Dataset Information

Association of cholesteryl ester transfer protein (CETP) gene polymorphism, high density lipoprotein cholesterol and risk of coronary artery disease: a meta-analysis using a Mendelian randomization approach.

ABSTRACT:

Background

Recent randomized controlled trials have challenged the concept that increased high density lipoprotein cholesterol (HDL-C) levels are associated with coronary artery disease (CAD) risk reduction. The causal role of HDL-C in the development of atherosclerosis remains unclear. To increase precision and to minimize residual confounding, we exploited the cholesteryl ester transfer protein (CETP)-TaqIB polymorphism as an instrument based on Mendelian randomization.

Methods

The Mendelian randomization analysis was performed by two steps. First, we conducted a meta-analysis of 47 studies, including 23,928 cases and 27,068 controls, to quantify the relationship between the TaqIB polymorphism and the CAD risk. Next, the association between the TaqIB polymorphism and HDL-C was assessed among 5,929 Caucasians. We further employed Mendelian randomization to evaluate the causal effect of HDL-C on CAD based on the findings from the meta-analysis.

Results

The overall comparison of the B2 allele with the B1 allele yielded a significant risk reduction of CAD (P < 0.0001; OR = 0.88; 95% CI: 0.84-0.92) with substantial between-study heterogeneity (I² = 55.2%; P(heterogeneity) <0.0001). The result was not materially changed after excluding the Hardy-Weinberg Equilibrium (HWE)-violation studies. Compared with B1B1 homozygotes, Caucasian carriers of the B2 allele had a 0.25 mmol/L increase in HDL-C level (95% CI: 0.20-0.31; P <0.0001; I² = 0; P(heterogeneity) =0.87). However, a 1 standard deviation (SD) elevation in HDL-C levels due to the TaqIB polymorphism, was marginal associated with CAD risk (OR =0.79; 95% CI: 0.54-1.03; P =0.08).

Conclusions

Taken together, our results lend support to the concept that increased HDL-C cannot be translated into a reduction in CAD risk.

SUBMITTER: Wu Z

PROVIDER: S-EPMC4258818 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Publications

Association of cholesteryl ester transfer protein (CETP) gene polymorphism, high density lipoprotein cholesterol and risk of coronary artery disease: a meta-analysis using a Mendelian randomization approach.

Wu Zhijun Z Lou Yuqing Y Qiu Xiaochun X Liu Yan Y Lu Lin L Chen Qiujing Q Jin Wei W

BMC medical genetics 20141023

<h4>Background</h4>Recent randomized controlled trials have challenged the concept that increased high density lipoprotein cholesterol (HDL-C) levels are associated with coronary artery disease (CAD) risk reduction. The causal role of HDL-C in the development of atherosclerosis remains unclear. To increase precision and to minimize residual confounding, we exploited the cholesteryl ester transfer protein (CETP)-TaqIB polymorphism as an instrument based on Mendelian randomization.<h4>Methods</h4> ...[more]

PMID: 25366166

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Project description:PurposeThe aim of this study was to investigate the causal relationship between low-density lipoprotein cholesterol (LDL-C) and five cancers (breast, cervical, thyroid, prostate and colorectal) using the Mendelian Randomization (MR) method, with a view to revealing the potential role of LDL-C in the development of these cancers.MethodsWe used gene variant data and disease data from the Genome-Wide Association Study (GWAS) database to assess the causal relationship between LDL-C and each cancer by Mendelian randomisation analysis methods such as inverse variance weighting and MR-Egger. Specifically, we selected Proprotein convertase subtilisin/kexin type 9 (PCSK9) and 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), genes associated with LDL-C levels, as instrumental variables, extracted the corresponding single nucleotide polymorphism (SNP) data and analysed the associations of these SNPs with five cancers.In addition, sensitivity analyses and heterogeneity tests were performed to ensure the reliability of the results.ResultsThe analyses showed that when using HMGCR gene, LDL-C were significantly and positively associated with breast (OR:1.200, 95% CI:1.082-1.329, p = 0.001), prostate (OR:1.198, 95% CI:1.050-1.366, p = 0.007), and thyroid cancers (OR:8.291, 95% CI:3.189- 21.555, p = 0.00001) were significantly positively correlated, whereas they were significantly negatively correlated with colorectal cancer (OR:0.641, 95% CI:0.442-0.928, p = 0.019); the results for cervical cancer were not significant (p = 0.050). When using the PCSK9 gene, LDL-C levels were significantly and positively associated with breast (OR:1.107, 95%:CI 1.031-1.187, p = 0.005) and prostate (OR:1.219, 95%:CI 1.101-1.349, p = 0.0001) cancers, but not with cervical (p = 0.294), thyroid cancer (p = 0.759) and colorectal cancer ( p = 0.572).ConclusionAnalyses using both the HMGCR and PCSK9 genes have shown that LDL-C may be a potential risk factor for breast and prostate cancer, while analyses of the HMGCR gene have also suggested that LDL-C may increase the risk of thyroid cancer and decrease the risk of colorectal cancer.

Project description:BackgroundA previous study demonstrated that low-density lipoprotein cholesterol (LDL-C) is associated with hepatocellular carcinoma (HCC); however, the causality between them has not been proven due to conflicting research results and the interference of confounders. This study utilized Mendelian randomization (MR) to investigate the causal relationship between LDL-C and HCC and identify the mediating factors.MethodsLDL-C, HCC, and coronary artery disease (CAD) genome-wide association study (GWAS) data were obtained from a public database. To investigate causality, inverse variance weighting (IVW) was the main analysis approach. MR‒Egger, simple mode, weighted median (WM), and weighted mode were employed as supplementary analytic methods. In addition, horizontal pleiotropy and heterogeneity were tested. To evaluate the stability of the MR results, a "leave-one-out" approach was used. Multivariate MR (MVMR) was utilized to correct the confounders that might affect causality, and mediation analysis was used to investigate the potential mediating effects. Finally, we used HCC risk to infer the reverse causality with LDL-C level.ResultsRandom effects IVW results were (LDL-C-HCC: odds ratio (OR) = 0.703, 95% confidence interval (CI) = [0.508, 0.973], P = 0.034; CAD-HCC: OR = 0.722, 95% CI = [0.645, 0.808], P = 1.50 × 10-8; LDL-C-CAD: OR = 2.103, 95% CI = [1.862, 2.376], P = 5.65 × 10-33), demonstrating a causal link between LDL-C levels and a lower risk of HCC. Through MVMR, after mutual correction, the causal effect of LDL-C and CAD on HCC remained significant (P < 0.05). Through mediation analysis, it was proven that CAD mediated the causative connection between LDL-C and HCC, and the proportion of mediating effect on HCC was 58.52%. Reverse MR showed that HCC could affect LDL-C levels with a negative correlation (ORIVW = 0.979, 95% CI = [0.961, 0.997], P = 0.025).ConclusionThis MR study confirmed the causal effect between LDL-C levels and HCC risk, with CAD playing a mediating role. It may provide a new view on HCC occurrence and development mechanisms, as well as new metabolic intervention targets for treatment.

Dataset Information

Association of cholesteryl ester transfer protein (CETP) gene polymorphism, high density lipoprotein cholesterol and risk of coronary artery disease: a meta-analysis using a Mendelian randomization approach.

Background

Methods

Results

Conclusions

Publications

Association of cholesteryl ester transfer protein (CETP) gene polymorphism, high density lipoprotein cholesterol and risk of coronary artery disease: a meta-analysis using a Mendelian randomization approach.

Similar Datasets

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