J Nutrigenet Nutrigenomics 2014;7:105–117 DOI: 10.1159/000365445 Received: February 17, 2014 Accepted: June 21, 2014 Published online: October 3, 2014
© 2014 S. Karger AG, Basel 1661–6499/14/0072–0105$39.50/0 www.karger.com/jnn
Original Paper
Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study Firoozeh Hosseini-Esfahani a, b Parvin Mirmiran a, b, e Maryam S. Daneshpour c Yadollah Mehrabi f Mehdi Hedayati c Maryam Zarkesh c Fereidoun Azizi d a
Nutrition and Endocrine Research Center, b Obesity Research Center, c Cellular and Molecular Endocrine Research Center, and d Endocrinology Research Center, Research Institute for Endocrine Science, e Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, and f Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Key Words Dietary patterns · Genetic polymorphisms · Metabolic syndrome
Maryam S. Daneshpour Cellular and Molecular Endocrine Research Center Research Institute for Endocrine Science, Shahid Beheshti University of Medical Sciences PO Box 19395-4763, Tehran 1985717413 (Iran) E-Mail daneshpour @ endocrine.ac.ir
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Abstract Background/Aims: Gene-dietary pattern interactions may contribute to the determination of a susceptibility to metabolic syndrome (MetS). The aim of this study was to evaluate the potential interactions of dietary patterns with the common genetic variant of APOC3 in relation to MetS in adults. Methods: In this individual matched nested case-control study, 755 MetS subjects and 755 controls were selected from among participants in the Tehran Lipid and Glucose Study. Dietary patterns were determined by factor analysis. APOC3 3238C>G rs5128 was genotyped by polymerase chain reaction and restriction fragment length polymorphism. Results: Fat-sweet, healthy and Western dietary patterns (WDP) were extracted from the data. In the joint analysis, the associations of the WDP and APOC3 rs5128 with MetS risk tended to be dependent on APOC3 3238C>G gene variants (p for interaction = 0.009) in women. The MetS risk was increased in women with the CC genotype with increasing tertiles of WDP scores compared with women with the CG + GG genotype, whose MetS risk was decreased with increasing tertiles of WDP scores. In addition, we found that intakes of fast food, salty snacks and soft drinks showed significant interactions with the rs5128 genotypes in relation to MetS risk (p for interactions G rs5128 variant is associated with increased Apoc3 and ApoB concentrations, low-density lipoprotein cholesterol (LDL-C) and plasma TG as well as high blood pressure (BP) and coronary heart disease [7–9]. No individual dietary component is wholly responsible for the association of a diet with MetS [10]. However, the optimal diet for the prevention and treatment of MetS remains unspecified, and physiologic differences can influence the effect of particular dietary patterns on the risk of MetS [11]. Food groups contributing to dietary patterns are not consistent across populations, which may yield discrepant results in dietary pattern studies among different populations [12]. The gene-diet interaction has helped to shed more light on an understanding of this variability, an area that has been poorly explored [6, 13]. Baylin et al. [14] reported that Samoans adhering to modern dietary patterns have high TG levels if they are homozygous for the rs9308762 C allele. In both Japanese and Chinese Malaysian subjects, significant interactions were found between selected dietary patterns and VEGFR2 single nucleotide polymorphisms (SNP) and blood lipids [15]. It is unknown whether dietary patterns modulate the relationship of the abovementioned APOC3 gene variant to MetS. The aim of this study was to evaluate the potential interactions of dietary patterns, derived by principal component analysis, with the common genetic variant of APOC3 rs5128 in relation to MetS and its components in a nested case-control study on a prospective cohort of Tehranian adults.
