Association of apolipoprotein A5 gene variants with metabolic syndrome in Tunisian population

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Original article

Association of apolipoprotein A5 gene variants with metabolic syndrome in Tunisian population Étude d’association du gène APOA5 au syndrome métabolique et à ses composantes dans la population tunisienne Rym Kefi a,b,∗,1 , Meriem Hechmi a,1 , Hamza Dallali a,c,1 , Sahar Elouej d,1 , Haifa Jmel a,c,1 , Yossra Ben Halima a,b,1 , Majdi Nagara d,1 , Mariem Chargui a,b,1 , Sihem Ben Fadhel a , Safa Romdhane a , Ines Kamoun e,1 , Zinet Turki e,1 , Abdelmajid Abid a,e,1 , Sonia Bahri f,1 , Afaf Bahlous f,1 , Ramon Gomis g,1 , Abdelhamid Baraket h,1 , Florin Grigorescu i,1 , Christophe Normand i,1 , Henda Jamoussi a,e,1 , Sonia Abdelhak a,b,1 a

Laboratory of Biomedical Genomics and Oncogenetics, Institut Pasteur de Tunis, BP 74, 13, place Pasteur, Tunis 1002, Tunisia b University of Tunis El Manar, 2092 El Manar I Tunis, Tunisia c University of Carthage, BP 77, 1054 Amilcar, Tunisia d Aix Marseille-University, Faculty of Medecine La Timone, Inserm, GMGF, 27, boulevard Jean-Moulin, 13385 Marseille, France e National Institute of Nutrition and Food Technology, 11, rue Jebel Lakhdar, Bab Saadoun, 1007 Tunis, Tunisia f Central Laboratory of Medical Biology, Institut Pasteur de Tunis, BP 74, 13, place Pasteur, Tunis 1002, Tunisia g August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Carrer del Rosselló, 149, 08036 Barcelona, Spain h Laboratory of Human molecular Genetics Institut Pasteur du Maroc 1, place Louis Pasteur, Casablanca, Morocco i IURC, Molecular Endocrinology Laboratory, Nutrition & Genomes, UMR-204, NUTRIPASS, Montpellier, France

Abstract Aim of the study. – APOA5 has been linked to metabolic syndrome (MetS) or its traits in several populations. In North Africa, only the Moroccan population was investigated. Our aim is to assess the association between APOA5 gene polymorphisms with the susceptibility to MetS and its components in the Tunisian population. Materials and methods. – A total of 594 participants from the Tunisian population were genotyped for two polymorphisms rs3135506 and rs651821 located in APOA5 gene using KASPar technology. Statistical analyses were performed using R software. Results. – The SNP rs651821 increased the risk of MetS under the dominant model (OR = 1.91 [1.17–3.12], P = 0.008) whereas the variant rs3135506 was not associated with MetS. After stratification of the cohort following the sex, only the variant rs651821 showed a significant association with MetS among the women group. The influence of the geographic origin of the studied population on the genotype distribution of APOA5 variants showed that the variant rs651821 was significantly associated with MetS only for the Northern population. The association analyses of the variants rs651821 and rs3135506 with different quantitative traits of MetS showed a significant association only between the variant rs3135506 and triglycerides levels. Conclusion. – This is the first study reporting the association of APOA5 gene variants with MetS in Tunisia. Our study emphasizes the role of APOA5 variants in the regulation of the triglycerides blood levels. Further studies are needed to confirm the clinical relevance of these associations and to better understand the physiopathology of the MetS. © 2017 Elsevier Masson SAS. All rights reserved. Keywords: Metabolic disorders; APOA5 gene; Polymorphism; Genetic association; North Africa

∗ 1

Corresponding author at: Institut Pasteur de Tunis, BP 74, 13, place Pasteur, 1002 Tunis Belvédère, Tunisia. E-mail addresses: [email protected], kefi [email protected] (R. Kefi). The MEDIGENE project, grant agreement number 279171, funded by the EC Seventh Framework Programme theme FP7-HEALTH-2011.

http://dx.doi.org/10.1016/j.ando.2017.01.005 0003-4266/© 2017 Elsevier Masson SAS. All rights reserved.

