Enzyme Activity and Genetic Polymorphisms of Paraoxonase 1 in Patients With Type 2 Diabetes Mellitus: A Case-Control Study

Enzyme Activity and Genetic Polymorphisms of Paraoxonase 1 in Patients With Type 2 Diabetes Mellitus: A Case-Control Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enzyme Activity and Genetic Polymorphisms of Paraoxonase 1 in Patients With Type 2 Diabetes Mellitus: A Case-Control Study Emine Kocyigit, Makbule Gezmen Karadağ, Mujde Akturk, Ahmet Varis This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5920397/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Paraoxonase-1 (PON1) plays a role in the prevention of lipid peroxidation and has been linked to type 2 diabetes mellitus, which is characterised by elevated oxidative stress. In this case-control study, 102 patients with T2DM and 102 healthy controls aged 30 to 60 were included. Anthropometric and body composition measurements of individuals were taken. Total antioxidant status (TAS), total oxidant status (TOS), PON1 activity, and metabolic parameters were analyzed in serum samples of all participants. These samples were genotyped by TaqMan. Dietary antioxidant capacity (DTAC) of individuals was assessed using 3-day food records. No statistically significant difference was observed between groups in the alleles and the genotype frequencies of SNPs. PON1 activity was significantly higher in controls compared to patients with T2DM. Furthermore, RR and LL genotypes were significantly associated with higher PON1 activity. In T2DM patients, HbA1c, fasting blood sugar (FBG), and LDL-cholesterol (LDL-c) were more elevated in all genotypes of the Q192R gene; triglyceride (TG) was higher in QQ and QR genotypes of the gene; TAS was higher in the RR genotype of the gene; and DTAC was lower in the QQ genotype of the gene compared to their respective controls. In controls, LDL-c and TG were lower in all genotypes of the L55M gene; HbA1c and FBG were lower in the LL and LM genotypes of the gene; total body fat was more down in MM genotype, but total body water, fat-free mass, and MET score were higher in MM genotype of the gene compared to their respective controls. Multiple linear regression analyses showed that several factors associated with the activity of PON1 were the PON1 genotypes, HDL-c, TAS, and TOS. Our study supports that the PON1 polymorphisms are associated with PON1 activity, glucose, and lipid metabolism parameters in patients with T2DM. Type 2 diabetes mellitus PON1 gene L55M Q192R PON1 activity Figures Figure 1 Introduction Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by increased insulin resistance caused by severe hyperglycemia, impaired insulin secretion, and abnormal β cell function. The increasing incidence of T2DM is a worldwide health problem [ 1 , 2 ]. The International Diabetes Federation stated in the latest report that there were 378 million patients who had diabetes. It is estimated that this number will increase to 643 million by the year 2030; 90 to 95 percent of diabetes (DM) diagnoses are T2DM [ 3 ]. It is a complex chronic disease impacted by genetic disposition, epigenetics, diet, physical inactivity, and lifestyle [ 4 , 5 ]. The human PON1 (EC 3.1.8.1) is a 43 kDa glycoprotein containing 354 amino acids, a calcium-dependent antioxidant enzyme that is mainly synthesized by the liver and secreted into the bloodstream, where it is strongly linked to high-density lipoprotein (HDL) [ 6 ]. PON1 is a member of the paraoxonase enzyme family, including PON2 and PON3. In humans, three genes encode these enzymes on the long arm of chromosome 7 (7q21.3-q22.1) [ 7 – 9 ]. The three members of this family have antioxidant properties. They are essential for preventing lipid oxidation in low-density lipoprotein (LDL) and cell membranes and changing the structure of HDL. PON1 is the most studied member of this family, which is regarded as a marker of oxidative stress [ 9 , 10 ]. PON1 is a gene that has more than 400 different variations in its single-nucleotide sequence, making it a highly polymorphic gene [ 11 – 13 ]. These polymorphisms influence the phenotype of the enzyme and about 60% of the variations in the activity and concentration of the PON1 enzyme. Therefore, inserting the most efficient polymorphism in establishing such a difference may lead us to candidates for T2DM susceptibility [ 14 , 15 ]. Variations in PON1 activity have been related to two single-nucleotide polymorphisms (SNPs) in the PON1 gene, especially Q192R (rs662) and L55M (rs854560) [ 16 – 18 ]. Several studies have found an association between PON1 polymorphisms, enzyme activity, and T2DM [ 19 – 21 ]. A recent meta-analysis showed that total PON1 activity was 1.25-fold higher in healthy controls than in subjects with T2DM. Also, polymorphisms in the PON1 coding region, particularly the RR and LL genotypes, affected serum PON1 activity [ 14 ]. Another meta-analysis found that the Q192R and L55M polymorphisms play significant roles in the risk of T2DM, with the European and Asian populations displaying substantially different effects of these roles. Moreover, it has been determined that racial/ethnic characteristics may influence the relationship between these functional variants and accuracy [ 19 ]. The human PON1 activity varies based on several factors, including age, environmental pollutants, nutrition and lifestyle, smoking, pregnancy, physical activity, and chronic diseases such as T2DM, polycystic ovary syndrome, cardiovascular disease, and atherosclerosis. In addition, genetic polymorphisms can affect the concentration and activity of an enzyme by altering its gene and protein expression [ 22 – 24 ]. The current study evaluated the association and susceptibility of polymorphic variants in PON1 (Q192R and L55M) with T2DM. The relationship between PON1 gene polymorphism, PON1 activity, biochemical parameters, physical activity level, and dietary antioxidant intake in T2DM patients and healthy controls was also investigated. Methods Study Design and Sample The current study involved 204 volunteers (92 males and 112 females) aged 30 to 60, comprising 102 healthy subjects and 102 persons diagnosed with T2DM. The selection of healthy controls was based on similarities in gender, age, and body mass index (BMI) with T2DM patients. The diagnostic criteria for T2DM as defined by the American Diabetes Association (ADA) include the following indicators: a hemoglobin A1c (HbA1c) level of 6.5% or higher, a fasting blood sugar (FBS) level of 126 mg/dL (7 mmol/L) or higher, a 2-hour postprandial glucose level of 200 mg/dL (11.1 mmol/L) or higher, or a random plasma glucose level of 200 mg/dL or higher [ 25 ]. Receiving insulin therapy, DM duration > 5 years, having microvascular and macrovascular complications of T2DM, chronic diseases, such as coronary heart disease, osteomalacia, chronic diarrhea, malabsorption, lung disease, and cancer were exclusion criteria for patients with T2DM. Moreover, exclusion criteria for both T2DM patients and controls included pregnancy and breastfeeding, consumption of alcohol, smoking, and an unwillingness to participate or continue cooperating. The [name removed for blind peer review] University Clinical Research Ethics Committee obtained ethical approval (278 numbered and dated 12/23/2019) for this study. The present study was conducted by the criteria specified in the Helsinki Declaration. Anthropometric Measurements Standard techniques were used to measure anthropometric parameters directly. Weight (kg), height (cm), neck circumference (cm), waist circumference (cm), and hip circumference (cm) were measured, and the waist-to-hip and waist-to-height ratios were calculated. The body weights of the participants were measured using the Tanita BC 545 N Inner Scan (Balance™) when they were fasting and wearing light clothing. The Tanita BC 545 N Inner Scan™ with bioelectrical impedance analysis was performed to determine body composition (body fat, body water, and fat-free mass). The height (in cm) was measured with the feet together and the head in the Frankfort plane using a stadiometer with an accuracy of 0.1 cm. The BMI was calculated using the “body weight / height2” (kg/m2). According to the BMI classification of the World Health Organization (WHO), The BMI values of the participants were grouped into four categories: underweight (BMI < 18.5 kg/m 2 ), normal weight (18.5–24.9 kg/m 2 ), overweight (25.0 ≤ BMI kg/m2), and obese (30.0 ≤ BMI kg/m2) [ 26 ]. Laboratory Measurements Blood samples were taken in the morning after an eight- to ten-hour overnight fast following dinner. Blood samples were taken using a conventional venipuncture technique. The serum was separated after centrifugation (Mikro 200 R, Hettich, Tuttlingen, Germany) performed at 3000 rpm for 10 minutes, and then the supernatant was placed in Eppendorf tubes. The aliquots obtained from the sample were promptly frozen and kept at a temperature of -80°C. Biochemical analyses were conducted using the techniques described by commercially available guidelines. The fasting blood glucose (FBG), total cholesterol (TC), triglyceride (TG), HDL-cholesterol (HDL-c), and LDL-cholesterol (LDL-c) analyses were conducted using the automatic Mindray BS-300 Chemistry Analyzer (Mindray, Shenzhen, China). The glycated hemoglobin (HbA1c) was determined using an automated high-performance liquid chromatography analyzer following standard protocols. The enzymatic activity of PON1 was determined using the Sandwich Enzyme-Linked Immunosorbent Assay (ELISA) method using the Human PON1 ELISA Kit (Cusabio®, China). TAS and TOS levels were measured by a colorimetric method using commercially available assay kits (Rel Assay, Türkiye) [ 27 , 28 ]. Oxidative stress index (OSI) was calculated using the following formula: OSI (arbitrary unit) = TOS (µmol H 2 O 2 equivalent/L) / TAS (mmol Trolox equivalent /L) x 100 [ 29 ]. DNA Extraction and Genotyping For genetic analysis, 4 mL of blood was collected from each subject and stored at -80°C in tubes containing ethylenediaminetetraacetic acid (EDTA) until analysis. For DNA isolation from blood samples taken from individuals in EDTA tubes, QuickGene DNA Extraction Whole Blood Kit S (Kurabo®, Germany) was used. Following isolation, the DNAs were stored in 1.5 mL microcentrifuge tubes that were nuclease-free. The concentration and purity of isolated genomic DNA were measured using a Colibri Microvolume Spectrometer (Titertek-Berthold, Germany). Real-time polymerase chain reaction (PCR) SensiFAST™ Probe No-ROX Kit (Bioline, UK) with a probe based on hydrolysis was used to identify the intronic PON1 gene rs854560 and rs662 SNPs. In the genetic analysis, the PCR protocol consisted of 5 minutes of pre-denaturation at 95°C (first denaturation), 10 seconds of denaturation at 95°C (DNA chain opening), 10 seconds of annealing at 59°C (primer attachment/bonding to the opened DNA chain), and 5 seconds of primary extension at 72°C. This cycle was performed forty times in all. After completing the PCR cycle, the products were cooled and kept at 40°C for 1 minute. In the current study, SNP genotyping was conducted using real-time PCR with a hydrolysis probe (TaqMan®). Primer sequences complementary to the target DNA sequence and probe oligonucleotides containing particular fluorescent dyes were used. Probe arrays used for genotyping include a fluorescent dye (FAM/HEX) and a chemical called a quencher that absorbs the radiation of the fluorescent dye. During fragment elongation, due to the 3'-5' exonuclease activity of the Taq polymerase enzyme, the probe separates from the 5' tip, moves away from the quencher, and reradiates. As the number of amplicons rises logarithmically, fluorescence and irradiation intensity progressively increase. The probes will increase Fam and Hex fluorescence luminescence when bound to the normal and mutant alleles, respectively. If both probe irradiations occur, the presence of the two alleles was understood. In the last step, the people were divided into three groups based on the presence of LL, LM, and MM genotypes based on the polymorphisms of rs854560 of the PON1 gene and QQ, QR, and RR genotypes based on the polymorphisms of rs662 of the PON1 gene. As a consequence of genetic analysis, the Hardy-Weinberg equilibrium evaluated the frequency of alleles identified in people, and genotype frequencies were compared with their predicted frequencies by the Hardy-Weinberg equilibrium. The International Physical Activity Questionnaire-Short Form (IPAQ-SF) The IPAQ-SF is a 7-item scale that assesses the number of minutes spent in physical activity, including vigorous intensity activities (e.g., running), moderate intensity activities (e.g., brisk walking), walking, and sitting during the last week. Counts of activities were reported as metabolic equivalents (METs). Individuals' physical activity levels were determined using the IPAQ-SF, for which validity and reliability tests have been conducted in Turkey [ 30 ]. Nutritional Assessment In order to assess the dietary antioxidant intake of participants, 3-day food records (2 weekdays and 1 weekend) were completed through face-to-face interviews and telephone calls. The amount of food consumed was determined through a photographic atlas of food portion sizes for the dietary intake [ 31 ]. For the evaluation of dietary antioxidant capacity, Nutrition Information Systems (Beslenme Bilgi Sistemi-BeBiS), which is a food software program compliant with Turkish food, was utilized [ 32 ]. Statistical Analysis The statistical data analysis used the Windows-based Statistical Package for the Social Sciences (SPSS, version 26.0) statistical package program. A power calculation was conducted a priori using G*Power (version 3.1; Heinrich Heine University Düsseldorf, Germany). The total sample size was determined to be n = 200 for 90% power at a 5% error; hence, our sample size of n = 204 is acceptable for this research. Count (n), percentage (%), and arithmetic mean ± standard deviation (x ± SD) values are given for the measured variables. Kolmogorov-Smirnov/Shapiro-Wilk tests were used to evaluate the convenience of data to normal distribution. The parametric variables were analyzed using t-tests or analysis of variance (ANOVA), while the nonparametric variables were assessed using Mann-Whitney or Kruskal-Wallis tests. The statistical methods employed to evaluate the Relationship Relationship between categorical variables were the Fisher exact test and the chi-square (χ2) test. The χ2 test also analyzed the Hardy-Weinberg