Study Population This study is part of the TLGS, an ongoing population-based cohort study conducted to determine the risk factors of noncommunicable diseases in a sample of residents of district No. 13 in Tehran, the capital of Iran. The first phase of the TLGS was a cross-sectional or baseline examination survey conducted from 1999 to 2001, for which the prevalence and distribution of high BP, dyslipidemia, diabetes and obesity were determined in 15,005 subjects aged ≥3 years selected by cluster random sampling. Follow-up examinations were conducted every 3 years (for the periods of 2002–2005, 2006–2008 and 2008–2011) to update healthrelated measurements of baseline characteristics and to identify newly developed diseases [16]. In the current study, cases were selected from among participants who were free of MetS at baseline and had developed MetS by the 3rd and 4th follow-up examinations. Each case was matched individually with a control for age (±5 years), sex and follow-up period from participants who had not developed any or at least 1 of the components of MetS. Considering the subjects who had developed MetS by the 3rd (n = 918) and 4th (n = 827) follow-ups, dietary data for 285 and 595 participants were available, respectively. After excluding individuals with a history of cardiovascular events, weight loss or gain >5 kg in the last 6 months, kidney or
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Subjects and Methods
107
J Nutrigenet Nutrigenomics 2014;7:105–117 DOI: 10.1159/000365445
© 2014 S. Karger AG, Basel www.karger.com/jnn
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
liver disease, pregnancy and lactating, taking any cardiovascular/anticoagulant/steroid or hormonal medication (n = 17) and lack of DNA purification in the range of 1.6 < A260/A280 < 2 (n = 108) as well as those for whom the reported energy intake divided by the predicted energy intake did not qualify for a ±3 SD range [17], 1,510 newly diagnosed MetS subjects and controls remained for the study. The study protocol was approved by the Research Ethics Committee of the Research Institute for Endocrine Science, Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran. Written informed consent was obtained from each participant. Dietary Intakes Dietary intake was assessed using a valid and reliable 168-item semiquantitative food frequency questionnaire. Based on macronutrient composition and using the available literature, 25 food groups were categorized [18, 19]. The dietary assessment at the 3rd or 4th follow-up survey was done on a selected random sample based on age groups and sex. Randomization was performed because of the costs and complexity of dietary data collection in large populations and also the fact that this process is time-consuming. The characteristics of the participants who completed the food frequency questionnaire were similar to those of the total population in the follow-up surveys [20]. Measurements Weight was measured using digital scales (Seca 707; Seca, Hamburg, Germany) and recorded to the nearest 100 g. Height was measured with a tape measure (model 208 Portable Body Meter Measuring Device; Seca). Waist circumference (WC) was measured at the umbilical level using an unstretched tape measure without any pressure to the body surface. The measurements were recorded to the nearest 0.1 cm. BP was examined twice after the participants had been sitting for 15 min. Between the two measurements, there was an interval of at least 30 s, and the mean BP of the two measurements recorded was reported as the subjects’ BP. The physical activity level was assessed using the reliable and valid Persian version of the Modifiable Activity Questionnaire (MAQ). Physical activity levels were expressed as metabolic equivalent hours per week [21–23].
Genetic Analysis The APOA1/C3/A4 gene cluster is the most characterized region in the human genome. Our previous study on TLGS participants showed that the presence of the G allele increased the TG concentration as a component of MetS [24]. For genotyping APOC3 polymorphism, buffy coats were separated from the noncoagulated whole-blood samples and stored at −70 ° C until processing, when genomic DNA was extracted by the proteinase K/salting-out method. The polymerase chain reaction (PCR) followed by restriction fragment length polymorphism technique was employed to investigate polymorphism in the gene fragments [24, 25]. PCR was done using the following primers: APOC3 (3238C>G) – forward 5′-GGT GAC CGA TGG CTT CAG TT-3′; reverse 5′-CAGAAG GTG GAT AGA GCG CT-3′. Hybridization was carried out in a DNA thermal cycler (Corbett Co., Australia), in which the DNA templates were denatured at 95 ° C for 3 min; amplification
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Laboratory Assays Between 7.00 and 9.00 a.m., after 12–14 h of overnight fasting, blood samples were drawn into vacutainer tubes in a sitting position from all study participants [16]. The samples were centrifuged within 30–45 min of collection according to the standard protocols. All biochemical analyses were performed at the TLGS research laboratory on the same day as the blood collection and conducted using a Selectra 2 autoanalyzer (Vital Scientific, Spankeren, The Netherlands). Fasting blood glucose (FBG) was measured by the enzymatic colorimetric method using glucose oxidase. TG was measured using TG kits (Pars Azmoon, Tehran, Iran) by enzymatic colorimetric tests and with glycerol phosphate oxidase. High-density lipoprotein cholesterol (HDL-C) was measured after the precipitation of ApoB-containing lipoproteins with phosphotungstic acid. Monitoring of assay performance was performed once every 20 tests, using lipid control serum, Percinorm (reference range) and Percipath (pathologic range) wherever applicable (Boehringer Mannheim, Mannheim, Germany; catalog No. 1446070 for Percinorm and No. 171778 for Percipath). Lipid standard (Cfas; Boehringer Mannheim; catalog No. 759350) was used to calibrate the Selectra 2 autoanalyzer for each day of laboratory analyses, and all samples were analyzed when they met the internal quality control criteria. The interand intra-assay coefficients of variation were both 2.2% for serum glucose and 1.6 and 0.6% for TG, respectively.
