The Combination of Genetic Variations in the PRDX3 Gene and Dietary Fat Intake Contribute to Obesity Risk
Oxidative stress is caused by an imbalance between the production of reactive oxygen species (ROS) and the antioxidant capacity of the cell. This imbalance and an excess of ROS induce tissue/cellular damage, which are implicated in chronic inflammation disorders such as obesity, insulin resistance, and metabolic syndromes. Peroxiredoxins (Prxs) are the most abundant and ancient cellular antioxidant proteins that help to control intracellular peroxide levels and ROS-dependent signaling. Of the six mammalian isoforms, Prx III is specifically localized in mitochondria. In this study, we detected novel associations between genetic variations of the PRDX3 gene and BMI and obesity risk in the general Japanese population. In addition, these associations were observed only in the subjects with high dietary fat intake, but not in the subjects with low dietary fat intake. These findings indicate that the interaction between genetic variations in the PRDX3 gene and dietary fat intake is important for modulation of BMI and obesity risk.
In all aerobic organisms, normal cellular processes involving oxygen result in the production of reactive oxygen species (ROS) such as superoxide (O2−), hydrogen peroxide (H2O2), and the hydroxyl radical (OH−). ROS plays an important role in immune protection due to the bactericidal infection and triggering of activation of signaling molecules that regulate various biological process (1,2). On the other hand, ROS cause damage to a wide variety of macromolecules including proteins, lipids, and DNA. Therefore, in aerobic organisms, there is a tightly regulated balance between ROS production and antioxidant systems.
Oxidative stress is caused by an imbalance between the production of ROS and the antioxidant capacity of the cell. This imbalance and an excess of ROS induce the tissue/cellular damage that is implicated in many age-related pathologies such as cancer, cardiovascular and degenerative diseases (1,3). In addition, oxidative stress has been suggested as a potential inducer of inflammatory status (4,5). Several studies have proposed that obesity, insulin resistance, and metabolic syndrome might be chronic inflammatory disorders (6,7,8). Therefore, increased oxidative stress may be one of the risk factors for obesity, insulin resistance, and metabolic syndrome.
Peroxiredoxins (Prxs) are a family of multifunctional antioxidant thioredoxin-dependent peroxidases that regulate intracellular levels of H2O2, peroxynitrite, and organic hydroperoxides (9,10,11). In addition to this antioxidant function, Prxs also play an important role in ROS-dependent signaling, including cell proliferation, differentiation, immune response, and apoptosis (2,10,11,12,13). The Prxs have been identified in almost all aerobic organisms ranging from bacteria to mammals. The broad distribution of Prxs and their high levels of expression suggest that they are both ancient and important antioxidant enzymes (11,14).
Six mammalian isoforms of Prxs have been identified, and each has a specific role in cellular redox regulation (9). Of the six mammalian isoforms, Prx III is abundantly and specifically localized in mitochondria (9,13). The mitochondria are the major intracellular source of ROS, accounting for up to 90% of the total ROS production (15). The specific localization of Prx III to mitochondria suggests that it might provide a primary line of defense against H2O2 produced by the mitochondrial respiratory chain.
Epidemiological and experimental studies have suggested that high-fat diets significantly increase ROS generation (4,16,17). In this study, we investigated the effect of genotypes/haplotypes of the PRDX3 gene on metabolic traits such as levels of fasting plasma glucose, lipid, blood pressure, and BMI, and analyzed the interaction between the genetic variations of the PRDX3 gene and dietary fat intake for modulation of BMI and obesity/overweight risk.
Methods and Procedures
The study subjects were recruited from the participants in routine medical checkups of a medical center near University of Shizuoka. The 71.3% of participants in this medical checkups were male, and some clinical characteristics were different between male and female (data not shown). Therefore, we selected 1,231 unrelated, apparently healthy Japanese men (mean age ± s.d.: 53.3 ± 7.7, range 31–76 years) for this study subjects. Informed consent was obtained from each subject for participation in this study, and the study was approved by the Ethics Committee of University of Shizuoka, Japan. After overnight fasting, blood was collected from each subject. Diabetes mellitus and hypertension were diagnosed by a physician according to the standard World Health Organization criteria. Obesity/overweight was defined as BMI ≥ 25. The clinical characteristics of the subjects are shown in Table 1.