equilibrium of the gene variants. Linear regression analysis was conducted to assess the variables affecting the PON1 activity in individuals. A linear regression model was performed before and after adjustment for age, gender, and BMI. The odds ratio (OR) and its corresponding 95% confidence intervals (CI) were computed as part of the analysis. Results were evaluated statistically at a p < 0.05 significance level. Results Study Population In this study, 102 T2DM patients and 102 controls were compared. Demographic, clinical, and biochemical characteristics of T2DM and controls are given in Table 1 . In the control group, most of the individuals were university (47.1%) and high school (31.4%) graduates and had a regular job (%94.1). The difference between the education level and employment status of T2DM patients and controls was statistically significant (p < 0.05). Patients with T2DM had significantly higher HbA1c, FBG, LDL-c, and TG than controls (p < 0.05). Significantly higher levels of PON1 activity and DTAC were observed in controls compared to patients with T2DM (p < 0.05). Table 1 Demographic, clinical, and biochemical characteristics of T2DM and controls T2DM (n = 102) Controls (n = 102) p-value Mean ± SD Mean ± SD Age (years) 49.8 ± 6.92 48.3 ± 7.11 0,103 Education level, [n (%)] Literate 1 (1.0) - Primary school 26 (25.4) 7 (6.9) < 0.01 Elementary school 17 (16.7) 6 (5.9) High school 28 (27.5) 32 (31.3) University 29 (28.4) 48 (47.1) Postgraduate 1 (1.0) 9 (8.8) Employment status, [n (%)] Employed 55 (53.9) 96 (94.1) < 0.01 Unemployed 47 (46.1) 6 (5.9) Weight (kg) 79.3 ± 14.31 79.3 ± 16.24 0.716 Neck circumference (cm) 37.1 ± 4.01 36.7 ± 3.74 0.427 Waist circumference (cm) 89.5 ± 9.28 89.1 ± 9.62 0.518 Waist-to-hip ratio 0.9 ± 0.08 0.9 ± 0.07 0.393 Waist-to-height ratio 0.5 ± 0.06 0.5 ± 0.06 0.340 BMI (kg/m 2 ) 28.7 ± 4.48 28.1 ± 4.54 0.298 Total body fat (%) 32.3 ± 10.52 30.0 ± 8.95 0.161 Total body water (kg) 48.6 ± 7.75 50.5 ± 5.94 0.104 Fat-free mass (kg) 49.9 ± 11.72 51.2 ± 11.90 0.223 MET score (min/week) 858.8 ± 1459.96 833.6 ± 993.13 0.134 HbA1c (%) 7.3 ± 1.81 6.0 ± 0.46 < 0.01 FBG (mg/dL) 143.6 ± 55.81 103.6 ± 14.60 < 0.01 HDL-c (mg/dL) 49.9 ± 11.69 54.9 ± 44.23 0.585 LDL-c (mg/dL) 126.7 ± 36.18 92.6 ± 26.11 < 0.01 TC (mg/dL) 206.9 ± 46.82 197.5 ± 34.63 0.073 TG (mg/dL) 167.1 ± 99.90 113.4 ± 75.38 < 0.01 TAS (µmol Trolox Eq/l) 1.5 ± 0.2 1.5 ± 1.7 0.150 TOS (µmol H 2 O 2 Eq/I) 5.7 ± 3.05 4.7 ± 1.4 0.261 OSI 0.1 ± 0.12 0.03 ± 0.01 0.890 PON1 enzyme activity (U/L) 296.7 ± 183.83 354.7 ± 233.01 0.039 DTAC (mmol) 2.0 ± 2.89 4.7 ± 11.24 0.026 T2DM patients and controls was statistically significant (p<0.05). Patients with T2DM had significantly higher HbA1c, FBG, LDL-c, and TG than controls (p<0.05). Significantly higher levels of PON1 activity and DTAC were observed in controls compared to patients with T2DM (p<0.05). Data were presented as mean ± SD and n (%); comparison between groups was performed with the Mann-Whitney U test, p-value < 0.05. BMI: Body mass index, BAI: Body adiposity index, MET: metabolic equivalents, FBG: Fasting blood glucose, TAS: Total antioxidant status, TC: Total cholesterol, TOC: Total oxidant status, TG: OSI: Oxidative stress index Genotype Distribution and Allele Frequencies The genotype distribution and allele frequencies for the Q192R and L55M polymorphisms of the PON1 gene are presented in Table 2 . The frequencies of the QQ, QR, and RR genotypes of the PON1 gene Q192R polymorphism in T2DM patients and controls were 49.0%, 39.2%, and 11.8% vs. 47.0%, 41.2%, and 11.8%, respectively. Also, the frequencies of the LL, LM, and MM genotypes of the PON1 gene L55M polymorphism were 30.4%, 57.8%, and 11.8% in patients with T2DM, and 31.4%, 49.0%, and 19.6% in controls, respectively. No significant differences were found in genotype distributions and allele frequencies between patients with T2DM and the controls (p > 0.05). Table 2 Comparison of genotypes and allele frequencies of PON1gene between patients with T2DM and control Genotypes T2DM (n = 102) Controls (n = 102) OR (95% CI) χ2 p-value PON1 192 QQ 50 (49.0) 48 (47.0) Ref Ref Ref QR 40 (39.2) 42 (41.2) 1,094(0,608-1,967) 0.090 0.765 RR 12 (11.8) 12 (11.8) 1,042(0,427-2,544) 0.008 0,929 QR + RR 52 (51.0) 54 (52.9) 1,082 (0,624-1,874) 0.079 0,779 Allele Q 140 (68.6) 138 (67.6) Ref Ref Ref R 64 (31.4) 66 (32.4) 1.046 (0.690–1.587) 0,045 0,832 PON1 55 LL 31 (30.4) 32 (31.4) Ref Ref Ref LM 59 (57.8) 50 (49.0) 0.821 (0.441–1.528) 0.388 0.533 MM 12 (11.8) 20 (19.6) 1.615 (0.677–3.852) 1.174 0.279 LM + MM 71 (69.6) 70 (68.6) 0.955 (0.527–1.730) 0.023 0.880 Allele L 121 (59.3) 114 (55.8) Ref Ref Ref M 83 (40.7) 90 (44.2) 0.995 (0.527–1.730) 0.23 0.880 Comparison between group was performed with Chi-square test, p < 0.05 T2DM: Type 2 diabetes mellitus, PON1: Paraoxonase1, OR: Odds ratio, CI: Confidence interval. PON1 Enzyme Activity PON1 activity according to the PON1 Q192R and L55M genotypes in patients with T2DM and controls are shown in Fig. 1 . PON1 activity was significantly highest in the RR genotype and lowest in the QQ genotype in patients with T2DM and controls (p < 0.05). In T2DM patients and controls, PON1 activity was considerably lower in the MM genotype than in the LM and LL genotypes (p < 0.05). While controls with the MM genotype had significantly higher PON1 activity than T2DM patients with the MM genotype, controls with the QQ genotype had significantly lower PON1 activity than T2DM patients with the QQ genotype (p < 0.05). The Relationship Between Anthropometric and Biochemical Characteristics, MET score, DTAC, and PON1 Genotypes The data were stratified based on anthropometric and biochemical characteristics, MET score, and DTAC of all subjects, classified by the genotypes QQ, QR, and RR of the PON1 Q192R polymorphism (Table 3 ). In patients with T2DM, the waist-to-hip ratio, HbA1c, FBG, LDL-c, and TG levels were higher in the QR genotype of the PON1 Q192R gene than in the controls (p < 0.05). Total body fat, HbA1c, FBG, LDL-c, and TG levels were higher in T2DM patients with the QQ genotype, whereas total body water, fat-free mass, and DTAC were lower in T2DM patients compared to their respective control genotype (p < 0.05). HbA1c, FBG, LDL-c, and TOC levels were lower in controls with the RR genotype of the gene than in T2DM subjects with the RR genotype (p < 0.05). We classified the anthropometric and biochemical characteristics, MET score, and DTAC of both T2DM patients and controls based on the genotypes LL, LM, and MM of the PON1 L55M polymorphism in the same way as the Q192R polymorphism (Table 4 ). In subjects with T2DM, total body fat, LDL-c, and TG levels were higher, but total body water, fat-free mass, MET score, and TC levels were lower in the MM genotype of the gene compared to their respective control (p < 0.05). HbA1c, FBG, LDL-c, and TG levels were higher in T2DM patients with the LL genotype, while fat-free mass was lower in T2DM patients with the LL genotype compared to their control genotype (p < 0.05). In controls, HbA1c, FBG, LDL-c, TC, and TG levels were lower in the LM genotype of the PON1 L55M gene than in T2DM patients (p < 0.05). Table 3 The anthropometric measurements, MET score, some biochemical parameters, and DTAC in subjects with T2DM and controls according to PON1 Q192 polymorphism T2DM Control QQ QR RR QQ QR RR Waist to height ratio 0.53 ± 0.06 0.55 ± 0.06 0.55 ± 0.06 0.53 ± 0.05 0.54 ± 0.06 0.54 ± 0.06 Waist to hip ratio 0.90 ± 0.08 0.93 ± 0.07 a 0.88 ± 0.08 0.92 ± 0.07 0.88 ± 0.06 0.88 ± 0.08 Total body fat (%) 31.69 ± 10.26 b 31.96 ± 10.90 36.75 ± 10.12 27.31 ± 9.76 31.43 ± 7.81 36.07 ± 4.60 Total body water (kg) 49.56 ± 7.75 b 48.46 ± 7.81 45.76 ± 7.39 52.32 ± 6.65 49.51 ± 4.92 46.49 ± 2.96 Fat free mass (kg) 48.72 ± 10.72 b 51.91 ± 12.91 48.68 ± 11.65 54.90 ± 12.17 47.68 ± 9.69 55.41 ± 14.03 MET score 673.90 ± 730.52 1144.66 ± 2108.73 676.79 ± 969.17 881.36 ± 813.72 815.18 ± 1272.61 707.00 ± 402.28 HbA1c (%) 7.44 ± 2.14 b 7.17 ± 1.20 a 7.48 ± 2.04 c 6.00 ± 0.51 5.97 ± 0.37 6.12 ± 0.54 FBG (mg/dL) 143.06 ± 58.69 b 140.57 ± 42.85 a 156.42 ± 80.83 c 103.83 ± 16.79 101.67 ± 7.87 110.08 ± 21.50 HDL-c (mg/dL) 51.80 ± 12.90 48.20 ± 9.35 47.67 ± 13.10 48.81 ± 16.20 55.86 ± 27.69 76.63 ± 115.34 LDL-c (mg/dL) 127.30 ± 38.68 b 123.40 ± 32.12 a 135.25 ± 39.67 c 92.72 ± 22.27 90.84 ± 31.06 98.48 ± 22.29 TC (mg/dL) 203.92 ± 49.46 208.23 ± 40.76 215.08 ± 56.73 191.54 ± 29.75 193.81 ± 38.62 192.50 ± 40.78 TG (mg/dL) 145.48 ± 87.02 b 196.40 ± 115.87 a 160.17 ± 70.71 124.04 ± 76.11 94.65 ± 49.58 137.01 ± 125.77 TAS (mmol Trolox eqv./l) 1.49 ± 0.19 1.53 ± 0.21 1.46 ± 0.18 1.57 ± 0.37 2.14 ± 0.55 4.46 ± 2.88 TOC (µmol H2O2 eqv./I) 6.03 ± 3.62 5.75 ± 2.40 3.99 ± 2.62 c 4.65 ± 1.12 4.92 ± 1.62 3.87 ± 2.05 OSI (arbitrary unit) 0.06 ± 0.17 0.04 ± 0.02 0.03 ± 0.02 0.03 ± 0.01 0.03 ± 0.02 0.02 ± 0.02 DTAC (mmol/d) 1.79 ± 2.26 b 2.29 ± 3.84 1.58 ± 1.05 5.46 ± 11.95 3.51 ± 11.03 5.97 ± 9.26 Data were presented as mean ± SD. a, b, and c indicate statistical significance (p < 0.05) a. QR genotypes in T2DM group vs.QR genotypes in controls, b. QQ genotypes in T2DM group vs.QQ genotypes in controls, c. RR genotypes in T2DM group vs.RR genotypes in controls DTAC: Dietary total antioxidant capacity, MET: metabolic equivalents, FBG: Fasting blood glucose, TAS: Total antioxidant status, TC: Total cholesterol, TOC: Total oxidant status, TG: triglyceride, OSI: Oxidative stress index Table 4 The anthropometric measurements, MET score, some biochemical parameters, and DTAC in subjects with T2DM and controls according to PON1 L155M polymorphism T2DM Control LL LM MM LL LM MM Waist to height ratio 0.53 ± 0.06 0.55 ± 0.06 0.54 ± 0.07 0.55 ± 0.06 0.53 ± 0.06 0.52 ± 0.04 Waist to hip ratio 0.91 ± 0.09 0.92 ± 0.07 0.88 ± 0.07 0.89 ± 0.07 0.90 ± 0.07 0.90 ± 0.08 Total body fat (%) 30.64 ± 10.54 32.63 ± 10.62 35.77 ± 9.85 a 33.14 ± 9.01 29.91 ± 8.20 25.40 ± 8.99 Total body water (kg) 49.49 ± 7.53 48.62 ± 8.04 46.90 ± 7.10 a 48.58 ± 5.95 50.68 ± 5.61 53.01 ± 5.97 Fat free mass (kg) 48.41 ± 11.26 b 52.06 ± 12.25 43.71 ± 7.15 a 54.05 ± 11.78 49.82 ± 11.38 54.11 ± 12.97 MET score 763.55 ± 842.96 971.03 ± 1785.02 553.54 ± 798.64 a 483.16 ± 377.16 924.92 ± 1239.27 1166.00 ± 839.72 HbA1c (%) 7.65 ± 2.13 b 7.31 ± 1.73 c 6.65 ± 0.99 6.05 ± 0.37 5.95 ± 0.54 6.04 ± 0.37 FBG (mg/dL) 150.16 ± 63.19 b 144.78 ± 55.79 c 121.33 ± 25.12 105.78 ± 14.17 101.54 ± 16.51 105.65 ± 8.93 HDL-c (mg/dL) 48.74 ± 12.10 50.93 ± 11.47 47.83 ± 12.15 55.06 ± 71.94 53.88 ± 25.16 57.61 ± 17.70 LDL-c (mg/dL) 122.00 ± 34.00 b 132.42 ± 36.59 c 110.75 ± 35.95 a 99.41 ± 29.81 89.58 ± 24.86 89.37 ± 21.63 TC (mg/dL) 207.39 ± 47.96 212.15 ± 46.00 c 180.00 ± 41.94 a 195.00 ± 44.35 188.04 ± 32.48 200.1 ± 17.96 TG (mg/dL) 173.84 ± 102.75 b 170.98 ± 104.84 c 131.25 ± 57.2 a 134.43 ± 91.76 104.82 ± 72.71 101.56 ± 41.82 TAS (mmol Trolox eqv./L) 1.47 ± 0.18 1.51 ± 0.18 1.35 ± 0.43 3.27 ± 2.44 2.44 ± 1.70 1.46 ± 0.11 TOC (µmol H2O2 eqv./L) 5.45 ± 3.47 5.61 ± 2.44 6.59 ± 4.92 4.41 ± 1.83 4.97 ± 1.37 4.33 ± 0.96 OSI (arbitrary unit) 0.04 ± 0.02 0.04 ± 0.02 0.14 ± 0.34 0.02 ± 0.02 0.03 ± 0.01 0.03 ± 0.01 DTAC (mmol/d) 1.56 ± 0.96 2.14 ± 3.69 2.15 ± 1.38 5.34 ± 10.84 4.65 ± 12.58 3.89 ± 8.36 Data were presented as mean ± SD. a, b, and c indicate statistical significance (p < 0.05) a. MM genotypes in T2DM group vs. MM genotypes in controls, b. LL genotypes in T2DM group vs. LL genotypes in controls, c. LM genotypes in T2DM group vs. LM genotypes in controls DTAC: Dietary total antioxidant capacity, MET: metabolic equivalents, FBG: Fasting blood glucose, TAS: Total antioxidant status, TC: Total cholesterol, TOC: Total oxidant status, TG: triglyceride, OSI: Oxidative stress index The Relationship Between Factors and PON1 Activity PON1 enzyme activity in the study sample was influenced by several factors (Tablo 5). The QQ and QR genotypes of PON1 Q192R polymorphism and LL and LM genotypes of PON1 L55M polymorphism modulate PON1 enzyme activity (p < 0.05). PON1 enzyme activity was associated with HDL-c, TAS, and TOS levels (p < 0.05). Tablo 5 Relationship between factors and PON1 activity in the study sample Factor Variable β CI 95% p-value PON1 Q192R polymorphism QQ genotype -224.78 -303.20-(-147.31) < 0.01 QR genotype -96.66 -171.58-(-21.75) 0.012 PON1 L55M polymorphism LL genotype 155.31 83.08-227.55 < 0.01 LM genotype 74.73 12.87-136.58 0.018 Anthropometric characteristics Waist to hip ratio 187.54 -204.05-579.14 0.346 Waist to height ratio -317.11 -820.25-186.04 0.215 Total body fat (%) 0.57 -7.83-8.98 0.893 Total body water (kg) -2.00 -12.55-8.56 0.710 Fat free mass (kg) 2.15 -0.303-4.60 0.085 Biochemical parameters HbA1c (%) -12.10 -52.07-27.87 0.551 FBG (mg/dL) 0.84 -0.28-1.97 0.142 HDL-c (mg/dL) 2.54 0.57–4.52 0.012 LDL-c (mg/dL) -0.04 -0.89-0.81 0.928 TC -0.38 -1.07-0.31 0.284 TG -0.01 -0.41-0.39 0.962 TAS 107.72 68.24–147.20 < 0.01 TOS -16.52 -30.98-(-2.05) 0.025 OSI -1327.45 -3177.02-5831.92 0.562 Assessment of nutrition DTAC (mmol/d) 2.13 -10.74-15.00 0.745 The β and p value were obtained by linear regression analysis. p < 0.05 was considered statistically significant. DTAC: Dietary total antioxidant capacity, MET: metabolic equivalents, FBG: Fasting blood glucose, TAS: Total antioxidant status, TC: Total cholesterol, TOS: Total oxidant status, TG: triglyceride, OSI: Oxidative stress index Discussion There is still uncertainty regarding the precise relationship between Q192R and L55M polymorphisms of the PON1 gene and activity in T2DM. Given this fact, this study aimed to examine the metabolic parameters, anthropometric measurements, DTAC, and possible links between PON1 activity and the Q192R and L55M and polymorphism in PON1 in Turkish patients with T2DM and controls. The investigation of genetic polymorphic variations for the serum PON1 enzyme began following identifying its activity [ 33 ]. The PON1 192Q allele and the PON1 55M allele have been identified as potential risk alleles for several diseases, including coronary artery disease [ 18 ], T1DM [ 34 ], T2DM [ 35 ], and polycystic ovarian syndrome [ 36 ], in some populations. The findings of the research exhibit discrepancies. In the present study, no significant differences were seen in the allele or genotype frequencies of the Q192R and L55M PON1 gene polymorphisms between the Turkish patients with T2DM and controls. However, the QQ and LM genotypes were more common in patients with T2DM and controls. Flekac et al. report that Q and M alleles are more frequent in patients with T2DM compared to the control group from the Czech Republic