Association of Dietary Total Antioxidant Capacity and MC4R Polymorphisms in Metabolically Healthy and Unhealthy Overweight/Obese Women

Background: 3-15% of people with obesity display a metabolically healthy phenotype. An inammatory diet impairs metabolic signaling pathways and eliciting metabolic syndrome. The main purpose of this study was to investigate how the Dietary Total Antioxidant Capacity (DTAC) and the MC4R variants affect the metabolic health status in overweight and obese Iranian women. Methods and results: This cross-sectional study was conducted on 237 overweight-obese Tehrani women with mean age of 36 years.The DTAC was calculated using the following indices: total reactive antioxidant potential (TRAP), Trolox equivalent antioxidant capacity (TEAC), and the ferric-reducing ability of plasma (FRAP). The Metabolic health was evaluated using the Karelis criteria. The MC4R genotypes were determined by the restriction fragment length polymorphism (PCR-RFLP) method. Approximately 43% of participants were identied as Metabolically Unhealthy Obesity (MUO), 6% Metabolically Healthy Obesity (MHO) including 42.5% of the total had T/T genotype ,23.8% had the C/T genotype, and 33.5% had the C/C genotype (P=0.05). In the C/C genotype people 75% were unhealthy whereas it was lower in T/T and T/C genotype people. Further, The C/C genotype with higher DTAC quartile had higher Karlis score than other DTAC quartile. A liner model test supported that the probability of MHO was signicantly higher in subjects with the T/C genotype (β=-0.001, 95% CI= -0.001-4.796; P ≤ 0.1). Conclusions: Our results indicated that the C/C genotype with higher DTAC had favorable lipid prole and were metabolically healthier. It is plausible that dietary modication targeting antioxidant intake may attenuate metabolic impairments associated with genetic predisposition.


Introduction
The global prevalence of obesity and its upcoming metabolic complications and chronic diseases such as insulin resistance, dyslipidemia, hypertension, in ammation, cardiovascular diseases (CVD), type 2 diabetes mellitus (DM2) continue to rise [1][2][3]. Interestingly, 3-15% of people with obesity do not present diagnosed metabolic complications [4][5][6]. Although, people with obesity considered metabolically healthy have a higher risk of CVD compared to normal weight individuals without metabolic alterations, the risk appears less than metabolically unhealthy obese people [7][8][9]. It is suggested that a nutrigenomic factor or mechanism affording some protection against metabolic syndrome [10].
Rare mutations in the melanocortin-4 receptor (MC4R), the second SNPs for obesity, are relared with lower energy expenditure and more likely to experience hyperphagia. According to estimates, polymorphisms in this gene are responsible for 2.4-9% of signi cant obesity and has a tight interaction with environmental factors [11][12][13] There are also some variants in the MC4R gene, which may have preventive effects on obesity [7,14]. Several variants in the MC4R gene have been identi ed which rs17782313 polymorphism (T/C) is one of those frequently described [15][16][17][18][19][20][21]. A higher BMI and energy intake in people with the common SNP rs17782313 near MC4R gene have also been observed [22][23][24]. Further, an association of rs17782313 polymorphism (T/C) with increased risk of obesity among subgroups of Europeans and East Asians, adults and children has been well reported [8,22,25].
The interaction of the MC4R polymorphisms and metabolism may be moderated by the adaptive response to oxidative stress. Oxidative stress represents an integral component of metabolic complications. Dietary total antioxidant capacity (DTAC) is an reliable indicator of diet quality and is typically used to estimate the cumulative effect of antioxidants in the diet overall [26]. It can also provide insight into synergistic effects that may exist between diverse antioxidants in a mixed diet [14,15]. The overproduction of reactive oxygen species may impair insulin signaling pathways and lead to endothelial damage. This causes insulin resistance and promotes acceleration of the atherogenic processes underlying metabolic syndrome, obesity, type 2 diabetes and CVD [18,19]. The relationship between DTAC and MC4R polymorphism has been investigated in limited studies mostly with healthy people. To our knowledge, there have been few human based studies in Middle East countries with different genotype structure and diet pattern, evaluating this relationship regarding metabolic health status. As high incidence of metabolic disorders continue to burden the region, the aim of this cross-sectional study was to assess the interaction between DTAC and MC4R among overweight and obese Iranian women with regard to their metabolic health status.

