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Clinical Chemistry 53: 1144-1152, 2007. First published April 19, 2007; 10.1373/clinchem.2006.084863
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(Clinical Chemistry. 2007;53:1144-1152.)
© 2007 American Association for Clinical Chemistry, Inc.

Nutrition

The –256T>C Polymorphism in the Apolipoprotein A-II Gene Promoter Is Associated with Body Mass Index and Food Intake in the Genetics of Lipid Lowering Drugs and Diet Network Study

Dolores Corella1,2, Donna K. Arnett3, Michael Y. Tsai4, Edmond K. Kabagambe3, James M. Peacock5, James E. Hixson6, Robert J. Straka7, Michael Province8, Chao-Qiang Lai1, Laurence D. Parnell1, Ingrid Borecki8 and Jose M. Ordovas1,a

1 Nutrition and Genomics Laboratory, Jean Mayer-US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA.
2 Genetic and Molecular Epidemiology Unit and CIBER Fisiopatología de la Obesidad y Nutrición, School of Medicine, University of Valencia, Valencia, Spain.
3 Department of Epidemiology, School of Public Health, and Clinical Nutrition Research Center, University of Alabama at Birmingham, AL.
4 Laboratory of Medicine and Pathology, University of Minnesota, Minneapolis, MN.
5 Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, MN.
6 Human Genetics Center, University of Texas Health Science Center, Houston, TX.
7 Experimental and Clinical Pharmacology Department, College of Pharmacy, University of Minnesota, Minneapolis, MN.
8 Division of Biostatistics, Washington University School of Medicine, St. Louis, MO.

aAddress correspondence to this author at: Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, 711 Washington St., Boston, MA 02111-1524. Fax 617-556-3211; e-mail jose.ordovas{at}tufts.edu.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: Apolipoprotein A-II (APOA2) plays an ambiguous role in lipid metabolism, obesity, and atherosclerosis.

Methods: We studied the association between a functional APOA2 promoter polymorphism (–265T>C) and plasma lipids (fasting and postprandial), anthropometric variables, and food intake in 514 men and 564 women who participated in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study. We obtained fasting and postprandial (after consuming a high-fat meal) measures. We measured lipoprotein particle concentrations by proton nuclear magnetic resonance spectroscopy and estimated dietary intake by use of a validated questionnaire.

Results: We observed recessive effects for this polymorphism that were homogeneous by sex. Individuals homozygous for the –265C allele had statistically higher body mass index (BMI) than did carriers of the T allele. Consistently, after multivariate adjustment, the odds ratio for obesity in CC individuals compared with T allele carriers was 1.70 (95% CI 1.02–2.80, P = 0.039). Interestingly, total energy intake in CC individuals was statistically higher [mean (SE) 9371 (497) vs 8456 (413) kJ/d, P = 0.005] than in T allele carriers. Likewise, total fat and protein intakes (expressed in grams per day) were statistically higher in CC individuals (P = 0.002 and P = 0.005, respectively). After adjustment for energy, percentage of carbohydrate intake was statistically lower in CC individuals. These associations remained statistically significant even after adjustment for BMI. We found no associations with fasting lipids and only some associations with HDL subfraction distribution in the postprandial state.

