Genetic Variants Influencing Circulating Lipid Levels and Risk of Coronary Artery Disease
Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides.
We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)).
We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.
Available from: Xin Chu
- "level of statistical significance. The well-documented association of LDL-C levels with APOE on chromosome 19 (Waterworth et al., 2010), was also detected, with a p-value of 1.56 × 10 −12 . "
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ABSTRACT: A variety of health-related data are commonly deposited into electronic health records (EHRs), including laboratory, diagnostic, and medication information. The digital nature of EHR data facilitates efficient extraction of these data for research studies, including genome-wide association studies (GWAS). Previous GWAS have identified numerous SNPs associated with variation in total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). These findings have led to the development of specialized genotyping platforms that can be used for fine-mapping and replication in other populations. We have combined the efficiency of EHR data and the economic advantages of the Illumina Metabochip, a custom designed SNP chip targeted to traits related to coronary artery disease, myocardial infarction, and type 2 diabetes, to conduct an array-wide analysis of lipid traits in a population with extreme obesity. Our analyses identified associations with 12 of 21 previously identified lipid-associated SNPs with effect sizes similar to prior results. Association analysis using several approaches to account for lipid-lowering medication use resulted in fewer and less strongly associated SNPs. The availability of phenotype data from the EHR and the economic efficiency of the specialized Metabochip can be exploited to conduct multi-faceted genetic association analyses.
Frontiers in Genetics 08/2014; 5:222. DOI:10.3389/fgene.2014.00222
Available from: Takao Ando
- "The present study indicated that TG was associated with TRIB1 rs2954029 only in women, which was partially consistent with previous studies (Teslovich et al. 2010; Waterworth et al. 2010; Zhang et al. 2011) because TC, LDL-C, and HDL-C were not associated with TRIB1 rs2954029 in this study. This difference might be due to the relatively small sample size compared to previous studies. "
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ABSTRACT: Recent genome-wide association studies have identified Tribbles homolog 1 (TRIB1) as one of the candidate genes associated with lipid profiles. TRIB1 is known to interact with MAP kinases, thereby regulating their activities. The single nucleotide polymorphism rs2954029 of TRIB1 is located within an intron and is associated with lipid profiles. The aim of the present study is to investigate the TRIB1 rs2954029 (A>T polymorphism) with conventional predictors of coronary artery diseases such as carotid intima-media thickness (CIMT) and cardio-ankle vascular index (CAVI), and with lipid profiles in general population. This study enrolled 2,581 Japanese adults, 942 men and 1,639 women with a median age of 68 years (range 29 to 94 years), who participated in a screening program for the general population living in Goto City, Nagasaki Prefecture, Japan from 2008 to 2010. For the determination of TRIB1 rs2954029 genotypes, the polymerase chain reaction method was used. The differences in each parameter among the TRIB1 rs2954029 genotypes were evaluated using analysis of covariance. Genotype frequencies of TRIB1 rs2954029 in all participants were 25.5% for AA, 50.4% for AT, and 24.0% for TT. In women, the AA genotype showed significantly higher log triglyceride (TG) concentrations than the AT genotype (P = 0.004) and the AT + TT genotypes (P = 0.004). On the other hand, there were no associations with CIMT and CAVI among the TRIB1 rs2954029 genotypes. In conclusion, the TRIB1 rs2954029 is associated with serum TG concentrations in Japanese community-dwelling women.
The Tohoku Journal of Experimental Medicine 06/2014; 233(2):149-53. DOI:10.1620/tjem.233.149 · 1.35 Impact Factor
Available from: José A Casasnovas
- "The association of the rs17248720 polymorphism with hypercholesterolemia confirms previous observations from GWAS suggesting that non-coding variants located at the LDLR locus are associated with blood lipid levels, including LDL-C [8,9,12,13]. While studies attempt to find new loci implicated in the hereditability of lipid levels, the strongest locus associated with LDL-C continues to be that containing the LDLR gene . "
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ABSTRACT: GWAS have consistently revealed that LDLR locus variability influences LDL-cholesterol in general population. Severe LDLR mutations are responsible for familial hypercholesterolemia (FH). However, most primary hypercholesterolemias are polygenic diseases. Although Cis-regulatory regions might be the cause of LDL-cholesterol variability; an extensive analysis of the LDLR distal promoter has not yet been performed. We hypothesized that genetic variants in this region are responsible for the LDLR association with LDL-cholesterol found in GWAS.
Four-hundred seventy-seven unrelated subjects with polygenic hypercholesterolemia (PH) and without causative FH-mutations and 525 normolipemic subjects were selected. A 3103 pb from LDLR (-625 to +2468) was sequenced in 125 subjects with PH. All subjects were genotyped for 4 SNPs (rs17242346, rs17242739, rs17248720 and rs17249120) predicted to be potentially involved in transcription regulation by in silico analysis. EMSA and luciferase assays were carried out for the rs17248720 variant. Multivariable linear regression analysis using LDL-cholesterol levels as the dependent variable were done in order to find out the variables that were independently associated with LDL-cholesterol.
The sequencing of the 125 PH subjects did not show variants with minor allele frequency >= 10%. The T-allele from g.3131C > T (rs17248720) had frequencies of 9% (PH) and 16.4% (normolipemic), p < 0.00001. Studies of this variant with EMSA and luciferase assays showed a higher affinity for transcription factors and an increase of 2.5 times in LDLR transcriptional activity (T-allele vs C-allele). At multivariate analysis, this polymorphism with the lipoprotein(a) and age explained [almost equal to] 10% of LDL-cholesterol variability.
Our results suggest that the T-allele at the g.3131 T > C SNP is associated with LDL-cholesterol levels, and explains part of the LDL-cholesterol variability. As a plausible cause, the T-allele produces an increase in LDLR transcriptional activity and lower LDL-cholesterol levels.
BMC Medical Genomics 04/2014; 7(1):17. DOI:10.1186/1755-8794-7-17 · 2.87 Impact Factor
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