Study population
In this cross-sectional study, 218 out of 288 healthy women with overweight and obesity who were referred to community health centers of Tehran university of medical science were randomly selected based on the following inclusion criteria: 1) body mass index (BMI) 25-40 kg.m2 -2) aged 18-50 years old. The primary exclusion criteria included the following:1) menopause 2) pregnancy 3) cardiovascular diseases 4) diabetes 5) Cancer 6) kidney disease 7) thyroid disease 8) acute or chronic diseases 9) use of dietary supplements for weight loss 10) follow up diet during the past year 11) use of lipid lowering drugs 12) use of blood glucose lowering drugs. More over, participants who did not complete more than 35 items of the food frequency questionnaire and those who reported total daily energy intakes ≤800 or ≥4500 kcal/d were excluded. This study carried out in accordance with the recommendations of the ethics committee of institution (Ethical number IR.TUMS.VCR.REC.1398.619 ) with written informed consent from all participants .

Anthropometric assessment
For each participant, the height, the weight, waist, and hip circumferences were measured. These measurements were made in compliance with WHO recommendations and the assessments were performed by an experience nutritionist. Participants were weighed without shoes and in minimal clothing on a solar digital scale recorded to the last 0.2 kg. The standing height was measured on a free-standing portable height meter with a precision of 0.5cm without shoes. BMI was calculated by weight (kg)/height (m) squared [10].

Dietary assessment and DTAC evaluation
Detailed dietary information was obtained through the use of the validated semi quantitative food frequency questionnaire (FFQ) [27]. The FFQ includes 147 items with a standard serving size commonly consumed by Iranians. The reported frequency for each food item was then converted to a daily intake. The nutrient content of foods were computed by the Nutritionist 4 software based on United States Department of Agriculture (USDA) food composition table modi ed for Iranian foods. DTAC was calculated using the following indices: total reactive antioxidant potential (TRAP), Trolox equivalent antioxidant capacity (TEAC), and the ferric-reducing ability of plasma (FRAP).Since no databases were available to calculate the quantity of antioxidants in Iranian foods, given the available resources, we chose databases that contained most of the foods that are consumed by the Iranian population. TRAP and TEAC values were obtained from published databases for Italian foods. For FRAP, we used a database developed by Halvorsen et al. Total antioxidant capacity values for each food item in the FFQ were matched to an equivalent food in each of the databases. If any food was not directly matched with a corresponding food in a database, a proxy estimation was used based on the mean value of a similar food or the value of a raw food as a substitute for the cooked food [19,21]. DTAC for every participant was obtained by multiplying the daily intake of each selected food item by its corresponding antioxidant value per food portion and summing the nal values. Antioxidants from supplements were not included in the calculation of DTAC reported as micromole of Trolox Equivalents per day (μmol TE/day).

Biochemical analysis
Venous blood was drawn at 8:00 AM to avoid variations due to circadian rhythm and after a fast equal to or>12 h. Samples were collected in two tubes, one containing sodium citrate and the other without anticoagulant centrifuged at 3000 rpm for 15 min at 4 °C, and aliquots of plasma and serum were prepared for testing. Glucose, total cholesterol, HDL-C, and triglycerides levels were determined by the semiautomatic chemical analyzer Ekem KontroLab. LDL-C serum concentration was calculated with Fried Ewald's formula. Insulin resistance was evaluated through homeostasis model assessment : HOMA-IR=insulin (mU/mL) x fasting glucose (mmol/L)/22.5[28].