Conclusions: The –265T>C polymorphism is consistently associated with food consumption and obesity, suggesting a new role for APOA2 in regulating dietary intake.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Apolipoprotein A-II (APOA2)1 is the 2nd most abundant protein of HDL particles, but its function remains largely unknown (1). Although some initial studies reported an inverse relationship between plasma APOA2 concentrations and cardiovascular disease (CVD) risk (2)(3), findings of subsequent studies did not reveal significant associations or even suggest a proatherogenic role (4)(5)(6). Overexpression of murine APOA22 in mice resulted in greater development of aortic fatty streak lesions (7). There are marked differences between murine and human APOA2, however, and overexpression of human APOA2 in mice does not exert effects similar to those of murine APOA2 on atherosclerosis (8)(9)(10). Relatively few studies have examined the association between APOA2 polymorphisms and phenotypic traits (11)(12)(13)(14). Moreover, few genetic variants have been identified in the APOA2 gene (15). Interestingly, a T>C transition at position –265 (rs no. 5082) affecting element D of the APOA2 promoter has been reported to be functional in 2 independent studies, both demonstrating an ~30% drop in basal transcription activity (16)(17). In one of these studies, the –265T>C polymorphism was associated with waist circumference in men (16). Another study (18) reported an association between this polymorphism and abdominal fat depots in women. Although Castellani et al. (19) found increased body weight in mice overexpressing murine APOA2, the mechanism by which APOA2 may influence body weight is largely unknown. APOA2 is a member of the apolipoprotein multigene superfamily, which includes genes encoding soluble apolipoproteins (e.g., APOA1 and APOA4) that share genomic structure and several functions. Although all these apolipoprotein genes have been found to be related to obesity in at least one epidemiological study (20), only APOA4 has been subscribed in regulation of food intake, acting as a satiety signal (21). Therefore, we hypothesized that APOA2 may also be involved in regulating food intake. Overall, our aims were to study the effect of the –65T>C polymorphism in the APOA2 gene on body weight, food intake, and plasma lipid concentrations (fasting and postprandial) in a North American population.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
study participants and study design
The study sample consisted of 514 men and 564 women who participated in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study. GOLDN is part of the Program for Genetic Interactions Network and is funded by the NIH through the University of Alabama at Birmingham and in collaboration with the University of Utah, Washington University, Tufts University, University of Texas, University of Michigan, University of Minnesota, and Fairview-University of Minnesota Medical Center. The majority of participants were re-recruited from 3-generational pedigrees from 2 National Heart, Lung, and Blood Institute Family Heart Study field centers (Minneapolis, MN, and Salt Lake City, UT) (22). Nearly all individuals were of European ancestry. Exclusion criteria were age <18 years; fasting triglycerides >16.5 mmol/L; recent history (6 months) of myocardial infarction; history of liver, kidney, pancreas, or gall bladder disease; history of malabsorption of nutrients; current use of insulin; abnormal renal or hepatic function; and pregnancy or nursing in women. Individuals who reported current use of hypolipidemic drugs or dietary supplements known to influence lipids were required to consult their physician for approval to discontinue these lipid-lowering agents for 4 weeks before study participation. Written informed consent was obtained from each participant. The protocol was approved by the Institutional Review Boards at the University of Alabama, the University of Minnesota, the University of Utah, and Tufts University.

The initially estimated sample size for the GOLDN study was ~1200 individuals. Complete fasting and postprandial data were obtained from 1118 individuals. Individuals with inconsistent dietary data (total daily energy intake outside the range of 800–5500 kcal in men or 600–4500 in women) were excluded, resulting in a final sample size of 1078 individuals (514 men and 564 women).

interventions and clinic visits
Participants were asked to fast for >12 h and abstain from using alcohol for >24 h before visiting the clinic. We measured weight with a beam balance, hip circumference at maximal hip girth, and waist circumference at the umbilicus. Body mass index (BMI) was calculated as weight (kg)/height (m)2, and obesity was defined as BMI ≥30 kg/m2. We administered clinical and lifestyle questionnaires and created an interviewer-administered, direct data entry system for the diet history questionnaire (DHQ) developed by the National Cancer Institute.

dietary intake
We estimated dietary intake by use of the DHQ, a food frequency questionnaire developed by staff at the Risk Factor Monitoring and Methods Branch. It consists of 124 food items and includes both portion size and dietary supplement questions. Two studies have been conducted to assess its validity (23)(24). The food list and nutrient database used with the DHQ are based on national dietary data [US Department of Agriculture (USDA) 1994–96 Continuing Survey of Food Intakes by Individuals, available from the USDA Food Surveys Research Group].

postprandial study fat challenge
The postprandial study fat challenge consisted of a meal formulated according to the protocol of Patsch et al. (25). The meal, which participants were instructed to consume within 15 min, had 700 calories/m2 body surface area (2.93 MJ/m2 body surface area); 3% of calories were derived from protein, 14% from carbohydrate, and 83% from fat sources. Cholesterol content was 240 mg and the ratio of polyunsaturated fat (PUFA) to saturated fat (SATFAT) was 0.06. The average person consumed 175 mL heavy whipping cream (39.5% fat) and 7.5 mL powdered, instant, nonfat dry milk, blended with ice and 15 mL chocolate- or strawberry-flavored syrup to increase palatability. We drew blood samples immediately before (time 0) and 3.5 and 6 h after the high-fat meal.

