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Association between PCSK9 and LDLR gene polymorphisms with coronary heart disease: Case-control study and meta-analysis
Clinical Biochemistry 46 (2013) 727–732
Contents lists available at SciVerse ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Association between PCSK9 and LDLR gene polymorphisms with coronary heart disease: Case-control study and meta-analysis Lina Zhang a,⁎, 1, Fang Yuan a, 1, Panpan Liu a, Lijuan Fei a, Yi Huang a, Limin Xu a, Lingmei Hao b, Xujun Qiu b, Yanping Le a, Xi Yang c, Weifeng Xu c, Xiaoyan Huang c, Meng Ye a, Jianqing Zhou c, Jiangfang Lian c,⁎, Shiwei Duan a,⁎ a b c
Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo 315211, Zhejiang Province, China Clinical laboratory, The Seventh Hospital of Ningbo, Ningbo 315211, Zhejiang Province, China Ningbo Medical Center, Lihuili Hospital, Ningbo University, Ningbo, Zhejiang 315041, China
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Article history: Received 6 September 2012 Received in revised form 15 January 2013 Accepted 21 January 2013 Available online 1 February 2013 Keywords: PCSK9 LDLR LDL-C SNP Meta-analysis
a b s t r a c t Objective: To explore the association of rs11206510 (PCSK9 gene) and rs1122608 (LDLR gene) polymorphisms with coronary heart disease (CHD) in Han Chinese. Methods: A total of 813 participants (290 CHD cases, 193 non-CHD controls and 330 healthy controls) were recruited in the case-control study. DNA genotyping was performed on the SEQUENOM® Mass–ARRAY iPLEX® platform. χ2-test was used to compare the genotype distribution and allele frequencies. Two meta-analyses were performed to establish the association between the two polymorphisms with CHD. Results: No significant associations between the two SNPs and the risk of CHD were observed in the present study. The meta-analysis of rs11206510 of PCSK9 gene comprises 11 case-control studies with a total of 69,054 participants. Significant heterogeneity was observed in Caucasian population in subgroup analysis of the association studies of rs11206510 with CHD (P=0.003, I2 =67.2%). The meta-analysis of LDLR gene rs1122608 polymorphism comprises 7 case-control studies with a total of 20,456 participants and the heterogeneity of seven studies was minimal (P =0.148, I2 =36.7%). Conclusion: The results of the meta-analyses indicated that both SNPs were associated with CHD in Caucasians (Pb 0.05) but not in Asians. The results from our case-control study and meta-analyses might be explained by genetic heterogeneity in the susceptibility of CHD and ethnic differences between Asians and Caucasians. © 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Introduction Coronary heart disease (CHD) is not only the crucial cause of mortality and disability in the industrialized countries but also remains a public health problem among the developing countries [1]. However, the pathogenesis of CHD remains largely unknown. The most generally accepted view is that CHD is a polygenic disease, resulting from the interaction of several genes and together with environmental factors such as unhealthy lifestyles and psychosocial factors. Genetic factors are estimated to account for 30–60% of the risk of CHD [2,3].
Abbreviations: CHD, coronary heart disease; PCSK9, proprotein convertase subtilisin/ kexin type serine protease 9; LDL, low-density lipoprotein; LDLR, low-density lipoprotein receptor; LDL-C, low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides; HDL, high-density lipoprotein; HWE, Hardy–Weinberg equilibrium; CI, confidence interval; OR, odds ratio. ⁎ Corresponding authors. E-mail addresses: [email protected] (L. Zhang), [email protected] (J. Lian), [email protected] (S. Duan). 1 Lina Zhang and Fang Yuan are the co-first authors.
Circulating blood lipid levels have been consistently associated with the risk of CHD [4,5]. In humans, nearly 60–70% of the total plasma cholesterol is transported by low-density lipoproteins (LDL) [6]. Epidemiological and clinical data indicate that elevated plasma level of low-density lipoprotein cholesterol (LDL-C) is a primary risk factor for the incidence of coronary events [7,8]. LDL metabolism is regulated by LDL receptor (LDLR) that is encoded by LDLR gene. Under normal circumstances LDL is removed from the circulation mainly by liver uptake via LDLR so that LDL-C remains a stable level of LDL-C in blood. In addition to LDLR, proprotein convertase subtilisin/kexin type serine protease 9 (PCSK9) can also impact the regulation of plasma levels of LDL-C. PCSK9 is a glycoprotein highly expressed in liver, intestine and kidney [9]. PCSK9 binds and favors the degradation of LDLR, thereby modulating the plasma levels of LDL-C [10]. Therefore, plasma levels of LDL-C and PCSK9 are likely to be directly correlated due to the PCSK9-promoted degradation of hepatic LDLR. High levels of PCSK9 were associated with the cardiovascular events in CHD patients with low statin usage [11]. Several GWASs have identified that rs11206510 of PCSK9 gene and rs1122608 of LDLR gene were associated with increased CHD risk
0009-9120/$ – see front matter © 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.clinbiochem.2013.01.013