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J Nutrigenet Nutrigenomics 2014;7:105–117 DOI: 10.1159/000365445
© 2014 S. Karger AG, Basel www.karger.com/jnn
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
consisted of 30 cycles at 95 ° C for 60 s, 55/5 ° C for 2 min and 72 ° C for 90 s, with a final extension at 72 ° C for 5 min. Amplified DNA (10 μl) was digested with 0.3 μl of SacI restriction enzyme (Roche, Germany) at 37 ° C overnight [26]; fragments were separated by electrophoresis on a 2% agarose gel. The DNA fragments were visualized by gel documentation (OptiGo; Isogen Life Science, Ijsselstein, The Netherlands). Fragments containing three possible genotypes were then distinguished: uncut homozygous CC (428 bp), cut heterozygous CG (428, 265 and 163 bp) and cut homozygous GG (265 and 163 bp). Five percent of the samples were randomly replicated and genotyped with ≥99% concordance. Also, 5% of the PCR samples were directly sequenced to confirm the results from PCR-restriction fragment length polymorphism. Definitions MetS subjects were defined as participants with 3 or more of the following conditions, as defined by the modified National Cholesterol Education Program/Adult Treatment Panel III (ATP III) [27, 28]: (1) TG ≥150 mg/dl, (2) HDL-C 14 years). Multiplicative interactions between dietary pattern scores or food group intakes, which were highly loaded on each pattern, and polymorphism in relation to MetS were examined separately in men and women by conditional logistic regression analysis after adjustment for baseline BMI and energy intake, using the likelihood ratio test, which is a comparison of the likelihood scores of the model with and that without the interaction term. Conditional logistic regression was used to examine the joint role of tertiles of dietary pattern scores or food group intakes and genotypes of rs5128 (CC and CG + GG) in predicting MetS risk, using the highest tertile of dietary pattern scores or food group intakes and the CG + GG genotype as the reference. This model was adjusted for baseline BMI and energy intake.
The mean ages (SD) of men [cases: 40.5 (13) years; controls: 40.6 (14) years] and women [cases: 44.8 (11) years; controls: 44.9 (11) years] did not differ between the MetS subjects and the controls. The cases had a higher mean BMI than the controls [26.1 (4) vs. 22.6 (4)]. Low HDL-C concentration (83%) and abdominal obesity (78%) had a higher prevalence in the MetS subjects (table 1). The genotype frequency did not deviate from Hardy-Weinberg equilibrium expectations (p = 0.20). Based on the dietary data, three major dietary patterns were extracted: the healthy (HDP), the Western (WDP) and the fat-sweet dietary pattern (FSDP; table 2). The HDP was characterized by a high consumption of different kinds of vegetables, fruit, nuts and seeds, liquid oils, low-fat dairy and legumes. The WDP was loaded heavily on fast food, soft drinks, salty snacks, organ meat, sweets, fish and sweetened fruit juices. The FSDP was characterized
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Results
109
J Nutrigenet Nutrigenomics 2014;7:105–117 DOI: 10.1159/000365445
© 2014 S. Karger AG, Basel www.karger.com/jnn
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
Table 1. Characteristics of the study population in the MetS and the control group
Age, years Total Men (n = 874) Women (n = 636) Current smokers, % Low physical activity, % Educational level ≥14 years, % Baseline BMI Obesity, n (%) Baseline WC, cm Abdominal obesity, n (%) Baseline systolic BP, mm Hg Baseline diastolic BP, mm Hg Hypertension, n (%) Baseline HDL-C, mg/dl Low HDL-C, n (%) Baseline TG, mg/dl High TG, n (%) Baseline FBG, mg/dl High FBG, n (%) Energy intake, kcal/day % Energy carbohydrate % Energy total fat % Energy saturated fat % Energy monounsaturated fat Fiber intake, g/1,000 kcal/day Allele frequency rs5128, n (%) C G Genotype frequency rs5128, n (%) CC CG GG
MetS (n = 755)
Controls (n = 755)
42.3 (13) 40.5 (13) 44.8 (11) 15.4 54.9 9.1 26.1 (4) 288 (38) 86.0 (11) 587 (78) 114 (13) 75.5 (9) 371 (49) 39.0 (9) 628 (83) 154 (93) 548 (73) 90.3 (12) 306 (41) 2,574 (982) 58.6 (7) 30.2 (6) 9.9 (2) 8.61 (4) 18.0 (7)
42.3 (13) 40.6 (14) 44.9 (11) 14.2 52.4 11.6 22.6 (4)* 22 (3)* 76.8 (10)* 28 (3.7)* 108 (11)* 71.3 (8)* 21 (3)* 47.7 (11)* 14 (2)* 101 (44)* 6 (1)* 86.2 (9)* 10 (1)* 2,445 (928)* 58.6 (6) 30.4 (6) 10.2 (2) 8.27 (4) 18.1 (6)
1,230 (82) 278 (18)
1,080 (81) 250 (19)
500 (66) 230 (31) 24 (3)
496 (65) 240 (32) 20 (3)
by a high consumption of sugar, tea and coffee, solid oils, red meat, high-fat dairy, sweets and green vegetables. The adjusted least-square means for the participant characteristics and MetS components according to quartiles of the three dietary patterns are shown in table 3. Adherence to the HDP was associated with higher age as well as lower serum TG and FBG concentrations. Adherence to the WDP was associated with lower physical activity and lower age. The greatest absolute differences between extreme quartiles of WDP were 3 cm for WC and 3 mg/dl for FBG. The subjects in the highest quartile of the FSDP were more likely to be older and to be smokers, and adherence to this pattern was associated with lower WC and FBG. The adjusted least-square means for the MetS components according to the APOC3 rs5128 genotype are presented in table 4 for the dominant and codominant models separately for men and women. The values for the MetS components were not different between the groups.
