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Association of a DNA polymorphism of the apolipoprotein AI–CIII–AIV gene cluster with myocardial infarction in a Tunisian population
European Journal of Internal Medicine 22 (2011) 407–411
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European Journal of Internal Medicine j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e j i m
Original article
Association of a DNA polymorphism of the apolipoprotein AI–CIII–AIV gene cluster with myocardial infarction in a Tunisian population Yousra Sediri a, Amani Kallel a, Moncef Feki a, Sami Mourali b, Monia Elasmi a, Salem Abdessalem b, Rachid Mechmeche b, Riadh Jemaa a,⁎, Naziha Kaabachi a a b
Research Laboratory LR99ES11, Department of Biochemistry, Hospital la Rabta, Tunis, Tunisia Department of Cardiology, Hospital la Rabta, Tunis, Tunisia
a r t i c l e
i n f o
Article history: Received 24 June 2010 Received in revised form 17 February 2011 Accepted 3 March 2011 Available online 21 April 2011 Keywords: ApoAI–CIII–AIV gene cluster Polymorphism Myocardial infarction
a b s t r a c t Background: Apolipoproteins AI–CIII–AIV play important roles in the metabolism of triglycerides and highdensity lipoprotein cholesterol. However, whether genetic variations in the ApoAI–CIII–AIV gene cluster are associated with the risk of myocardial infarction (MI) remains uncertain. In the present study, we examined a possible association of the ApoCIII SacI polymorphism in the ApoAI–CIII–AIV gene cluster with lipid parameters and MI in a sample of the Tunisian population. Methods: A total of 326 Tunisian patients with MI and 361 controls were included in the study. Genotypes were determined by polymerase chain reaction — restriction fragment length polymorphism (PCR-RFLP) analysis. Results: A significant difference in genotype distribution and allele frequency was observed between patients and controls. At the multivariate analysis after adjustment for traditional vascular risk factors, the ApoCIII SacI polymorphism was significantly associated with MI, according to co-dominant and dominant models (codominant model odds ratio [OR]: 1.53, 95% confidence interval [CI]: 1.0–2.35, p = 0.04; dominant model OR: 2.02, 95% CI: 1.11–3.67, p = 0.02). The MI patient group showed a significant higher frequency of the S2 allele compared to the controls (10.2% vs. 6.5%; OR: 1.64, 95% CI: 1.10–2.47, p = 0.01). There was no statistically significant association between ApoAI–CIII–AIV cluster gene polymorphism and lipid, lipoprotein, and apolipoprotein levels in both MI patients and controls. Conclusion: In the current study, a significant association between the ApoCIII SacI polymorphism (presence of S2 allele) and MI in the Tunisian population was found. © 2011 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.
1. Introduction Plasma lipids and lipoproteins are important determinants for cardiovascular disease susceptibility. The genes of ApoAI–CIII–AIV cluster play an important role in the transport of cholesterol, triglycerides and phospholipids in plasma [1]. Molecular alterations within this cluster may result in the defective plasma lipid transport system which augments the proatherogenic conditions for the development of coronary artery disease (CAD) [2]. The genes coding for Apolipoproteins AI, CIII and AIV are closely linked and are present in a cluster spanning about 15 kb on the long arm of chromosome 11. Several polymorphisms within the ApoAI–CIII–AIV cluster gene have been detected, and several studies have suggested associations between some restriction fragment length polymorphism (RFLP) loci of this cluster gene and variations in plasma lipid concentrations [3–5], although the results have not always been concordant in general populations [6]. Several polymorphic sites have been detected ⁎ Corresponding author at: Laboratoire de Biochimie, Hôpital la Rabta, 1007, Jabbari, Tunis, Tunisia. Tel.: +216 71 561 912, +216 98 819 168; fax: +216 71 561 912. E-mail address: [email protected] (R. Jemaa).
within and around the ApoCIII gene. The most extensively studied is the SacI polymorphism, due to a C¬G substitution at nucleotide 3238 (rs5128), in the 3′ untranslated region of the gene. This transversion generates two alleles: S1 and S2. The frequency of the less common allele (S2) varies among different ethnic groups. In several case–control studies, this SacI polymorphism has been associated with hypertriglyceridemia, hypercholesterolemia and CAD [7–12]. However, some other studies have shown contradictory results [13,14] . Association studies of the ApoAI–CIII–AIV cluster gene have mainly reported on Caucasian populations. Up to date, no study had tested this association in Tunisian population. The aim of the present study was to investigate the possible association between the ApoCIII SacI polymorphism and MI in a subgroup of the Tunisian population. 2. Materials and methods 2.1. Study population The total population of this study consisted of 687 unrelated subjects living in the City of Tunis (Tunisia). A total of 326 male patients with MI were enrolled from the Department of Cardiology, Rabta University
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Table 1 Anthropometric and metabolic variables of the study population. Variables
Controls (n = 361)
Patients (n = 326)
P
Age (years) BMI (kg/m2) Diabetes (%) Hypertension (%) Obesity (%) Dyslipidemia (%) Smoking (%) TC (mmol/L) TG (mmol/L) LDL-C (mmol/L) HDL-C (mmol/L) Apo B (g/L) Apo AI (g/L)
51.1 ± 9.5 26.1 ± 5.0 15.6 17.8 37.1 16.6 55.6 4.84 ± 0.98 1.54 ± 0.90 2.95 ± 0.85 1.13 ± 0.28 0.88 ± 0.22 1.33 ± 0.25
53.8 ± 8.6 25.2 ± 3.5 37.9 29.0 30.8 30.5 88.8 5.05 ± 1.11 1.88 ± 0.81 3.34 ± 1.01 0.85 ± 0.23 1.14 ± 0.32 1.27 ± 0.32
b 0.001 0.005 b 0.001 b 0.001 0.074 b 0.001 b 0.001 0.007 b 0.001 b 0.001 b 0.001 b 0.001 b 0.001
Data are expressed as means ± SD for some and as percent in others variables.
