This meta-analysis aims to evaluate the relationships between seven functional polymorphisms in the CETP gene and myocardial infarction (MI) risk.
The PubMed, CISCOM, CINAHL, Web of Science, Google Scholar, EBSCO, Cochrane Library, and CBM databases were searched for relevant articles published before March 1st, 2013 without any language restrictions. Meta-analysis was conducted using the STATA 12.0 software.
Nine case-control studies with a total 8,623 MI cases and 8,564 healthy subjects met the inclusion criteria. The results of our meta-analysis suggested that CETP rs708272 (C>T) polymorphism might be correlated with an increased risk of MI, especially among Caucasians. Furthermore, we observed that CETP rs1800775 (C>A) polymorphism might increase the risk of MI. Nevertheless, no similar findings were found for CETP rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A) polymorphisms.
Citation: Wang Q, Zhou S-B, Wang L-J, Lei M-M, Wang Y, Miao C, et al. (2014) Seven Functional Polymorphisms in the CETP Gene and Myocardial Infarction Risk: A Meta-Analysis and Meta-Regression. PLoS ONE 9(2): e88118. https://doi.org/10.1371/journal.pone.0088118
Editor: Mohammad Arfan Ikram, University Medical Center Rotterdam, Netherlands
Received: May 3, 2013; Accepted: January 4, 2014; Published: February 12, 2014
Copyright: © 2014 Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by a grant from the Tianqing Research Foundation (No. TQGB20120101). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Myocardial infarction (MI) remains the leading cause of death and disability worldwide, accounting for up to 40% of all deaths . Due to high mortality and disability rates, MI is becoming a global epidemiological health concern . Rupturing of coronary atherosclerotic plaque with consequent platelet aggregation and thrombus formation is the major cause of MI –. Many intrinsic and extrinsic risk factors for MI have been established, including dyslipidemia, hypertension, smoking, obesity, etc. , . Atherogenic dyslipidemia is usually characterized by three lipid abnormalities: increases in plasma triglyceride, small low density cholesterol (LDL-C) and very low density lipoprotein cholesterol (VLDL-C) levels, and decreased high-density lipoprotein cholesterol (HDL-C) levels –. Although the exact cellular and molecular mechanisms leading to the development of MI remain unclear, it is believed that functionally relevant mutations in the dyslipidemia-related genes may contribute to increased susceptibility to MI .
Cholesteryl ester transfer protein (CETP) is a plasma protein that mediates the exchange of neutral lipids, including cholesteryl esters and triglycerides between plasma lipoproteins . CETP plays a critical role in reverse cholesteryl transport of cholesteryl esters and triglycerides from HDL-C to LDL-C and VLDL-C , . It is well established that HDL-C has a protective role against cardiovascular disease . Plasma HDL particles play an important role in removing cellular cholesterol and delivering it to the liver for re-utilization . Furthermore, it should be noted that levels of HDL-C is significantly negatively correlated with arterial stenosis whose occurrence is strongly associated with the phenomenon of plaque rupture . Thus higher levels of HDL-C tend to have fewer problems with cardiovascular diseases such as MI, while those with low HDL-C cholesterol levels may easily suffer from MI , . Variation in CETP activity could influence HDL-C levels and thus contribute to increased susceptibility to cardiovascular disease such as MI . Genetic and epigenetic changes in the CETP gene may enhance plasma cholesteryl ester formation and lead to low HDL-C levels and thereby possibly explain the inter-individual differences in MI risk , .
Human CETP gene is located on chromosome 6q21 and consists of 16 exons and 15 introns, spanning approximately 25 kb , . Some genetic variations in the CETP gene have been found in the CETP gene, such as rs708272 (C>T), rs1800775 (C>A), rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A); among these, rs708272 (C>T) and rs1800775 (C>A) are the most common variants that have been widely investigated , . Rs708272, a SNP in intron 1 (known as TaqIB), results from a C-to-T substitution at position 277 ; rs1800775 is a promoter SNP arising from a substitution of C-to-A at position 629 . Many previous studies have demonstrated that CETP genetic polymorphisms might be a reliable predictor for the incidence of MI –. Nevertheless, contradictory results were also reported in many of the other studies –. Consequently, we performed the present meta-analysis to evaluate the relationships of seven functional polymorphisms in the CETP gene and the risk of MI.