biochemical analyses
We drew venous blood after study participants had fasted overnight. Plasma samples were stored and analyzed together. We measured triglycerides by glycerol-blanked enzymatic method on the Roche COBAS FARA centrifugal analyzer (Roche Diagnostics). We measured cholesterol on the Hitachi 911 Automatic Analyzer (Roche Diagnostics) using a cholesterol esterase, cholesterol oxidase reaction (Chol R1; Roche Diagnostics). We used the same reaction to measure HDL cholesterol after precipitation of non-HDL cholesterol with magnesium/dextran. We measured LDL cholesterol by use of a homogeneous direct method (LDL Direct Liquid SelectTM Cholesterol Reagent; Equal Diagnostics) on the Hitachi 911. We measured lipoprotein particle concentrations and size by proton nuclear magnetic resonance spectroscopy (26)(27). Data were obtained from the measured amplitudes of their spectroscopically distinct lipid methyl group nuclear magnetic resonance signals. We measured the concentrations of the following subclasses: small LDL (diameter 18.0–21.2 nm), large LDL (21.2–23.0 nm), intermediate-density lipoprotein (IDL; 23.0–27.0 nm), large HDL (8.8–13.0 nm), medium HDL (8.2–8.8 nm), small HDL (7.3–8.2 nm), large VLDL (>60 nm), medium VLDL (35.0–60.0 nm), and small VLDL (27.0–35.0 nm). The small LDL subclass encompassed both intermediate small (19.8–21.2 nm) and very small (18.0–19.0 nm) particles.

dna isolation and apoa2 genotyping
DNA was isolated from blood samples using routine DNA isolation sets (Qiagen). We performed genotyping of the –265C>T polymorphism (rs5082) using a Taqman assay with allele-specific probes on the ABIPrism 7900HT Sequence Detection System (Applied Biosystems) according to routine laboratory protocols.

statistical analysis
Triglyceride concentrations were log transformed and IDL and VLDL were square-root transformed for statistical testing. We used Pearson {chi}2 and Fisher tests to test differences in percentages. We applied ANOVA and the Student t-test to compare crude means. We tested codominant, dominant, and recessive models for the APOA2 polymorphism. We carried out multivariate adjustments of the associations by analysis of covariance and estimated adjusted means. First, we adjusted analyses for demographic, clinical, and lifestyle variables and then for family relationships. To evaluate replication, we performed statistical analyses for the whole sample and for men and women separately. We also tested the statistical homogeneity of the effects by sex in the corresponding regression model with interaction terms. Obesity was defined as BMI ≥30 kg/m2. We fitted logistic regression models to estimate the odds ratio (OR) and 95% CI of obesity associated with the APOA2 polymorphism and to control for the effect of covariates and family relationships.

We performed ANOVA for repeated measures to analyze data obtained in the postprandial study. In this analysis, we studied the statistical effects of the APOA2 genotype alone, the effect of time (change in the variable after the high-fat load over the entire lipemic period), and the effect of the interaction of the 2 factors (genotype and time), which is indicative of the magnitude of the postprandial response in each group of individuals. We also carried out multivariate adjustment for covariates including demographic, clinical, lifestyle, and family relationships. We used routine regression diagnostic procedures to ensure the appropriateness of the models. Statistical analyses were done using SPSS 14.0 software (SPSS). All reported probability tests were 2-sided. Differences between means were considered significant at P <0.05.