Hospital of Tunis. The mean age of this group was 53± 8 years. Diagnosis of MI was confirmed by chest symptoms, electrocardiographic changes and serum creatine kinase-MB isoenzyme elevations more than twice the upper normal level. The control group included 361 male volunteers, with no history of angina pectoris or MI, and with a normal electrocardiogram. Their mean age was 51 ± 9 years. Informed written consent was obtained from all participants and the design of the study was approved by the local Ethics Committee. Weight and height were measured on the subjects barefooted and lightly clothed. Body mass index (BMI; kg/m2) was calculated and obesity was defined as BMI≥ 30 kg/m2 [15]. Diabetes mellitus was defined as hyperglycemia, requiring antidiabetic drugs or testing blood sugar over 7.0 mmol/L. Hypertension was defined as systolic blood pressure ≥ 140 mm Hg and/or diastolic blood pressure ≥ 90 mm Hg, or the use of antihypertensive drug treatment, or a combination of these. Dyslipidemia was defined as a total cholesterol (TC) level N 6.47 mmol/L and/or triglyceride (TG) level N 2.26 mmol/L. A daily consumption of N 5 cigarettes was considered a smoking habit. 2.2. Laboratory analysis Blood samples were obtained after an overnight fast. Plasma levels of TC, TG, and HDL-cholesterol (HDL-C) were measured by standardized enzymatic procedures, and ApoAI and ApoB were measured using turbidimetric assay on a Hitachi 912 analyzer. LDL-cholesterol (LDL-C) was calculated according to Friedewald's formula [16]. 2.3. DNA analysis Genomic DNA was prepared from white blood cells by phenol extraction [17]. A method similar to that described by Hixon et al. [18]
was used to detect the polymorphic nucleotide recognized by the restriction enzyme SacI (SacI is an isoschizomer of SstI). A 254 bp region of the 3′ end of the ApoCIII gene containing the polymorphic site was amplified by the polymerase chain reaction (PCR). The primers used were 5′-AGGACAAGTTCTCTGAGTTCT-3′ (forward), and 5′-ATAGCAGCTTCTTGTCCAGCTT-3′ (reverse). Digestion with SacI yields fragments of 254 base pairs in the presence of the S1 allele, and 144 and 110 base pairs in the presence of the S2 allele. The products were separated in 3% agarose gel, stained with ethidium bromide. To ensure that the genotyping was of adequate quality, all gels were reread blindly by 2 persons without any change, and 20% of the analyses was repeated randomly. 2.4. Statistical analysis The Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS 10.0 for Windows; SPSS Inc., Chicago, IL, USA). Distributions of continuous variables in groups were expressed as mean ± SD, and compared with unpaired Student's t-tests. χ2 tests were used to test for departures from Hardy–Weinberg equilibrium and to compare genotype distributions between groups. The ApoAI–CIII–AVI SacI polymorphism was first assessed in three genotype categories (wild-type, heterozygote, and homozygote variants) and then grouped into two categories with heterozygote and homozygote variants combined because of the dominant model of inheritance observed for this polymorphism. Data for triglyceride were log transformed to reduce skewness of the data. Odds ratio (OR) and 95% confidence intervals (CI) were calculated using unconditional logistic regression. Crude and adjusted models for age, diabetes, HTA, dyslipidemia, BMI, smoking and genotypes were fitted. Associations of quantitative variables with genotype were examined by analysis of covariance (General Linear Model procedure). A two-tailed p-value b 0.05 was considered statistically significant. 3. Results The demographic and clinical characteristics of the MI and control groups are summarized in Table 1. There were significant differences for age (p = 0.001), BMI (p = 0.005), and the frequencies of diabetes (p b 0.001), hypertension (p b 0.001), obesity (p = 0.074), dyslipidemia (p b 0.001) and cigarette smoking (p b 0.001) between the MI and control groups. MI patients had higher levels of TC (p = 0.007), LDL-C, TG and Apo B (p b 0.001), and lower levels of HDL-C and ApoAI (p b 0.001) than control subjects. Genotype distributions were in Hardy–Weinberg equilibrium in patients (χ2 = 3.945, p = 0.139) and controls (χ2 = 3.567, p = 0.168). A significant difference in both genotype distribution and allele frequency between MI patients and controls subjects was observed. The univariate
Table 2 Genotype distributions and allele frequencies of the ApoCIII SacI polymorphism among MI patients and controls, and crude and adjusted estimations for MI. Controls (n = 361)
MI patients (n = 326)
Unadjusted OR 95%CIa
P
Adjusted OR 95%CIb
P
Codominant model S1S1 n (%) S1S2 n (%) S2S2 n (%)
315 (87.3) 45 (12.4) 1 (0.3)
266 (81.6) 53 (16.3) 7 (2.1)
1 1.39 (0.90–2.14) 8.28 (1.01–67.80)
0.129 0.049
1.49 (0.88–2.50) 1.53 (1.0–2.35)
0.133 0.048
Dominant model S1S1 n (%) S1S2 + S2S2 n (%)
315 (87.3) 46 (12.7)
266 (81.6) 60 (18.4)
1 1.54 (1.01–2.34)
0.041
1 2.02 (1.11–3.67)
0.020
– 1 .64 (1.10–2.47)
0.011
Allele frequency S1 (%) S2 (%)
93.45 6.55
89.75 10.25
S1S1, homozygous; S1S2, heterozygous; S2S2, homozygous for the mutation. OR, odds ratio; CI, confidence interval. a Crude logistic regression model. b Adjusted for age, HTA, diabetes, dyslipidemia, BMI and smoking.