and have been associated with the pathogenesis of T2DM. Also, the predominant genotypes observed in people diagnosed with DM were PON1 55LM and PON1 192QQ [ 37 ]. Likewise, it was determined in the Egyptian population that the common genotype among individuals with T2DM was PON1 192QQ, with the Q allele being identified as a risk allele for T2DM. The M allele and PON1 55LM genotype were shown to be dominant in T2DM patients in the same research. However, no statistically significant difference was found [ 38 ]. The common genotypes seen in patients with T2DM and controls in the Turkish population were PON1 QQ192 and PON1 LM55. Notably, no statistically significant distinction was found between these two groups [ 39 ]. Gokcen et al. revealed no significant differences in the frequencies of the QQ, QR, and RR genotypes of the PON1 192 polymorphism between patients diagnosed with T2DM mellitus and the control group [ 40 ]. Genotype and allele frequencies differ due to variables such as ethnicity, genotyping techniques, changes in DM control selection and statistical power, sample size, heterogeneity of individuals, and gene-gene and gene-environment interactions. PON1 activity is affected by various factors, including age, nutrition, lifestyle, physical activity level, anthropometric measurements and body composition, and drug use, but gene polymorphisms of PON1 are particularly important [ 22 ]. Previous research has demonstrated through in vitro and in vivo studies that the administration of PON1 to β cells exhibits a beneficial effect on β cell activity, perhaps reducing the onset of DM [ 41 , 42 ]. Thus, PON1 may be considered a significant enzyme with potential antidiabetic properties. Our results show that PON1 enzyme activity was increased significantly in controls compared to T2DM patients. PON1 enzyme activity was affected by the PON1 Q192R and L55M polymorphisms. PON1 enzyme activity was significantly increased in the QQ < QR < RR order among patients with T2DM and controls. In addition, PON1 enzyme activity was significantly increased in the order of the MM < LM < LL genotypes among all subjects, patients with T2DM, and controls. Our findings were consistent with the results of several prior studies [ 39 , 43 , 44 ]. In a systematic review and meta-analysis, serum PON1 activity was 1.25 times higher in healthy individuals than in patients with T2DM. When evaluated according to genotypes, there was a statistically significant difference between the PON1 LM55 and all genotypes of PON1 Q192R polymorphism (QQ < QR < RR) [ 14 ]. Individuals carrying the PON1 L allele show elevated levels of PON1 mRNA, resulting in higher concentrations and activities [ 45 ]. The replacement of arginine for glutamine at position 192 causes variations in PON1's catalytic activity toward synthetic substrates, which is correlated with PON1 activity. At this point, the paraoxonase level of the PON1 R allele is higher than that of the PON1 Q allele [ 46 ]. Besides polymorphisms, several variables such as nutrition, age, lifestyle, medication treatments, epigenetic factors, and gene-environment interactions also impact the modulation of PON1 activity [ 47 ]. Chronic hyperglycemia in patients with T2DM is believed to decrease enzyme activity through the process of enzymatic or nonenzymatic glycation of PON1. One of the significant results obtained in this study was that PON1 Q192R and PON1 L55M variants significantly affected glycemic control and lipid parameters in T2DM patients when we analyzed the effects of the study variants on glycemic control. Patients with T2DM showed significantly elevated HbA1c, FBG, and LDL-c levels compared with the control group across all genotypes of the PON1 Q192R polymorphism. Compared to controls, T2DM patients had higher TG levels of QQ and QR genotypes. Also, HbA1c and FBG levels were much higher in T2DM patients with the LL and LM genotypes than in controls. LDL-c, TC, and TG levels were significantly higher for all PON1 L55M polymorphism genotypes than controls with the same genotype. The study conducted on the role of PON1 polymorphisms in glucose metabolism in 14 centers across 11 European countries found that the L55M polymorphism showed an independent association with glucose metabolism. However, no such association was observed for the Q192R polymorphism [ 48 ]. The findings obtained by Sarıkaya et al. [ 49 ] showed that individuals having QQ phenotypes had a 1.85-fold and 2.16-fold increased likelihood of developing insulin resistance and impaired fasting glucose, respectively. Fridman et al. reported that patients with coronary artery disease and healthy individuals with the QQ genotype or M allele had increased serum glucose levels [ 50 ]. On the contrary, Pappa et al. [ 51 ] and Susi et al. [ 52 ] did not find any significant effect of the Q192R polymorphism on metabolic and glycemic parameters in women with GDM and in patients with T2DM. Previous research on the Relationship between PON1 polymorphisms and lipid levels has shown inconsistent results [ 53 – 55 ]. It was reported that the Q192R and L55M polymorphisms of the PON1 gene may influence insulin resistance by decreasing PON1 enzyme concentration and altering GLUT-4 expression [ 55 ]. Insulin resistance and increased lipid accumulation, notably of diacylglycerol, accompany high concentrations of hexose molecules [ 47 ]. It was also reported that a higher prevalence of QQ and MM genotypes in DM might be related to poorer glucose regulation, accelerated nonenzymatic glycation, and increased oxidative stress [ 37 ]. The study findings are likely influenced by variations in the distribution frequencies of people based on their genotypes and constraints in the selection process of participants incorporated in the study. Glycemic control and lipid profile may also be impacted by variations in pancreatic β-cell activity in patients with T2DM, time to diagnosis, hyperinsulinemia, medication therapy, body composition, physical activity level, and the existence of other polymorphisms linked to T2DM but not yet identified. A further significant finding of the study indicates that the QQ and QR genotypes of the PON Q192R polymorphism harmed the activity of the PON1 enzyme. Conversely, the LL and LM genotypes of the PON L55M polymorphism have shown positive effects. HDL-c significantly impacts PON1 enzyme activity. The antioxidant and antiatherogenic properties of HDL-C are facilitated by various interconnected enzymes, with particular emphasis on PON1 [ 56 , 57 ]. The decrease in PON1 activity is primarily caused by the glycation of HDL-PON1, which is related to elevated glucose levels and other factors like hyperinsulinemia, dyslipidemia, and oxidative stress. Glycated HDL cannot metabolize membrane lipid peroxides and sustain cholesterol efflux [ 58 , 59 ]. The organism maintains a balance between oxidant and antioxidant systems. The TAS represents the total effect of all antioxidants in plasma and bodily fluids, while the TOS represents the overall impact of all oxidants [ 60 , 61 ]. PON1, as an antioxidant protein, is crucial for maintaining the balance between oxidants and antioxidants [ 62 ]. Based on the provided information, the regression model indicates that TAS positively affects PON1 activity, while TOS has a negative impact. This outcome is considered favorable. However, no significant relationship was found between DTAC and PON1 activity. The DTAC level was significantly lower in patients with T2DM who had the QQ genotype than the control group. DTAC was calculated using 3-day food records from participants. 3-day food records may not accurately represent an individual's typical diet due to variations in daily dietary intake among individuals. Long-term food records may provide more insight into assessing the correlation between DTAC and PON1 activity. There are some limitations to this study. First, we did not evaluate the mRNA expression levels of PON1 Q192R and L55M genotypes. Second, we did not measure other oxidative stress markers and PON1 enzyme concentration. Third, only paraoxon substrates were assessed to test PON1 activity; other possible substrates were not included. Moreover, the limited sample size in the present study should be recognized as a constraint, necessitating the validation and reinforcement of the findings by studies including larger sample sizes. Conclusions T2DM is a multifaceted disease impacted by genetic, metabolic, and environmental variables. These factors interact, collectively contributing to the overall prevalence of T2DM [ 63 ]. The current study shows that PON1 activity is higher in healthy individuals compared to patients with T2DM. This difference is influenced by different genotypes of the PON1 enzyme associated with the L55M and Q192R polymorphisms. Additionally, it has been observed that the Q192R and L55M genotypes of PON1 impact glucose and lipid metabolism parameters. These observations strongly support the role of PON1 polymorphisms and their activity in contributing to the pathophysiology of T2DM. Extensive and comprehensive studies are required to clarify the exact role of PON1 polymorphisms in the development of T2DM. Declarations Funding This work was supported by Gazi University Projects of Scientific Investigation (47/2020 and 08). Author M.G.K. has received research support from Gazi University Projects of Scientific Investigation. Competing Interests The authors have no relevant financial or non-financial interests to disclose . Author Contributions E.K., M.G.K., and M.A. conceptualized and designed the study, and critically reviewed the manuscript for important intellectual content. E.K, and M.A. evaluated and recruited patients, recorded clinical and laboratory results, and collected the samples. E.K, and A.V. designed the data collection instruments, carried out the analyses, and performed laboratory analysis. All authors read and approved the final manuscript. Data Availability All pertinent data are included in the main manuscript. The analysed data are available from the corresponding author and can be provided upon reasonable request via email. Ethical Approval The Gazi University Clinical Research Ethics Committee obtained ethical approval (278 numbered and dated 12/23/2019) for this study. Consent to Participate Informed consent was obtained from all individual participants included in the study. References Ahmad E, Lim S, Lamptey R, Webb DR, Davies MJ (2022) Type 2 diabetes. The Lancet 400(10365):1803-1820. https://doi.org/10.1016/S0140-6736(22)01655-5 Misra S, Ke C, Srinivasan S, Goyal A, Nyriyenda MJ, Florez JC, Khunti K, Magliano DJ, Luk A (2023) Current insights and emerging trends in early-onset type 2 diabetes. Lancet Diabetes Endocrinol 11(10):768-782. https://doi.org/10.1016/S2213-8587(23)00225-5 Dubey R, Prabhakar PK, Gupta J (2022). Epigenetics: Key to improve delayed wound healing in type 2 diabetes. Mol Cell Biochem 477, 371-383. https://doi.org/10.1007/s11010-021-04285-0 International Diabetes Federation. IDF Diabetes Atlas 2021. https://diabetesatlas.org/atlas/tenth-edition/ Accessed 29 October 2024 American Diabetes Association Professional Practice Committee (2024) 2. Diagnosis and classification of diabetes: standards of care in diabetes—2024. Diabetes Care 47(Supplement_1):S20-S42. https://doi.org/10.2337/dc24-S002 Dornas W, Silva M (2024) Modulation of the antioxidant enzyme paraoxonase-1 for protection against cardiovascular diseases. Nutr Metab Cardiovasc Dis 34(12), 2611–2622. https://doi.org/10.1016/j.numecd.2024.04.005 Taler-Verčič A, Goličnik M, Bavec A (2020) The structure and function of paraoxonase-1 and its comparison to paraoxonase-2 and-3. Molecules (Basel, Switzerland) 25(24), 5980. https://doi.org/10.3390/molecules25245980 Khalaf FK, Connolly J, Khatib-Shahidi B, Albehadili A, Tassavvor I, Ranabothu M, Eid N, Dube P, Khouri SJ, Malhotra D (2023) Paraoxonases at the Heart of Neurological Disorders. Int J Mol Sci 24(8):6881. https://doi.org/10.3390/ijms24086881 Kunachowicz D, Ściskalska M, Kepinska M (2023) Modulatory effect of lifestyle-related, environmental and genetic factors on paraoxonase-1 activity: a review. Int J Environ Res Public Health 20(4):2813. https://doi.org/10.3390/ijerph20042813 Jakubowski H (2023). Proteomic Exploration of Paraoxonase 1 Function in Health and Disease. Int J Mol Sci 24 (9), 7764. https://doi.org/10.3390/ijms24097764 Mahrooz A, Mackness M, Bagheri A, Ghaffari-Cherati M, Masoumi P (2019) The epigenetic regulation of paraoxonase 1 (PON1) as an important enzyme in HDL function: The missing link between environmental and genetic regulation. Clin Biochem 73:1-10. https://doi.org/10.1016/j.clinbiochem.2019.07.010 Zhou M, Liu X-H, Liu Q-Q, Chen M, Bai H, Guan L-B, Fan P (2020) Lactonase activity, status, and genetic variations of paraoxonase 1 in women with gestational diabetes mellitus. J Diabetes Res 2020(1):3483427. https://doi.org/10.1155/2020/3483427 Medina-Díaz IM, Ponce-Ruíz N, Rojas-García AE, Zambrano-Zargoza JF, Bernal-Hernández YY, González-Arias CA, Barrón-Vivanco BS, Herrera-Moreno JF (2022) The relationship between cancer and paraoxonase 1. Antioxidants 11(4):697. https://doi.org/10.3390/antiox11040697 Hashemi MM, Mousavi E, Arab-Bafrani Z, Nezhadebrahimi A, Marjani A (2019) The most effective polymorphisms of paraoxonase-1 gene on enzyme activity and concentration of paraoxonase-1 protein in type 2 diabetes mellitus patients and non-diabetic individuals: A systematic review and meta-analysis. Diabetes Res Clin Pract 152:135-145. https://doi.org/10.1016/j.diabres.2019.05.007 Shokri Y, Variji A, Nosrati M, Khonakdar-Tarsi A, Kianmehr A, Kashi Z, Bahar A, Bagheri A, Mahrooz A (2020) Importance of paraoxonase 1 (PON1) as an antioxidant and antiatherogenic enzyme in the cardiovascular complications of type 2 diabetes: Genotypic and phenotypic evaluation. Diabetes Res Clin Pract 161:108067. https://doi.org/10.1016/j.diabres.2020.108067 Mackness M, Sozmen EY (2021) A critical review on human serum Paraoxonase-1 in the literature: truths and misconceptions. Turk J Biol 46(1):3-8. https://doi.org/10.1515/tjb-2020-0186 Kaur S, Bhatti GK, Vijayvergiya R, Singh P, Mastana SS, Tewari R, Bhatti JS (2019) Paraoxonase 1 gene polymorphisms (Q192R and L55M) are associated with coronary artery disease susceptibility in Asian Indians. Dubai Diabetes and Endocrinology Journal 24(1-4):38-47. https://doi.org/10.1159/000494508 Ashiq S, Ashiq K (2021) The role of paraoxonase 1 (PON1) gene polymorphisms in coronary artery disease: a systematic review and meta-analysis. Biochem Genet 59(4):919-939. https://doi.org/10.1007/s10528-021-10043-0 Luo JQ, Ren H, Liu MZ, Fang PF, Xiang DX (2018) European versus Asian differences for the associations between paraoxonase‐1 genetic polymorphisms and susceptibility to type 2 diabetes mellitus. J Cell Mol Med 22(3):1720-1732. https://doi.org/10.1111/jcmm.13453 Wu D, Wu C, Zhong Y (2018) The association between paraoxonase 1 activity and the susceptibilities of diabetes mellitus, diabetic macroangiopathy and diabetic microangiopathy. J Cell Mol Med 22(9):4283-4291. https://doi.org/10.1111/jcmm.13711 Wamique M, Ali W, Himanshu D (2020) Association of SRB1 and PON1 gene polymorphisms with type 2 diabetes mellitus: A case control study. Int J Diabetes Dev Ctries 40:209-215. https://doi.org/10.1007/s13410-019-00787-2 del Carmen Xotlanihua-Gervacio M, Herrera-Moreno JF, Medina-Díaz IM, Bernal-Hernández YY, Rothenberg SJ, Barrón-Vivanco BS, Rojas-García AE (2019) Relationship between internal and external factors and the activity of PON1. Environ Sci Pollut Res Int 26(24):24946-24957. https://doi.org/10.1007/s11356-019-05696-9 Mahrooz A, Mackness M (2020) Epigenetics of paraoxonases. Curr Opin Lipidol 31(4):200-205. https://doi.org/10.1097/MOL.0000000000000687 Sirca TB, Mureșan ME, Pallag A, Marian E, Jurca T, Vicaș LG, Tunduc IP, Manole F, Ștefan L (2024) The Role of Polyphenols in Modulating PON1 Activity Regarding Endothelial Dysfunction and Atherosclerosis. Int J Mol Sci 25(5):2962. https://doi.org/10.3390/ijms25052962 Davies MJ, Aroda VR, Collins BS, Gabbay RA, Green J, Maruthur NM, Rosas SE, Del Prato S, Mathieu C, Mingrone G, Rossing P, Tankova T, Tsapas A, Buse JB. Management of Hyperglycemia in Type 2 Diabetes, 2022. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care 45 (11):2753–2786. https://doi.org/10.2337/dci22-0034 Khanna D, Peltzer C, Kahar P, Parmar MS (2022) Body mass index (BMI): a screening tool analysis. Cureus 14(2):e22119. https://doi.org/10.7759/cureus.22119 Erel O (2004) A novel automated direct measurement method for total antioxidant capacity using a new generation, more stable ABTS radical cation. Clin Biochem 37(4):277-285. https://doi.org/10.1016/j.clinbiochem.2003.11.015 Erel O (2005) A new automated colorimetric method for measuring total oxidant status. Clin Biochem 38(12):1103-1111. https://doi.org/10.1016/j.clinbiochem.2005.08.008 Al-Kuraishy HM, Sami OM, Hussain NR, Al-Gareeb AI (2020) Metformin and/or vildagliptin mitigate type II diabetes mellitus induced-oxidative stress: the intriguing effect. J Adv Pharm Technol Res 11(3):142. https://doi.org/10.4103/japtr.JAPTR_18_20 Saglam M, Arikan H, Savci S, Inal-Ince D, Bosnak-Guclu M, Karabulut E, Tokgozoglu L (2010) International physical activity questionnaire: reliability and validity of the Turkish version. Percept Mot Skills 111(1):278-284. https://doi.org/10.2466/06.08.PMS.111.4.278-284 Rakıcıoğlu N, Tek A, Ayaz A, Pekcan G (2020). Photograph catalog of food and dishes: portion sizes and amounts. 7th ed. Ata Ofset Pub, Ankara, Turkey. Istanbul Beslenme Bilgi Sistemi (BEB_IS) nutrition data base software version 9. Data base: the German food code and nutrient data base (BLS) with additions from USDA-sr and other sources. Stuttgart, Germany: Hohenhim University; 2018. Avaliable from: https://bebis.com.tr/anasayfa. Shunmoogam N, Naidoo P, Chilton R (2018) Paraoxonase (PON)-1: a brief overview on genetics, structure, polymorphisms and clinical relevance. Vasc Health Risk Manag 14:137-143. https://doi.org/10.2147/VHRM.S165173 Gallego PH, Craig ME, Duffin AC, Bennetts B, Jenkins AJ, Hofer S, Lam A, Donaghue KC (2008) Association between p. Leu54Met polymorphism at the paraoxonase-1 gene and plantar fascia thickness in young subjects with type 1 diabetes. Diabetes care 31(8):1585-1589. https://doi.org/10.2337/dc07-2236 Moasser E, Azarpira N, Ghorbani dalini A, Shirazi B (2018) Paraoxonase 1 (PON1) gene polymorphism and haplotype analysis in type 2 diabetes mellitus: a case–control study in the south Iranian population. Int J Diabetes Dev Ctries 38:62-68. https://doi.org/10.1007/s13410-016-0544-z Jiang X, Ding C, Wang C, Yu J, Hua Z, Chen X, Ma J, Chen W (2020) Association of paraoxonase 1 gene polymorphisms and polycystic ovarian syndrome susceptibility: a systematic review and meta-analysis. Gynecol Obstet Invest 85(2):167-177. https://doi.org/10.1159/000505452 Flekač M, Škrha J, Zidkova K, Lacinova Z, Hilgertova J (2008) Paraoxonase 1 gene polymorphisms and enzyme activities in diabetes mellitus. Physiol Res 57(5):717-726. https://doi.org/10.33549/physiolres.931285 Elattar N, Swelam E, Hamed E, Elnahal A, Mostafa E (2012) Paraoxonase 1 gene polymorphism relationship with type 2 diabetes mellitus. Life Sci J 9(3):1742-1751 Altuner D, Ates I, Suzen SH, Koc GV, Aral Y, Karakaya A (2011) The relationship of PON1 QR 192 and LM 55 polymorphisms with serum paraoxonase activities of Turkish diabetic patients. Toxicol Ind Health 27(10):873-878. https://doi.org/10.1177/0748233711399317 Gökçen S, Cengiz M, Özaydın A (2013) Serum paraoxonase levels and PON1 (192) polymorphism in type 2 diabetes mellitus patients. Gazi Med J 24(3):70-73. doi:http://dx.doi.org/10.12996/gmj.2013.20 Koren-Gluzer M, Aviram M, Meilin E, Hayek T (2011) The antioxidant HDL-associated paraoxonase-1 (PON1) attenuates diabetes development and stimulates β-cell insulin release. Atherosclerosis 219(2):510-518. https://doi.org/10.1016/j.atherosclerosis.2011.07.119 Yu W, Liu X, Feng L, Yang H, Yu W, Feng T, Wang S, Wang J, Liu N (2017) Glycation of paraoxonase 1 by high glucose instigates endoplasmic reticulum stress to induce endothelial dysfunction in vivo. Sci Rep 7(1):45827. https://doi.org/10.1038/srep45827 Nawaka N, Pansang P, Saniwa A, Chaibut N, Jeenduang N (2021) Paraoxonase 1 (PON1) L55M and Q192R polymorphisms are not associated with chronic kidney disease in Thai individuals with type 2 diabetes. Int J Clin Pract 75(12):e14982. https://doi.org/10.1111/ijcp.14982 Arpaci A, Yalın S, Ecevit H, Comelekoglu U, Mete T (2020) Enzyme activity and genetic polymorphisms in patients with type II diabetes mellitus. Adv Clin Exp Med 29(9):1057-1063. https://doi.org/10.17219/acem/125397 Jeelani H, Ganie MA, Amin S, Fatima Q, Kawa IA, Manzoor S, Parvez T, Ahmad DN, Rashid F (2019) Effect of Paraoxonase1 (PON1) gene polymorphisms on PON1 activity, HDL, LDL and MDA levels in women with polycystic ovary syndrome (PCOS): A case-control study. Meta Gene 20:100552. https://doi.org/10.1016/j.mgene.2019.100552 Rainwater DL, Rutherford S, Dyer TD, Rainwater ED, Cole SA, VandeBerg JL, Almasy L, Blangero J, MacCluer JW, Mahaney MC (2009) Determinants of variation in human serum paraoxonase activity. Heredity 102(2):147-154. https://doi.org/10.1038/hdy.2008.110 Meneses MJ, Silvestre R, Sousa-Lima I, Macedo MP (2019) Paraoxonase-1 as a regulator of glucose and lipid homeostasis: impact on the onset and progression of metabolic disorders. Int J Mol Sci 20(16):4049. https://doi.org/10.3390/ijms20164049 Deakin S, Leviev I, Nicaud V, Meynet M-CB, Tiret L, James RW, Group EarS (2002) Paraoxonase-1 L55M polymorphism is associated with an abnormal oral glucose tolerance test and differentiates high risk coronary disease families. J Clin Endocrinol Metab 87(3):1268-1273. https://doi.org/10.1210/jcem.87.3.8335 Sarıkaya U, Meydan S, Selek Ş, Sarıkaya A, Demirel M, Gül AZ, Yıldız T (2023) Could the PON1 phenotype play a key role in insulin resistance? Int J Diabetes Dev Ctries 43(3):476-481. https://doi.org/10.1007/s13410-022-01096-x Fridman O, Gariglio L, Riviere S, Porcile R, Fuchs A, Potenzoni M (2016) Paraoxonase 1 gene polymorphisms and enzyme activities in coronary artery disease and its relationship to serum lipids and glycemia. Arch Cardiol Mex 86(4):350-357. https://doi.org/10.1016/j.acmx.2016.08.001 Pappa KI, Gazouli M, Anastasiou E, Loutradis D, Anagnou NP (2017) The Q192R polymorphism of the paraoxonase-1 (PON1) gene is associated with susceptibility to gestational diabetes mellitus in the Greek population. Gynecol Endocrinol 33(8):617-620. https://doi.org/10.1080/09513590.2017.1302419 Sumi A, Nakamura U, Iwase M, Fujii H, Ohkuma T, Ide H, Jodai-Kitamura T, Komorita Y, Yoshinari M, Hirakawa Y (2017) The gene–treatment interaction of paraoxonase-1 gene polymorphism and statin therapy on insulin secretion in Japanese patients with type 2 diabetes: Fukuoka diabetes registry. BMC Med Genet 18(1):146. https://doi.org/10.1186/s12881-017-0509-1 Gupta N, Binukumar B, Singh S, Sunkaria A, Kandimalla R, Bhansali A, Gill KD (2011) Serum paraoxonase-1 (PON1) activities (PONase/AREase) and polymorphisms in patients with type 2 diabetes mellitus in a North-West Indian population. Gene 487(1):88-95. https://doi.org/10.1016/j.gene.2011.07.011 Gupta N, Singh S, Maturu VN, Sharma YP, Gill KD (2011) Paraoxonase 1 (PON1) polymorphisms, haplotypes and activity in predicting cad risk in North-West Indian Punjabis. PLoS One 6(5):e17805. https://doi.org/10.1371/journal.pone.0017805 Gomathi P, Iyer AC, Murugan PS, Sasikumar S, Raj NBAJ, Ganesan D, Nallaperumal S, Murugan M, Selvam GS (2018) Association of paraoxonase-1 gene polymorphisms with insulin resistance in South Indian population. Gene 650:55-59. https://doi.org/10.1016/j.gene.2018.01.094 Vaisar T, Kanter JE, Wimberger J, Irwin AD, Gauthier J, Wolfson E, Bahnam V, Wu I-H, Shah H, Keenan HA (2020) High concentration of medium-sized HDL particles and enrichment in HDL paraoxonase 1 associate with protection from vascular complications in people with long-standing type 1 diabetes. Diabetes Care 43(1):178-186. https://doi.org/10.2337/dc19-0772 Mahrooz A, Khosravi-Asrami OF, Alizadeh A, Mohmmadi N, Bagheri A, Kashi Z, Bahar A, Nosrati M, Mackness M (2023) Can HDL cholesterol be replaced by paraoxonase 1 activity in the prediction of severe coronary artery disease in patients with type 2 diabetes? Nutr Metab Cardiovasc Dis 33(8), 1599–1607. https://doi.org/10.1016/j.numecd.2023.05.020 Grzegorzewska AE, Ostromecka K, Adamska P, Mostowska A, Warchoł W, Jagodziński PP (2020) Paraoxonase 1 gene polymorphisms concerning non-insulin-dependent diabetes mellitus nephropathy in hemodialysis patients. J Diabetes Complications 34(11):107687. https://doi.org/10.1016/j.jdiacomp.2020.107687 Younis NN, Durrington PN (2012) HDL functionality in diabetes mellitus: potential importance of glycation. Clin Lipidol 7(5):561-578. https://doi.org/10.2217/clp.12.60 Kuet O, Kilit T, Kocak E (2022) Comparison of oxidative stress status and quality of life in participants with type 2 diabetes mellitus according to treatment modality. Niger J Clin Pract 25(2):130-136. https://doi.org/10.4103/njcp.njcp_92_20 Alu SN, Los EA, Ford GA, Stone WL (2022) Oxidative stress in type 2 diabetes: The case for future pediatric redoxomics studies. Antioxidants 11(7):1336. https://doi.org/10.3390/antiox11071336 Öztaş B, Eraldemir FC, Kır HM (2022) Serum Paraoxonase 1 as a Biomarker: Features and Applications in Type 2 Diabetes Mellitus. In: Patel, V.B., Preedy, V.R. (eds) Biomarkers in Diabetes. Biomarkers in Disease: Methods, Discoveries and Applications. Springer, Cham. pp 1-13. https://doi.org/10.1007/978-3-030-81303-1_22-1 Galicia-Garcia U, Benito-Vicente A, Jebari S, Larrea-Sebal A, Siddiqi H, Uribe KB, Ostolaza H, Martín C (2020) Pathophysiology of type 2 diabetes mellitus. Int J Mol Sci 21(17):6275. https://doi.org/10.3390/ijms21176275 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5920397","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":408673509,"identity":"5672c333-c4e8-4071-a275-2b3bdbf4e3e4","order_by":0,"name":"Emine Kocyigit","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACCRCRAKaYD4D4MkRrAdJsCSA+D3FaIDSPAYhBWItke/MziQe/LOr4xc58fnWjxoKHgf3w0Q34tEjzHDOTSOyTkJCcnbvNOucY0GE8aWk38GmRk8hhk0jskZAwuJ27zRjI5gF6x4w4Lfa3c54Z5/wjQos0SEvCD6At0jnMj3PbiNAi2XPM2CKxQUJyxu00M+bcPgkeNkJ+kTje/PDmjz91/Pyzkx9/zvlWJ8fPfvgYXi1AwCLB2AZmsIEjiY2AchBg/sDwB8YYBaNgFIyCUYAFAAAXWkHUAgUN5wAAAABJRU5ErkJggg==","orcid":"","institution":"Ordu University","correspondingAuthor":true,"prefix":"","firstName":"Emine","middleName":"","lastName":"Kocyigit","suffix":""},{"id":408673510,"identity":"4f640afa-e20c-4066-8929-d0cc36cc12cf","order_by":1,"name":"Makbule Gezmen Karadağ","email":"","orcid":"","institution":"Gazi University","correspondingAuthor":false,"prefix":"","firstName":"Makbule","middleName":"Gezmen","lastName":"Karadağ","suffix":""},{"id":408673511,"identity":"8f0b9e4f-4efb-4177-a070-c35f79f0ee15","order_by":2,"name":"Mujde Akturk","email":"","orcid":"","institution":"Gazi University","correspondingAuthor":false,"prefix":"","firstName":"Mujde","middleName":"","lastName":"Akturk","suffix":""},{"id":408673513,"identity":"82170919-97df-4338-ba73-582fa5a927d4","order_by":3,"name":"Ahmet Varis","email":"","orcid":"","institution":"DiaGen Biotechnology","correspondingAuthor":false,"prefix":"","firstName":"Ahmet","middleName":"","lastName":"Varis","suffix":""}],"badges":[],"createdAt":"2025-01-28 18:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5920397/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5920397/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75189810,"identity":"c8d0622b-7f98-4fb6-a6d4-9188cbe3d077","added_by":"auto","created_at":"2025-01-31 18:05:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":138056,"visible":true,"origin":"","legend":"\u003cp\u003ePON1 enzyme activity in patients with T2DM and controls with the PON1\u003cem\u003e \u003c/em\u003eQ192R and L55M polymorphisms. (A) PON1 enzyme activity and the PON1\u003cstrong\u003e \u003c/strong\u003eQ192R polymorphism; (B) PON1 enzyme activity and the PON1\u003cstrong\u003e \u003c/strong\u003eQ192R polymorphism\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5920397/v1/12e462eac186d64bb1135ac5.png"},{"id":76527364,"identity":"35946d65-6e3d-49a1-94a8-7f3b1a758bbd","added_by":"auto","created_at":"2025-02-18 06:03:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1315307,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5920397/v1/f36fa967-21ca-4709-8cd2-9a4ae5d89707.