Please cite this article in press as: Kefi R, et al. Association of apolipoprotein A5 gene variants with metabolic syndrome in Tunisian population. Ann Endocrinol (Paris) (2017), http://dx.doi.org/10.1016/j.ando.2017.01.005

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Résumé Objectif. – Des variants du gène APOA5 ont été décrits comme étant associés au syndrome métabolique (Smet) ou à ses composantes dans plusieurs populations. En Afrique du Nord, seule la population marocaine a été étudiée. Notre objectif est de tester l’association de deux polymorphismes : rs3135506 (c.56C>G) et rs651821 (–3A>G) localisés au niveau du gène APOA5, avec le Smet et ses composantes dans la population tunisienne. Patients et méthodes. – Un total de 594 individus tunisiens ont été génotypés pour les variants rs3135506 et rs651821. Le génotypage par discrimination allélique a été effectué en utilisant la technique Kaspar. Les analyses statistiques ont été réalisées à l’aide du logiciel R. Résultats. – Le polymorphisme rs651821 augmente le risque de développer un Smet suivant le modèle dominant (OR = 1,91 [1,17–3,12], p = 0,008). Aucune association n’a été trouvée pour le variant rs3135506. Après stratification de la cohorte étudiée suivant le sexe, seulement le variant rs651821 est associé significativement avec le Smet pour le groupe des femmes. L’investigation de l’impact de l’origine géographique sur la distribution génotypique des variants du gène APOA5 montre une association significative entre le variant rs651821 et le Smet seulement pour les individus originaires du Nord de la Tunisie. L’analyse de l’association des variants rs651821 et rs3135506 avec les différents traits quantitatifs du Smet montre seulement une association significative entre le polymorphisme rs3135506 et les taux de triglycérides. Conclusion. – Cette étude fournit la première évidence de l’association des polymorphismes du gène APOA5 avec le syndrome métabolique et ses composantes dans la population tunisienne. © 2017 Elsevier Masson SAS. Tous droits r´eserv´es. Mots clés : Maladie métabolique ; APOA5 ; Polymorphisme ; Association génétique ; Afrique du Nord

1. Introduction Metabolic syndrome (MetS) is a complex disease characterised by multiple metabolic abnormalities, including central obesity, hypertension, dyslipidemia and insulin resistance [1]. Many studies have linked MetS with the risk of developing type 2 diabetes (DT2) and cardiovascular diseases (CVD) [2]. A recent report of the World Health Organization (WHO) revealed that 17.5 million of all cases of deaths were mainly caused by cardiovascular diseases in 2012 [3], while diabetes caused up to 5 million deaths in 2015 worldwide [4]. Consequently, MetS represents a health burden aggravated by an increasing incidence worldwide [5]. The prevalence of MetS in the Tunisian population is 30% [6]. MetS is defined by the interaction between multiple environmental influences (such as smoking, unhealthy diet and sedentary life style) and genetic factors [7,8]. Therefore, the pathological mechanism of MetS is still unclear. Several studies have linked common genetic variants with the increased risk of MetS [9]. Apoliprotein A5 (APOA5) gene is located on chromosome 11q23 within the gene cluster APOA1/APOC3/APOA4 [10]. Human APOA5 consists of four exons, translated into a 366 amino acid protein apoliprotein A-V (ApoAV) synthesized in the liver [10]. Numerous observations have identified ApoAV as a strong modulator of plasma triglyceride (TG) levels. The mechanism is still not completely elucidated [11]. The occurrence of elevated TG levels with metabolic syndrome, obesity and type 2 diabetes often exists [12]. APOA5 has been linked to MetS or its traits in several populations from Europe [13,14], Asia [15,16] and in Middle East [17]. In North Africa, only the Moroccan population was investigated [18]. Candidate gene association studies [19] and genome wide association studies [20] highlighted the association of several single nucleotide polymorphisms (SNPs) in APOA5 gene with MetS and its components. Among these variants rs3135506 (c.56C>G) located in the exon 3 also known as S19W [13] and rs651821 (–3A>G) located in the untranslated region 5 of exon 2 [21].