bioinformatics analysis
Analysis of the genomic DNA sequence segment centered on the –265 variant was conducted with MAPPER (28) to identify potential transcription factor binding sites.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Characteristics of the study participants are shown in Table 1 . APOA2 genotype frequencies did not deviate from Hardy-Weinberg equilibrium expectations (P = 0.941) and did not differ between men and women (P = 0.670). We first examined the association between the APOA2 –265T>C polymorphism and anthropometric variables (Table 2 ). Recessive effects were observed, and thus TT and CT individuals were grouped and compared with CC homozygotes. Men and women were analyzed together because homogeneity of the effect was observed by sex (P for interaction APOA2 genotype*gender > 0.05 for all the anthropometric variables examined). In the crude analysis, we detected statistically significant mean differences in weight, BMI, and waist and hip circumferences between CC homozygotes and carriers of the common allele. These differences remained statistically significant even after multivariate adjustment for age, sex, tobacco smoking, alcohol consumption, diabetes, and CVD. After additional adjustment for family relationships, weight and BMI remained statistically significant. Furthermore, when we estimated the effect of the APOA2 polymorphism on obesity risk, we found a consistent and statistically significant association following a recessive pattern. Homogeneity of the effect was detected in both men and women. We estimated ORs and 95% CIs for CC homozygotes compared with carriers of the –265T allele, when each indicated variable was included into the logistic regression models (models 1 to 3). Model 1 was adjusted only for sex, and the OR for obesity associated with the CC genotype was 1.45 (95% CI 1.03–2.04, P = 0.032). After adjustment for sex, age, tobacco smoking, alcohol consumption, diabetes, and CVD (model 2), the higher risk of obesity associated with the CC genotype remained statistically significant (OR 1.47, 95% CI 1.03–2.09, P = 0.034). After additional adjustment for the previous variables plus family relationships (model 3), the OR was 1.70 (95% CI 1.02–2.80, P = 0.039), revealing a strong consistency in the estimations.


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  		Table 1. General characteristics of the study population.1


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  		Table 2. Association between the APOA2 –265T>C polymorphism and anthropometric variables in men and women.1

We next examined if the –265T>C APOA2 polymorphism may relate to food intake in this population. A recessive model of association was also found. Homogeneity of the associations was detected in both men and women; results for the overall sample are presented (Table 3 ). Homozygous individuals for the CC allele had a statistically higher mean of energy intake than carriers of the T allele, which remained statistically significant even after multivariate adjustment for sex, age, tobacco smoking, alcohol consumption, diabetes, CVD, and familial relationships. Thus, daily energy intake was ~900 KJ/d (200 Kcal/d) higher in CC homozygotes than in T allele carriers (P = 0.005). In terms of amount of food, CC homozygotes had significantly higher absolute intake than T allele carriers, even after multivariate adjustment. Total fat presented strong associations with the APOA2 polymorphism. Means of total fat intake (g/day) in men (Fig. 1A ) and women (Fig. 1B ) depending on the APOA2 polymorphism exemplify the recessive genetic effects and the internal replication of results. Moreover, when SATFAT, monounsaturated fat (MUFA), and PUFA as well as specific fatty acids were analyzed, significant differences were found even after multivariate adjustment. When macronutrients were expressed as percentage of daily energy intake, carbohydrate intake was statistically lower in CC homozygotes than in T allele carriers [mean (SE) 46.8% (1.7%) in TT + CT vs 44.9% (1.9%) in CC individuals, P = 0.012, in the multivariate adjusted model including sex, age, tobacco smoking, alcohol consumption, diabetes, CVD, and family relationships]. Likewise, after this multivariate adjustment, total fat intake expressed as percentage of daily energy intake was statistically higher in CC homozygotes than in T allele carriers [37.2% (1.4%) in TT + CT vs 38.6% (1.5%) in CC individuals; P = 0.023].


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  		Table 3. Association between the APOA2 –265T>C polymorphism and dietary intake in men and women.1


Figure 1
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  		Figure 1. Total fat intake (g/day) in men (A) and women (B) depending on the –265T>C polymorphism in the APOA2 gene promoter.

Crude means and P values are displayed. Multivariate P values were adjusted for age, tobacco smoking, alcohol consumption, diabetes, CVD, and family relationships. Error bars: SE.

Taking into account that CC individuals had higher BMI, we performed additional adjustment for BMI of the associations presented in Table 3Up (results not shown). This additional adjustment slightly modified the P values and did not change the inference.