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enzyme Activity and Genetic Polymorphisms of Paraoxonase 1 in Patients With Type 2 Diabetes Mellitus: A Case-Control Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eType 2 diabetes mellitus (T2DM) is a metabolic disease characterized by increased insulin resistance caused by severe hyperglycemia, impaired insulin secretion, and abnormal β cell function. The increasing incidence of T2DM is a worldwide health problem [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The International Diabetes Federation stated in the latest report that there were 378\u0026nbsp;million patients who had diabetes. It is estimated that this number will increase to 643\u0026nbsp;million by the year 2030; 90 to 95 percent of diabetes (DM) diagnoses are T2DM [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is a complex chronic disease impacted by genetic disposition, epigenetics, diet, physical inactivity, and lifestyle [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe human PON1 (EC 3.1.8.1) is a 43 kDa glycoprotein containing 354 amino acids, a calcium-dependent antioxidant enzyme that is mainly synthesized by the liver and secreted into the bloodstream, where it is strongly linked to high-density lipoprotein (HDL) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. PON1 is a member of the paraoxonase enzyme family, including PON2 and PON3. In humans, three genes encode these enzymes on the long arm of chromosome 7 (7q21.3-q22.1) [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The three members of this family have antioxidant properties. They are essential for preventing lipid oxidation in low-density lipoprotein (LDL) and cell membranes and changing the structure of HDL. PON1 is the most studied member of this family, which is regarded as a marker of oxidative stress [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePON1 is a gene that has more than 400 different variations in its single-nucleotide sequence, making it a highly polymorphic gene [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These polymorphisms influence the phenotype of the enzyme and about 60% of the variations in the activity and concentration of the PON1 enzyme. Therefore, inserting the most efficient polymorphism in establishing such a difference may lead us to candidates for T2DM susceptibility [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Variations in PON1 activity have been related to two single-nucleotide polymorphisms (SNPs) in the PON1 gene, especially Q192R (rs662) and L55M (rs854560) [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have found an association between PON1 polymorphisms, enzyme activity, and T2DM [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. A recent meta-analysis showed that total PON1 activity was 1.25-fold higher in healthy controls than in subjects with T2DM. Also, polymorphisms in the PON1 coding region, particularly the RR and LL genotypes, affected serum PON1 activity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Another meta-analysis found that the Q192R and L55M polymorphisms play significant roles in the risk of T2DM, with the European and Asian populations displaying substantially different effects of these roles. Moreover, it has been determined that racial/ethnic characteristics may influence the relationship between these functional variants and accuracy [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe human PON1 activity varies based on several factors, including age, environmental pollutants, nutrition and lifestyle, smoking, pregnancy, physical activity, and chronic diseases such as T2DM, polycystic ovary syndrome, cardiovascular disease, and atherosclerosis. In addition, genetic polymorphisms can affect the concentration and activity of an enzyme by altering its gene and protein expression [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The current study evaluated the association and susceptibility of polymorphic variants in PON1 (Q192R and L55M) with T2DM. The relationship between PON1 gene polymorphism, PON1 activity, biochemical parameters, physical activity level, and dietary antioxidant intake in T2DM patients and healthy controls was also investigated.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Sample\u003c/h2\u003e \u003cp\u003eThe current study involved 204 volunteers (92 males and 112 females) aged 30 to 60, comprising 102 healthy subjects and 102 persons diagnosed with T2DM. The selection of healthy controls was based on similarities in gender, age, and body mass index (BMI) with T2DM patients. The diagnostic criteria for T2DM as defined by the American Diabetes Association (ADA) include the following indicators: a hemoglobin A1c (HbA1c) level of 6.5% or higher, a fasting blood sugar (FBS) level of 126 mg/dL (7 mmol/L) or higher, a 2-hour postprandial glucose level of 200 mg/dL (11.1 mmol/L) or higher, or a random plasma glucose level of 200 mg/dL or higher [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Receiving insulin therapy, DM duration\u0026thinsp;\u0026gt;\u0026thinsp;5 years, having microvascular and macrovascular complications of T2DM, chronic diseases, such as coronary heart disease, osteomalacia, chronic diarrhea, malabsorption, lung disease, and cancer were exclusion criteria for patients with T2DM. Moreover, exclusion criteria for both T2DM patients and controls included pregnancy and breastfeeding, consumption of alcohol, smoking, and an unwillingness to participate or continue cooperating.\u003c/p\u003e \u003cp\u003eThe \u003cb\u003e[name removed for blind peer review]\u003c/b\u003e University Clinical Research Ethics Committee obtained ethical approval (278 numbered and dated 12/23/2019) for this study. The present study was conducted by the criteria specified in the Helsinki Declaration.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnthropometric Measurements\u003c/h3\u003e\n\u003cp\u003eStandard techniques were used to measure anthropometric parameters directly. Weight (kg), height (cm), neck circumference (cm), waist circumference (cm), and hip circumference (cm) were measured, and the waist-to-hip and waist-to-height ratios were calculated.\u003c/p\u003e \u003cp\u003eThe body weights of the participants were measured using the Tanita BC 545 N Inner Scan (Balance\u0026trade;) when they were fasting and wearing light clothing. The Tanita BC 545 N Inner Scan\u0026trade; with bioelectrical impedance analysis was performed to determine body composition (body fat, body water, and fat-free mass). The height (in cm) was measured with the feet together and the head in the Frankfort plane using a stadiometer with an accuracy of 0.1 cm. The BMI was calculated using the \u0026ldquo;body weight / height2\u0026rdquo; (kg/m2). According to the BMI classification of the World Health Organization (WHO), The BMI values of the participants were grouped into four categories: underweight (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), normal weight (18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI kg/m2), and obese (30.0\u0026thinsp;\u0026le;\u0026thinsp;BMI kg/m2) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eLaboratory Measurements\u003c/h3\u003e\n\u003cp\u003eBlood samples were taken in the morning after an eight- to ten-hour overnight fast following dinner. Blood samples were taken using a conventional venipuncture technique. The serum was separated after centrifugation (Mikro 200 R, Hettich, Tuttlingen, Germany) performed at 3000 rpm for 10 minutes, and then the supernatant was placed in Eppendorf tubes. The aliquots obtained from the sample were promptly frozen and kept at a temperature of -80\u0026deg;C. Biochemical analyses were conducted using the techniques described by commercially available guidelines. The fasting blood glucose (FBG), total cholesterol (TC), triglyceride (TG), HDL-cholesterol (HDL-c), and LDL-cholesterol (LDL-c) analyses were conducted using the automatic Mindray BS-300 Chemistry Analyzer (Mindray, Shenzhen, China). The glycated hemoglobin (HbA1c) was determined using an automated high-performance liquid chromatography analyzer following standard protocols.\u003c/p\u003e \u003cp\u003eThe enzymatic activity of PON1 was determined using the Sandwich Enzyme-Linked Immunosorbent Assay (ELISA) method using the Human PON1 ELISA Kit (Cusabio\u0026reg;, China). TAS and TOS levels were measured by a colorimetric method using commercially available assay kits (Rel Assay, T\u0026uuml;rkiye) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Oxidative stress index (OSI) was calculated using the following formula: OSI (arbitrary unit)\u0026thinsp;=\u0026thinsp;TOS (\u0026micro;mol H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e equivalent/L) / TAS (mmol Trolox equivalent /L) x 100 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eDNA Extraction and Genotyping\u003c/h3\u003e\n\u003cp\u003eFor genetic analysis, 4 mL of blood was collected from each subject and stored at -80\u0026deg;C in tubes containing ethylenediaminetetraacetic acid (EDTA) until analysis. For DNA isolation from blood samples taken from individuals in EDTA tubes, QuickGene DNA Extraction Whole Blood Kit S (Kurabo\u0026reg;, Germany) was used. Following isolation, the DNAs were stored in 1.5 mL microcentrifuge tubes that were nuclease-free. The concentration and purity of isolated genomic DNA were measured using a Colibri Microvolume Spectrometer (Titertek-Berthold, Germany).\u003c/p\u003e \u003cp\u003eReal-time polymerase chain reaction (PCR) SensiFAST\u0026trade; Probe No-ROX Kit (Bioline, UK) with a probe based on hydrolysis was used to identify the intronic PON1 gene rs854560 and rs662 SNPs. In the genetic analysis, the PCR protocol consisted of 5 minutes of pre-denaturation at 95\u0026deg;C (first denaturation), 10 seconds of denaturation at 95\u0026deg;C (DNA chain opening), 10 seconds of annealing at 59\u0026deg;C (primer attachment/bonding to the opened DNA chain), and 5 seconds of primary extension at 72\u0026deg;C. This cycle was performed forty times in all. After completing the PCR cycle, the products were cooled and kept at 40\u0026deg;C for 1 minute.\u003c/p\u003e \u003cp\u003eIn the current study, SNP genotyping was conducted using real-time PCR with a hydrolysis probe (TaqMan\u0026reg;). Primer sequences complementary to the target DNA sequence and probe oligonucleotides containing particular fluorescent dyes were used. Probe arrays used for genotyping include a fluorescent dye (FAM/HEX) and a chemical called a quencher that absorbs the radiation of the fluorescent dye. During fragment elongation, due to the 3'-5' exonuclease activity of the Taq polymerase enzyme, the probe separates from the 5' tip, moves away from the quencher, and reradiates. As the number of amplicons rises logarithmically, fluorescence and irradiation intensity progressively increase. The probes will increase Fam and Hex fluorescence luminescence when bound to the normal and mutant alleles, respectively. If both probe irradiations occur, the presence of the two alleles was understood.\u003c/p\u003e \u003cp\u003eIn the last step, the people were divided into three groups based on the presence of LL, LM, and MM genotypes based on the polymorphisms of rs854560 of the PON1 gene and QQ, QR, and RR genotypes based on the polymorphisms of rs662 of the PON1 gene. As a consequence of genetic analysis, the Hardy-Weinberg equilibrium evaluated the frequency of alleles identified in people, and genotype frequencies were compared with their predicted frequencies by the Hardy-Weinberg equilibrium.\u003c/p\u003e\n\u003ch3\u003eThe International Physical Activity Questionnaire-Short Form (IPAQ-SF)\u003c/h3\u003e\n\u003cp\u003eThe IPAQ-SF is a 7-item scale that assesses the number of minutes spent in physical activity, including vigorous intensity activities (e.g., running), moderate intensity activities (e.g., brisk walking), walking, and sitting during the last week. Counts of activities were reported as metabolic equivalents (METs). Individuals' physical activity levels were determined using the IPAQ-SF, for which validity and reliability tests have been conducted in Turkey [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eNutritional Assessment\u003c/h2\u003e \u003cp\u003e In order to assess the dietary antioxidant intake of participants, 3-day food records (2 weekdays and 1 weekend) were completed through face-to-face interviews and telephone calls. The amount of food consumed was determined through a photographic atlas of food portion sizes for the dietary intake [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. For the evaluation of dietary antioxidant capacity, Nutrition Information Systems (Beslenme Bilgi Sistemi-BeBiS), which is a food software program compliant with Turkish food, was utilized [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe statistical data analysis used the Windows-based Statistical Package for the Social Sciences (SPSS, version 26.0) statistical package program. A power calculation was conducted a priori using G*Power (version 3.1; Heinrich Heine University D\u0026uuml;sseldorf, Germany). The total sample size was determined to be n\u0026thinsp;=\u0026thinsp;200 for 90% power at a 5% error; hence, our sample size of n\u0026thinsp;=\u0026thinsp;204 is acceptable for this research.\u003c/p\u003e \u003cp\u003eCount (n), percentage (%), and arithmetic mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (x\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) values are given for the measured variables. Kolmogorov-Smirnov/Shapiro-Wilk tests were used to evaluate the convenience of data to normal distribution. The parametric variables were analyzed using t-tests or analysis of variance (ANOVA), while the nonparametric variables were assessed using Mann-Whitney or Kruskal-Wallis tests. The statistical methods employed to evaluate the Relationship Relationship between categorical variables were the Fisher exact test and the chi-square (χ2) test. The χ2 test also analyzed the Hardy-Weinberg equilibrium of the gene variants. Linear regression analysis was conducted to assess the variables affecting the PON1 activity in individuals. A linear regression model was performed before and after adjustment for age, gender, and BMI. The odds ratio (OR) and its corresponding 95% confidence intervals (CI) were computed as part of the analysis. Results were evaluated statistically at a p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 significance level.