The main goal of this study is to assess the association between APOA5 gene polymorphisms with the susceptibility to MetS and its components in the Tunisian population. 2. Materials and methods 2.1. Study subjects This study is a part of an international collaborative project MEDIGENE FP7-279171-1 that aims to study the genetic and environmental factors of MetS in the Mediterranean region (www.medigene-fp7.eu) [22]. A total of 594 participants (299 controls and 295 MetS patients) were randomly recruited among women and men aged between 35 and 75 years from the National Institute of Nutrition (INN) (Tunis, Tunisia) and Institut Pasteur de Tunis (IPT). Samples were collected under the approval of the Ethical committee of IPT (reference IPT/LR11-05/Etude 04/2013) and after a signed written consent from all the participants. MetS was diagnosed according to the International Diabetes Federation (IDF) [23]. All patients must have central obesity as a central criteria for selecting the patients (waist circumference ≥ 90 cm for men and ≥ 80 cm for women) in addition to two among these components: • elevated plasma triglyceride (TG) (≥ 1.69 mmol/L); • low plasma HDL-cholesterol (< 1.04 mmol/L in men and < 1.29 mmol/L in women); • high blood pressure (HBP) (systolic blood pressure [SBP] ≥ 130 or diastolic blood pressure [DBP] ≥ 80 mmHg or current medication for HBP; • fasting plasma glucose [impaired fasting glucose (IFG)] ≥ 5.6 mmol/L or diagnosed with T2D. 2.2. Clinical features All measurements were performed by the medical doctors during the external consultations in the National Institute of

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Nutrition (INN). The weight, height, waist and hip circumference were measured for all individuals. BMI was calculated as weight (kg)/height2 (m2 ). Clinical parameters including IFG, SBP and DBP, total cholesterol, TG, HDL-cholesterol, LDLcholesterol were performed in the Biochemistry Laboratory of INN and IPT. Low-density lipoprotein cholesterol level was calculated according to the Friedwald’s formula. Arterial pressure was measured by the auscultatory method using a stethoscope and a sphygmomanometer. 2.3. Genetic analysis Genomic DNA was isolated from the whole blood using the salt fractionation method [24]. Genotyping of SNPs was ® performed by KASPar technology (KBioscience, UK). PCR amplification and genotypes reading were performed using the ® LightCycler 480 system (Roche Diagnostics, Switzerland). The genotyping success rate was 97.5% for the rs651821 and 97.14% for the rs3135506. A random of 10% sample set was re-tested with the same method to confirm genotype accuracy. 2.4. Statistical analyses Statistical analyses were performed as described in [25]: numerical variables were expressed as means ± standard deviation, and differences between groups were assessed with Student’s t-test. Nominal variables were analyzed using the χ2 test. Statistical analyses were performed using R software. Hardy–Weinberg equilibrium (HWE) was assessed using SNPHWE program. Variation of SNPs in the population was assessed by calculation of their allelic frequency and the frequency of their genotypes. The associations with MetS were estimated using multivariate logistic regression model after adjustment for sex, age and BMI. Genotypes and allelic analysis were carried-out using the SNPassoc R library. Genetic effect of the single nucleotide polymorphisms (SNPs) was assessed by univariate and multivariate methods based on logistic regression analyses. Intergroup comparisons of genotypes frequency differences were performed by regression analysis for dominant, recessive and additive models of inheritance. Results were expressed as nominal P, odds ratio (OR) and 95% confidence interval (CI). The P-values were corrected with the Bonferroni correction by multiplying with the number of comparisons. Genotype–phenotype correlation and interactions were tested by ANOVA. A value of P < 0.05 was considered statistically significant for statistical tests. As for the Hardy–Weinberg equilibrium, the P-value was set among controls at α = 10−3 . The power of the case control study was performed using PS: power and sample size calculations software version (3.2.1). 3. Results 3.1. Characteristics of the studied population The biochemical and clinical data of the studied population (299 controls and 295 cases) are presented in Table 1.

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Table 1 Clinical and biochemical characteristics of the Tunisian studied population. Total

n Age WC BMI IFG TC HDL LDL TG DBP SBP

Controls

Mets

P

299 52.56 ± 10.09 97.07 ± 11.87 28.41 ± 4.83 6.13 ± 2.51 5.08 ± 0.92 1.48 ± 0.41 3.12 ± 0.89 1.29 ± 0.56 7.74 ± 1.26 13.20 ± 1.97

295 56.58 ± 8.56 106.50 ± 9.94 31.53 ± 5.12 9.52 ± 4.28 5.16 ± 1.01 1.13 ± 0.34 3.16 ± 1.34 2.02 ± 0.93 8.35 ± 1.40 14.6 ± 2.1

< 0.001 < 0.001 < 0.001 < 0.001 0.28 < 0.001 0.049 < 0.001 < 0.001 < 0.001

n: number; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; TC: total cholesterol; TG: triglycerides; HDL-C: high density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol; IFG: impaired fasting glucose; WC: waist circumference. Data are presented as mean ± SD.