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[12–14]. The two SNPs had significant association with CHD in European population through a meta-analysis of previous GWASs (Pb 5× 10−8) [15], but the positive significance needs to be confirmed since only two studies were included in the meta-analysis. In addition, a casecontrol study in Han Chinese showed that rs11206510-C allele was associated with increased risk of early-onset CHD (P= 0.002, OR= 1.89, 95% CI =1.25–2.34), but not with overall CHD (P =0.82, OR= 1.04, 95% CI = 0.77–1.41) [16]. However, another study in Han Chinese found that rs11206510 was significantly associated with CHD (P = 0.029, OR = 1.41, 95% CI= 1.04–1.93) [17]. As the contradictory results in Han Chinese, the goal of our study is to explore the association between the two SNPs and CHD in Eastern Han Chinese and establish the contribution of the two SNPs to the risk of CHD through two meta-analyses. Methods Sample collection A total of 483 patients (290 CHD cases and 193 non-CHD controls) from the Lihuili Hospital were recruited between May 2008 and November 2011. The mean (±SD) age was 61.98±9.49 years, and 72% were men in CHD cases, while the mean (±SD) age was 58.65± 9.36 years, and 51% were men in non-CHD controls. All patients had been examined by standardized coronary angiography according to the Seldinger's method [18], and the results were judged by at least two independent cardiologists. According to the coronary angiographic results, patients diagnosed with CHD had at least one or more major coronary arteries with 50% or greater stenosis. Patients with a history of prior angioplasty or coronary artery bypass surgery were also selected as CHD cases. The rest of the patients with less than 50% occlusion of any coronary vessel and no history of any atherosclerotic vascular diseases were grouped as non-CHD controls. Additional 330 healthy persons as the healthy controls were selected from a well-characterized random sample of the Ximen Community residents in Ningbo city. All the individuals were excluded from having congenital heart disease, cardiomyopathy, liver and renal disease. Blood samples were collected from subjects in a fasting state and treated by the same investigators. Then blood samples were stored at − 80 °C with 3.2% citrate sodium-treated tubes until analysis was performed. The study protocol was approved by the ethic committees of Ningbo University. All participants gave written informed consent that included consent for genetic studies. Disease history, demographic and risk factor data were extracted from the medical records. SNP Genotyping
the GeneAmp® PCR System 9700 (dual 384-well blocks) (Applied Biosystems, Foster City, CA). The PCR procedure included an initial denaturation step of 15 s at 94 °C was followed by 45 cycles of a 3step amplification profile of 20 s at 94 °C for denaturation, 30 s at 56 °C for annealing, 1 min at 72 °C for primer extension, then 3 min at 72 °C for a final extension. PCR products for genotyping were performed on the SEQUENOM® Mass-ARRAY iPLEX® platform according to the manufacturer's instructions. Statistical analyses Hardy–Weinberg equilibrium (HWE) was analyzed using Arlequin program (version 3.5) [19]. The Pearson's χ2-test was used to compare the genotype distribution, allele frequencies and other categorical phenotypes between CHD cases and each of two controls. The comparison of genotype and allele frequencies among the three degrees of coronary artery stenosis with CHD was performed by the Kruskal–Wallis test. All data were analyzed with SPSS statistical software (version 16.0). All tests were two-tailed and P values less than 0.05 were considered to be significant. Meta-analysis The literatures were obtained from the databases of Chinese Biomedical Literature Database (CBM), Chinese Knowledge Internet (CNKI) and PubMed. Taking the keywords ‘coronary heart disease’, ‘PCSK9’, ‘LDL receptor’, ‘polymorphism’, ‘gene’, ‘gene variant’ and ‘association’ as the search terms. Meanwhile, the papers should be published in Chinese or English from 2000 to 2012. Only the papers that examined the relationship between CHD and PCSK9 rs11206510 or LDLR rs1122608 can be used for the meta-analysis. The research papers were excluded if they did not provide genotype frequencies in both cases and controls or odds ratio (OR) and 95% confidence interval (95% CI). Information was collected from each study, including author, publication year, study population, distribution of genotype and allele in both cases and controls, OR and 95% CI. Meta-analysis was performed by the STATA software (version 11.0). Heterogeneity of the studies was done by the I2 test at the significant level of 0.05. If there was heterogeneity in the studies, a pooled OR was calculated by the random effect model; otherwise, the fixed effect model was used [20,21]. The publication bias was measured by funnel plots. Power analysis Power analysis was performed by the Power and Sample Size Calculation Software (PS). The significance level sets at 0.05.
Human genomic DNA was extracted from peripheral blood samples using the Nucleic acid extraction automatic analyzer (Lab-Aid 820, Xiamen City, China). Then DNA was quantified using the PicoGreen® double strand (dsDNA) DNA Quantification Kit (Molecular Probes, Inc. Eugene, USA). PCR for genotyping experiments was performed on
Results Genotype distributions did not deviate from Hardy–Weinberg equilibrium (HWE) in CHD cases, non-CHD controls and healthy controls,
Table 1 Comparison of genotype distributions and allele frequencies between CHD cases and two groups of controls. χ2
Genotype rs11206510 CHD cases (n = 290) Control 1 (n = 193) Control 2 (n = 330)
TT 253(87.2) 171(88.6) 285(86.4)
TC 37(12.8) 21(10.9) 45(13.6)
CC 0 1(0.5) 0
rs1122608 Cases (n = 289) Control 1 (n = 191) Control 2 (n = 330)
GG 232(80.3) 151(79.1) 263(79.7)
GT 54(18.7) 40(20.9) 63(19.1)
TT 3(1) 0 4(1.2)
Control 1: non-CHD controls. Control 2: healthy controls. a Fisher's exact test.
1.77 0.1
a
1.88a 0.12a
P (df = 2)
Allele
0.42 0.81
T 543(93.6) 363(94) 615(93.2)
0.39 0.98
G 518(89.6) 342(89.5) 589(89.2)
χ2
P (df = 1)
HWE
C 37(6.4) 23(6) 45(6.8)
0.07 0.1
0.89 0.82
0.3 0.7 0.2
T 60(10.4) 40(10.5) 71(10.8)
0.002 0.05
1.0 0.85
0.9 0.1 0.9
L. Zhang et al. / Clinical Biochemistry 46 (2013) 727–732 Table 2 Characteristics of published studies of the association between rs11206510 and CHD in the meta-analysis.