De nition of metabolically healthy and unhealthy phenotypes
There are no general de nition of metabolically healthy obesity (MHO).Throughout this paper, the MHO was described using adapted Karelis criteria. In the case of the Karelis criteria : total cholesterol ≤200 mg/dL, triglycerides≤150 mg/dL(≤1.7mmol.L), high-density lipoprotein cholesterol (HDL_C) ≥50 mg/dL and no treatment, low-density lipoprotein cholesterol (LDL-C) ≤100 mg/dL and no treatment, and HOMA-IR ≤2.8 ; that ≥4 positive score criteria de ned as Metabolic Healthy. Thus, participants were classi ed

The Genotype determination
The chromosome 9p21 rs17782313 SNP (genotypes C &T) was genotyped by the polymerase chain reaction-restriction fragment length polymorphism (PCRRFLP) technique. The Genomic DNA was extracted from 200 mL of whole blood using the Mini Columns Type G kit manual (GeneAll, South Korea).
The extracted DNA was used to assess two reported SNPs near MC4R gene, rs17782313 and rs17700633 SNPs. Polymerase chain reaction (PCR) was performed on the rs17782313 and rs17700633 SNPs using the following primers: forward primer 5AAGTTCTACCTACCATGTTCTTGG-3 and reverse primer 5-TTCCCCCTGAAGCTTTTCTTGTCATTTTGAT-3. PCR was carried out on a total volume of 20 μL, containing 1 μl extracted DNA, 0.5 μl primers F, 0.5 μl primers R, 10 μl Permix (Amplicon, Germany), and 8 μl Distilled water, with the following conditions in a DNA thermocycler: 1-primary denaturation at 95°C for 2 min; 2-Thirty-ve cycles of denaturation at 95°C for 30 seconds, annealing at 58°C for 30 seconds, extension at 72°C for 30 seconds; 3-nal extension at 72°C for 5 min; 4-nal step at 4°C. The ampli cation protocol consisted of a primary denaturation step at 94 ° C for 5 min, followed by 35 cycles of denaturation at 60 ° C for 1 min, annealing at 94 ° C for 45 s, and extension at 72 ° C for 1 min, and nal extension at 72 ° C for 10 min. The digestion products were stained with ethidium bromide on a 2% agarose gel and imaged. 10% of the samples were directly sequenced for con rmation the PCR-RFLP results. The sequencing process performed using the ABI PRISM 3730 automated sequencer (Applied Biosystems, Foster City, CA, USA) [29]. Ampli ed DNA (7 μl) was digested with 0.5 μl of BCII restriction enzyme (Fermentase, Germany) at 56 °C overnight. All products were visualized by agarose gel electrophoresis. Then, fragments containing three genotypes were distinguished: CC, CT, and TT.

Statistical analyses
Statistical analyses were performed using SPSS 20 (SPSS Inc., Chicago, IL, USA). Normal data distribution was determined using the Kolmogorov-Smirnov test. The ANOVA test and general linear model were used to assess differences in biochemical measurements and characteristics between groups. A general linear model adjusted for MC4R, DTACT as confounder effects was used. Coding of the SNPs was performed using an additive model. The study population characteristics are reported as mean ± standard deviation (SD). The Statistical signi cance was de ned as p ≤ 0.05 for all analyses.

Results
The mean and standard deviation (SD) of age of the participants were 36.23 ± 8.2 years, range 18-50 years. The characteristics of participants are summarized in Table 1. Participants were 43% MUOB, 6.3% MHOB, 29.5% MUOW and 20.6% MHOW, according to Karelis criteria. In the C/C genotype people 75% were unhealthy where as it declined to 67.1% and 67.4% in T/T and T/C genotype people respectively. There was a signi cant difference between groups in metabolic health status. All Subjects in the metabolically unhealthy groups had higher BMI, TG, LDL-C, HOMA-Index, insulin and lower HDL-C than those in the metabolically healthy groups signi cantly(P ≤ 0.05) ( Table 2).  Furthermore, the T/T genotype was identi ed in 42.5%, 23.8% the C/T genotype, and 33.5% the C/C genotype. The C/C genotype with higher DTAC quartile had higher Karlis score than other DTAC quartile.
The T/C genotype had higher TG, LDL-C and HOMA-INDEX but not statistically different from other genotypes. Although, meaningful correlation was observed between this genotype and insulin (P ≤ 0.05 ) and HOMA-INDEX (P ≤ 0.05) ( Table 4). To assess the interaction between particular polymorphisms and the MUO and MHO, a liner model test was applied ( Table 5). The test revealed that the probability of being MHO was lower in subjects with the C/C genotype than two other genotypes. The test value was statistically signi cant (β = 0, 95% CI: 0.000-0.001; P ≤ 0.05 ). Interestingly, it was observed that C/C genotype with higher DTAC were metabolically healthier. In contrast, T/C genotype with lower DTAC values were metabolically healthier (Fig. 1).No signi cant correlation detected between the T/T genotype and DTAC level.