Materials and Methods
The PubMed, CISCOM, CINAHL, Web of Science, Google Scholar, EBSCO, Cochrane Library, and CBM databases were searched for relevant articles published before March 1st, 2013 without any language restrictions. The following keywords and MeSH terms were used: (“SNP” or “mutation” or “genetic polymorphism” or “variation” or “polymorphism” or “single nucleotide polymorphism” or “variant”) and (“myocardial infarction” or “myocardial infarct” or “MI” or “AMI” or “heart attacks”) and (“cholesterol ester transfer protein” or “CETP” or “cholesteryl ester exchange protein” or “CE transport protein”). We also performed a manual search of the reference lists from the relevant articles to find other potential articles.
The included studies must meet all four of the following criteria: (1) the study design must be clinical cohort or case-control study that focused on the relationships of CETP genetic polymorphisms with the risk of MI; (2) all patients met the diagnostic criteria for MI; (3) the genotype frequencies of healthy controls should follow the Hardy-Weinberg equilibrium (HWE); (4) the study must provide sufficient information about the genotype frequencies. If the study could not meet the inclusion criteria, it would be excluded. The most recent or the largest sample size publication was included when the authors published several studies using the same subjects. The PRISMA checklist is available in Checklist S1.
Relevant data were systematically extracted from all included studies by two observers by using a standardized form. The researchers collected the following data: language of publication, publication year of article, the first author's surname, geographical location, design of study, sample size, the source of the subjects, genotype frequencies, source of samples, genotyping method, evidence of HWE, etc.
Methodological quality was evaluated separately by two observers using the Newcastle-Ottawa Scale (NOS) criteria . The NOS criteria included three aspects: (1) subject selection: 0∼4; (2) comparability of subject: 0∼2; (3) clinical outcome: 0∼3. NOS scores ranged from 0 to 9; and a score ≥7 indicate a good quality. The NOS criteria are available in File S1.
The STATA version 12.0 (Stata Corp, College Station, TX, USA) software was used for meta-analysis. We calculated crude odds ratio (OR) with their 95% confidence interval (95%CI) to evaluate their relationships under 5 genetic models. Genotype frequencies of healthy controls were tested for the HWE using the χ2 test. The statistical significance of pooled ORs was assessed by the Z test. The Cochran's Q-statistic and I2 test were used to evaluate potential heterogeneity between studies –. If Q-test shows a P<0.05 or I2 test exhibits >50% which indicates significant heterogeneity, the random-effect model was conducted, or else the fixed-effects model was used. We also performed subgroup and meta-regression analyses to investigate potential sources of heterogeneity. We conducted a sensitivity analysis to assess the influence of single studies on the overall ORs. Begger's funnel plots and Egger's linear regression test were used to investigate publication bias .
Baseline characteristics of included studies
Initially, the searched keywords identified 90 articles. We reviewed the titles and abstracts of all articles and excluded 44 articles; full texts were also reviewed and 34 articles were further excluded. Three other studies were excluded due to no sufficient data about seven common SNPs in the CETP gene –. Figure 1 shows the selection process of eligible articles. Finally, 9 case-control studies with a total 8,623 MI cases and 8,564 healthy subjects met our inclusion criteria for qualitative data analysis –, . Population-based controls were used in 6 studies, and hospital-based controls were used in 3 studies. Overall, seven studies were conducted among Caucasians and two studies among Asians. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RELP) method was conducted in 7studies, and 2 studies used direct sequencing method. Seven common polymorphisms in the CETP gene were assessed, including rs708272 (C>T), rs1800775 (C>A), rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A); and among these, rs708272 (C>T) and rs1800775 (C>A) were the most common SNPs. None of the studies deviated from the HWE (all P>0.05). NOS scores of all included studies were ≥5. We summarized the study characteristics and methodological quality in Table 1. The genotypic distributions of CETP genetic polymorphisms are shown in File S2.