The mean age of MetS group was significantly (P < 10−4 ) higher (56.58 ± 8.56) than in controls (52.56 ± 10.09). Body mass index BMI, waist circumference, triglycerides, LDL level, impaired fasting glucose (IFG), diastolic blood pressure (DBP) and systolic blood pressure (PAS) were also significantly higher in MetS patients than in controls (p < 10−4 ). HDL level was lower in MetS patients than in controls (p < 10−4 ). Only the total cholesterol did not differ significantly between the two groups. Only few patients (10 among 295 cases) have cardiovascular diseases or complications, such as peripheral artery disease, angina pectoris and tachycardia. They have received different combinations of antihypertensives and lipid-lowering medications. Antihypertensives include drugs from several classes, particularly calcium channel blockers with vasodilator effect and the antagonists of angiotensin II receptor as well as its converting-enzymes inhibitors and generic beta-blockers used to manage the tachycardia. Lipid-lowering medications include statins and fibrates. In addition, one patient had undergone angioplasty process in order to widen obstructed arteries. 3.2. Association with MetS The genotypic and allelic distribution of APOA5 variants (rs651821 and rs3135506) and the results of the association with MetS are shown in Table 2. The genotypic and allelic distribution for the two SNPs did not deviate from Hardy–Weinberg equilibrium. The frequency of the C allele of the variant rs651821 in cases is significantly higher than in controls (cases = 13.9% vs. controls = 9.4%, P = 0.024). The C allele was significantly associated with MetS (OR = 1.56 [1.08–2.25], P = 0.024). Based on the probability of exposure in controls (0.094) found in our study, we obtained a power of 40.5% to detect an OR of 1.56 at P < 0.05. The SNP rs651821 increases the risk of MetS under the dominant model (OR = 1.91 [1.17–3.12], P = 0.008) and under the additive model (OR = 1.61 [1.07–2.43], P = 0.02). The association remains significant after Bonferroni correction for the

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rs651821 TT TC CC RAF HWE AIC rs3135506 GG GC CC RAF HWE AIC

Additive model

MetS

Controls

215 (74.9%) 64 (22.3%) 8 (2.8%) 0.139 0.2207

244 (83.6%) 41 (14.0%) 7 (2.4%) 0.094 0.0073

OR (95% CI) 0.59 (0.39–089) 1.76 (1.14–2.71) 1.15 (0.41–3.21) 1.56 (1.08–2.25)

P

P*

0.0107* 0.0105* 0.788 0.0245*

0.14

OR (95% CI)

1.61 (1.07–2.43)

Dominant Model Padj

0.02*

P*

OR (95% CI)

0.12

1.91 (1.17–3.12)

645.3 225 (77.9%) 61 (21.1%) 3 (1.0%) 0.116 0.7792

233 (80.9%) 51 (17.7%) 4 (1.4%) 0.102 0.5167

0.83 (0.55–1.24) 1.24 (0.82–1.88) 0.74 (0.16–3.34) 1.15 (0.79–1.67)

0.365 0.302 0.701 0.51

1

1.39 (0.90–2.14)

0.14 643.1

Recessive model Padj

0.008*

P*

OR (95% CI)

Padj

P*

0.048*

1.26 (0.38–4.18)

0.709

1

643.8

0.84

1.40 (0.88–2.23)

0.15 643.3

650.6

0.9

1.89 (0.27–13.16)

0.52

1

644.9

MetS: metabolic syndrome patients; Genotype distributions are shown as number (%); RAF: risk allele frequency; HWE: P-value for Hardy–Weinberg equilibrium; AIC: Akaike information criterion; P* : P-value after Bonferroni correction; Padj : P-value adjusted for age, sex and BMI. * Significant P-value (P-value < 0.05).

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Table 2 Association of APOA5 genotypes with metabolic syndrome in the Tunisian population.