We investigated the effect of the –265T>C APOA2 polymorphism on fasting plasma lipids, lipoproteins, and particle size in both men and women. No heterogeneity by sex was found. Neither in the crude model nor in the multivariate-adjusted model (Table 4 ) were statistically significant differences between APOA2 genotypes found. Considering that a high-fat intake increases APOA2 concentrations, a postprandial study of fat challenge was also performed in the 1078 participants. Blood samples were drawn before time 0 and at 3.5 and 6 h after consuming the high-fat meal. After multivariate adjustment, no statistically significant genotype effects or genotype*time interactions were observed for total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, small LDL particles, large LDL particles, mean LDL particle size, mean VLDL particle size, or mean HDL particle size (results not shown). Statistically significant genotype effects were observed for HDL and VLDL particles (Fig. 2A –F). The amount of small HDL particles, which decreased after the fat load, was significantly higher in CC homozygotes over the entire postprandial period than in carriers of the T allele (P = 0.029) and reached its highest statistical significance (P = 0.014) at 3.5 h after the fatty meal. Conversely, the amount of medium-sized HDL particles increased and was lower in CC homozygotes over the entire period (P = 0.049). The fat-loading test increased postprandial large VLDL particles, which were lower in homozygous individuals for the –265C allele. These results suggested a faster clearance in CC homozygotes than in carriers of the T allele.


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  		Table 4. Association between the APOA2 –265T>C polymorphism and fasting plasma lipid and lipoprotein concentrations and particle size.1


Figure 2
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  		Figure 2. Postprandial concentrations of large HDL (A), intermediate HDL (B), small HDL (C), large VLDL (D), intermediate VLDL (E), and small VLDL (F) after a high-fat meal depending on the –265T>C polymorphism in both men and women (at 0, 3.5, and 6 h after the oral fat tolerance test).

Multivariate adjusted means were estimated from a repeated-measures ANOVA model. Models were adjusted for sex, age, BMI, tobacco smoking, alcohol consumption, diabetes, CVD, medications, and family relationships. Multivariate P values for time, genotype, and the interaction genotype*time were estimated. *Statistically significant P values at every specific time point. n = 913 TT + TC and 165 CC.

The bioinformatic analysis of the APOA2 gene control (upstream) region indicates the potential for a CEBPA [CCAAT/enhancer binding protein (C/EBP) {alpha}] binding site that is not predicted with the minor C allele.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Since its discovery, APOA2 has been a protein in search of a function (29). In fact, it has often been stated that APOA2 has no major function in HDL metabolism (1)(5)(14)(29). This view is now changing as results become available of more recent findings proposing roles for this apolipoprotein in insulin resistance, obesity, and even cancer (16)(18)(19)(30)(31). In the current study, we found a strong association between the APOA2 –265T>C polymorphism and anthropometric measures that was replicated in both men and women, adding evidence to previous studies that reported a role for APOA2 in obesity (16)(18). Moreover, we observed for the first time a consistent association between the APOA2 –265T>C polymorphism and food consumption that also showed internal replication, suggesting a potential new role of APOA2 in the regulation of human appetite. In both men and women, we found a recessive effect of this polymorphism. Thus, homozygous individuals for the variant allele C had significantly higher daily energy intake than T allele carriers. When other variables (sex, age, tobacco smoking, alcohol consumption, diabetes, CVD, and family relationships) were progressively added to the crude model, only slight variation of the initially estimated P values was observed, revealing an independent significant association of this polymorphism. In analyzing macronutrient intake, we found that CC homozygotes had higher intake of fat and proteins than T allele carriers. Although some twin and family studies have documented the genetic component of total energy and macronutrient intake (32)(33), only a few reports (34)(35)(36) have shown that a gene polymorphism may partly determine energy or macronutrient intake in humans. These studies have focused on the HTR2A [5-hydroxytryptamine (serotonin) receptor 2A] gene. Herbeth et al. (36) found that the –1438G/A polymorphism in the HTR2A gene was significantly associated with lower energy, total fat, MUFA, and SATFAT intakes in children and adolescents from the Stanislas Family Study. They also found homogeneity by sex. These results were consistent with the findings of a previous study of overweight individuals from France (34). These genotypic effects can be easily explained by the relevant role of the serotonergic system as a determinant of food intake. In the case of APOA2, however, no previous studies show a role of this protein in determining food intake—only a recent report linking ethanol self-administration in monkeys with higher serum APOA2 concentrations (37). Collaku et al. (38), in a genomic scan in white sibling pairs, identified several chromosomal regions that contribute to variations in food intake. The strongest evidence of linkage for dietary energy and fat intake was found on chromosome 1p21.2 (P <0.001). Although the authors did not mention APOA2 as a potential candidate gene in explaining such results, the APOA2 gene is in this locus.