Quantitative data synthesis
The relationships of CETP rs708272 (C>T) polymorphism with the risk of MI were reported in 5 studies. The heterogeneity obviously existed (P<0.05), so the random effects model was conducted. Our meta-analysis results revealed that CETP rs708272 polymorphism may increase the risk of MI (T allele vs. C allele: OR = 1.39, 95%CI: 1.31–1.47, P<0.001; CT+TT vs. CC: OR = 1.54, 95%CI: 1.42–1.67, P<0.001; TT vs. CC+CT: OR = 1.52, 95%CI: 1.37–1.70, P<0.001; TT vs. CC: OR = 1.87, 95%CI: 1.66–2.11, P<0.001; TT vs. CT: OR = 1.29, 95%CI: 1.15–1.45, P<0.001) (Figure 2). Among different ethnic subgroups, the results revealed positive correlations between CETP rs708272 (C>T) polymorphism and an increased risk of MI among Caucasians (Figure 3), but not among Asians (all P>0.05). The results of subgroup analyses also suggested that CETP rs708272 (C>T) polymorphism was associated with increased risk of MI in the UK, population-based, hospital-based, PCR-RFLP and direct sequencing subgroups (as shown in Table 2). However, CETP rs708272 (C>T) polymorphism showed no association with MI susceptibility in studies conducted in China, Iceland and USA.
There were 4 studies that referred to the relationships of CETP rs1800775 (C>A) polymorphism with MI risk. Since heterogeneity was significantly observed (P<0.05), the random effects model was used. Meta-analysis of these studies indicated positive correlations of CETP rs1800775 (C>A) polymorphism with an increased risk of MI (A allele vs. C allele: OR = 1.13, 95%CI: 1.05–1.22, P = 0.002; CA+AA vs. CC: OR = 1.34, 95%CI: 1.18–1.53, P<0.001; AA vs. CC: OR = 1.27, 95%CI: 1.08–1.49, P = 0.004) (Figure 4). We also conducted subgroup analyses by country and genotype; the results indicated that CETP rs1800775 (C>A) polymorphism might increase susceptibility to MI in most subgroups (as shown in Table 2).
The relationships of rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A) polymorphisms with MI risk were also evaluated. Nevertheless, no similar associations were found for CETP rs5882 (A>G), rs2303790 (A>G), rs1800776 (C>A), rs12149545 (G>A), and rs4783961 (G>A) polymorphisms (all P>0.05) (as shown in Table 3).
Meta-regression analyses were conducted for rs708272 (C>T) and rs1800775 (C>A) polymorphisms. The results confirmed that ethnicity might be a main source of heterogeneity (as shown in Table 4). The results of sensitivity analysis indicated that the overall pooled ORs could not be affected by single study (Figure 5). No evidence for asymmetry was observed in the Begger's funnel plots (Figure 6). Egger's test also failed to reveal any evidence of publication bias (rs708272: t = −1.92, P = 0.151; rs1800775: t = −0.07, P = 0.951).
Each point represents a separate study for the indicated association. Log[OR], natural logarithm of OR. Horizontal line, mean magnitude of the effect.
CETP, a hydrophobic glycoprotein secreted mainly by the liver, catalyzes the transfer of cholesteryl esters from HDL to other lipoproteins and influences plasma HDL-C levels , . Previous studies have demonstrated a protective effect of HDL-C against cardiovascular disease by inhibiting lipoprotein oxidation , , . High plasma levels of CETP are correlated with low HDL-C levels, and it has been implicated as a strong risk factor for cardiovascular disease, including MI . Although MI is one of the most common heritable cardiovascular diseases, the fundamental molecular pathways remain undefined , . Thus, it was speculated that CETP genetic variations may be involved in the development of MI , . The CETP gene has been mapped to locus 16q21 encoding cholesteryl ester transfer protein . Common polymorphisms of CETP gene may result in the over-expression of this protein and a subsequent decrease of HDL-C levels, thus contributing to the incidence of MI . Indeed, several studies have demonstrated positive correlations of CETP genetic polymorphisms with an increased risk of MI –, but the controversy still persists.