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Values are means with SD in parentheses unless specified otherwise. * p < 0.05.
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J Nutrigenet Nutrigenomics 2014;7:105–117 © 2014 S. Karger AG, Basel www.karger.com/jnn
DOI: 10.1159/000365445
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
Table 2. Factor loadings for three identified food patterns in the study participants
Food patterns
Legumes Nuts and seeds Low-fat dairy Liquid oils Green vegetables Yellow-red vegetables Starchy vegetables Other vegetables Fruit Whole grains Refined grains Fruit juices Fish Sweets Organ meat Salty snacks Soft drinks Eggs Poultry Fast food Red meat Sugar High-fat dairy Solid oils Tea and coffee Variance, %a
HDP
WDP
0.32 0.39 0.34 0.38 0.61 0.71 0.32 0.70 0.56 0.21 –0.33 0.25 0.24
0.25 0.23
–0.23
–0.39
0.29 0.33 0.21 –0.23 –0.37 0.40 0.41 0.45 0.46 0.57 0.64 0.25 0.27 0.68 0.24
–0.23 11.2
FSDP
9.8
0.30
0.24 0.36 0.57 0.36 0.37 0.50 7.0
In the joint analysis, the associations of the WDP and APOC3 rs5128 with MetS risk tended to be dependent on APOC3 3238C>G gene variants (p for interaction = 0.009) in women. The MetS risk was increased in women with the CC genotype with increasing tertiles of WDP [OR T1: 2.52 (1.11–5.67); T2: 3.48 (1.49–8.13); T3: 2.62 (1.13–6.02)] as compared with women with the CG + GG genotype, whose MetS risk was decreased with increasing tertiles of WDP [OR T1: 4.83 (1.87–12.44); T2: 2.76 (1.12–6.78); T3: 1]. In addition, we found that intakes of fast food, salty snacks and soft drinks showed a significant interaction with the APOC3 rs5128 genotypes in relation to MetS risk (p for interaction < 0.05; table 5). There were no interactions between dietary patterns and genotype in relation to components of MetS, except in men with the CC genotype, for whom the OR for the risk of high BP decreased with increasing tertiles of WDP scores [T1: 1.01 (0.54–1.90); T2: 0.92 (0.49–1.72); T3: 0.79 (0.42–1.49)] compared with men with the CG + GG genotype, whose risk of high BP increased [T1: 0.77 (0.35–1.72); T2: 0.26 (0.10–0.66); T3: 1; p for interaction = 0.02]. Conversely, the risk of low HDL-C was increased in men with the CG + GG genotype with increasing tertiles of WDP scores [OR T1: 0.40 (0.18–0.85); T2: 0.76 (0.37–1.59); T3: 1] compared with men with the CC genotype [T1: 0.93 (0.50–1.71); T2: 0.54 (0.30–1.00); T3: 0.68 (0.38–1.23); p for interaction = 0.02; data not shown].
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Values are factor loadings of food patterns measured by factor analysis (n = 1,510). Factor loadings below ±0.2 are not shown in the table for reasons of simplicity. a Eigenvalues >1; Kaiser-Meyer-Olkin value: 0.714.