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Table 3 Characteristics of published studies of the association between rs1122608 and CHD in the meta-analysis.
Author
Year
Case
Control
Population
Risk allele
Author
Year
Case
Control
Population
Risk allele
Muredach P Reilly et al. [12] Lu Qi-NHS et al. [23] Lu Qi-HPFS et al. [23] Lu Qi-JHS et al. [23] Dawn M. Waterworth et al. [21] Ilaria Guella et al. [22] Chengqi Xu et al. [15] Sekar Kathiresan et al. [11] Cristen J Willer et al. [13] Xiaofei Lv et al. [16] Our study
2011 2011 2011 2011 2010 2010 2010 2009 2008 2012 2012
6886 309 345 422 6988 1880 1543 2967 1925 1007 290
3226 544 451 435 19,945 1880 1240 3075 12,284 889 523
Caucasian Caucasian Caucasian Caucasian Caucasian Caucasian Asian Caucasian Caucasian Asian Asian
T T T T T T C T T T T
Muredach P Reilly et al. [12] Lu Qi-NHS et al. [23] Lu Qi-HPFS et al. [23] Lu Qi-JHS et al. [23] Sekar Kathiresan et al. [11] Nicola Martinelli et al. [24] Our study
2011 2011 2011 2011 2009 2010 2012
6886 309 345 422 2967 692 290
3226 544 451 435 3075 291 523
Caucasian Caucasian Caucasian Caucasian Caucasian Caucasian Asian
G G G G G G G
suggesting that our case-control study had a well-characterized random sampling. Genotype and allele frequencies of rs11206510 of PCSK9 gene and rs1122608 of LDLR gene were summarized in Table 1. No significant associations of the two SNPs with CHD were found in the case-control comparisons. A further breakdown analyses by gender also produced negative association results (Supplemental Table 1 and Supplemental Table 2). Under the dominant and recessive genetic model, we failed to find any difference in the allelic and genotypic distribution of the two SNPs between CHD cases and each of the two controls (Supplemental Table 3). Significant association was found between the degree of coronary artery stenosis and the genotype of rs1122608 (Pb 0.001). However, this result may be biased by the rare number of TT. The number of TT in one coronary vessel lesion level was only 2 and 1 in three coronary vessel lesion. Our data indicated that the two SNPs were not associated with the severity of CHD in other conditions (Supplemental Table 4). A total of 11 studies were selected into the meta-analysis for the association of rs11206510 of PCSK9 gene with CHD (Table 2). Flow diagram of articles searching in the meta-analysis was shown in Supplemental Fig. 1. Among them, four studies were GWASs [12–14,22] and the rest five (including our study) were case–control studies [16,17,23,24]. For the study with multiple subgrouped case-control
associations [24], we separately integrated them into our metaanalysis. The studies in the meta-analysis were carried out in multiple places including Europe, America, and Asia. A heterogeneity test showed that there were significant heterogeneity among the eleven studies (P = 0.007, I 2 = 58.5%). In order to recognize the source of heterogeneity, a further subgroup analysis of population was performed. It suggested that heterogeneity mainly existed in Caucasians (P = 0.003, I2 = 67.2%). As shown in Fig. 1, meta-analysis showed that rs11206510 of PCSK9 gene was a risk factor of CHD in Caucasians (P = 0.007, OR= 1.09, 95% CI = 1.03–1.17, random-effects model), but not in Asians (P = 0.167, OR= 1.16, 95% CI = 0.94–1.43, random-effects model). Seven studies were included in the meta-analysis of rs1122608 of LDLR gene [12,13,24,25] (Table 3). Details of articles in the metaanalysis were shown in Supplemental Fig. 2. Among them, two were GWASs [12,13]. The studies in the meta-analysis were carried out in the population of European and American. The heterogeneity of seven studies was minimal (P = 0.148, I2 = 36.7%). As shown in Fig. 2, the subgroup meta-analysis showed that rs1122608 of LDLR gene was a risk factor of CHD, especially in Caucasians (OR= 1.10, 95% CI= 1.02– 1.19, P = 0.011, random effects model). As shown in Figs. 3 and 4, no visual evidence of publication bias for the two meta-analyses was observed by the funnel plots. Furthermore, the Egger's test was not significant for the meta-analyses of rs11206510 of PCSK9 gene (P = 0.83) and rs1122608 of LDLR gene (P =0.085).
Fig. 1. Forest plot of the association between rs11206510 of PCSK9 gene and CHD in different populations.
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Fig. 2. Forest plot for the association between rs1122608 of LDLR gene and CHD in different populations.