In the present meta-analysis, our findings revealed that CETP rs708272 (C>T) polymorphism might increase the risk of MI, especially among Caucasians, while similar results were not observed among Asians. There also existed positive correlations of CETP rs1800775 (C>A) polymorphism with an increased risk of MI among Caucasians. Although ethnic differences in to the risk of MI are well known, potential molecular mechanism is not fully understood. One possible reason for ethnic difference might be that CETP gene mutations might affect cholesteryl ester synthesis and result in low HDL-C levels, thereby possibly explaining interindividual differences in the incidence of MI . Another likely explanation for this difference could be that large differences in common SNPs that influence the risk of MI are mostly due to genetic drift and natural selection . The results of subgroup analyses demonstrated positive correlations of CETP rs708272 (C>T) polymorphism with an increased risk of MI in the UK, population-based, hospital-based, PCR-RFLP and direct sequencing subgroups, indicating that country, source of controls and genotype method may be the potential sources of heterogeneity. However, our meta-regression analyses indicated that only ethnicity was the major source of heterogeneity. These disparate results may be due to small sample size resulting in substantial errors from estimation. Nevertheless, we observed no associations between the other 5 common polymorphisms in the CETP gene and MI risk. In short, the results of our meta-analysis were consistent with previous studies that CETP genetic polymorphisms may be closely linked to the risk of MI, suggesting that CETP genetic polymorphism could be useful and promising biomarkers for early diagnosis of MI.
The current meta-analysis also had many limitations that should be acknowledged. First, our results had lacked sufficient statistical power to assess the correlations between CETP genetic polymorphisms and MI risk. Secondly, meta-analysis is a retrospective study that may lead to subject selection bias, and thereby affecting the reliability of our results . Thirdly, our meta-analysis failed to obtain original data from the included studies, which may limit further evaluation of potential role of CETP genetic polymorphisms in the development of MI. Although our study has many limitations, this is the first meta-analysis focusing on the relationships between CETP genetic polymorphisms and the risk of MI. Furthermore, we performed a highly sensitive literature search strategy for electronic databases. A manual search of the reference lists from the relevant articles was also conducted to find other potential articles. The selection process of eligible articles was based on strict inclusion and exclusion criteria. Importantly, rigorous statistical analysis of SNP data provided a basis for pooling of information from individual studies.
In conclusion, our findings provide empirical evidence that CETP rs708272 (C>T) and rs1800775 (C>A) polymorphisms may contribute to MI susceptibility, especially among Caucasians. Thus, CETP rs708272 and rs1800775 polymorphisms may be promising and potential biomarkers for early diagnosis of MI. However, due to the limitations mentioned above, more researches with larger sample size are needed to provide a more representative statistical analysis precisely.
The Newcastle-Ottawa quality assessment scale.
We would like to acknowledge the reviewers for their helpful comments on this paper.
Conceived and designed the experiments: QW SBZ YZJ. Performed the experiments: LJW MML. Analyzed the data: YW CM. Contributed reagents/materials/analysis tools: QW SBZ. Wrote the paper: QW. Final approval of manuscript: YZJ.
- 1. White HD, Chew DP (2008) Acute myocardial infarction. Lancet 372 (9638) 570–584.
- 2. Manrique-Garcia E, Sidorchuk A, Hallqvist J, Moradi T (2011) Socioeconomic position and incidence of acute myocardial infarction: a meta-analysis. J Epidemiol Community Health 65 (4) 301–309.
- 3. Ohki T, Itabashi Y, Kohno T, Yoshizawa A, Nishikubo S, et al. (2012) Detection of periodontal bacteria in thrombi of patients with acute myocardial infarction by polymerase chain reaction. Am Heart J 163 (2) 164–167.
- 4. Yamada Y, Izawa H, Ichihara S, Takatsu F, Ishihara H, et al. (2002) Prediction of the risk of myocardial infarction from polymorphisms in candidate genes. New Engl J Med 347 (24) 1916–1923.