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J Nutrigenet Nutrigenomics 2014;7:105–117 © 2014 S. Karger AG, Basel www.karger.com/jnn
DOI: 10.1159/000365445
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
Table 3. Characteristics and MetS components of the participants by quartiles of dietary patterns
Age, yearsa HDP WDP FSDP Men, %b HDP WDP FSDP Baseline current smokers, %b HDP WDP FSDP Low physical activity, %b HDP WDP FSDP WC, cmc HDP WDP FSDP Systolic BP, mm Hgc HDP WDP FSDP Diastolic BP, mm Hgc HDP WDP FSDP HDL-C, mg/dlc HDP WDP FSDP TG, lnc HDP WDP FSDP FBG, mg/dlc HDP WDP FSDP
Quartile 1
Quartile 2
Quartile 3
Quartile 4
38.5 (13) 48.7 (13) 41.7 (13)
40.9 (12) 42.9 (12) 42.6 (13)
43.6 (13) 40.8 (11) 41.4 (12)
46.1 (12) 36.8 (12) 43.5 (13)
© 2014 S. Karger AG, Basel 1661–6499/14/0072–0105$39.50/0 www.karger.com/jnn
Original Paper
Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study Firoozeh Hosseini-Esfahani a, b Parvin Mirmiran a, b, e Maryam S. Daneshpour c Yadollah Mehrabi f Mehdi Hedayati c Maryam Zarkesh c Fereidoun Azizi d a
Nutrition and Endocrine Research Center, b Obesity Research Center, c Cellular and Molecular Endocrine Research Center, and d Endocrinology Research Center, Research Institute for Endocrine Science, e Faculty of Nutrition Sciences and Food Technology, National Nutrition and Food Technology Research Institute, and f Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Key Words Dietary patterns · Genetic polymorphisms · Metabolic syndrome
Maryam S. Daneshpour Cellular and Molecular Endocrine Research Center Research Institute for Endocrine Science, Shahid Beheshti University of Medical Sciences PO Box 19395-4763, Tehran 1985717413 (Iran) E-Mail daneshpour @ endocrine.ac.ir
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Abstract Background/Aims: Gene-dietary pattern interactions may contribute to the determination of a susceptibility to metabolic syndrome (MetS). The aim of this study was to evaluate the potential interactions of dietary patterns with the common genetic variant of APOC3 in relation to MetS in adults. Methods: In this individual matched nested case-control study, 755 MetS subjects and 755 controls were selected from among participants in the Tehran Lipid and Glucose Study. Dietary patterns were determined by factor analysis. APOC3 3238C>G rs5128 was genotyped by polymerase chain reaction and restriction fragment length polymorphism. Results: Fat-sweet, healthy and Western dietary patterns (WDP) were extracted from the data. In the joint analysis, the associations of the WDP and APOC3 rs5128 with MetS risk tended to be dependent on APOC3 3238C>G gene variants (p for interaction = 0.009) in women. The MetS risk was increased in women with the CC genotype with increasing tertiles of WDP scores compared with women with the CG + GG genotype, whose MetS risk was decreased with increasing tertiles of WDP scores. In addition, we found that intakes of fast food, salty snacks and soft drinks showed significant interactions with the rs5128 genotypes in relation to MetS risk (p for interactions G rs5128 variant is associated with increased Apoc3 and ApoB concentrations, low-density lipoprotein cholesterol (LDL-C) and plasma TG as well as high blood pressure (BP) and coronary heart disease [7–9]. No individual dietary component is wholly responsible for the association of a diet with MetS [10]. However, the optimal diet for the prevention and treatment of MetS remains unspecified, and physiologic differences can influence the effect of particular dietary patterns on the risk of MetS [11]. Food groups contributing to dietary patterns are not consistent across populations, which may yield discrepant results in dietary pattern studies among different populations [12]. The gene-diet interaction has helped to shed more light on an understanding of this variability, an area that has been poorly explored [6, 13]. Baylin et al. [14] reported that Samoans adhering to modern dietary patterns have high TG levels if they are homozygous for the rs9308762 C allele. In both Japanese and Chinese Malaysian subjects, significant interactions were found between selected dietary patterns and VEGFR2 single nucleotide polymorphisms (SNP) and blood lipids [15]. It is unknown whether dietary patterns modulate the relationship of the abovementioned APOC3 gene variant to MetS. The aim of this study was to evaluate the potential interactions of dietary patterns, derived by principal component analysis, with the common genetic variant of APOC3 rs5128 in relation to MetS and its components in a nested case-control study on a prospective cohort of Tehranian adults.
Study Population This study is part of the TLGS, an ongoing population-based cohort study conducted to determine the risk factors of noncommunicable diseases in a sample of residents of district No. 13 in Tehran, the capital of Iran. The first phase of the TLGS was a cross-sectional or baseline examination survey conducted from 1999 to 2001, for which the prevalence and distribution of high BP, dyslipidemia, diabetes and obesity were determined in 15,005 subjects aged ≥3 years selected by cluster random sampling. Follow-up examinations were conducted every 3 years (for the periods of 2002–2005, 2006–2008 and 2008–2011) to update healthrelated measurements of baseline characteristics and to identify newly developed diseases [16]. In the current study, cases were selected from among participants who were free of MetS at baseline and had developed MetS by the 3rd and 4th follow-up examinations. Each case was matched individually with a control for age (±5 years), sex and follow-up period from participants who had not developed any or at least 1 of the components of MetS. Considering the subjects who had developed MetS by the 3rd (n = 918) and 4th (n = 827) follow-ups, dietary data for 285 and 595 participants were available, respectively. After excluding individuals with a history of cardiovascular events, weight loss or gain >5 kg in the last 6 months, kidney or