Discussion Previous studies have suggested that the levels of TC, LDL-C and HDL-C were independent heritable risk factors for cardiovascular diseases [26]. Some of the genetic risk loci for CHD may exert their effects by modulating or interacting with these factors. Recent GWASs have identified multiple loci and candidate genes for blood lipid-related traits [5]. Ilaria Guella et al. observed that the minor allele C of the rs11206510 of PCSK9 gene was strongly related to lower concentration of both LDL (OR = 0.82, 95% CI = 0.73-0.93, P = 1.89 × 10 −3) and total cholesterol (OR = 0.80, 95% CI= 0.72–0.89, P = 8.12× 10−5) in Italian population [23]. Tanya M. Teslovich and colleagues recently published a case-control study involving with more than 100,000 European ancestry participants to test the association of CHD with several polymorphisms of PCSK9 and LDLR [5]. Their results showed that
log[or]
.5
rs11206510-T of PCSK9 gene and rs1122608-G of LDLR gene were associated with increased LDL-C and TC levels and the risk of CHD. Cristen J Willer et al. found that rs11206510 of PCSK9 gene had a positive association with both the concentration of LDL-C and the risk of CHD in Europeans [14]. Other three GWASs confirmed the contribution of rs11206510 (T > C) of PCSK9 gene to the risk of CHD in Europeans [15,22,27]. However, Muredach P Reilly and colleagues performed a GWAS in Europeans and were unable to find an association between rs11206510 (T > C) and CHD [13]. For rs1122608 (G > T) of LDLR gene, there were four GWASs which have observed its association with CHD in participants of European ancestry [13,15,27,28]. The crucial role of PCSK9 gene and LDLR gene in the LDL-C metabolism made this result meaningful and prompted us to explore the contribution of the two SNPs with CHD in Chinese population [5]. Neither rs11206510 nor rs1122608 was associated with the incidence and the
Begg's funnel plot with pseudo 95% confidence limits
0
-.5 0
.05
.1
.15
.2
s.e. of: log[or] Fig. 3. Funnel plot of the association between rs11206510 of PCSK9 gene and CHDa. aHorizontal axis represents the standard error of log OR. Vertical axis represents the log OR. The s.e. denotes standard error.
L. Zhang et al. / Clinical Biochemistry 46 (2013) 727–732
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Begg's funnel plot with pseudo 95% confidence limits
log[or]
.5
0
-.5 0
.1
.2
s.e. of: log[or] a a
Fig. 4. Funnel plot for the association between rs1122608 of LDLR gene and CHD . Horizontal axis represents the standard error of log OR. Vertical axis represents the log OR. The s.e. denotes standard error.
severity of CHD, and no interaction of the two SNPs with gender was found in our study (data not shown). However, a study in Han Chinese found that rs11206510 was associated with early-onset CHD but not with overall CHD, which defined early-onset CHD as males aged 50 years or younger and females aged 55 years or younger at the first time of the diagnosis of CHD[16]. The results were consistent with our findings that rs11206510 was not associated with overall CHD. In our study, we did not explore the association between rs11206510 and early-onset CHD. The patients with angiographic results were simply divided into three levels, one coronary vessel lesion, two coronary vessel lesion, three and more coronary vessel lesion, according to the degree of coronary artery stenosis. A lack of association between rs11206510 and the severity of CHD might be due to the imperfect classification method of CHD, since the severity of CHD could be reflected by both the number of coronary artery stenosis and the percent area stenosis inside the coronary arteries. A combined grading method with both parameters might be more precise to define the severity of CHD. Meta-analysis established that both rs11206510 of PCSK9 gene and rs1122608 of LDLR gene were associated with the risk of CHD. The conclusion was the same as the previous meta-analysis in Europeans [15]. Compared to the previous meta-analysis of rs11206510, our meta-analysis comprised eleven studies in European, American, and Asian populations to ensure reliability of the results. A further subgroup analysis in our study showed that large heterogeneity mainly existed in Caucasian population. Association study of the two SNPs was only significant in Caucasians but not in Asians. The minor allele frequency of rs11206510-C of PCSK9 gene is 6.5% in present study, but it is 19% in Caucasians. The minor allele frequency of rs1122608-T in Chinese (10.6%) was lower than that in Europeans (25%) and a previous study in Han Chinese discovered that the minor allele C of rs11206510 was associated with increased LDL-C levels, but genome-wide association studies found that the common allele T of rs11206510 was associated with increased LDL-C levels[16]. Since most of the studies in the metaanalysis were performed in Caucasians, the conflicting results between our association study and meta-analyses may be explained by genetic heterogeneity and the ethnic differences between Han Chinese and Caucasians. Our study is the first association test between rs1122608 and CHD in Chinese population. Compared to the two case–control association studies of rs11206510 with CHD in Han Chinese, our study analyzed the association of
rs11206510 with CHD not only in two genetic models (dominant model and recessive model) but also in different severity of CHD. We also set two controls (non-CHD controls and healthy controls) and explored the gender-stratified association of rs11206510 with CHD, though we failed to observe significant associations between the two SNPs and the risk of CHD. The statistics power of our study reached 70% at alpha level of 0.05. However, we could not exclude the possibility of a lack of power in our study mainly due to the relatively small sample size. In addition, we chose the rs11206510T > C polymorphism and rs1122608G> T polymorphism for susceptibility loci research, but we cannot exclude the possibility that other SNPs in linkage disequilibrium are responsible for our findings or that a tag-SNP strategy could have had a better chance of capturing the association of PCSK9 gene and LDLR gene with CHD. In conclusion, our meta-analysis has established a strong contribution of rs11206510 and rs1122608 to the risk of CHD, especially in Caucasians. We chose the two SNPs for the association of PCSK9 gene and LDLR gene with CHD. Although our case–control study was unable to find association of the two genes with the risk of CHD, further investigation on other SNPs on the two genes is warranted to validate our findings in Chinese population.
Acknowledgments The research was supported by the grants from: National Natural Science Foundation of China (31100919 and 30772155), Zhejiang Provincial Program for the Cultivation of High Level Innovative Health Talents, Natural Science Foundation of Zhejiang Province (Y206608), Ningbo social development research projects (2012C50032), and Youth and Doctor Foundation of Ningbo (2005A610016), and K.C. Wong Magna Fund in Ningbo University. We also thank Lihuili Hospital and the Seventh Hospital in Ningbo city for providing blood samples and detailed information of participants.