- 5. Licastro F, Chiappelli M, Porcellini E, Campo G, Buscema M, et al. (2010) Gene-gene and gene-clinical factors interaction in acute myocardial infarction: a new detailed risk chart. Curr Pharm Des 16 (7) 783–788.
- 6. Romero-Corral A, Somers VK, Sierra-Johnson J, Korenfeld Y, Boarin S, et al. (2010) Normal weight obesity: a risk factor for cardiometabolic dysregulation and cardiovascular mortality. Eur Heart J 31 (6) 737–746.
- 7. Canto JG, Kiefe CI, Rogers WJ, Peterson ED, Frederick PD, et al. (2011) Number of coronary heart disease risk factors and mortality in patients with first myocardial infarction. JAMA 306 (19) 2120–2127.
- 8. Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, Barbalic M, et al. (2012) Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet 380 (9841) 572–580.
- 9. Vinueza R, Boissonnet CP, Acevedo M, Uriza F, Benitez FJ, et al. (2010) Dyslipidemia in seven Latin American cities: CARMELA study. Preventive medicine 50 (3) 106–111.
- 10. Poss J, Custodis F, Werner C, Weingartner O, Bohm M, et al. (2011) Cardiovascular disease and dyslipidemia: beyond LDL. Current pharmaceutical design 17 (9) 861–870.
- 11. Holzmann MJ, Jungner I, Walldius G, Ivert T, Nordqvist T, et al. (2012) Dyslipidemia is a strong predictor of myocardial infarction in subjects with chronic kidney disease. Annals of medicine 44 (3) 262–270.
- 12. Masson D, Jiang X-C, Lagrost L, Tall AR (2009) The role of plasma lipid transfer proteins in lipoprotein metabolism and atherogenesis. Journal of lipid research 50 (Supplement) S201–S206.
- 13. Rader DJ, Alexander ET, Weibel GL, Billheimer J, Rothblat GH (2009) The role of reverse cholesterol transport in animals and humans and relationship to atherosclerosis. Journal of lipid research 50 (Supplement) S189–S194.
- 14. Tall AR (2010) Functions of cholesterol ester transfer protein and relationship to coronary artery disease risk. J Clin Lipidol 4 (5) 389–393.
- 15. Cooney M, Dudina A, De Bacquer D, Wilhelmsen L, Sans S, et al. (2009) HDL cholesterol protects against cardiovascular disease in both genders, at all ages and at all levels of risk. Atherosclerosis 206 (2) 611–616.
- 16. von Eckardstein A (2010) Implications of torcetrapib failure for the future of HDL therapy: is HDL-cholesterol the right target? Expert Rev Cardiovasc Ther 8 (3) 345–358.
- 17. Qian Y, Pu Y, Liu L, Wang DZ, Zhao X, et al. (2013) Low HDL-C level is associated with the development of intracranial artery stenosis: analysis from the Chinese IntraCranial AtheroSclerosis (CICAS) study. PLoS One 8 (5) e64395.
- 18. Boekholdt SM, Arsenault BJ, Hovingh GK, Mora S, Pedersen TR, et al. (2013) Levels and changes of HDL cholesterol and apolipoprotein A-I in relation to risk of cardiovascular events among statin-treated patients: a meta-analysis. Circulation 128 (14) 1504–1512.
- 19. Barn K, Laftavi M, Pierce D, Ying C, Boden WE, et al. (2010) Low levels of high-density lipoprotein cholesterol: an independent risk factor for late adverse cardiovascular events in renal transplant recipients. Transpl Int 23 (6) 574–579.
- 20. Wu JH, Lee YT, Hsu HC, Hsieh LL (2001) Influence of CETP gene variation on plasma lipid levels and coronary heart disease: a survey in Taiwan. Atherosclerosis 159 (2) 451–458.
- 21. Ridker PM, Paré G, Parker AN, Zee RY, Miletich JP, et al. (2009) Polymorphism in the CETP Gene Region, HDL Cholesterol, and Risk of Future Myocardial Infarction Genomewide Analysis Among 18 245 Initially Healthy Women From the Women's Genome Health Study. Circ Cardiovasc Genet 2 (1) 26–33.