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Genotype distribution MetS

Controls

OR (95% CI)

Padj

139 (75.1%) 40 (21.6%) 6 (3.2%) 0.141 0.2144

179 (83.6%) 28 (13.1%) 7 (3.3%) 0.098 0.0013

0.59 (0.36–0.97) 1.83 (1.08–3.11) 0.99 (0.33–3) 1.4 (0.97–2.31)

0.036* 0.025* 0.987 0.065

0.195

OR (95% CI)

1.63 (1.08–2.59)

Dominant model Padj

0.035*

P*

OR (95% CI)

0.105

2.11 (1.18–3.77)

450.1

74 (77.9%) 20 (21.1%) 1 (1.1%) 0.116 0.840

65 (83.3%) 13 (16.7%) 0 0.083 0.858

0.7 (0.32–1.51) 1.33 (0.61–2.88) 2.5 (0.1–62) 1.44 (0.7–2.96)

0.372 0.466 0.577 0.361

1.67 (0.68–4.08)

0.253

Recessive model Padj

0.01*

P*

OR (95% CI)

0.03*

1.12 (0.32–3.88)

448.0

1

1.62 (0.64–4.10)

0.305

Padj

0.858

P*

1

454.5

1

0

0.318

1

1 196.9

197.2

197.2

MetS: metabolic syndrome patients; HWE: P-value for Hardy–Weinberg equilibrium; genotype distributions are shown as number (%); RAF: risk allele frequency; AIC: Akaike information criterion. P* : P-value after Bonferroni correction; Padj : P-value adjusted for age, sex and BMI. * Significant P-value (P-value < 0.05).

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Women rs651821 TT TC CC RAF HWE AIC Men rs651821 TT TC CC RAF HWE AIC

Additive model P*

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Table 3 Association of rs651821 genotypes with metabolic syndrome in the groups of women and men.

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Genotype distribution

Northern population rs651821 178 (76.1%) TT 50 (21.4%) TC CC 6 (2.6%) rs3135506 GG 179 (75.5%) GC 56 (23.6%) CC 2 (0.8%) Southern population rs651821 TT 18 (58.1%) TC 12 (38.7%) CC 1 (3.2%) rs3135506 GG 26 (86.7%) 3 (10.0%) GC CC 1 (3.3%)

Dominant model

P*

OR (95% CI)

Padj

0.01* 0.008* 0.85

0.06 0.048* 1

1.60 (1.06–2.41)

0.023*

0.67 (0.42–1.06) 1.56 (0.97–2.5) 0.59 (0.1–3.57)

0.09 0.06 0.57

0.54 0.36 1

1.36 (0.89–2.08)

38 (71.7%) 13 (24.5%) 2 (3.8%)

0.55 (0.22–1.39) 1.94 (0.75–5.05) 0.87 (0.08–10)

0.2 0.17 0.89

1 1 1

40 (75.5%) 12 (22.6%) 1 (1.9%)

2.11 (0.62–7.18) 0.38 (0.1–1.47) 1.79 (0.11–29.7)

0.23 0.16 0.68

1 0.96 1

Controls

OR (95% CI)

186 (85.7%) 26 (12.0%) 5 (2.3%)

0.53 (0.33–0.86) 2 (1.19–3.35) 1.12 (0.34–3.72)

174 (82.1%) 35 (16.5%) 3 (1.4%)

Padj

P*

Recessive model OR (95% CI)

Padj

P*

0.048*

1.12 (0.34–3.71)

0.85

1

0.09

0.54

0.59 (0.10–3.58)

0.56

1

1.83 (0.72–4.64)

0.2

1

0.85 (0.07–9.78)

0.89

1

0.47 (0.14–1.61)

0.21

1

1.79 (0.11–29.75) 0.68

1

OR (95% CI)

Padj

0.138

1.89 (1.16–3.06)

0.008*

0.15

0.9

1.48 (0.94–2.35)

1.52 (0.69–3.37)

0.29

1

0.62 (0.22–1.76)

0.35

1

P*

Data are presented as mean ± standard deviation. Student test was used to compare geometric mean levels of continuous characteristics across genotypes. WC: Waist circumference; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; TC: total cholesterol; TG: triglycerides; HDL-C: high density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol; IFG: impaired fasting glucose. Significant results are in bold. P*: P-value after Bonferroni correction. Padj: P-value adjusted for age, sex and BMI.

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Mets

Additive model

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Table 4 Genotypic and allelic distribution of APOA5 variants in the studied population stratified following the geographic origin.