Table 1. Characteristics of the study subjects
Dietary energy, fat intake assessment
The total energy, fat, carbohydrate, protein, and alcohol intake were estimated by using a brief-type self-administered diet history questionnaire (BDHQ) (18,19). The BDHQ was developed based on the self-administered diet history questionnaire (DHQ), which had been validated using three different standard methods for dietary assessment (19). The BDHQ and DHQ were designed to assess dietary habits for the previous month with regard to total energy and 38 nutrients intake. Intake of fat, carbohydrate, or protein was expressed as percentages of the total nonalcohol energy intake. Dietary data were available for 1,142 subjects (92.8%) in this study. The amount of energy, fat, carbohydrate, protein, and alchohol intakes were not different between the normal weight group and obesity/overweight group (Table 1).
Genomic DNA was isolated from peripheral blood leukocytes by the phenol extraction method. In the PRDX3 gene, functional and nonsynonymous variants with relatively high heterozygosity were not reported, but ten common single-nucleotide polymorphisms (SNPs) (MAF > 0.10 in Japan or Asian population) were reported on the public NCBI dbSNP database (http:www.ncbi.nlm.nih.govprojectsSNP) or HapMap database (http:hapmap.ncbi.nlm.nih.gov). We have selected five SNPs (rs1553850 in promoter region, rs3740562 in intron 1, rs2271362 in intron 5, rs7768 and rs3377 in 3′UTR) from them and determined the genotypes by PCR-restriction fragment length polymorphisms.
The relationships between genotypes of each SNPs of the PRDX3 gene and plasma glucose, lipid, blood pressure levels were analyzed by multiple linear regression analyses incorporating age, BMI, alcohol intake, and smoking status as covariates. The regression analyses assessing the relationships between the genotypes/haplotypes of PRDX3 and BMI or obesity/overweight phenotype were adjusted for age, alcohol intake, and smoking status. Statistical analyses were performed by using the JMP software package (SAS Institute, Cary, NC). All significant associations were corrected for multiple testing by applying a Bonferroni correction. The coefficients of linkage disequilibrium value (|D'| and r2) among five SNPs were calculated by using the SNPAlyze program (Dynacom, Tokyo, Japan). The haplotypes and their frequencies were estimated by the maximum-likelihood method with an expectation-maximization-based algorithm using the SNPAlyze program.
We examined the relationships between the genotypes of five SNPs (rs 1553850, rs3740562, rs2271362, rs7768, and rs3377) in the PRDX3 gene and metabolic phenotypes such as levels of fasting plasma glucose, triglycerides, high-density lipoprotein cholesterol, blood pressure, and BMI (Table 2). Significant associations were observed between BMI and four SNPs in multiple linear regression analysis with age, alcohol intake, and smoking as covariates. These associations were still significant after Bonferroni correction. The association between BMI and genotypes of rs1553850, and between other metabolic phenotypes and these five SNPs were not significant after Bonferroni correction.
Table 2. The relationships between genotypes/haplotypes of PRDX3 and metabolic phenotypes
Strong linkage disequilibriums were observed among these five SNPs (|D'| > 0.86, r2 > 0.38) (Table 3). We estimated haplotype frequencies consisting of these five SNPs, the two frequent haplotypes (haplotype 1: A-A-T-G-A) and (haplotype 2: T-G-C-C-C) account for 69.5% of all chromosomes in the subjects. Haplotype 2 was associated with increased BMI, and haplotype 1 was associated with decreased BMI.
