Associations of lipoprotein lipase gene rs326 with changes of lipid profiles after a high-carbohydrate and low-fat diet in healthy Chinese Han youth

Genetic association of LPL rs326 with BMI among the Kuwaiti population

Supplemental Digital Content is available in the text.

Lipoprotein lipase is a key enzyme in lipid metabolism with reported variants associated with obesity, hypertension, type 2 diabetes, and coronary heart disease. This study was performed to investigate the association between common lipoprotein lipase single nucleotide polymorphisms and metabolic disorders in a sample of Kuwaiti cohort (n = 494). Five lipoprotein lipase variants (rs1801177, rs295, rs326, ss2137497749, and ss2137497750) across the lipoprotein lipase gene were genotyped by real-time PCR employing the TaqMan allele discrimination assay. Genotype, allelic frequencies, and Hardy-Weinberg Equilibrium were determined for each variant in the cohort followed by multivariate and logistic regression analysis. A novel finding was observed for the G allele of single nucleotide polymorphism rs326 which was associated with increased BMI after adjusting for age and sex (β = 1.04; 95% confidence interval = 0.15–1.94; P = 0.02). Moreover, a significant difference in the distribution of the minor C allele of rs295 among coronary heart disease subjects compared with noncoronary heart disease, however, this significance was diminished after controlling for age, sex, and BMI. This study demonstrated that lipoprotein lipase rs326 may be indicative for the increased risk of obesity and possibly rs295 for coronary heart disease. The findings are also in agreement with other reports suggesting that intronic variants are important genetic markers in association studies. The findings warrant further studies in a large cohort to confirm and validate the results presented.

Common Genetic Variations Involved in the Inter-Individual Variability of Circulating Cholesterol Concentrations in Response to Diets: A Narrative Review of Recent Evidence

The number of nutrigenetic studies dedicated to the identification of single nucleotide polymorphisms (SNPs) modulating blood lipid profiles in response to dietary interventions has increased considerably over the last decade. However, the robustness of the evidence-based science supporting the area remains to be evaluated. The objective of this review was to present recent findings concerning the effects of interactions between SNPs in genes involved in cholesterol metabolism and transport, and dietary intakes or interventions on circulating cholesterol concentrations, which are causally involved in cardiovascular diseases and established biomarkers of cardiovascular health. We identified recent studies (2014-2020) that reported significant SNP-diet interactions in 14 cholesterol-related genes (NPC1L1, ABCA1, ABCG5, ABCG8, APOA1, APOA2, APOA5, APOB, APOE, CETP, CYP7A1, DHCR7, LPL, and LIPC), and which replicated associations observed in previous studies. Some studies have also shown that combinations of SNPs could explain a higher proportion of variability in response to dietary interventions. Although some findings still need replication, including in larger and more diverse study populations, there is good evidence that some SNPs are consistently associated with differing circulating cholesterol concentrations in response to dietary interventions. These results could help clinicians provide patients with more personalized dietary recommendations, in order to lower their risk for cardiovascular disease.

There is an association between a genetic polymorphism in the ZNF259 gene involved in lipid metabolism and coronary artery disease

BACKGROUND

Recent genome-wide association studies (GWAS) have identified several genetic variants that influence the risk of dyslipidemia and coronary artery disease (CAD). In this study, we have examined the potential association of five SNPs variants related to lipid pathway, previously identified in GWAS studies (ZNF259 C>G, CETP I405VA/G, LPA C>T, LPLS447X and PSRC1 A>G) with CAD.

METHODS

Two hundred and ninety subjects including 194 patients with coronary artery disease and 96 controls were enrolled, followed by the analyses of anthropometric/biochemical parameters. Genotyping was carried out using Taq-Man real-time PCR based method. The association of the genetic polymorphisms with CAD was determined using univariate and multivariate analyses.

RESULTS

CAD patients had a higher (p < 0.05) fasting blood glucose (FBG), total cholesterol (TC), high sensitivity C-reactive protein (hs-CRP), low-density lipoprotein cholesterol (LDL-C) and waist circumference. Results showed that subjects with CETP rs5882 genetic variant, AA&AG genotypes, had a higher risk of developing Coronary artery disease [OR: 2.1, 95% CI (1.2-4.1), p value = 0.015]. Also subjects who carried the G allele of the ZNF259 polymorphism were at an increased the risk of developing CAD [OR 1.86, 95% CI: 1.06-3.25, p value = 0.029] and had an increased TC, LDL and TG levels (p < 0.05). Furthermore, no statistically significant association was found between genetic polymorphisms of PSRC1 A>G, LPL S447X and LPA C>T and CAD.

CONCLUSION

We identified a relationship between a genetic variant in CETP and ZNF259 gene with CAD and CAD and lipid profile, respectively. Further investigation in a larger population may help to investigate the value of emerging marker as a risk stratification marker in CAD and its risk factors.

Prediction of cholesterol ratios within a Korean population

Cholesterol ratios (total cholesterol (TC)/high-density lipoprotein cholesterol (HDL-c) and triglyceride (TG)/HDL-c) have been suggested as better indicators to predict various clinical features such as insulin resistance and heart disease. Therefore, we aimed to build a single nucleotide polymorphism (SNP) set to predict constitutional lipid metabolism. The genotype data of 7795 samples were obtained from the Korea Association Resource. Among the total of 7795 samples, 7016 subjects were used to perform 10-fold cross-validation. We selected the SNPs that showed significance constantly throughout all 10 cross-validation sets; another 779 samples were used as the final validation set. After performing the 10-fold cross-validation, the six SNPs (rs4420638 (APOC1), rs12421652 (BUD13), rs17411126 (LPL), rs6589566 (ZPR1), rs16940212 (LOC101928635) and rs10852765 (ABCA8)) were finally selected for predicting cholesterol ratios. The weighted genetic risk scores (wGRS) were calculated based on the regression slopes of the six selected SNPs. Our results showed upward trends of wGRS for both the TC/HDL-c and TG/HDL-c ratios within the 10-fold cross-validation. Similarly, the wGRS of the six SNPs also showed upward trends in analyses using the SNP selection set and final validation set. The selected six SNPs can be used to explain both the TC/HDL-c and TG/HDL-c ratios. Our results may be useful for the prospective predictions of cholesterol-related diseases.