Appendix A. Supplementary data Supplementary data to this article can be found online at http:// dx.doi.org/10.1016/j.clinbiochem.2013.01.013.
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Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Association between PCSK9 and LDLR gene polymorphisms with coronary heart disease: Case-control study and meta-analysis Lina Zhang a,⁎, 1, Fang Yuan a, 1, Panpan Liu a, Lijuan Fei a, Yi Huang a, Limin Xu a, Lingmei Hao b, Xujun Qiu b, Yanping Le a, Xi Yang c, Weifeng Xu c, Xiaoyan Huang c, Meng Ye a, Jianqing Zhou c, Jiangfang Lian c,⁎, Shiwei Duan a,⁎ a b c
Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo 315211, Zhejiang Province, China Clinical laboratory, The Seventh Hospital of Ningbo, Ningbo 315211, Zhejiang Province, China Ningbo Medical Center, Lihuili Hospital, Ningbo University, Ningbo, Zhejiang 315041, China
a r t i c l e
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Article history: Received 6 September 2012 Received in revised form 15 January 2013 Accepted 21 January 2013 Available online 1 February 2013 Keywords: PCSK9 LDLR LDL-C SNP Meta-analysis
a b s t r a c t Objective: To explore the association of rs11206510 (PCSK9 gene) and rs1122608 (LDLR gene) polymorphisms with coronary heart disease (CHD) in Han Chinese. Methods: A total of 813 participants (290 CHD cases, 193 non-CHD controls and 330 healthy controls) were recruited in the case-control study. DNA genotyping was performed on the SEQUENOM® Mass–ARRAY iPLEX® platform. χ2-test was used to compare the genotype distribution and allele frequencies. Two meta-analyses were performed to establish the association between the two polymorphisms with CHD. Results: No significant associations between the two SNPs and the risk of CHD were observed in the present study. The meta-analysis of rs11206510 of PCSK9 gene comprises 11 case-control studies with a total of 69,054 participants. Significant heterogeneity was observed in Caucasian population in subgroup analysis of the association studies of rs11206510 with CHD (P=0.003, I2 =67.2%). The meta-analysis of LDLR gene rs1122608 polymorphism comprises 7 case-control studies with a total of 20,456 participants and the heterogeneity of seven studies was minimal (P =0.148, I2 =36.7%). Conclusion: The results of the meta-analyses indicated that both SNPs were associated with CHD in Caucasians (Pb 0.05) but not in Asians. The results from our case-control study and meta-analyses might be explained by genetic heterogeneity in the susceptibility of CHD and ethnic differences between Asians and Caucasians. © 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Introduction Coronary heart disease (CHD) is not only the crucial cause of mortality and disability in the industrialized countries but also remains a public health problem among the developing countries [1]. However, the pathogenesis of CHD remains largely unknown. The most generally accepted view is that CHD is a polygenic disease, resulting from the interaction of several genes and together with environmental factors such as unhealthy lifestyles and psychosocial factors. Genetic factors are estimated to account for 30–60% of the risk of CHD [2,3].
Abbreviations: CHD, coronary heart disease; PCSK9, proprotein convertase subtilisin/ kexin type serine protease 9; LDL, low-density lipoprotein; LDLR, low-density lipoprotein receptor; LDL-C, low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides; HDL, high-density lipoprotein; HWE, Hardy–Weinberg equilibrium; CI, confidence interval; OR, odds ratio. ⁎ Corresponding authors. E-mail addresses: [email protected] (L. Zhang), [email protected] (J. Lian), [email protected] (S. Duan). 1 Lina Zhang and Fang Yuan are the co-first authors.
Circulating blood lipid levels have been consistently associated with the risk of CHD [4,5]. In humans, nearly 60–70% of the total plasma cholesterol is transported by low-density lipoproteins (LDL) [6]. Epidemiological and clinical data indicate that elevated plasma level of low-density lipoprotein cholesterol (LDL-C) is a primary risk factor for the incidence of coronary events [7,8]. LDL metabolism is regulated by LDL receptor (LDLR) that is encoded by LDLR gene. Under normal circumstances LDL is removed from the circulation mainly by liver uptake via LDLR so that LDL-C remains a stable level of LDL-C in blood. In addition to LDLR, proprotein convertase subtilisin/kexin type serine protease 9 (PCSK9) can also impact the regulation of plasma levels of LDL-C. PCSK9 is a glycoprotein highly expressed in liver, intestine and kidney [9]. PCSK9 binds and favors the degradation of LDLR, thereby modulating the plasma levels of LDL-C [10]. Therefore, plasma levels of LDL-C and PCSK9 are likely to be directly correlated due to the PCSK9-promoted degradation of hepatic LDLR. High levels of PCSK9 were associated with the cardiovascular events in CHD patients with low statin usage [11]. Several GWASs have identified that rs11206510 of PCSK9 gene and rs1122608 of LDLR gene were associated with increased CHD risk
0009-9120/$ – see front matter © 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.clinbiochem.2013.01.013