Downloaded by: Glasgow Univ.Lib. 130.209.6.50 - 10/9/2014 9:46:19 PM
Subjects and Methods
107
J Nutrigenet Nutrigenomics 2014;7:105–117 DOI: 10.1159/000365445
© 2014 S. Karger AG, Basel www.karger.com/jnn
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
liver disease, pregnancy and lactating, taking any cardiovascular/anticoagulant/steroid or hormonal medication (n = 17) and lack of DNA purification in the range of 1.6 < A260/A280 < 2 (n = 108) as well as those for whom the reported energy intake divided by the predicted energy intake did not qualify for a ±3 SD range [17], 1,510 newly diagnosed MetS subjects and controls remained for the study. The study protocol was approved by the Research Ethics Committee of the Research Institute for Endocrine Science, Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran. Written informed consent was obtained from each participant. Dietary Intakes Dietary intake was assessed using a valid and reliable 168-item semiquantitative food frequency questionnaire. Based on macronutrient composition and using the available literature, 25 food groups were categorized [18, 19]. The dietary assessment at the 3rd or 4th follow-up survey was done on a selected random sample based on age groups and sex. Randomization was performed because of the costs and complexity of dietary data collection in large populations and also the fact that this process is time-consuming. The characteristics of the participants who completed the food frequency questionnaire were similar to those of the total population in the follow-up surveys [20]. Measurements Weight was measured using digital scales (Seca 707; Seca, Hamburg, Germany) and recorded to the nearest 100 g. Height was measured with a tape measure (model 208 Portable Body Meter Measuring Device; Seca). Waist circumference (WC) was measured at the umbilical level using an unstretched tape measure without any pressure to the body surface. The measurements were recorded to the nearest 0.1 cm. BP was examined twice after the participants had been sitting for 15 min. Between the two measurements, there was an interval of at least 30 s, and the mean BP of the two measurements recorded was reported as the subjects’ BP. The physical activity level was assessed using the reliable and valid Persian version of the Modifiable Activity Questionnaire (MAQ). Physical activity levels were expressed as metabolic equivalent hours per week [21–23].
Genetic Analysis The APOA1/C3/A4 gene cluster is the most characterized region in the human genome. Our previous study on TLGS participants showed that the presence of the G allele increased the TG concentration as a component of MetS [24]. For genotyping APOC3 polymorphism, buffy coats were separated from the noncoagulated whole-blood samples and stored at −70 ° C until processing, when genomic DNA was extracted by the proteinase K/salting-out method. The polymerase chain reaction (PCR) followed by restriction fragment length polymorphism technique was employed to investigate polymorphism in the gene fragments [24, 25]. PCR was done using the following primers: APOC3 (3238C>G) – forward 5′-GGT GAC CGA TGG CTT CAG TT-3′; reverse 5′-CAGAAG GTG GAT AGA GCG CT-3′. Hybridization was carried out in a DNA thermal cycler (Corbett Co., Australia), in which the DNA templates were denatured at 95 ° C for 3 min; amplification
Downloaded by: Glasgow Univ.Lib. 130.209.6.50 - 10/9/2014 9:46:19 PM
Laboratory Assays Between 7.00 and 9.00 a.m., after 12–14 h of overnight fasting, blood samples were drawn into vacutainer tubes in a sitting position from all study participants [16]. The samples were centrifuged within 30–45 min of collection according to the standard protocols. All biochemical analyses were performed at the TLGS research laboratory on the same day as the blood collection and conducted using a Selectra 2 autoanalyzer (Vital Scientific, Spankeren, The Netherlands). Fasting blood glucose (FBG) was measured by the enzymatic colorimetric method using glucose oxidase. TG was measured using TG kits (Pars Azmoon, Tehran, Iran) by enzymatic colorimetric tests and with glycerol phosphate oxidase. High-density lipoprotein cholesterol (HDL-C) was measured after the precipitation of ApoB-containing lipoproteins with phosphotungstic acid. Monitoring of assay performance was performed once every 20 tests, using lipid control serum, Percinorm (reference range) and Percipath (pathologic range) wherever applicable (Boehringer Mannheim, Mannheim, Germany; catalog No. 1446070 for Percinorm and No. 171778 for Percipath). Lipid standard (Cfas; Boehringer Mannheim; catalog No. 759350) was used to calibrate the Selectra 2 autoanalyzer for each day of laboratory analyses, and all samples were analyzed when they met the internal quality control criteria. The interand intra-assay coefficients of variation were both 2.2% for serum glucose and 1.6 and 0.6% for TG, respectively.