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Table 3 Clinical and biochemical characteristics of patients and controls according to genotypes. apoA-I–CIII–AIV genotypes Variables
Controls (n = 361)
Cholesterol (mmol/L) Triglycerides (mmol/L) LDL-cholesterol (mmol/L) HDL-cholesterol (mmol/L) Apo AI (g/L) Apo B (g/L)
MI patients (n = 326)
S1S1 n = 312
S1S2 + S2S2 n = 46
P
S1S1 n = 260
S1S2 + S2S2 n = 60
P
4.84 ± 0.95 1.54 ± 0.92 2.97 ± 0.82 1.13 ± 0.31 1.33 ± 0.25 0.87 ± 0.21
4.81 ± 1.03 1.46 ± 0.84 2.95 ± 0.90 1.19 ± 0.28 1.33 ± 0.21 0.86 ± 0.26
0.875 0.566 0.840 0.295 0.882 0.717
4.99 ± 1.13 1.88 ± 0.82 3.31 ± 1.03 0.85 ± 0.23 1.28 ± 0.33 1.13 ± 0.31
5.18 ± 1.08 1.92 ± 0.82 3.44 ± 0.93 0.85 ± 0.23 1.25 ± 0.28 1.19 ± 0.40
0.294 0.787 0.329 0.733 0.445 0.182
Data presented are mean ± SD.
logistic regression analysis showed a significant association of the ApoCIII SacI polymorphism and MI according to co-dominant and dominant models (co-dominant model OR: 8.28, 95% CI: 1.01–67.80; p = 0.04 and dominant model OR: 1.54; 95% CI: 1.01–2.34; p = 0.04) (Table 2). After adjustment for age, diabetes, hypertension, HTA, BMI, dyslipidemia and smoking (Table 2), the ApoCIII SacI polymorphism was found to be significantly associated with MI, according to the models considered. The MI patient group showed a significant higher frequency of the S2 allele compared to the controls (10.2% vs. 6.5%; OR: 1.64, 95% CI: 1.10–2.47, p = 0.01). Serum lipid, lipoprotein and apolipoprotein concentrations according to genotype in the control group and MI patients are given in Table 3. Because of the rarity of homozygosity for the S2 allele and the small numbers of those available, data from those having a S2 allele (S1S2+ S2S2) were compared with that from those homozygous for the common S1 allele. There were no significant differences among any genotypes for any lipid and lipoprotein traits. When MI patients and controls were divided into those with hypertriglyceridemia or hypercholesterolemia and those with normal triglyceride and cholesterol levels, there was no evidence for statistically significant association between the ApoAI–CIII–AIV SacI polymorphism and dyslipidemia (data not shown). 4. Discussion The principal aim of this study was to investigate the relationship between variation at the ApoAI–CIII–AIV SacI locus and lipids and MI in a Tunisian population. Both patients with MI and controls belonged to the same ethnic background and all shared a common geographic origin in North Tunisia. We showed that the ApoAI–CIII–AIV SacI polymorphism was associated with MI in Tunisian patients. This association persisted after adjusting for several potential confounding factors. The S2 allele frequency of ApoCIII SacI polymorphism in controls varied considerably
among populations, ranging from 0.06 (Caucasians) [10] to 0.37 (Japanese) [19]. The frequency of the S2 allele in our controls is 0.06, consistent with that previously reported in normal Danish men (0.09) [20] and US men in the Framingham Offspring Study (0.08) [21]. Previous studies of the ApoCIII SacI polymorphism in CAD risk have yielded conflicting results, with some studies indicating a possible link with genetic variability at this locus [10,22–26] and others not confirming these associations [14,19,27–29] (Table 4). The reason for this discrepancy remains unclear. These different results are likely to be a consequence not only of the different sample sizes or the different allelic frequencies observed in different ethnic groups, but also and most importantly of different selection criteria adopted for patients and controls, in particular clinical presentation, extent of disease, age, race, geographical area, concomitant environmental risk factors and the interactions, gene–gene and gene–environment. Another explanation could be that a putative disease-marker could be population specific or that the non-random associations between the marker alleles and the important mutations may differ among populations. As such, the functionally important mutations may be present in some and not in other populations [9,30,31]. The mechanism by which the ApoCIII SacI polymorphism confers susceptibility to MI is not clear. But, since ApoAI–CIII–AIV SacI is located in the 3′ untranslated region of the ApoCIII gene, it is possible that this polymorphism is in linkage disequilibrium with some other functional polymorphic loci in the nearby region of chromosome 11 acting through a yet unknown mechanism. It was suggested by Patsch et al. [32] in 1994 that sequence variation in the ApoAI–CIII–AIV gene cluster region might alter plasma lipid transport and thus affect susceptibility to atherosclerosis. In our study, there was no significant difference among genotypes for any lipid, or lipoprotein traits. These findings are in agreement with some earlier studies [6,27,28,33], but not all [14,20,34–40]. The discrepancies between the studies may be