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[12–14]. The two SNPs had significant association with CHD in European population through a meta-analysis of previous GWASs (Pb 5× 10−8) [15], but the positive significance needs to be confirmed since only two studies were included in the meta-analysis. In addition, a casecontrol study in Han Chinese showed that rs11206510-C allele was associated with increased risk of early-onset CHD (P= 0.002, OR= 1.89, 95% CI =1.25–2.34), but not with overall CHD (P =0.82, OR= 1.04, 95% CI = 0.77–1.41) [16]. However, another study in Han Chinese found that rs11206510 was significantly associated with CHD (P = 0.029, OR = 1.41, 95% CI= 1.04–1.93) [17]. As the contradictory results in Han Chinese, the goal of our study is to explore the association between the two SNPs and CHD in Eastern Han Chinese and establish the contribution of the two SNPs to the risk of CHD through two meta-analyses. Methods Sample collection A total of 483 patients (290 CHD cases and 193 non-CHD controls) from the Lihuili Hospital were recruited between May 2008 and November 2011. The mean (±SD) age was 61.98±9.49 years, and 72% were men in CHD cases, while the mean (±SD) age was 58.65± 9.36 years, and 51% were men in non-CHD controls. All patients had been examined by standardized coronary angiography according to the Seldinger's method [18], and the results were judged by at least two independent cardiologists. According to the coronary angiographic results, patients diagnosed with CHD had at least one or more major coronary arteries with 50% or greater stenosis. Patients with a history of prior angioplasty or coronary artery bypass surgery were also selected as CHD cases. The rest of the patients with less than 50% occlusion of any coronary vessel and no history of any atherosclerotic vascular diseases were grouped as non-CHD controls. Additional 330 healthy persons as the healthy controls were selected from a well-characterized random sample of the Ximen Community residents in Ningbo city. All the individuals were excluded from having congenital heart disease, cardiomyopathy, liver and renal disease. Blood samples were collected from subjects in a fasting state and treated by the same investigators. Then blood samples were stored at − 80 °C with 3.2% citrate sodium-treated tubes until analysis was performed. The study protocol was approved by the ethic committees of Ningbo University. All participants gave written informed consent that included consent for genetic studies. Disease history, demographic and risk factor data were extracted from the medical records. SNP Genotyping
the GeneAmp® PCR System 9700 (dual 384-well blocks) (Applied Biosystems, Foster City, CA). The PCR procedure included an initial denaturation step of 15 s at 94 °C was followed by 45 cycles of a 3step amplification profile of 20 s at 94 °C for denaturation, 30 s at 56 °C for annealing, 1 min at 72 °C for primer extension, then 3 min at 72 °C for a final extension. PCR products for genotyping were performed on the SEQUENOM® Mass-ARRAY iPLEX® platform according to the manufacturer's instructions. Statistical analyses Hardy–Weinberg equilibrium (HWE) was analyzed using Arlequin program (version 3.5) [19]. The Pearson's χ2-test was used to compare the genotype distribution, allele frequencies and other categorical phenotypes between CHD cases and each of two controls. The comparison of genotype and allele frequencies among the three degrees of coronary artery stenosis with CHD was performed by the Kruskal–Wallis test. All data were analyzed with SPSS statistical software (version 16.0). All tests were two-tailed and P values less than 0.05 were considered to be significant. Meta-analysis The literatures were obtained from the databases of Chinese Biomedical Literature Database (CBM), Chinese Knowledge Internet (CNKI) and PubMed. Taking the keywords ‘coronary heart disease’, ‘PCSK9’, ‘LDL receptor’, ‘polymorphism’, ‘gene’, ‘gene variant’ and ‘association’ as the search terms. Meanwhile, the papers should be published in Chinese or English from 2000 to 2012. Only the papers that examined the relationship between CHD and PCSK9 rs11206510 or LDLR rs1122608 can be used for the meta-analysis. The research papers were excluded if they did not provide genotype frequencies in both cases and controls or odds ratio (OR) and 95% confidence interval (95% CI). Information was collected from each study, including author, publication year, study population, distribution of genotype and allele in both cases and controls, OR and 95% CI. Meta-analysis was performed by the STATA software (version 11.0). Heterogeneity of the studies was done by the I2 test at the significant level of 0.05. If there was heterogeneity in the studies, a pooled OR was calculated by the random effect model; otherwise, the fixed effect model was used [20,21]. The publication bias was measured by funnel plots. Power analysis Power analysis was performed by the Power and Sample Size Calculation Software (PS). The significance level sets at 0.05.
Human genomic DNA was extracted from peripheral blood samples using the Nucleic acid extraction automatic analyzer (Lab-Aid 820, Xiamen City, China). Then DNA was quantified using the PicoGreen® double strand (dsDNA) DNA Quantification Kit (Molecular Probes, Inc. Eugene, USA). PCR for genotyping experiments was performed on
Results Genotype distributions did not deviate from Hardy–Weinberg equilibrium (HWE) in CHD cases, non-CHD controls and healthy controls,
Table 1 Comparison of genotype distributions and allele frequencies between CHD cases and two groups of controls. χ2
Genotype rs11206510 CHD cases (n = 290) Control 1 (n = 193) Control 2 (n = 330)
TT 253(87.2) 171(88.6) 285(86.4)
TC 37(12.8) 21(10.9) 45(13.6)
CC 0 1(0.5) 0
rs1122608 Cases (n = 289) Control 1 (n = 191) Control 2 (n = 330)
GG 232(80.3) 151(79.1) 263(79.7)
GT 54(18.7) 40(20.9) 63(19.1)
TT 3(1) 0 4(1.2)
Control 1: non-CHD controls. Control 2: healthy controls. a Fisher's exact test.
1.77 0.1
a
1.88a 0.12a
P (df = 2)
Allele
0.42 0.81
T 543(93.6) 363(94) 615(93.2)
0.39 0.98
G 518(89.6) 342(89.5) 589(89.2)
χ2
P (df = 1)
HWE
C 37(6.4) 23(6) 45(6.8)
0.07 0.1
0.89 0.82
0.3 0.7 0.2
T 60(10.4) 40(10.5) 71(10.8)
0.002 0.05
1.0 0.85
0.9 0.1 0.9
L. Zhang et al. / Clinical Biochemistry 46 (2013) 727–732 Table 2 Characteristics of published studies of the association between rs11206510 and CHD in the meta-analysis.
