures as well as genotype-specific associations between alcohol consumption and liver stress at the ADH1B gene. Our catalog of variance-quantitative trait loci and gene-environment interactions is publicly available in an online portal.
“…The locus surrounding rs5117 near the APOE / APOC cluster was the most pleiotropic, associated with the variance of nine biomarkers (including lipids [TC, LDL-C, HDL-C, TG], lipoproteins [ApoA, ApoB, LipA], liver enzymes [ALT], and hsCRP). This locus has strong main effects on the same biomarkers and is known to interact with lifestyle factors in determining cardiovascular disease risk 19 . Fig.…”
Gene-environment interactions represent the modification of genetic effects by environmental exposures and are critical for understanding disease and informing personalized medicine. These often induce differential phenotypic variance across genotypes; these variance-quantitative trait loci can be prioritized in a two-stage interaction detection strategy to greatly reduce the computational and statistical burden and enable testing of a broader range of exposures. We perform genome-wide variance-quantitative trait locus analysis for 20 serum cardiometabolic biomarkers by multi-ancestry meta-analysis of 350,016 unrelated participants in the UK Biobank, identifying 182 independent locus-biomarker pairs (p < 4.5×10−9). Most are concentrated in a small subset (4%) of loci with genome-wide significant main effects, and 44% replicate (p < 0.05) in the Women’s Genome Health Study (N = 23,294). Next, we test each locus-biomarker pair for interaction across 2380 exposures, identifying 847 significant interactions (p < 2.4×10−7), of which 132 are independent (p < 0.05) after accounting for correlation between exposures. Specific examples demonstrate interaction of triglyceride-associated variants with distinct body mass- versus body fat-related exposures as well as genotype-specific associations between alcohol consumption and liver stress at the ADH1B gene. Our catalog of variance-quantitative trait loci and gene-environment interactions is publicly available in an online portal.
“…These plaques can erode or rapture, while the coagulatory proteins circulating in the blood can interact with them, resulting in thrombosis and acute coronary syndrome [198,199]. Chronic CAD can cause heart failure [200], altered heart rate [201], myocardial ischemia, and left ventricular dysfunction [202]. In epidemiological research, the risk pattern for coronary artery disease has been thoroughly investigated.…”
Section: Coronary Artery Disease (Cad) and Lycopenementioning
Lycopene is a bioactive red pigment found in plants, especially in red fruits and vegetables, including tomato, pink guava, papaya, pink grapefruit, and watermelon. Several research reports have advocated its positive impact on human health and physiology. For humans, lycopene is an essential substance obtained from dietary sources to fulfil the body requirements. The production of reactive oxygen species (ROS) causing oxidative stress and downstream complications include one of the major health concerns worldwide. In recent years, oxidative stress and its counter strategies have attracted biomedical research in order to manage the emerging health issues. Lycopene has been reported to directly interact with ROS, which can help to prevent chronic diseases, including diabetes and neurodegenerative and cardiovascular diseases. In this context, the present review article was written to provide an accumulative account of protective and ameliorative effects of lycopene on coronary artery disease (CAD) and hypertension, which are the leading causes of death worldwide. Lycopene is a potent antioxidant that fights ROS and, subsequently, complications. It reduces blood pressure via inhibiting the angiotensin-converting enzyme and regulating nitrous oxide bioavailability. It plays an important role in lowering of LDL (low-density lipoproteins) and improving HDL (high-density lipoproteins) levels to minimize atherosclerosis, which protects the onset of coronary artery disease and hypertension. Various studies have advocated that lycopene exhibited a combating competence in the treatment of these diseases. Owing to all the antioxidant, anti-diabetic, and anti-hypertensive properties, lycopene provides a potential nutraceutical with a protective and curing ability against coronary artery disease and hypertension.
“…2,5 ApoE gene polymorphisms affect lipoprotein clearing and lipid profile, and also the development of CAD. 6,7 Lipid metabolism is influenced by ApoE genotypes. A previous study found that ε4 carriers can increase CAD risk by approximately 42%.…”
Purpose
The association between apolipoprotein E (ApoE) gene polymorphisms and the risk of coronary artery disease (CAD) among different populations has been assessed in numerous previous studies, but the results remain inconclusive. The present study aimed to determine the role of ApoE genotypes in CAD risk and the interrelationships between lipid profiles and ApoE alleles and genotypes among the population of northwest China.
Patients and Methods
This study was performed on 308 patients with CAD and 308 control participants. ApoE gene polymorphism was analysed using the polymerase chain reaction and hybridization.
Results
The findings indicated that the frequencies of ε3/ε4 genotype and ε4 allele frequency were significantly higher in patients with CAD than in the control participants. ε2 carriers had significantly lower total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and triglycerides (TG) levels than did ε3 or ε4 carriers among the control participants. However, our study found no significant differences in plasma lipoprotein levels between ɛ2, ɛ3 and ɛ4 carriers in patients with CAD. Moreover, ε4 carriers had significantly higher ApoB, ApoB/ApoA-I levels and significantly lower ApoE levels in both patients with CAD and control participants. ε4 allele presence was associated with a nearly two-fold higher CAD risk. After adjusting for other established risk factors, ε4 allele was an independent risk factor for CAD. After stratified by age (≤ 60 years and >60 years), ε4 allele was indicated to increase the CAD risk 3.3-fold in elderly patients with CAD, but not in young patients with CAD. After stratified by sex, ε4 allele was not a risk factor in females and males patients with CAD.
Conclusion
This study provides evidence that the ε4 allele, drinking, smoking, hypertension, and TG and ApoE levels are independent risk factor for CAD among patients in northwest China.
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