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eIn this study, 102 T2DM patients and 102 controls were compared. Demographic, clinical, and biochemical characteristics of T2DM and controls are given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In the control group, most of the individuals were university (47.1%) and high school (31.4%) graduates and had a regular job (%94.1). The difference between the education level and employment status of T2DM patients and controls was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Patients with T2DM had significantly higher HbA1c, FBG, LDL-c, and TG than controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Significantly higher levels of PON1 activity and DTAC were observed in controls compared to patients with T2DM (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic, clinical, and biochemical characteristics of T2DM and controls\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level, [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElementary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (5.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (31.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (47.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostgraduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (8.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment status, [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (53.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (94.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (46.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (5.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.3\u0026thinsp;\u0026plusmn;\u0026thinsp;14.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeck circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist-to-hip ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist-to-height ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal body fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal body water (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat-free mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMET score (min/week)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e858.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1459.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e833.6\u0026thinsp;\u0026plusmn;\u0026thinsp;993.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143.6\u0026thinsp;\u0026plusmn;\u0026thinsp;55.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-c (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.9\u0026thinsp;\u0026plusmn;\u0026thinsp;44.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.585\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-c (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126.7\u0026thinsp;\u0026plusmn;\u0026thinsp;36.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.6\u0026thinsp;\u0026plusmn;\u0026thinsp;26.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206.9\u0026thinsp;\u0026plusmn;\u0026thinsp;46.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e197.5\u0026thinsp;\u0026plusmn;\u0026thinsp;34.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167.1\u0026thinsp;\u0026plusmn;\u0026thinsp;99.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113.4\u0026thinsp;\u0026plusmn;\u0026thinsp;75.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAS (\u0026micro;mol Trolox Eq/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOS (\u0026micro;mol H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e Eq/I)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePON1 enzyme activity (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e296.7\u0026thinsp;\u0026plusmn;\u0026thinsp;183.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354.7\u0026thinsp;\u0026plusmn;\u0026thinsp;233.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTAC (mmol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003eT2DM patients and controls was statistically significant (p\u0026lt;0.05). Patients with T2DM had significantly higher HbA1c, FBG, LDL-c, and TG than controls (p\u0026lt;0.05). Significantly higher levels of PON1 activity and DTAC were observed in controls compared to patients with T2DM (p\u0026lt;0.05).\u003c/p\u003e \u003cp\u003eData were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and n (%); comparison between groups was performed with the Mann-Whitney U test, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eBMI: Body mass index, BAI: Body adiposity index, MET: metabolic equivalents, FBG: Fasting blood glucose, TAS: Total antioxidant status, TC: Total cholesterol, TOC: Total oxidant status, TG: OSI: Oxidative stress index\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGenotype Distribution and Allele Frequencies\u003c/h2\u003e \u003cp\u003eThe genotype distribution and allele frequencies for the Q192R and L55M polymorphisms of the PON1 gene are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The frequencies of the QQ, QR, and RR genotypes of the PON1 gene Q192R polymorphism in T2DM patients and controls were 49.0%, 39.2%, and 11.8% vs. 47.0%, 41.2%, and 11.8%, respectively. Also, the frequencies of the LL, LM, and MM genotypes of the PON1 gene L55M polymorphism were 30.4%, 57.8%, and 11.8% in patients with T2DM, and 31.4%, 49.0%, and 19.6% in controls, respectively. No significant differences were found in genotype distributions and allele frequencies between patients with T2DM and the controls (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of genotypes and allele frequencies of PON1gene between patients with T2DM and control\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;102)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePON1 192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50 (49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48 (47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40 (39.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42 (41.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,094(0,608-1,967)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,042(0,427-2,544)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,929\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQR\u0026thinsp;+\u0026thinsp;RR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52 (51.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (52.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,082 (0,624-1,874)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,779\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e140 (68.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e138 (67.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64 (31.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66 (32.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.046 (0.690\u0026ndash;1.587)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,832\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePON1 55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (31.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59 (57.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50 (49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.821 (0.441\u0026ndash;1.528)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.533\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.615 (0.677\u0026ndash;3.852)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM\u0026thinsp;+\u0026thinsp;MM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71 (69.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70 (68.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.955 (0.527\u0026ndash;1.730)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e121 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e114 (55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.995 (0.527\u0026ndash;1.730)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eComparison between group was performed with Chi-square test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003cp\u003eT2DM: Type 2 diabetes mellitus, PON1: Paraoxonase1, OR: Odds ratio, CI: Confidence interval.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePON1 Enzyme Activity\u003c/h2\u003e \u003cp\u003ePON1 activity according to the PON1 Q192R and L55M genotypes in patients with T2DM and controls are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. PON1 activity was significantly highest in the RR genotype and lowest in the QQ genotype in patients with T2DM and controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In T2DM patients and controls, PON1 activity was considerably lower in the MM genotype than in the LM and LL genotypes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). While controls with the MM genotype had significantly higher PON1 activity than T2DM patients with the MM genotype, controls with the QQ genotype had significantly lower PON1 activity than T2DM patients with the QQ genotype (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eThe Relationship Between Anthropometric and Biochemical Characteristics, MET score, DTAC, and PON1 Genotypes\u003c/h2\u003e \u003cp\u003eThe data were stratified based on anthropometric and biochemical characteristics, MET score, and DTAC of all subjects, classified by the genotypes QQ, QR, and RR of the PON1 Q192R polymorphism (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In patients with T2DM, the waist-to-hip ratio, HbA1c, FBG, LDL-c, and TG levels were higher in the QR genotype of the PON1 Q192R gene than in the controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Total body fat, HbA1c, FBG, LDL-c, and TG levels were higher in T2DM patients with the QQ genotype, whereas total body water, fat-free mass, and DTAC were lower in T2DM patients compared to their respective control genotype (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). HbA1c, FBG, LDL-c, and TOC levels were lower in controls with the RR genotype of the gene than in T2DM subjects with the RR genotype (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eWe classified the anthropometric and biochemical characteristics, MET score, and DTAC of both T2DM patients and controls based on the genotypes LL, LM, and MM of the PON1 L55M polymorphism in the same way as the Q192R polymorphism (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In subjects with T2DM, total body fat, LDL-c, and TG levels were higher, but total body water, fat-free mass, MET score, and TC levels were lower in the MM genotype of the gene compared to their respective control (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). HbA1c, FBG, LDL-c, and TG levels were higher in T2DM patients with the LL genotype, while fat-free mass was lower in T2DM patients with the LL genotype compared to their control genotype (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In controls, HbA1c, FBG, LDL-c, TC, and TG levels were lower in the LM genotype of the PON1 L55M gene than in T2DM patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe anthropometric measurements, MET score, some biochemical parameters, and DTAC in subjects with T2DM and controls according to PON1 Q192 polymorphism\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQQ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQQ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist to height ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist to hip ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal body fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.69\u0026thinsp;\u0026plusmn;\u0026thinsp;10.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.96\u0026thinsp;\u0026plusmn;\u0026thinsp;10.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.75\u0026thinsp;\u0026plusmn;\u0026thinsp;10.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e27.31\u0026thinsp;\u0026plusmn;\u0026thinsp;9.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e31.43\u0026thinsp;\u0026plusmn;\u0026thinsp;7.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e36.07\u0026thinsp;\u0026plusmn;\u0026thinsp;4.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal body water (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.56\u0026thinsp;\u0026plusmn;\u0026thinsp;7.75\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.46\u0026thinsp;\u0026plusmn;\u0026thinsp;7.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.76\u0026thinsp;\u0026plusmn;\u0026thinsp;7.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e52.32\u0026thinsp;\u0026plusmn;\u0026thinsp;6.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e49.51\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e46.49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat free mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.72\u0026thinsp;\u0026plusmn;\u0026thinsp;10.72\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.91\u0026thinsp;\u0026plusmn;\u0026thinsp;12.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.68\u0026thinsp;\u0026plusmn;\u0026thinsp;11.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e54.90\u0026thinsp;\u0026plusmn;\u0026thinsp;12.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e47.68\u0026thinsp;\u0026plusmn;\u0026thinsp;9.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e55.41\u0026thinsp;\u0026plusmn;\u0026thinsp;14.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMET score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e673.90\u0026thinsp;\u0026plusmn;\u0026thinsp;730.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1144.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2108.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e676.79\u0026thinsp;\u0026plusmn;\u0026thinsp;969.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e881.36\u0026thinsp;\u0026plusmn;\u0026thinsp;813.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e815.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1272.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e707.00\u0026thinsp;\u0026plusmn;\u0026thinsp;402.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e6.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e5.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e6.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143.06\u0026thinsp;\u0026plusmn;\u0026thinsp;58.69\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140.57\u0026thinsp;\u0026plusmn;\u0026thinsp;42.85\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156.42\u0026thinsp;\u0026plusmn;\u0026thinsp;80.83\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e103.83\u0026thinsp;\u0026plusmn;\u0026thinsp;16.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e101.67\u0026thinsp;\u0026plusmn;\u0026thinsp;7.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e110.08\u0026thinsp;\u0026plusmn;\u0026thinsp;21.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-c (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.80\u0026thinsp;\u0026plusmn;\u0026thinsp;12.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.20\u0026thinsp;\u0026plusmn;\u0026thinsp;9.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.67\u0026thinsp;\u0026plusmn;\u0026thinsp;13.