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Table 3 Characteristics of published studies of the association between rs1122608 and CHD in the meta-analysis.
Author
Year
Case
Control
Population
Risk allele
Author
Year
Case
Control
Population
Risk allele
Muredach P Reilly et al. [12] Lu Qi-NHS et al. [23] Lu Qi-HPFS et al. [23] Lu Qi-JHS et al. [23] Dawn M. Waterworth et al. [21] Ilaria Guella et al. [22] Chengqi Xu et al. [15] Sekar Kathiresan et al. [11] Cristen J Willer et al. [13] Xiaofei Lv et al. [16] Our study
2011 2011 2011 2011 2010 2010 2010 2009 2008 2012 2012
6886 309 345 422 6988 1880 1543 2967 1925 1007 290
3226 544 451 435 19,945 1880 1240 3075 12,284 889 523
Caucasian Caucasian Caucasian Caucasian Caucasian Caucasian Asian Caucasian Caucasian Asian Asian
T T T T T T C T T T T
Muredach P Reilly et al. [12] Lu Qi-NHS et al. [23] Lu Qi-HPFS et al. [23] Lu Qi-JHS et al. [23] Sekar Kathiresan et al. [11] Nicola Martinelli et al. [24] Our study
2011 2011 2011 2011 2009 2010 2012
6886 309 345 422 2967 692 290
3226 544 451 435 3075 291 523
Caucasian Caucasian Caucasian Caucasian Caucasian Caucasian Asian
G G G G G G G
suggesting that our case-control study had a well-characterized random sampling. Genotype and allele frequencies of rs11206510 of PCSK9 gene and rs1122608 of LDLR gene were summarized in Table 1. No significant associations of the two SNPs with CHD were found in the case-control comparisons. A further breakdown analyses by gender also produced negative association results (Supplemental Table 1 and Supplemental Table 2). Under the dominant and recessive genetic model, we failed to find any difference in the allelic and genotypic distribution of the two SNPs between CHD cases and each of the two controls (Supplemental Table 3). Significant association was found between the degree of coronary artery stenosis and the genotype of rs1122608 (Pb 0.001). However, this result may be biased by the rare number of TT. The number of TT in one coronary vessel lesion level was only 2 and 1 in three coronary vessel lesion. Our data indicated that the two SNPs were not associated with the severity of CHD in other conditions (Supplemental Table 4). A total of 11 studies were selected into the meta-analysis for the association of rs11206510 of PCSK9 gene with CHD (Table 2). Flow diagram of articles searching in the meta-analysis was shown in Supplemental Fig. 1. Among them, four studies were GWASs [12–14,22] and the rest five (including our study) were case–control studies [16,17,23,24]. For the study with multiple subgrouped case-control
associations [24], we separately integrated them into our metaanalysis. The studies in the meta-analysis were carried out in multiple places including Europe, America, and Asia. A heterogeneity test showed that there were significant heterogeneity among the eleven studies (P = 0.007, I 2 = 58.5%). In order to recognize the source of heterogeneity, a further subgroup analysis of population was performed. It suggested that heterogeneity mainly existed in Caucasians (P = 0.003, I2 = 67.2%). As shown in Fig. 1, meta-analysis showed that rs11206510 of PCSK9 gene was a risk factor of CHD in Caucasians (P = 0.007, OR= 1.09, 95% CI = 1.03–1.17, random-effects model), but not in Asians (P = 0.167, OR= 1.16, 95% CI = 0.94–1.43, random-effects model). Seven studies were included in the meta-analysis of rs1122608 of LDLR gene [12,13,24,25] (Table 3). Details of articles in the metaanalysis were shown in Supplemental Fig. 2. Among them, two were GWASs [12,13]. The studies in the meta-analysis were carried out in the population of European and American. The heterogeneity of seven studies was minimal (P = 0.148, I2 = 36.7%). As shown in Fig. 2, the subgroup meta-analysis showed that rs1122608 of LDLR gene was a risk factor of CHD, especially in Caucasians (OR= 1.10, 95% CI= 1.02– 1.19, P = 0.011, random effects model). As shown in Figs. 3 and 4, no visual evidence of publication bias for the two meta-analyses was observed by the funnel plots. Furthermore, the Egger's test was not significant for the meta-analyses of rs11206510 of PCSK9 gene (P = 0.83) and rs1122608 of LDLR gene (P =0.085).
Fig. 1. Forest plot of the association between rs11206510 of PCSK9 gene and CHD in different populations.
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Fig. 2. Forest plot for the association between rs1122608 of LDLR gene and CHD in different populations.