- 22. Thompson JF, Durham LK, Lira ME, Shear C, Milos PM (2005) CETP polymorphisms associated with HDL cholesterol may differ from those associated with cardiovascular disease. Atherosclerosis 181 (1) 45–53.
- 23. Drayna D, Jarnagin AS, McLean J, Henzel W, Kohr W, et al. (1987) Cloning and sequencing of human cholesteryl ester transfer protein cDNA. Nature 327 (6123) 632–634.
- 24. Ordovas JM (2000) Genetic polymorphisms and activity of cholesterol ester transfer protein (CETP): should we be measuring them? Clin Chem Lab Med 38 (10) 945–949.
- 25. van Venrooij FV, Stolk RP, Banga J-D, Sijmonsma TP, van Tol A, et al. (2003) Common cholesteryl ester transfer protein gene polymorphisms and the effect of atorvastatin therapy in type 2 diabetes. Diabetes Care 26 (4) 1216–1223.
- 26. Dullaart RP, Sluiter WJ (2008) Common variation in the CETP gene and the implications for cardiovascular disease and its treatment: an updated analysis. Pharmacogenomics 2008 Jun, 9 (6) 747–763.
- 27. Mohrschladt MF, van der Sman-de Beer F, Hofman MK, van der Krabben M, Westendorp RG, et al. (2005) TaqIB polymorphism in CETP gene: the influence on incidence of cardiovascular disease in statin-treated patients with familial hypercholesterolemia. Eur J Hum Genet 13 (7) 877–882.
- 28. Dachet C, Poirier O, Cambien F, Chapman J, Rouis M (2000) New Functional Promoter Polymorphism, CETP/− 629, in Cholesteryl Ester Transfer Protein (CETP) Gene Related to CETP Mass and High Density Lipoprotein Cholesterol Levels Role of Sp1/Sp3 in Transcriptional Regulation. Arterioscler Thromb Vasc Biol 20 (2) 507–515.
- 29. Eiriksdottir G, Bolla MK, Thorsson B, Sigurdsson G, Humphries SE, et al. (2001) The −629C>A polymorphism in the CETP gene does not explain the association of TaqIB polymorphism with risk and age of myocardial infarction in Icelandic men. Atherosclerosis 159 (1) 187–192.
- 30. Keavney B, Palmer A, Parish S, Clark S, Youngman L, et al. (2004) Lipid-related genes and myocardial infarction in 4685 cases and 3460 controls: discrepancies between genotype, blood lipid concentrations, and coronary disease risk. Int J Epidemiol 33 (5) 1002–1013.
- 31. Tobin MD, Braund PS, Burton PR, Thompson JR, Steeds R, et al. (2004) Genotypes and haplotypes predisposing to myocardial infarction: a multilocus case-control study. Eur Heart J 25 (6) 459–467.
- 32. Meiner V, Friedlander Y, Milo H, Sharon N, Ben-Avi L, et al. (2008) Cholesteryl ester transfer protein (CETP) genetic variation and early onset of non-fatal myocardial infarction. Ann Hum Genet 72 (Pt 6) 732–741.
- 33. Liu S, Schmitz C, Stampfer MJ, Sacks F, Hennekens CH, et al. (2002) A prospective study of TaqIB polymorphism in the gene coding for cholesteryl ester transfer protein and risk of myocardial infarction in middle-aged men. Atherosclerosis 161 (2) 469–474.
- 34. Andrikopoulos GK, Richter DJ, Needham EW, Zairis MN, Karabinos EN, et al. (2004) Association of the ile405val mutation in cholesteryl ester transfer protein gene with risk of acute myocardial infarction. Heart 90 (11) 1336–1337.
- 35. Zhang GB, Jiang ZW, Sun BG, Lu YS, Wen QZ, et al. (2005) Relationship of Taq IB Polymorphism in the Cholesteryl Ester Transfer Protein Gene to Coronary Artery Disease. Chin J Arterioscler (01) 88–90.