Table 3. The pairwise linkage disequilibrium (LD) values of |D'| (upper) and r2 (lower)
Next, to examine the interaction between the genotypes/haplotypes at PRDX3 and dietary fat intake for modulating BMI, we classified the subjects into two groups according to the population median for dietary total fat intake (25.1% energy). The significant associations between the genotypes/haplotypes of PRDX3 and BMI were observed only in the group with high dietary fat intake, but not observed in the group with low dietary fat intake (Table 4). Although the association between genotypes in rs2271362 and BMI were not significant after Bonferroni correction in both groups.
Table 4. Interactions between genotypes/haplotypes of PRDX3 and dietary fat intake on BMI
We then compared the distributions of genotypes/haplotypes of PRDX3 between obesity/overweight group and normal weight group. Of all subjects, the frequencies of homozygotes for each allele associated with increased BMI or haplotype 2 were significantly higher in the obesity/overweight group than that in the normal weight group (Table 5). These associations between obesity/overweight and the genotypes/haplotypes of PRDX3 were observed only in group with high dietary fat intake, but not in group with low dietary fat intake. These findings indicate that the combination of genetic variations in the PRDX3 gene and dietary fat intake is important for modulation of BMI and obesity risk.
Table 5. The distributions of genotypes/haplotypes of PRDX3 in the obesity/overweight and normal weight groups
Obesity is a major clinical problem worldwide and one of the initial signs is the development of metabolic syndrome. Oxidative stress has been suggested as a potential inducer of inflammatory status, and there is an idea that both obesity and metabolic syndrome are states of chronic oxidative stress and inflammation (4,6).
It seems that a high-fat diet is an important risk factor of obesity and significantly increases ROS generation (4,16,17). However, the amount of fat intake of our subjects was not different between normal weight group and obesity/overweight group (Table 1). And no significant correlation between BMI and dietary fat intake were observed (data not shown). The responses to nutrient intake are complex and thought to vary considerably among individuals, and genetic differences may contribute to variations in the responses to nutrient intake.
Prxs are the most abundant cellular antioxidant proteins that help to control intracellular peroxide levels (9,10). The level of such antioxidants is undoubtedly important in maintaining homeostatic conditions and protecting cells/tissues against the damaging effects of oxidative stress (1,20).
In this study, we detected a novel interaction between variations at the PRDX3 gene and dietary fat intake in modulating BMI and obesity risk in the general Japanese population. The possibility exists the activity of such Prx III variants are decreased. Under an appropriate redox conditions, these variants may effectively scavenge H2O2; however, when excess H2O2 is produced as a consequence of increased dietary fat intake, they may not be able to neutralize the excess H2O2 adequately and maintain safe intracellular ROS levels.
However, at present, we have no direct evidence that the variants of the PRDX3 gene detected in this study cause alterations in the activity and/or function of Prx III, and we have no data for the intracellular ROS levels and/or oxidative stress status for our subjects. Further in vivo and in vitro studies are needed to assess the functional consequences of these Prx III variants and their role in the oxidative stress regulatory systems. Furthermore, antioxidant capacities of individuals have changed depending on age and/or dietary habit. This study is cross-sectional, almost subjects were middle and elderly men (90.0% of subjects were over 45 years old) and dietary data of each subject was restricted to dietary habits for the previous month. We have necessary to ascertain these associations between genetic variations of PRDX3 gene and BMI and obesity risk in other various populations containing female, young people, children, or another ethnic group with different dietary habit.
Further studies containing prospective cohort studies would be needed to know interactions between genetic and environmental factors such as dietary nutrient intake affecting oxidative stress-related disease containing obesity, insulin resistance, and metabolic syndrome.
We are grateful to the subjects for their participation in this study. This study was supported by Grant-in-Aid for Scientific Research (C) (19500602) from Japan Society for the Promotion of Science (JSPS) and the Global COE program from the Ministry of Education, Culture, Sport, Science and Technology of Japan (MEXT).
The authors declared no conflict of interest