Discussion Previous studies have suggested that the levels of TC, LDL-C and HDL-C were independent heritable risk factors for cardiovascular diseases [26]. Some of the genetic risk loci for CHD may exert their effects by modulating or interacting with these factors. Recent GWASs have identified multiple loci and candidate genes for blood lipid-related traits [5]. Ilaria Guella et al. observed that the minor allele C of the rs11206510 of PCSK9 gene was strongly related to lower concentration of both LDL (OR = 0.82, 95% CI = 0.73-0.93, P = 1.89 × 10 −3) and total cholesterol (OR = 0.80, 95% CI= 0.72–0.89, P = 8.12× 10−5) in Italian population [23]. Tanya M. Teslovich and colleagues recently published a case-control study involving with more than 100,000 European ancestry participants to test the association of CHD with several polymorphisms of PCSK9 and LDLR [5]. Their results showed that
log[or]
.5
rs11206510-T of PCSK9 gene and rs1122608-G of LDLR gene were associated with increased LDL-C and TC levels and the risk of CHD. Cristen J Willer et al. found that rs11206510 of PCSK9 gene had a positive association with both the concentration of LDL-C and the risk of CHD in Europeans [14]. Other three GWASs confirmed the contribution of rs11206510 (T > C) of PCSK9 gene to the risk of CHD in Europeans [15,22,27]. However, Muredach P Reilly and colleagues performed a GWAS in Europeans and were unable to find an association between rs11206510 (T > C) and CHD [13]. For rs1122608 (G > T) of LDLR gene, there were four GWASs which have observed its association with CHD in participants of European ancestry [13,15,27,28]. The crucial role of PCSK9 gene and LDLR gene in the LDL-C metabolism made this result meaningful and prompted us to explore the contribution of the two SNPs with CHD in Chinese population [5]. Neither rs11206510 nor rs1122608 was associated with the incidence and the
Begg's funnel plot with pseudo 95% confidence limits
0
-.5 0
.05
.1
.15
.2
s.e. of: log[or] Fig. 3. Funnel plot of the association between rs11206510 of PCSK9 gene and CHDa. aHorizontal axis represents the standard error of log OR. Vertical axis represents the log OR. The s.e. denotes standard error.
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Begg's funnel plot with pseudo 95% confidence limits
log[or]
.5
0
-.5 0
.1
.2
s.e. of: log[or] a a
Fig. 4. Funnel plot for the association between rs1122608 of LDLR gene and CHD . Horizontal axis represents the standard error of log OR. Vertical axis represents the log OR. The s.e. denotes standard error.
severity of CHD, and no interaction of the two SNPs with gender was found in our study (data not shown). However, a study in Han Chinese found that rs11206510 was associated with early-onset CHD but not with overall CHD, which defined early-onset CHD as males aged 50 years or younger and females aged 55 years or younger at the first time of the diagnosis of CHD[16]. The results were consistent with our findings that rs11206510 was not associated with overall CHD. In our study, we did not explore the association between rs11206510 and early-onset CHD. The patients with angiographic results were simply divided into three levels, one coronary vessel lesion, two coronary vessel lesion, three and more coronary vessel lesion, according to the degree of coronary artery stenosis. A lack of association between rs11206510 and the severity of CHD might be due to the imperfect classification method of CHD, since the severity of CHD could be reflected by both the number of coronary artery stenosis and the percent area stenosis inside the coronary arteries. A combined grading method with both parameters might be more precise to define the severity of CHD. Meta-analysis established that both rs11206510 of PCSK9 gene and rs1122608 of LDLR gene were associated with the risk of CHD. The conclusion was the same as the previous meta-analysis in Europeans [15]. Compared to the previous meta-analysis of rs11206510, our meta-analysis comprised eleven studies in European, American, and Asian populations to ensure reliability of the results. A further subgroup analysis in our study showed that large heterogeneity mainly existed in Caucasian population. Association study of the two SNPs was only significant in Caucasians but not in Asians. The minor allele frequency of rs11206510-C of PCSK9 gene is 6.5% in present study, but it is 19% in Caucasians. The minor allele frequency of rs1122608-T in Chinese (10.6%) was lower than that in Europeans (25%) and a previous study in Han Chinese discovered that the minor allele C of rs11206510 was associated with increased LDL-C levels, but genome-wide association studies found that the common allele T of rs11206510 was associated with increased LDL-C levels[16]. Since most of the studies in the metaanalysis were performed in Caucasians, the conflicting results between our association study and meta-analyses may be explained by genetic heterogeneity and the ethnic differences between Han Chinese and Caucasians. Our study is the first association test between rs1122608 and CHD in Chinese population. Compared to the two case–control association studies of rs11206510 with CHD in Han Chinese, our study analyzed the association of
rs11206510 with CHD not only in two genetic models (dominant model and recessive model) but also in different severity of CHD. We also set two controls (non-CHD controls and healthy controls) and explored the gender-stratified association of rs11206510 with CHD, though we failed to observe significant associations between the two SNPs and the risk of CHD. The statistics power of our study reached 70% at alpha level of 0.05. However, we could not exclude the possibility of a lack of power in our study mainly due to the relatively small sample size. In addition, we chose the rs11206510T > C polymorphism and rs1122608G> T polymorphism for susceptibility loci research, but we cannot exclude the possibility that other SNPs in linkage disequilibrium are responsible for our findings or that a tag-SNP strategy could have had a better chance of capturing the association of PCSK9 gene and LDLR gene with CHD. In conclusion, our meta-analysis has established a strong contribution of rs11206510 and rs1122608 to the risk of CHD, especially in Caucasians. We chose the two SNPs for the association of PCSK9 gene and LDLR gene with CHD. Although our case–control study was unable to find association of the two genes with the risk of CHD, further investigation on other SNPs on the two genes is warranted to validate our findings in Chinese population.
Acknowledgments The research was supported by the grants from: National Natural Science Foundation of China (31100919 and 30772155), Zhejiang Provincial Program for the Cultivation of High Level Innovative Health Talents, Natural Science Foundation of Zhejiang Province (Y206608), Ningbo social development research projects (2012C50032), and Youth and Doctor Foundation of Ningbo (2005A610016), and K.C. Wong Magna Fund in Ningbo University. We also thank Lihuili Hospital and the Seventh Hospital in Ningbo city for providing blood samples and detailed information of participants.
Appendix A. Supplementary data Supplementary data to this article can be found online at http:// dx.doi.org/10.1016/j.clinbiochem.2013.01.013.
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