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e48.81\u0026thinsp;\u0026plusmn;\u0026thinsp;16.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e55.86\u0026thinsp;\u0026plusmn;\u0026thinsp;27.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e76.63\u0026thinsp;\u0026plusmn;\u0026thinsp;115.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-c (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127.30\u0026thinsp;\u0026plusmn;\u0026thinsp;38.68\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123.40\u0026thinsp;\u0026plusmn;\u0026thinsp;32.12\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135.25\u0026thinsp;\u0026plusmn;\u0026thinsp;39.67\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e92.72\u0026thinsp;\u0026plusmn;\u0026thinsp;22.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e90.84\u0026thinsp;\u0026plusmn;\u0026thinsp;31.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e98.48\u0026thinsp;\u0026plusmn;\u0026thinsp;22.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203.92\u0026thinsp;\u0026plusmn;\u0026thinsp;49.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208.23\u0026thinsp;\u0026plusmn;\u0026thinsp;40.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e215.08\u0026thinsp;\u0026plusmn;\u0026thinsp;56.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e191.54\u0026thinsp;\u0026plusmn;\u0026thinsp;29.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e193.81\u0026thinsp;\u0026plusmn;\u0026thinsp;38.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e192.50\u0026thinsp;\u0026plusmn;\u0026thinsp;40.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145.48\u0026thinsp;\u0026plusmn;\u0026thinsp;87.02\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196.40\u0026thinsp;\u0026plusmn;\u0026thinsp;115.87\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160.17\u0026thinsp;\u0026plusmn;\u0026thinsp;70.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e124.04\u0026thinsp;\u0026plusmn;\u0026thinsp;76.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e94.65\u0026thinsp;\u0026plusmn;\u0026thinsp;49.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e137.01\u0026thinsp;\u0026plusmn;\u0026thinsp;125.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAS (mmol Trolox eqv./l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e4.46\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOC (\u0026micro;mol H2O2 eqv./I)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.03\u0026thinsp;\u0026plusmn;\u0026thinsp;3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.99\u0026thinsp;\u0026plusmn;\u0026thinsp;2.62\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e4.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e3.87\u0026thinsp;\u0026plusmn;\u0026thinsp;2.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOSI (arbitrary unit)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTAC (mmol/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.29\u0026thinsp;\u0026plusmn;\u0026thinsp;3.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e5.46\u0026thinsp;\u0026plusmn;\u0026thinsp;11.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e3.51\u0026thinsp;\u0026plusmn;\u0026thinsp;11.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e5.97\u0026thinsp;\u0026plusmn;\u0026thinsp;9.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. a, b, and c indicate statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003cp\u003ea. QR genotypes in T2DM group vs.QR genotypes in controls, b. QQ genotypes in T2DM group vs.QQ genotypes in controls, c. RR genotypes in T2DM group vs.RR genotypes in controls\u003c/p\u003e \u003cp\u003eDTAC: Dietary total antioxidant capacity, MET: metabolic equivalents, FBG: Fasting blood glucose, TAS: Total antioxidant status, TC: Total cholesterol, TOC: Total oxidant status, TG: triglyceride, OSI: Oxidative stress index\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe anthropometric measurements, MET score, some biochemical parameters, and DTAC in subjects with T2DM and controls according to PON1 L155M polymorphism\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist to height ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist to hip ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal body fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.64\u0026thinsp;\u0026plusmn;\u0026thinsp;10.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.63\u0026thinsp;\u0026plusmn;\u0026thinsp;10.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.77\u0026thinsp;\u0026plusmn;\u0026thinsp;9.85\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e33.14\u0026thinsp;\u0026plusmn;\u0026thinsp;9.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e29.91\u0026thinsp;\u0026plusmn;\u0026thinsp;8.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e25.40\u0026thinsp;\u0026plusmn;\u0026thinsp;8.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal body water (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.49\u0026thinsp;\u0026plusmn;\u0026thinsp;7.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.62\u0026thinsp;\u0026plusmn;\u0026thinsp;8.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.90\u0026thinsp;\u0026plusmn;\u0026thinsp;7.10\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e48.58\u0026thinsp;\u0026plusmn;\u0026thinsp;5.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e50.68\u0026thinsp;\u0026plusmn;\u0026thinsp;5.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e53.01\u0026thinsp;\u0026plusmn;\u0026thinsp;5.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat free mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.41\u0026thinsp;\u0026plusmn;\u0026thinsp;11.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.06\u0026thinsp;\u0026plusmn;\u0026thinsp;12.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.71\u0026thinsp;\u0026plusmn;\u0026thinsp;7.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e54.05\u0026thinsp;\u0026plusmn;\u0026thinsp;11.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e49.82\u0026thinsp;\u0026plusmn;\u0026thinsp;11.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e54.11\u0026thinsp;\u0026plusmn;\u0026thinsp;12.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMET score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e763.55\u0026thinsp;\u0026plusmn;\u0026thinsp;842.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e971.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1785.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e553.54\u0026thinsp;\u0026plusmn;\u0026thinsp;798.64\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e483.16\u0026thinsp;\u0026plusmn;\u0026thinsp;377.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e924.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1239.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e1166.00\u0026thinsp;\u0026plusmn;\u0026thinsp;839.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e6.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e5.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e6.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150.16\u0026thinsp;\u0026plusmn;\u0026thinsp;63.19\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144.78\u0026thinsp;\u0026plusmn;\u0026thinsp;55.79\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121.33\u0026thinsp;\u0026plusmn;\u0026thinsp;25.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e105.78\u0026thinsp;\u0026plusmn;\u0026thinsp;14.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e101.54\u0026thinsp;\u0026plusmn;\u0026thinsp;16.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e105.65\u0026thinsp;\u0026plusmn;\u0026thinsp;8.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-c (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.74\u0026thinsp;\u0026plusmn;\u0026thinsp;12.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.93\u0026thinsp;\u0026plusmn;\u0026thinsp;11.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.83\u0026thinsp;\u0026plusmn;\u0026thinsp;12.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e55.06\u0026thinsp;\u0026plusmn;\u0026thinsp;71.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e53.88\u0026thinsp;\u0026plusmn;\u0026thinsp;25.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e57.61\u0026thinsp;\u0026plusmn;\u0026thinsp;17.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-c (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122.00\u0026thinsp;\u0026plusmn;\u0026thinsp;34.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132.42\u0026thinsp;\u0026plusmn;\u0026thinsp;36.59\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110.75\u0026thinsp;\u0026plusmn;\u0026thinsp;35.95\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e99.41\u0026thinsp;\u0026plusmn;\u0026thinsp;29.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e89.58\u0026thinsp;\u0026plusmn;\u0026thinsp;24.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e89.37\u0026thinsp;\u0026plusmn;\u0026thinsp;21.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207.39\u0026thinsp;\u0026plusmn;\u0026thinsp;47.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e212.15\u0026thinsp;\u0026plusmn;\u0026thinsp;46.00\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e180.00\u0026thinsp;\u0026plusmn;\u0026thinsp;41.94\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e195.00\u0026thinsp;\u0026plusmn;\u0026thinsp;44.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e188.04\u0026thinsp;\u0026plusmn;\u0026thinsp;32.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e200.1\u0026thinsp;\u0026plusmn;\u0026thinsp;17.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e173.84\u0026thinsp;\u0026plusmn;\u0026thinsp;102.75\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e170.98\u0026thinsp;\u0026plusmn;\u0026thinsp;104.84\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131.25\u0026thinsp;\u0026plusmn;\u0026thinsp;57.2\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e134.43\u0026thinsp;\u0026plusmn;\u0026thinsp;91.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e104.82\u0026thinsp;\u0026plusmn;\u0026thinsp;72.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e101.56\u0026thinsp;\u0026plusmn;\u0026thinsp;41.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAS (mmol Trolox eqv./L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e3.27\u0026thinsp;\u0026plusmn;\u0026thinsp;2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOC (\u0026micro;mol H2O2 eqv./L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.59\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e4.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e4.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOSI (arbitrary unit)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTAC (mmol/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;3.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e5.34\u0026thinsp;\u0026plusmn;\u0026thinsp;10.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e4.65\u0026thinsp;\u0026plusmn;\u0026thinsp;12.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e3.89\u0026thinsp;\u0026plusmn;\u0026thinsp;8.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. a, b, and c indicate statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003cp\u003ea. MM genotypes in T2DM group vs. MM genotypes in controls, b. LL genotypes in T2DM group vs. LL genotypes in controls, c. LM genotypes in T2DM group vs. LM genotypes in controls\u003c/p\u003e \u003cp\u003eDTAC: Dietary total antioxidant capacity, MET: metabolic equivalents, FBG: Fasting blood glucose, TAS: Total antioxidant status, TC: Total cholesterol, TOC: Total oxidant status, TG: triglyceride, OSI: Oxidative stress index\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe Relationship Between Factors and PON1 Activity\u003c/h2\u003e \u003cp\u003ePON1 enzyme activity in the study sample was influenced by several factors (Tablo 5). The QQ and QR genotypes of PON1 Q192R polymorphism and LL and LM genotypes of PON1 L55M polymorphism modulate PON1 enzyme activity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). PON1 enzyme activity was associated with HDL-c, TAS, and TOS levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTablo 5\u003c/b\u003e Relationship between factors and PON1 activity in the study sample\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCI 95%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePON1 Q192R polymorphism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQQ genotype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-224.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-303.20-(-147.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQR genotype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-96.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-171.58-(-21.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePON1 L55M polymorphism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLL genotype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e155.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.08-227.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLM genotype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.87-136.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnthropometric characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWaist to hip ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e187.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-204.05-579.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWaist to height ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-317.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-820.25-186.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal body fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-7.83-8.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal body water (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-12.55-8.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFat free mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.303-4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiochemical parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHbA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-12.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-52.07-27.