Table 4 Associations with hypertriglyceridemia or coronary artery disease of the S2 allele in various sample populations during the last 10 years. Authors
Years
Country
Cases/events
Controls
Endpoints
Statistically significant results
Hussain et al. [25] Kee et al. [28] Buzza et al. [6] Chhabra et al. [8] Corella et al. [34] Liu et al. [14] Islam et al. [24] Relvas et al. [29] De França et al. [35] Herron et al. [38] Huang et al. [37] Shanker et al. [26] Parzianello et al. [40] Bhanushali and Das [12] Li et al. [39]
1999 1999 2001 2002 2002 2004 2005 2005 2005 2006 2006 2008 2008 2010 2010
Saudi Arabia France European Asian Indians Spain United States Finland Brazil Brazil United States Taiwan Asians Indians Japanese India China
54 614 – – – 385 214 119 – – 159 523 families – 90 –
38 764 2003 139 1029 373 – 100 414 91 90 – 159 150 1030
CHD MI HTG HTG HTG MI IMT T2D, MI HTG HTG HTG CAD HTG CAD HTG
Yes No No Yes Yes No Yes No No Yes Yes Yes Yes Yes Yes
HTG, hypertriglyceridemia; MI, myocardial infarction; CHD, Coronary heart disease. T2D, type 2 diabetes; IMT, intima-media thickness; CAD, coronary artery disease.
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explained by genetic difference between the Tunisian population used in our study and populations where this association has been detected. It clear from other studies that lifestyle factors may modify certain genotype effects [31,41–43]. Peacock et al. [41] found that the effects of the ApoAI–CIII loci on circulating levels of triglycerides, HDL-C, and ApoAI were modulated by gender and smoking. On the other hand, in our population studied, there are many obese people in the control and MI patients which could cancel the genetic effect. Some limitations of our study should be taken into consideration. For example, our study was limited to a cohort of almost exclusively Tunisian men. Another was the small size of screened population; this caveat may limit our conclusions. Finally our study focused on a single SNP approach rather than a haplotype approach. 5. Conclusion The present study showed a significant association between the ApoAI–CIII–AIV SacI polymorphism and MI, but there was no association between this polymorphism and lipid and lipoprotein levels in the male Tunisian population. Further research involving additional polymorphisms of the region spanning and extending beyond the ApoAI–CIII–AIV gene complex chromosomal locus might help to locate the responsible gene and identify the mechanism by which it affects MI. 6. Learning points • Coronary artery disease (CAD) is one of the leading causes of morbidity and mortality in much of the world today. CAD is a complex condition, resulting from genetic and environmental contributions. • Many genes are suspected to be involved in its etiology. Several studies have suggested that genetic variations of the apolipoprotein (apo) AI–CIII–AIV cluster gene are associated with hyperlipidemia and atherosclerosis in the general population. • Moreover, conflicting results emerge from the literature and suggest that the effect is context-dependent. • To our knowledge there were no previous studies about the relation of apo AI–CIII–AIV cluster gene polymorphism with myocardial infarction (MI) in the Tunisian population. • This study was conducted to elucidate the association between SacI polymorphism and MI in the Tunisian population. • A significant and independent association between the Apo-CIII SacI polymorphism and MI in the Tunisian population was found. Conflict of interest The authors do not have any conflicts of interest in connection with this paper. Acknowledgment This work was supported by a grant from the Ministry of Higher Education, Scientific Research and Technology of Tunisia. References [1] Wang QF, Liu X, O'Connell J. Haplotypes in the APOA1–C3–A4–A5 gene cluster affect plasma lipids in both humans and baboons. Hum Mol Genet 2004;10:1049–56. [2] Lamarche B, Moojani S, Lupien PJ, Cantin B, Bernard PM, Dagenais GR, et al. Apoliporotein A-1 and B levels and the risk of ischemic heart disease during a five-year follow-up of men in the Quebec cardiovascular study. Circulation 1996;94:273–8. [3] Lai CQ, Parnell LD, Ordovas JM. The APOA1/C3/A4/A5 gene cluster, lipid metabolism and cardiovascular disease risk. Curr Opin Lipidol 2005;16:153–66. [4] Waterworth DM, Talmud PJ, Bujac SR, Fisher RM, Miller GJ, Humphries SE. Contribution of apolipoprotein C-III gene variants to determination of triglyceride levels and interaction with smoking in middle-aged men. Atherioscler Thromb Vasc Biol 2000;20:2663–9. [5] Hegele RA, Connelly PW, Hanley AJ, Sun F, Harris SB, Zinman B. Common genomic variation in the APOC3 promoter associated with variation in plasma lipoproteins. Arterioscler Thromb Vasc Biol 1997;17:2753–8.