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Table 5 Association of APOA5 genotypes with metabolic syndrome traits in the Tunisian population. Traits

rs651821

rs3135506

TT WC (cm) BMI (kg/cm2 ) IFG (mmol/L) SBP (mmHg) DBP (mmHg) TC (mmol/L) HDL (mmol/L) LDL (mmol/L) TG (mmol/L)

101.51 30.02 7.76 13.9 8.07 5.12 1.31 3.15 1.67

CT + CC ± ± ± ± ± ± ± ± ±

11.65 5.21 3.81 2.14 1.39 0.95 0.41 1.14 0.97

102.58 30.19 8.37 14.24 8.03 5.09 1.32 3.09 1.7

± ± ± ± ± ± ± ± ±

11.58 5.31 4.35 2.22 1.26 1.07 0.45 1.11 0.79

P*

GG

0.42 0.77 0.16 0.16 0.81 0.72 0.77 0.64 0.72

101.87 30.01 7.74 14.01 8.07 5.13 1.32 3.17 1.16

GC + CC ± ± ± ± ± ± ± ± ±

11.67 5.11 3.82 2.14 1.39 0.95 0.41 1.13 0.82

101.24 ± 13.39 30.18 ± 5.68 8.58 ± 4.29 13.98 ± 2.25 8.18 ± 1.38 5.12 ± 1 1.28 ± 0.42 3.07 ± 1.17 1.88 ± 0.94

P* 0.65 0.76 0.046 0.89 0.5 0.91 0.46 0.42 0.003**

Data are presented as mean ± standard deviation. Student test was used to compare geometric mean levels of continuous characteristics across genotypes. WC: waist circumference; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; TC: total cholesterol; TG: triglycerides; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; IFG: impaired fasting glucose. Significant results are in bold. P* : P-value adjusted by age, sex and BMI. ** P-values remained significant after Bonferroni correction.

dominant model (P = 0.048) but not for the additive model (P = 0.12). Moreover, a significant difference was observed for the genotype frequencies between controls and cases: TT (P = 0.0107) and CT (0.0105) (Table 2). The C allele frequency of the SNP rs3135506 in cases (11.6%) is not significantly different from controls (10.2%) Pvalue = 0.51. The variant rs3135506 was not associated with MetS under any genotypic and allelic model. In addition, we investigated the association of APOA5 variants with MetS in the group of women and men (Table 3). Only the variant rs651821 showed a significant association with MetS for women but not for men. This correlation was found under the dominant (OR = 2.11 [1.18–3.77], P = 0.01) and additive (OR = 1.63 [1.08–2.59], P = 0.035) models (Table 3). After Bonferroni correction, the association remained significant for this variant only under the dominant model (P = 0.03). Instead, the SNPs rs3135506 was not associated with MetS neither for men or women (data not shown). 3.3. Associations with geographic origin We investigated the impact of the geographic origin on the genotype distribution of APOA5 variants rs3135506 and rs651821. Statistical analysis performed after stratification of the cohort following Northern and Southern origins showed that the variant rs651821 was significantly associated with MetS only for the Northern population, under the dominant model (P = 0.008) and the additive model (P = 0.023). This association remained significant after Bonferroni correction for the dominant model (Table 4). However, statistical analysis showed that the variant rs3135506 was not significantly associated with MetS under any genotypic model neither for Northern nor Southern region (Table 4). 3.4. Association with quantitative traits The association analyses of the variants rs651821 and rs3135506 with different quantitative traits of MetS, such as

impaired fasting glucose, BMI, LDL, HDL, systolic blood pressure, diastolic blood pressure, triglycerides and waist circumference are reported in Table 5. To choose the right model to perform the association with traits, AIC Akaike Information Criterion was calculated. The dominant model was applied since it has the lowest AIC value. According to Table 5, the carriers of the GC or CC genotype of the variant rs3135506 have higher TG levels, lower HDL levels and higher IFG levels than the carriers of the GG. Statistical analysis showed a significant association between the variant rs3135506 and IFG (P = 0.046) and TG (P = 0.003) levels. After Bonferroni correction, only the association between the variant rs3135506 and TG levels remained significant (P = 0.006). Regarding the variant rs651821, we did not found any association for any trait of the MetS. The investigation of the interaction gene/gender was performed after stratifying of our cohort following the sex (Table 6). A significant association was observed for TG levels with rs3135506 among women (P = 0.0028). This association remained significant after Bonferroni correction. The TG levels were significantly elevated among the carriers of the C alleles comparing to the carriers of the G allele (GC + CC:1.77 ± 0.86 vs. GG:1.51 ± 0.71), P = 0.0028 among women. 4. Discussion MetS is considered as one of the major spreading disease worldwide [5]. The consequences of this disease on human public health are very heavy because of its complications, including a higher risk of developing cardiovascular disease and type 2 diabetes [26]. Several studies have shown the role of APOA5 polymorphisms rs651821 and rs3135506 in MetS and its components in different populations [27–29]. To our knowledge, no study has investigated the association between MetS and polymorphisms in APOA5 gene for the Tunisian population. We genotyped APOA5 gene through two SNPs: rs651821 and rs3135506 in a population from Tunisia well characterized at the phenotypical level.