108
J Nutrigenet Nutrigenomics 2014;7:105–117 DOI: 10.1159/000365445
© 2014 S. Karger AG, Basel www.karger.com/jnn
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
consisted of 30 cycles at 95 ° C for 60 s, 55/5 ° C for 2 min and 72 ° C for 90 s, with a final extension at 72 ° C for 5 min. Amplified DNA (10 μl) was digested with 0.3 μl of SacI restriction enzyme (Roche, Germany) at 37 ° C overnight [26]; fragments were separated by electrophoresis on a 2% agarose gel. The DNA fragments were visualized by gel documentation (OptiGo; Isogen Life Science, Ijsselstein, The Netherlands). Fragments containing three possible genotypes were then distinguished: uncut homozygous CC (428 bp), cut heterozygous CG (428, 265 and 163 bp) and cut homozygous GG (265 and 163 bp). Five percent of the samples were randomly replicated and genotyped with ≥99% concordance. Also, 5% of the PCR samples were directly sequenced to confirm the results from PCR-restriction fragment length polymorphism. Definitions MetS subjects were defined as participants with 3 or more of the following conditions, as defined by the modified National Cholesterol Education Program/Adult Treatment Panel III (ATP III) [27, 28]: (1) TG ≥150 mg/dl, (2) HDL-C 14 years). Multiplicative interactions between dietary pattern scores or food group intakes, which were highly loaded on each pattern, and polymorphism in relation to MetS were examined separately in men and women by conditional logistic regression analysis after adjustment for baseline BMI and energy intake, using the likelihood ratio test, which is a comparison of the likelihood scores of the model with and that without the interaction term. Conditional logistic regression was used to examine the joint role of tertiles of dietary pattern scores or food group intakes and genotypes of rs5128 (CC and CG + GG) in predicting MetS risk, using the highest tertile of dietary pattern scores or food group intakes and the CG + GG genotype as the reference. This model was adjusted for baseline BMI and energy intake.
The mean ages (SD) of men [cases: 40.5 (13) years; controls: 40.6 (14) years] and women [cases: 44.8 (11) years; controls: 44.9 (11) years] did not differ between the MetS subjects and the controls. The cases had a higher mean BMI than the controls [26.1 (4) vs. 22.6 (4)]. Low HDL-C concentration (83%) and abdominal obesity (78%) had a higher prevalence in the MetS subjects (table 1). The genotype frequency did not deviate from Hardy-Weinberg equilibrium expectations (p = 0.20). Based on the dietary data, three major dietary patterns were extracted: the healthy (HDP), the Western (WDP) and the fat-sweet dietary pattern (FSDP; table 2). The HDP was characterized by a high consumption of different kinds of vegetables, fruit, nuts and seeds, liquid oils, low-fat dairy and legumes. The WDP was loaded heavily on fast food, soft drinks, salty snacks, organ meat, sweets, fish and sweetened fruit juices. The FSDP was characterized
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Results
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J Nutrigenet Nutrigenomics 2014;7:105–117 DOI: 10.1159/000365445
© 2014 S. Karger AG, Basel www.karger.com/jnn
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
Table 1. Characteristics of the study population in the MetS and the control group
Age, years Total Men (n = 874) Women (n = 636) Current smokers, % Low physical activity, % Educational level ≥14 years, % Baseline BMI Obesity, n (%) Baseline WC, cm Abdominal obesity, n (%) Baseline systolic BP, mm Hg Baseline diastolic BP, mm Hg Hypertension, n (%) Baseline HDL-C, mg/dl Low HDL-C, n (%) Baseline TG, mg/dl High TG, n (%) Baseline FBG, mg/dl High FBG, n (%) Energy intake, kcal/day % Energy carbohydrate % Energy total fat % Energy saturated fat % Energy monounsaturated fat Fiber intake, g/1,000 kcal/day Allele frequency rs5128, n (%) C G Genotype frequency rs5128, n (%) CC CG GG
MetS (n = 755)
Controls (n = 755)
42.3 (13) 40.5 (13) 44.8 (11) 15.4 54.9 9.1 26.1 (4) 288 (38) 86.0 (11) 587 (78) 114 (13) 75.5 (9) 371 (49) 39.0 (9) 628 (83) 154 (93) 548 (73) 90.3 (12) 306 (41) 2,574 (982) 58.6 (7) 30.2 (6) 9.9 (2) 8.61 (4) 18.0 (7)
42.3 (13) 40.6 (14) 44.9 (11) 14.2 52.4 11.6 22.6 (4)* 22 (3)* 76.8 (10)* 28 (3.7)* 108 (11)* 71.3 (8)* 21 (3)* 47.7 (11)* 14 (2)* 101 (44)* 6 (1)* 86.2 (9)* 10 (1)* 2,445 (928)* 58.6 (6) 30.4 (6) 10.2 (2) 8.27 (4) 18.1 (6)
1,230 (82) 278 (18)
1,080 (81) 250 (19)
500 (66) 230 (31) 24 (3)
496 (65) 240 (32) 20 (3)
by a high consumption of sugar, tea and coffee, solid oils, red meat, high-fat dairy, sweets and green vegetables. The adjusted least-square means for the participant characteristics and MetS components according to quartiles of the three dietary patterns are shown in table 3. Adherence to the HDP was associated with higher age as well as lower serum TG and FBG concentrations. Adherence to the WDP was associated with lower physical activity and lower age. The greatest absolute differences between extreme quartiles of WDP were 3 cm for WC and 3 mg/dl for FBG. The subjects in the highest quartile of the FSDP were more likely to be older and to be smokers, and adherence to this pattern was associated with lower WC and FBG. The adjusted least-square means for the MetS components according to the APOC3 rs5128 genotype are presented in table 4 for the dominant and codominant models separately for men and women. The values for the MetS components were not different between the groups.