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European Journal of Internal Medicine j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e j i m
Original article
Association of a DNA polymorphism of the apolipoprotein AI–CIII–AIV gene cluster with myocardial infarction in a Tunisian population Yousra Sediri a, Amani Kallel a, Moncef Feki a, Sami Mourali b, Monia Elasmi a, Salem Abdessalem b, Rachid Mechmeche b, Riadh Jemaa a,⁎, Naziha Kaabachi a a b
Research Laboratory LR99ES11, Department of Biochemistry, Hospital la Rabta, Tunis, Tunisia Department of Cardiology, Hospital la Rabta, Tunis, Tunisia
a r t i c l e
i n f o
Article history: Received 24 June 2010 Received in revised form 17 February 2011 Accepted 3 March 2011 Available online 21 April 2011 Keywords: ApoAI–CIII–AIV gene cluster Polymorphism Myocardial infarction
a b s t r a c t Background: Apolipoproteins AI–CIII–AIV play important roles in the metabolism of triglycerides and highdensity lipoprotein cholesterol. However, whether genetic variations in the ApoAI–CIII–AIV gene cluster are associated with the risk of myocardial infarction (MI) remains uncertain. In the present study, we examined a possible association of the ApoCIII SacI polymorphism in the ApoAI–CIII–AIV gene cluster with lipid parameters and MI in a sample of the Tunisian population. Methods: A total of 326 Tunisian patients with MI and 361 controls were included in the study. Genotypes were determined by polymerase chain reaction — restriction fragment length polymorphism (PCR-RFLP) analysis. Results: A significant difference in genotype distribution and allele frequency was observed between patients and controls. At the multivariate analysis after adjustment for traditional vascular risk factors, the ApoCIII SacI polymorphism was significantly associated with MI, according to co-dominant and dominant models (codominant model odds ratio [OR]: 1.53, 95% confidence interval [CI]: 1.0–2.35, p = 0.04; dominant model OR: 2.02, 95% CI: 1.11–3.67, p = 0.02). The MI patient group showed a significant higher frequency of the S2 allele compared to the controls (10.2% vs. 6.5%; OR: 1.64, 95% CI: 1.10–2.47, p = 0.01). There was no statistically significant association between ApoAI–CIII–AIV cluster gene polymorphism and lipid, lipoprotein, and apolipoprotein levels in both MI patients and controls. Conclusion: In the current study, a significant association between the ApoCIII SacI polymorphism (presence of S2 allele) and MI in the Tunisian population was found. © 2011 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.
1. Introduction Plasma lipids and lipoproteins are important determinants for cardiovascular disease susceptibility. The genes of ApoAI–CIII–AIV cluster play an important role in the transport of cholesterol, triglycerides and phospholipids in plasma [1]. Molecular alterations within this cluster may result in the defective plasma lipid transport system which augments the proatherogenic conditions for the development of coronary artery disease (CAD) [2]. The genes coding for Apolipoproteins AI, CIII and AIV are closely linked and are present in a cluster spanning about 15 kb on the long arm of chromosome 11. Several polymorphisms within the ApoAI–CIII–AIV cluster gene have been detected, and several studies have suggested associations between some restriction fragment length polymorphism (RFLP) loci of this cluster gene and variations in plasma lipid concentrations [3–5], although the results have not always been concordant in general populations [6]. Several polymorphic sites have been detected ⁎ Corresponding author at: Laboratoire de Biochimie, Hôpital la Rabta, 1007, Jabbari, Tunis, Tunisia. Tel.: +216 71 561 912, +216 98 819 168; fax: +216 71 561 912. E-mail address: [email protected] (R. Jemaa).
within and around the ApoCIII gene. The most extensively studied is the SacI polymorphism, due to a C¬G substitution at nucleotide 3238 (rs5128), in the 3′ untranslated region of the gene. This transversion generates two alleles: S1 and S2. The frequency of the less common allele (S2) varies among different ethnic groups. In several case–control studies, this SacI polymorphism has been associated with hypertriglyceridemia, hypercholesterolemia and CAD [7–12]. However, some other studies have shown contradictory results [13,14] . Association studies of the ApoAI–CIII–AIV cluster gene have mainly reported on Caucasian populations. Up to date, no study had tested this association in Tunisian population. The aim of the present study was to investigate the possible association between the ApoCIII SacI polymorphism and MI in a subgroup of the Tunisian population. 2. Materials and methods 2.1. Study population The total population of this study consisted of 687 unrelated subjects living in the City of Tunis (Tunisia). A total of 326 male patients with MI were enrolled from the Department of Cardiology, Rabta University
0953-6205/$ – see front matter © 2011 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved. doi:10.1016/j.ejim.2011.03.002
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Table 1 Anthropometric and metabolic variables of the study population. Variables
Controls (n = 361)
Patients (n = 326)
P
Age (years) BMI (kg/m2) Diabetes (%) Hypertension (%) Obesity (%) Dyslipidemia (%) Smoking (%) TC (mmol/L) TG (mmol/L) LDL-C (mmol/L) HDL-C (mmol/L) Apo B (g/L) Apo AI (g/L)
51.1 ± 9.5 26.1 ± 5.0 15.6 17.8 37.1 16.6 55.6 4.84 ± 0.98 1.54 ± 0.90 2.95 ± 0.85 1.13 ± 0.28 0.88 ± 0.22 1.33 ± 0.25
53.8 ± 8.6 25.2 ± 3.5 37.9 29.0 30.8 30.5 88.8 5.05 ± 1.11 1.88 ± 0.81 3.34 ± 1.01 0.85 ± 0.23 1.14 ± 0.32 1.27 ± 0.32
b 0.001 0.005 b 0.001 b 0.001 0.074 b 0.001 b 0.001 0.007 b 0.001 b 0.001 b 0.001 b 0.001 b 0.001
Data are expressed as means ± SD for some and as percent in others variables.