Please cite this article in press as: Kefi R, et al. Association of apolipoprotein A5 gene variants with metabolic syndrome in Tunisian population. Ann Endocrinol (Paris) (2017), http://dx.doi.org/10.1016/j.ando.2017.01.005

Men

TT WC (cm) BMI (kg/cm2 ) IFG (mmol/L) SBP (mmHg) DBP (mmHg) TC (mmol/L) HDL (mmol/L) LDL (mmol/L) TG (mmol/L)

101.44 30.98 7.51 13.77 7.99 5.18 1.36 3.17 1.57

CT + CC ± ± ± ± ± ± ± ± ±

11.74 5.36 3.54 2.11 1.34 0.97 0.39 1.21 0.76

103.21 30.93 8.41 14.24 8.03 5.20 1.43 3.01 1.59

± ± ± ± ± ± ± ± ±

12.22 5.31 4.51 2.42 1.19 1.15 0.47 1.17 0.77

P*

TT

0.35 0.96 0.11 0.09 0.88 0.89 0.31 0.22 0.93

101.7 27.82 8.34 14.21 8.26 5.00 1.18 3.11 1.89

Women CT + CC ± ± ± ± ± ± ± ± ±

11.46 4.09 4.31 2.21 1.49 0.88 0.41 0.98 1.05

101.13 28.37 8.28 14.25 8.05 4.82 1.06 3.30 1.96

± ± ± ± ± ± ± ± ±

10.01 4.94 4.01 1.72 1.45 0.81 0.26 0.93 0.81

P*

GG

0.65 0.43 0.82 0.61 0.35 0.26 0.27 0.65 0.62

101.96 30.84 7.56 13.98 8.05 5.20 1.38 3.15 1.51

Men P*

GC + CC ± ± ± ± ± ± ± ± ±

11.99 5.27 3.67 2.23 1.35 0.98 0.41 1.20 0.71

101.25 31.35 8.36 13.63 8.03 5.14 1.36 3.07 1.77

± ± ± ± ± ± ± ± ±

13.69 5.58 4.10 1.97 1.28 1.05 0.41 1.22 0.86

GG

0.49 101.68 ± 10.90 0.45 28.05 ± 4.10 0.06 8.16 ± 4.15 0.17 14.07 ± 1.91 0.79 8.13 ± 1.48 0.76 4.98 ± 0.86 0.83 1.17 ± 0.39 0.73 3.22 ± 0.94 0.0028** 1.86 ± 0.99

P*

GC + CC 101.21 27.21 9.13 14.95 8.61 5.07 1.06 3.04 2.15

± ± ± ± ± ± ± ± ±

12.58 4.89 4.76 2.70 1.58 0.86 0.35 1.02 1.09

0.18 0.33 0.21 0.07 0.17 0.61 0.16 0.42 0.09

Data are presented as mean ± standard deviation. Student test was used to compare geometric mean levels of continuous characteristics across genotypes. WC: waist circumference; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; TC: total cholesterol; TG: triglycerides; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; IFG: impaired fasting glucose. Significant results are in bold. P* : P-value adjusted by age, sex and BMI. ** P-values remained significant after Bonferroni correction.

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Table 6 Association of APOA5 genotypes with metabolic syndrome traits after stratification of the studied population following the sex.