Despite the scarcity of previous data supporting a role of APOA2 in regulating food intake, copious experimental evidence demonstrates a pivotal role of another apolipoprotein, APOA4, as a satiety signal (20)(21)(39)(40). Fujimoto et al. (39) were the first to report that APOA4 is a satiety factor secreted by the intestine after fat absorption and that this function of APOA4 is not shared by gut APOA1. Unfortunately, Fujimoto et al. (39) did not test the effects of APOA2, and its potential effects remain to be elucidated. If APOA2 acts as a satiety signal, taking into account that the –265T>C polymorphism results in lower APOA2 concentrations, individuals homozygous for –265C can have a higher food intake than carriers of the T allele. A direct consequence of the involvement of APOA2 in regulating food intake is its influence in body weight regulation. Only 2 population studies have examined the association between the –265T>C polymorphism and anthropometric measures, with controversial results (16)(18). In this American population, we have found that in both men and women, homozygous individuals for the –265C allele had higher obesity risk than carriers of the T allele. Our findings are in agreement with Lara-Castro et al. (18), who reported statistically higher amounts of visceral adipose tissue in white women carriers of the –265C allele. Neither of these studies examined the influence of the –265T>C polymorphism in determining food intake. Van’t Hooft et al. (16) studied the association between this polymorphism and fasting plasma glucose, insulin, lipids, and lipoproteins and found no significant associations, in agreement with our results. Moreover, they also carried out an oral fat tolerance test and found that the overall response of plasma triglycerides during the entire 6-h period was unassociated with the APOA2 –265T>C polymorphism. Interestingly, postprandial APOB-100 concentrations in the Sf >60 of triglyceride-rich protein (a measure of large VLDL particles) were significantly lower in individuals homozygous for the –265C allele, suggesting that the reduced plasma APOA2 concentrations associated with the C allele enhances the ability to remove large VLDL from circulation during alimentary lipemia. In our study, we measured large VLDL particles and obtained results in agreement with these observations. In addition, we measured HDL particle size in the postprandial period and observed a significant increase in the small HDL subfraction associated with the –265C allele.

In conclusion, in this population study the –265T>C polymorphism has no significant role in determining fasting plasma lipids and particle size. Postprandial state increases the effects of this polymorphism, and significant differences were observed in HDL subfraction distribution as well as borderline effects on large VLDL particles. However, the most consistent effects of this polymorphism were observed on anthropometric variables and food intake. Homozygous individuals for the –265C allele had higher obesity risk than carriers of the T allele. CC individuals also had statistically higher total energy and fat intake. As these effects were consistently found in both men and women, we suggest a new role for APOA2 in regulating food intake. More population studies are needed to replicate these findings.


   Acknowledgments
 
Grant/funding support: This work was supported by National Heart, Lung, and Blood Institute Grant U 01 HL72524, Genetic and Environmental Determinants of Triglycerides Grant HL-54776, by contracts 53-K06-5-10 and 58-1950-9-001 from the US Department of Agriculture Research Service, the Ministerio de Educación (PR2006-0258), and CIBER CB06/03/0035 from the Instituto de Salud Carlos III, Spain.

Financial disclosures: None declared.


   Footnotes
 
1 Nonstandard abbreviations: APOA2, apolipoprotein A-II; CVD, cardiovascular disease; GOLDN, Genetics of Lipid Lowering Drugs and Diet Network; BMI, body mass index; DHQ, diet history questionnaire; PUFA, polyunsaturated fat; SATFAT, saturated fat; IDL, intermediate-density lipoprotein; OR, odds ratio; MUFA, monounsaturated fat.

2 Human genes: APOA2, apolipoprotein A-II; HTR2A, 5-hydroxytryptamine (serotonin) receptor 2A.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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