Hospital of Tunis. The mean age of this group was 53± 8 years. Diagnosis of MI was confirmed by chest symptoms, electrocardiographic changes and serum creatine kinase-MB isoenzyme elevations more than twice the upper normal level. The control group included 361 male volunteers, with no history of angina pectoris or MI, and with a normal electrocardiogram. Their mean age was 51 ± 9 years. Informed written consent was obtained from all participants and the design of the study was approved by the local Ethics Committee. Weight and height were measured on the subjects barefooted and lightly clothed. Body mass index (BMI; kg/m2) was calculated and obesity was defined as BMI≥ 30 kg/m2 [15]. Diabetes mellitus was defined as hyperglycemia, requiring antidiabetic drugs or testing blood sugar over 7.0 mmol/L. Hypertension was defined as systolic blood pressure ≥ 140 mm Hg and/or diastolic blood pressure ≥ 90 mm Hg, or the use of antihypertensive drug treatment, or a combination of these. Dyslipidemia was defined as a total cholesterol (TC) level N 6.47 mmol/L and/or triglyceride (TG) level N 2.26 mmol/L. A daily consumption of N 5 cigarettes was considered a smoking habit. 2.2. Laboratory analysis Blood samples were obtained after an overnight fast. Plasma levels of TC, TG, and HDL-cholesterol (HDL-C) were measured by standardized enzymatic procedures, and ApoAI and ApoB were measured using turbidimetric assay on a Hitachi 912 analyzer. LDL-cholesterol (LDL-C) was calculated according to Friedewald's formula [16]. 2.3. DNA analysis Genomic DNA was prepared from white blood cells by phenol extraction [17]. A method similar to that described by Hixon et al. [18]
was used to detect the polymorphic nucleotide recognized by the restriction enzyme SacI (SacI is an isoschizomer of SstI). A 254 bp region of the 3′ end of the ApoCIII gene containing the polymorphic site was amplified by the polymerase chain reaction (PCR). The primers used were 5′-AGGACAAGTTCTCTGAGTTCT-3′ (forward), and 5′-ATAGCAGCTTCTTGTCCAGCTT-3′ (reverse). Digestion with SacI yields fragments of 254 base pairs in the presence of the S1 allele, and 144 and 110 base pairs in the presence of the S2 allele. The products were separated in 3% agarose gel, stained with ethidium bromide. To ensure that the genotyping was of adequate quality, all gels were reread blindly by 2 persons without any change, and 20% of the analyses was repeated randomly. 2.4. Statistical analysis The Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS 10.0 for Windows; SPSS Inc., Chicago, IL, USA). Distributions of continuous variables in groups were expressed as mean ± SD, and compared with unpaired Student's t-tests. χ2 tests were used to test for departures from Hardy–Weinberg equilibrium and to compare genotype distributions between groups. The ApoAI–CIII–AVI SacI polymorphism was first assessed in three genotype categories (wild-type, heterozygote, and homozygote variants) and then grouped into two categories with heterozygote and homozygote variants combined because of the dominant model of inheritance observed for this polymorphism. Data for triglyceride were log transformed to reduce skewness of the data. Odds ratio (OR) and 95% confidence intervals (CI) were calculated using unconditional logistic regression. Crude and adjusted models for age, diabetes, HTA, dyslipidemia, BMI, smoking and genotypes were fitted. Associations of quantitative variables with genotype were examined by analysis of covariance (General Linear Model procedure). A two-tailed p-value b 0.05 was considered statistically significant. 3. Results The demographic and clinical characteristics of the MI and control groups are summarized in Table 1. There were significant differences for age (p = 0.001), BMI (p = 0.005), and the frequencies of diabetes (p b 0.001), hypertension (p b 0.001), obesity (p = 0.074), dyslipidemia (p b 0.001) and cigarette smoking (p b 0.001) between the MI and control groups. MI patients had higher levels of TC (p = 0.007), LDL-C, TG and Apo B (p b 0.001), and lower levels of HDL-C and ApoAI (p b 0.001) than control subjects. Genotype distributions were in Hardy–Weinberg equilibrium in patients (χ2 = 3.945, p = 0.139) and controls (χ2 = 3.567, p = 0.168). A significant difference in both genotype distribution and allele frequency between MI patients and controls subjects was observed. The univariate
Table 2 Genotype distributions and allele frequencies of the ApoCIII SacI polymorphism among MI patients and controls, and crude and adjusted estimations for MI. Controls (n = 361)
MI patients (n = 326)
Unadjusted OR 95%CIa
P
Adjusted OR 95%CIb
P
Codominant model S1S1 n (%) S1S2 n (%) S2S2 n (%)
315 (87.3) 45 (12.4) 1 (0.3)
266 (81.6) 53 (16.3) 7 (2.1)
1 1.39 (0.90–2.14) 8.28 (1.01–67.80)
0.129 0.049
1.49 (0.88–2.50) 1.53 (1.0–2.35)
0.133 0.048
Dominant model S1S1 n (%) S1S2 + S2S2 n (%)
315 (87.3) 46 (12.7)
266 (81.6) 60 (18.4)
1 1.54 (1.01–2.34)
0.041
1 2.02 (1.11–3.67)
0.020
– 1 .64 (1.10–2.47)
0.011
Allele frequency S1 (%) S2 (%)
93.45 6.55
89.75 10.25
S1S1, homozygous; S1S2, heterozygous; S2S2, homozygous for the mutation. OR, odds ratio; CI, confidence interval. a Crude logistic regression model. b Adjusted for age, HTA, diabetes, dyslipidemia, BMI and smoking.