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Values are means with SD in parentheses unless specified otherwise. * p < 0.05.
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J Nutrigenet Nutrigenomics 2014;7:105–117 © 2014 S. Karger AG, Basel www.karger.com/jnn
DOI: 10.1159/000365445
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
Table 2. Factor loadings for three identified food patterns in the study participants
Food patterns
Legumes Nuts and seeds Low-fat dairy Liquid oils Green vegetables Yellow-red vegetables Starchy vegetables Other vegetables Fruit Whole grains Refined grains Fruit juices Fish Sweets Organ meat Salty snacks Soft drinks Eggs Poultry Fast food Red meat Sugar High-fat dairy Solid oils Tea and coffee Variance, %a
HDP
WDP
0.32 0.39 0.34 0.38 0.61 0.71 0.32 0.70 0.56 0.21 –0.33 0.25 0.24
0.25 0.23
–0.23
–0.39
0.29 0.33 0.21 –0.23 –0.37 0.40 0.41 0.45 0.46 0.57 0.64 0.25 0.27 0.68 0.24
–0.23 11.2
FSDP
9.8
0.30
0.24 0.36 0.57 0.36 0.37 0.50 7.0
In the joint analysis, the associations of the WDP and APOC3 rs5128 with MetS risk tended to be dependent on APOC3 3238C>G gene variants (p for interaction = 0.009) in women. The MetS risk was increased in women with the CC genotype with increasing tertiles of WDP [OR T1: 2.52 (1.11–5.67); T2: 3.48 (1.49–8.13); T3: 2.62 (1.13–6.02)] as compared with women with the CG + GG genotype, whose MetS risk was decreased with increasing tertiles of WDP [OR T1: 4.83 (1.87–12.44); T2: 2.76 (1.12–6.78); T3: 1]. In addition, we found that intakes of fast food, salty snacks and soft drinks showed a significant interaction with the APOC3 rs5128 genotypes in relation to MetS risk (p for interaction < 0.05; table 5). There were no interactions between dietary patterns and genotype in relation to components of MetS, except in men with the CC genotype, for whom the OR for the risk of high BP decreased with increasing tertiles of WDP scores [T1: 1.01 (0.54–1.90); T2: 0.92 (0.49–1.72); T3: 0.79 (0.42–1.49)] compared with men with the CG + GG genotype, whose risk of high BP increased [T1: 0.77 (0.35–1.72); T2: 0.26 (0.10–0.66); T3: 1; p for interaction = 0.02]. Conversely, the risk of low HDL-C was increased in men with the CG + GG genotype with increasing tertiles of WDP scores [OR T1: 0.40 (0.18–0.85); T2: 0.76 (0.37–1.59); T3: 1] compared with men with the CC genotype [T1: 0.93 (0.50–1.71); T2: 0.54 (0.30–1.00); T3: 0.68 (0.38–1.23); p for interaction = 0.02; data not shown].
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Values are factor loadings of food patterns measured by factor analysis (n = 1,510). Factor loadings below ±0.2 are not shown in the table for reasons of simplicity. a Eigenvalues >1; Kaiser-Meyer-Olkin value: 0.714.
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J Nutrigenet Nutrigenomics 2014;7:105–117 © 2014 S. Karger AG, Basel www.karger.com/jnn
DOI: 10.1159/000365445
Hosseini-Esfahani et al.: Western Dietary Pattern Interaction with APOC3 Polymorphism in the Risk of Metabolic Syndrome: Tehran Lipid and Glucose Study
Table 3. Characteristics and MetS components of the participants by quartiles of dietary patterns
Age, yearsa HDP WDP FSDP Men, %b HDP WDP FSDP Baseline current smokers, %b HDP WDP FSDP Low physical activity, %b HDP WDP FSDP WC, cmc HDP WDP FSDP Systolic BP, mm Hgc HDP WDP FSDP Diastolic BP, mm Hgc HDP WDP FSDP HDL-C, mg/dlc HDP WDP FSDP TG, lnc HDP WDP FSDP FBG, mg/dlc HDP WDP FSDP
Quartile 1
Quartile 2
Quartile 3
Quartile 4
38.5 (13) 48.7 (13) 41.7 (13)
40.9 (12) 42.9 (12) 42.6 (13)
43.6 (13) 40.8 (11) 41.4 (12)
46.1 (12) 36.8 (12) 43.5 (13)