- 36. Li Y, Guo JX, Li JP, Fang YP, Guan BX, et al. (1999) Association between cholesterol ester transfer protein gene polymorphism with myocardial infarction. Chin Circul J (03) 16.
- 37. Stang A (2010) Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 25 (9) 603–605.
- 38. Jackson D, White IR, Riley RD (2012) Quantifying the impact of between-study heterogeneity in multivariate meta-analyses. Stat Med 31 (29) 3805–3820.
- 39. Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L (2006) Comparison of two methods to detect publication bias in meta-analysis. JAMA 295 (6) 676–680.
- 40. Ioannidis JP, Patsopoulos NA, Rothstein HR (2008) Reasons or excuses for avoiding meta-analysis in forest plots. BMJ 336 (7658) 1413–1415.
- 41. Zintzaras E, Ioannidis JP (2005) HEGESMA: genome search meta-analysis and heterogeneity testing. Bioinformatics 21 (18) 3672–3673.
- 42. Tenkanen H, Koshinen P, Kontula K, Aalto-Setala K, Manttari M, et al. (1991) Polymorphisms of the gene encoding cholesterol ester transfer protein and serum lipoprotein levels in subjects with and without coronary heart disease. Hum Genet 87 (5) 574–578.
- 43. Zhuang Y, Wang J, Qiang H, Li Y, Liu X, et al. (2002) Cholesteryl ester transfer protein levels and gene deficiency in Chinese patients with cardio-cerebrovascular diseases. Chin Med J (Engl) 115 (3) 371–374.
- 44. Enquobahrie DA, Smith NL, Bis JC, Carty CL, Rice KM, et al. (2008) Cholesterol ester transfer protein, interleukin-8, peroxisome proliferator activator receptor alpha, and Toll-like receptor 4 genetic variations and risk of incident nonfatal myocardial infarction and ischemic stroke. Am J Cardiol 101 (12) 1683–1688.
- 45. Zee RY, Cook NR, Cheng S, Erlich HA, Lindpaintner K, et al. (2006) Multi-locus candidate gene polymorphisms and risk of myocardial infarction: a population-based, prospective genetic analysis. J Thromb Haemost 4 (2) 341–348.
- 46. Barter P (2000) CETP and atherosclerosis. Arterioscler Thromb Vasc Biol 20 (9) 2029–2031.
- 47. Zhang L, Yan F, Zhang S, Lei D, Charles MA, et al. (2012) Structural basis of transfer between lipoproteins by cholesteryl ester transfer protein. Nat Chem Biol 8 (4) 342–349.
- 48. Banka CL (1996) High density lipoprotein and lipoprotein oxidation. Curr Opin Lipidol 7 (3) 139–142.
- 49. Ansell BJ, Navab M, Watson KE, Fonarow GC, Fogelman AM (2004) Anti-inflammatory properties of HDL. Reviews in Endocrine and Metabolic Disorders 5 (4) 351–358.
- 50. de Grooth GJ, Kuivenhoven JA, Stalenhoef AF, de Graaf J, Zwinderman AH, et al. (2002) Efficacy and safety of a novel cholesteryl ester transfer protein inhibitor, JTT-705, in humans a randomized phase II dose-response study. Circulation 105 (18) 2159–2165.
- 51. Rich MW (2009) Epidemiology of atrial fibrillation. J Interv Card Electrophysiol 25 (1) 3–8.
- 52. Nattel S (2002) New ideas about atrial fibrillation 50 years on. Nature 415 (6868) 219–226.
- 53. Topol EJ, Smith J, Plow EF, Wang QK (2006) Genetic susceptibility to myocardial infarction and coronary artery disease. Hum Mol Genet 15 Spec No 2: R117–123.
- 54. Serre D, Montpetit A, Pare G, Engert JC, Yusuf S, et al. (2008) Correction of population stratification in large multi-ethnic association studies. PLoS One 3 (1) e1382.
- 55. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, et al. (2000) Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 283 (15) 2008–2012.