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Table 3 Clinical and biochemical characteristics of patients and controls according to genotypes. apoA-I–CIII–AIV genotypes Variables
Controls (n = 361)
Cholesterol (mmol/L) Triglycerides (mmol/L) LDL-cholesterol (mmol/L) HDL-cholesterol (mmol/L) Apo AI (g/L) Apo B (g/L)
MI patients (n = 326)
S1S1 n = 312
S1S2 + S2S2 n = 46
P
S1S1 n = 260
S1S2 + S2S2 n = 60
P
4.84 ± 0.95 1.54 ± 0.92 2.97 ± 0.82 1.13 ± 0.31 1.33 ± 0.25 0.87 ± 0.21
4.81 ± 1.03 1.46 ± 0.84 2.95 ± 0.90 1.19 ± 0.28 1.33 ± 0.21 0.86 ± 0.26
0.875 0.566 0.840 0.295 0.882 0.717
4.99 ± 1.13 1.88 ± 0.82 3.31 ± 1.03 0.85 ± 0.23 1.28 ± 0.33 1.13 ± 0.31
5.18 ± 1.08 1.92 ± 0.82 3.44 ± 0.93 0.85 ± 0.23 1.25 ± 0.28 1.19 ± 0.40
0.294 0.787 0.329 0.733 0.445 0.182
Data presented are mean ± SD.
logistic regression analysis showed a significant association of the ApoCIII SacI polymorphism and MI according to co-dominant and dominant models (co-dominant model OR: 8.28, 95% CI: 1.01–67.80; p = 0.04 and dominant model OR: 1.54; 95% CI: 1.01–2.34; p = 0.04) (Table 2). After adjustment for age, diabetes, hypertension, HTA, BMI, dyslipidemia and smoking (Table 2), the ApoCIII SacI polymorphism was found to be significantly associated with MI, according to the models considered. The MI patient group showed a significant higher frequency of the S2 allele compared to the controls (10.2% vs. 6.5%; OR: 1.64, 95% CI: 1.10–2.47, p = 0.01). Serum lipid, lipoprotein and apolipoprotein concentrations according to genotype in the control group and MI patients are given in Table 3. Because of the rarity of homozygosity for the S2 allele and the small numbers of those available, data from those having a S2 allele (S1S2+ S2S2) were compared with that from those homozygous for the common S1 allele. There were no significant differences among any genotypes for any lipid and lipoprotein traits. When MI patients and controls were divided into those with hypertriglyceridemia or hypercholesterolemia and those with normal triglyceride and cholesterol levels, there was no evidence for statistically significant association between the ApoAI–CIII–AIV SacI polymorphism and dyslipidemia (data not shown). 4. Discussion The principal aim of this study was to investigate the relationship between variation at the ApoAI–CIII–AIV SacI locus and lipids and MI in a Tunisian population. Both patients with MI and controls belonged to the same ethnic background and all shared a common geographic origin in North Tunisia. We showed that the ApoAI–CIII–AIV SacI polymorphism was associated with MI in Tunisian patients. This association persisted after adjusting for several potential confounding factors. The S2 allele frequency of ApoCIII SacI polymorphism in controls varied considerably
among populations, ranging from 0.06 (Caucasians) [10] to 0.37 (Japanese) [19]. The frequency of the S2 allele in our controls is 0.06, consistent with that previously reported in normal Danish men (0.09) [20] and US men in the Framingham Offspring Study (0.08) [21]. Previous studies of the ApoCIII SacI polymorphism in CAD risk have yielded conflicting results, with some studies indicating a possible link with genetic variability at this locus [10,22–26] and others not confirming these associations [14,19,27–29] (Table 4). The reason for this discrepancy remains unclear. These different results are likely to be a consequence not only of the different sample sizes or the different allelic frequencies observed in different ethnic groups, but also and most importantly of different selection criteria adopted for patients and controls, in particular clinical presentation, extent of disease, age, race, geographical area, concomitant environmental risk factors and the interactions, gene–gene and gene–environment. Another explanation could be that a putative disease-marker could be population specific or that the non-random associations between the marker alleles and the important mutations may differ among populations. As such, the functionally important mutations may be present in some and not in other populations [9,30,31]. The mechanism by which the ApoCIII SacI polymorphism confers susceptibility to MI is not clear. But, since ApoAI–CIII–AIV SacI is located in the 3′ untranslated region of the ApoCIII gene, it is possible that this polymorphism is in linkage disequilibrium with some other functional polymorphic loci in the nearby region of chromosome 11 acting through a yet unknown mechanism. It was suggested by Patsch et al. [32] in 1994 that sequence variation in the ApoAI–CIII–AIV gene cluster region might alter plasma lipid transport and thus affect susceptibility to atherosclerosis. In our study, there was no significant difference among genotypes for any lipid, or lipoprotein traits. These findings are in agreement with some earlier studies [6,27,28,33], but not all [14,20,34–40]. The discrepancies between the studies may be