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We found an association between the SNP rs651821 and MetS. Our results are in accordance with other association studies performed on Chinese [30] and Korean populations [27]. However, no association was observed for the other SNP rs3135506 and MetS under any genotypic or allelic models. The involvement of this variant in the MetS physiopathology is contradictory in the literature: no association with MetS was found in Iranian population [31] whereas others studies performed in European, Asian and Moroccan populations showed an association of the SNP rs3135506 with MetS [18,32–35]. The difference observed between APOA5 variants may be explained by the impact of the allele variation at different loci in APOA5 gene. Indeed they might be under different selective pressure. This difference between polymorphisms located in the same gene was reported in previous studies investigating APOA5 gene variants [18]. Furthermore, we highlighted the impact of the geographic origin on the genotype distribution of APOA5 variants. The variant rs651821 was significantly associated with MetS only for the individuals originating from Northern Tunisia. This result emphasizes an inter-regional variation within the Tunisian population. Indeed, the genetic landscape of the Tunisian population is a mosaic, which has been shaped by successive invasions and migratory flows since the prehistoric period [36]. We investigated also the association of the variants rs651821 and rs3135506 with MetS quantitative traits, such as impaired fasting glucose, BMI, LDL, HDL, systolic blood pressure, diastolic blood pressure, triglycerides and waist circumference. We found that the carriers of CC + CG genotype of the variant rs3135506 had an increased TG levels compared to the other genotypes. Our results are in agreement with previous studies reporting an association of the C allele of the rs3135506 with an increased TG levels in Korean, Chinese, and EuropeanAmerican populations [27,29,37]. In addition, a significant association of rs3135506 with TG levels was observed among women. Our result is in conformity with a study conducted on a cohort of Caucasian diabetic women which reported a significant association with higher TG levels, P = 0.001 [38]. Pennacchio et al. have identified APOA5 gene as a modulator of TG levels, which was revealed by comparing the DNA sequence of humans versus Mice. They have noticed that the knockout mice for the APOA5 gene had a higher TG levels than the transgenic mice overexpressing the human APOA5 gene. They identified four SNPs with a significant association with TG levels independently of the diet among them rs3135506. APOA5 is implicated in many pathways, such as the lipoprotein metabolism, statin pathway and metabolism of lipids and hypertriglyceridemia [39–41]. The variant rs3135506 is a missense variant generating a serine to tryptophan residues change near the cleavage site of the APOA5 signal sequence. This substitution increases the probability to form an ␣ helix instead of a break or a turn in the helix, which modifies the secondary structure with a concomitant change in the tertiary structure [42]. In addition, the variant rs3135506 is likely to affect transcription factor binding site. With the exception of TG levels, no significant association was observed between the SNP rs3135506 and the others traits

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(BMI, LDL, HDL, systolic blood pressure, diastolic blood pressure, and waist circumference). In addition, no association was found between the different traits of MetS and the SNP rs651821. Our finding is different of those reported by some studies reporting a significant association of the variants rs651821 and rs3135506 with HDL levels, obesity and hypertension in different populations [29,43,44]. These contradictory results may be explained by the heterogeneity of criteria used to define the studied cohorts (such as age, sex, Smet definition: IDF, ATP-III) and by the heterogeneity of the population ethnic origins. This emphasizes the complexity of the investigation of the MetS. Previous study reported that the risk of developing CVD in individuals with MetS is twice as high as in healthy individuals [45]. Since we have only 10 patients among 295 presenting CVD, we did not investigate the relationship between the APOA5 variants and CVD. It would of interest to increase the number of the studied population in order to analyse the relationship between the APOA5 variants and MetS complications, such as type 2 diabetes and CVD. 5. Conclusion This is the first study reporting the involvement of APOA5 gene in MetS development in Tunisia. We highlighted the significant association of the variant rs651821 with MetS and the association of the variant rs3135506 with TG levels. We reported also a gender-specific differences and an inter-regional variability in Tunisia. Nevertheless, a replication of our study in a greater sample of Tunisian and functional investigation are needed to confirm the clinical relevance of these associations and to better understand the physiopathology of the MetS. Disclosure of interest The authors declare that they have no competing interest. Acknowledgments This work was supported by the E.C. Grant agreement no. 279171-1 for FP7 project MEDIGENE and by the Tunisian Ministry of Public Health and the Tunisian Ministry of Higher Education and Scientific Research (LR11IPT05). We would like to thank the study participants for their collaboration. References [1] Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet 2005;365:1415–28. [2] Wilson PWF, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation 2005;112:3066–72. [3] Mendis S, Davis S, Norrving B. Organizational update: the World Health Organization global status report on noncommunicable diseases 2014; one more landmark step in the combat against stroke and vascular disease. Stroke 2015;46:e121–2.

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Please cite this article in press as: Kefi R, et al. Association of apolipoprotein A5 gene variants with metabolic syndrome in Tunisian population. Ann Endocrinol (Paris) (2017), http://dx.doi.org/10.1016/j.ando.2017.01.005