Discussion
This cross-sectional study investigated how the DTAC and MC4R gene variants were related to being MHO/MUO in overweight and obese women. Interactions between genetic and environmental factors play an important part in the metabolic health status and obesity. Our results showed that a signi cant correlation was between the DTAC and the MC4R SNPs and the MHO. MUOW-OB diagnosed on the basis of the Karelis criteria was observed in 67.4% of these overweight-obese women. It was slightly more common in the subgroup with the C/C genotype (75%).The liner model test showed that the C allele raises the risk of metabolically unhealthy signi cantly. For the rst time, this study provided evidence for a signi cant relation between the MC4R gene and the DTAC level. The C/C genotype subjects with higher DTAC had favorable lipid pro le and were metabolically healthier. Conversely, T/C genotype subjects with lower DTAC values were metabolically healthier. These results supported the interaction was found between the T/C genotype and the metabolism in some previous studies [5].
MHO/OW incidence in this study was similar previous studies [4,8,30,31]. The recent Hosseinpanah cohort study showed that 26.9% of male and 39.4% of female Iranian people were MHO [31].
Pervious studies have demonstrated that metabolically healthy obese people (MHO) have a lower risk of CVD compared to the MUO population [7,8]. Although the causes of this metabolic alterations are still not clearly understood, evidence suggests that interactions between the genetic and life style factors including diet can in uence such phenotypes in various population.
The MC4R SNPs prevalence in the Iranian ow/ob women was similar to the results of Mollahosseini et al study with the prevalence of the C/C allele 52.85% [3]. Furthermore, we observed a close connection between (SNP) of this gene and increased BMI. In line with our ndings, previous studies showed that the C/C allele carriers , BMI was higher by 0.2 kg.m 2 on average [5,22,23]. German authors reported Comparable results, who claimed that the presence of the C/C allele entailed a considerably higher BMI.
Even though we were unable to demonstrate a signi cant correlation between the DTAC values and TG, LDL, HOMA-INDEX values, earlier researches revealed an inverse relationship between these factors. This apparent lack of correlation could be attributed to hard to control entity of the DTAC and method of study.
Mousavizadeh , s study suggested that the healthy diet interacts with MC4RSNP (rs17782313) which decrease the risk of general obesity in C-allele carriers [24].
In another similar study, high DTAC were signi cantly associated with a reduced odds ratio for the prevalence of chronic diseases and metabolic syndrome components [32]. Besides, the ndings of longitudinal Tehran Lipid and Glucose Study showed that higher DTAC were positively associated with a lower occurrence of metabolic complications, hence being healthy [33]. The European Prospective Investigation into Cancer and Nutrition study pointed out the DTAC might play an essential role in reducing the risk of diabetes in women [34]. MC4R SNPs changes metabolic pro le through uncertain mechanisms. Their phenotypic expression is affected by environmental factors, such as quantitative and qualitative composition of diet [13].
In line with previous studies, a statically signi cant association between MC4R genotype and Insulin and HOMA-INDEX was observed [1,4,8] .This to some extent con rms that insulin resistance may be the mechanism through which the MC4R polymorphisms affect metabolism leading to be metabolically healthy or unhealthy obese.  The association between Karelis scores and DTAC level tertile and the chromosome 9p21 rs1333048 SNP Polymorphisms L, low level of DTAC; M, median level of DTAC; H, high level of DTAC, P-value≤0.05.