Table 4 Associations with hypertriglyceridemia or coronary artery disease of the S2 allele in various sample populations during the last 10 years. Authors
Years
Country
Cases/events
Controls
Endpoints
Statistically significant results
Hussain et al. [25] Kee et al. [28] Buzza et al. [6] Chhabra et al. [8] Corella et al. [34] Liu et al. [14] Islam et al. [24] Relvas et al. [29] De França et al. [35] Herron et al. [38] Huang et al. [37] Shanker et al. [26] Parzianello et al. [40] Bhanushali and Das [12] Li et al. [39]
1999 1999 2001 2002 2002 2004 2005 2005 2005 2006 2006 2008 2008 2010 2010
Saudi Arabia France European Asian Indians Spain United States Finland Brazil Brazil United States Taiwan Asians Indians Japanese India China
54 614 – – – 385 214 119 – – 159 523 families – 90 –
38 764 2003 139 1029 373 – 100 414 91 90 – 159 150 1030
CHD MI HTG HTG HTG MI IMT T2D, MI HTG HTG HTG CAD HTG CAD HTG
Yes No No Yes Yes No Yes No No Yes Yes Yes Yes Yes Yes
HTG, hypertriglyceridemia; MI, myocardial infarction; CHD, Coronary heart disease. T2D, type 2 diabetes; IMT, intima-media thickness; CAD, coronary artery disease.
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explained by genetic difference between the Tunisian population used in our study and populations where this association has been detected. It clear from other studies that lifestyle factors may modify certain genotype effects [31,41–43]. Peacock et al. [41] found that the effects of the ApoAI–CIII loci on circulating levels of triglycerides, HDL-C, and ApoAI were modulated by gender and smoking. On the other hand, in our population studied, there are many obese people in the control and MI patients which could cancel the genetic effect. Some limitations of our study should be taken into consideration. For example, our study was limited to a cohort of almost exclusively Tunisian men. Another was the small size of screened population; this caveat may limit our conclusions. Finally our study focused on a single SNP approach rather than a haplotype approach. 5. Conclusion The present study showed a significant association between the ApoAI–CIII–AIV SacI polymorphism and MI, but there was no association between this polymorphism and lipid and lipoprotein levels in the male Tunisian population. Further research involving additional polymorphisms of the region spanning and extending beyond the ApoAI–CIII–AIV gene complex chromosomal locus might help to locate the responsible gene and identify the mechanism by which it affects MI. 6. Learning points • Coronary artery disease (CAD) is one of the leading causes of morbidity and mortality in much of the world today. CAD is a complex condition, resulting from genetic and environmental contributions. • Many genes are suspected to be involved in its etiology. Several studies have suggested that genetic variations of the apolipoprotein (apo) AI–CIII–AIV cluster gene are associated with hyperlipidemia and atherosclerosis in the general population. • Moreover, conflicting results emerge from the literature and suggest that the effect is context-dependent. • To our knowledge there were no previous studies about the relation of apo AI–CIII–AIV cluster gene polymorphism with myocardial infarction (MI) in the Tunisian population. • This study was conducted to elucidate the association between SacI polymorphism and MI in the Tunisian population. • A significant and independent association between the Apo-CIII SacI polymorphism and MI in the Tunisian population was found. Conflict of interest The authors do not have any conflicts of interest in connection with this paper. Acknowledgment This work was supported by a grant from the Ministry of Higher Education, Scientific Research and Technology of Tunisia. References [1] Wang QF, Liu X, O'Connell J. Haplotypes in the APOA1–C3–A4–A5 gene cluster affect plasma lipids in both humans and baboons. Hum Mol Genet 2004;10:1049–56. [2] Lamarche B, Moojani S, Lupien PJ, Cantin B, Bernard PM, Dagenais GR, et al. Apoliporotein A-1 and B levels and the risk of ischemic heart disease during a five-year follow-up of men in the Quebec cardiovascular study. Circulation 1996;94:273–8. [3] Lai CQ, Parnell LD, Ordovas JM. The APOA1/C3/A4/A5 gene cluster, lipid metabolism and cardiovascular disease risk. Curr Opin Lipidol 2005;16:153–66. [4] Waterworth DM, Talmud PJ, Bujac SR, Fisher RM, Miller GJ, Humphries SE. Contribution of apolipoprotein C-III gene variants to determination of triglyceride levels and interaction with smoking in middle-aged men. Atherioscler Thromb Vasc Biol 2000;20:2663–9. [5] Hegele RA, Connelly PW, Hanley AJ, Sun F, Harris SB, Zinman B. Common genomic variation in the APOC3 promoter associated with variation in plasma lipoproteins. Arterioscler Thromb Vasc Biol 1997;17:2753–8.
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