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.551\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFBG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.28-1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHDL-c (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u0026ndash;4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLDL-c (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.89-0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.07-0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.41-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e107.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.24\u0026ndash;147.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-16.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-30.98-(-2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOSI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1327.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3177.02-5831.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssessment of nutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDTAC (mmol/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-10.74-15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eThe β and p value were obtained by linear regression analysis. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. DTAC: Dietary total antioxidant capacity, MET: metabolic equivalents, FBG: Fasting blood glucose, TAS: Total antioxidant status, TC: Total cholesterol, TOS: Total oxidant status, TG: triglyceride, OSI: Oxidative stress index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThere is still uncertainty regarding the precise relationship between Q192R and L55M polymorphisms of the PON1 gene and activity in T2DM. Given this fact, this study aimed to examine the metabolic parameters, anthropometric measurements, DTAC, and possible links between PON1 activity and the Q192R and L55M and polymorphism in PON1 in Turkish patients with T2DM and controls.\u003c/p\u003e \u003cp\u003eThe investigation of genetic polymorphic variations for the serum PON1 enzyme began following identifying its activity [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The PON1 192Q allele and the PON1 55M allele have been identified as potential risk alleles for several diseases, including coronary artery disease [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], T1DM [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], T2DM [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and polycystic ovarian syndrome [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], in some populations. The findings of the research exhibit discrepancies. In the present study, no significant differences were seen in the allele or genotype frequencies of the Q192R and L55M PON1 gene polymorphisms between the Turkish patients with T2DM and controls. However, the QQ and LM genotypes were more common in patients with T2DM and controls. Flekac et al. report that Q and M alleles are more frequent in patients with T2DM compared to the control group from the Czech Republic and have been associated with the pathogenesis of T2DM. Also, the predominant genotypes observed in people diagnosed with DM were PON1 55LM and PON1 192QQ [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Likewise, it was determined in the Egyptian population that the common genotype among individuals with T2DM was PON1 192QQ, with the Q allele being identified as a risk allele for T2DM. The M allele and PON1 55LM genotype were shown to be dominant in T2DM patients in the same research. However, no statistically significant difference was found [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The common genotypes seen in patients with T2DM and controls in the Turkish population were PON1 QQ192 and PON1 LM55. Notably, no statistically significant distinction was found between these two groups [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Gokcen et al. revealed no significant differences in the frequencies of the QQ, QR, and RR genotypes of the PON1 192 polymorphism between patients diagnosed with T2DM mellitus and the control group [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Genotype and allele frequencies differ due to variables such as ethnicity, genotyping techniques, changes in DM control selection and statistical power, sample size, heterogeneity of individuals, and gene-gene and gene-environment interactions.\u003c/p\u003e \u003cp\u003ePON1 activity is affected by various factors, including age, nutrition, lifestyle, physical activity level, anthropometric measurements and body composition, and drug use, but gene polymorphisms of PON1 are particularly important [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Previous research has demonstrated through in vitro and in vivo studies that the administration of PON1 to β cells exhibits a beneficial effect on β cell activity, perhaps reducing the onset of DM [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Thus, PON1 may be considered a significant enzyme with potential antidiabetic properties. Our results show that PON1 enzyme activity was increased significantly in controls compared to T2DM patients. PON1 enzyme activity was affected by the PON1 Q192R and L55M polymorphisms. PON1 enzyme activity was significantly increased in the QQ\u0026thinsp;\u0026lt;\u0026thinsp;QR\u0026thinsp;\u0026lt;\u0026thinsp;RR order among patients with T2DM and controls. In addition, PON1 enzyme activity was significantly increased in the order of the MM\u0026thinsp;\u0026lt;\u0026thinsp;LM\u0026thinsp;\u0026lt;\u0026thinsp;LL genotypes among all subjects, patients with T2DM, and controls. Our findings were consistent with the results of several prior studies [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In a systematic review and meta-analysis, serum PON1 activity was 1.25 times higher in healthy individuals than in patients with T2DM. When evaluated according to genotypes, there was a statistically significant difference between the PON1 LM55 and all genotypes of PON1 Q192R polymorphism (QQ\u0026thinsp;\u0026lt;\u0026thinsp;QR\u0026thinsp;\u0026lt;\u0026thinsp;RR) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Individuals carrying the PON1 L allele show elevated levels of PON1 mRNA, resulting in higher concentrations and activities [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The replacement of arginine for glutamine at position 192 causes variations in PON1's catalytic activity toward synthetic substrates, which is correlated with PON1 activity. At this point, the paraoxonase level of the PON1 R allele is higher than that of the PON1 Q allele [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Besides polymorphisms, several variables such as nutrition, age, lifestyle, medication treatments, epigenetic factors, and gene-environment interactions also impact the modulation of PON1 activity [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Chronic hyperglycemia in patients with T2DM is believed to decrease enzyme activity through the process of enzymatic or nonenzymatic glycation of PON1.\u003c/p\u003e \u003cp\u003eOne of the significant results obtained in this study was that PON1 Q192R and PON1 L55M variants significantly affected glycemic control and lipid parameters in T2DM patients when we analyzed the effects of the study variants on glycemic control. Patients with T2DM showed significantly elevated HbA1c, FBG, and LDL-c levels compared with the control group across all genotypes of the PON1 Q192R polymorphism. Compared to controls, T2DM patients had higher TG levels of QQ and QR genotypes. Also, HbA1c and FBG levels were much higher in T2DM patients with the LL and LM genotypes than in controls. LDL-c, TC, and TG levels were significantly higher for all PON1 L55M polymorphism genotypes than controls with the same genotype. The study conducted on the role of PON1 polymorphisms in glucose metabolism in 14 centers across 11 European countries found that the L55M polymorphism showed an independent association with glucose metabolism. However, no such association was observed for the Q192R polymorphism [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The findings obtained by Sarıkaya et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] showed that individuals having QQ phenotypes had a 1.85-fold and 2.16-fold increased likelihood of developing insulin resistance and impaired fasting glucose, respectively. Fridman et al. reported that patients with coronary artery disease and healthy individuals with the QQ genotype or M allele had increased serum glucose levels [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. On the contrary, Pappa et al. [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] and Susi et al. [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] did not find any significant effect of the Q192R polymorphism on metabolic and glycemic parameters in women with GDM and in patients with T2DM. Previous research on the Relationship between PON1 polymorphisms and lipid levels has shown inconsistent results [\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. It was reported that the Q192R and L55M polymorphisms of the PON1 gene may influence insulin resistance by decreasing PON1 enzyme concentration and altering GLUT-4 expression [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Insulin resistance and increased lipid accumulation, notably of diacylglycerol, accompany high concentrations of hexose molecules [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. It was also reported that a higher prevalence of QQ and MM genotypes in DM might be related to poorer glucose regulation, accelerated nonenzymatic glycation, and increased oxidative stress [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The study findings are likely influenced by variations in the distribution frequencies of people based on their genotypes and constraints in the selection process of participants incorporated in the study. Glycemic control and lipid profile may also be impacted by variations in pancreatic β-cell activity in patients with T2DM, time to diagnosis, hyperinsulinemia, medication therapy, body composition, physical activity level, and the existence of other polymorphisms linked to T2DM but not yet identified.\u003c/p\u003e \u003cp\u003eA further significant finding of the study indicates that the QQ and QR genotypes of the PON Q192R polymorphism harmed the activity of the PON1 enzyme. Conversely, the LL and LM genotypes of the PON L55M polymorphism have shown positive effects. HDL-c significantly impacts PON1 enzyme activity. The antioxidant and antiatherogenic properties of HDL-C are facilitated by various interconnected enzymes, with particular emphasis on PON1 [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The decrease in PON1 activity is primarily caused by the glycation of HDL-PON1, which is related to elevated glucose levels and other factors like hyperinsulinemia, dyslipidemia, and oxidative stress. Glycated HDL cannot metabolize membrane lipid peroxides and sustain cholesterol efflux [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The organism maintains a balance between oxidant and antioxidant systems. The TAS represents the total effect of all antioxidants in plasma and bodily fluids, while the TOS represents the overall impact of all oxidants [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. PON1, as an antioxidant protein, is crucial for maintaining the balance between oxidants and antioxidants [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Based on the provided information, the regression model indicates that TAS positively affects PON1 activity, while TOS has a negative impact. This outcome is considered favorable. However, no significant relationship was found between DTAC and PON1 activity. The DTAC level was significantly lower in patients with T2DM who had the QQ genotype than the control group. DTAC was calculated using 3-day food records from participants. 3-day food records may not accurately represent an individual's typical diet due to variations in daily dietary intake among individuals. Long-term food records may provide more insight into assessing the correlation between DTAC and PON1 activity.\u003c/p\u003e \u003cp\u003eThere are some limitations to this study. First, we did not evaluate the mRNA expression levels of PON1 Q192R and L55M genotypes. Second, we did not measure other oxidative stress markers and PON1 enzyme concentration. Third, only paraoxon substrates were assessed to test PON1 activity; other possible substrates were not included. Moreover, the limited sample size in the present study should be recognized as a constraint, necessitating the validation and reinforcement of the findings by studies including larger sample sizes.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eT2DM is a multifaceted disease impacted by genetic, metabolic, and environmental variables. These factors interact, collectively contributing to the overall prevalence of T2DM [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The current study shows that PON1 activity is higher in healthy individuals compared to patients with T2DM. This difference is influenced by different genotypes of the PON1 enzyme associated with the L55M and Q192R polymorphisms. Additionally, it has been observed that the Q192R and L55M genotypes of PON1 impact glucose and lipid metabolism parameters. These observations strongly support the role of PON1 polymorphisms and their activity in contributing to the pathophysiology of T2DM. Extensive and comprehensive studies are required to clarify the exact role of PON1 polymorphisms in the development of T2DM.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Gazi University Projects of Scientific Investigation (47/2020 and 08). Author M.G.K. has received research support from Gazi University Projects of Scientific Investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.K., M.G.K., and M.A. conceptualized and designed the study, and critically reviewed the manuscript for important intellectual content. \u0026nbsp;E.K, and M.A. evaluated and recruited patients, recorded clinical and laboratory results, and collected the samples. E.K, and A.V. designed the data collection instruments, carried out the analyses, and performed laboratory analysis. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll pertinent data are included in the main manuscript. The analysed data are available from the corresponding author and can be provided upon reasonable request via email.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Gazi University Clinical Research Ethics Committee obtained ethical approval (278 numbered and dated 12/23/2019) for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAhmad E, Lim S, Lamptey R, Webb DR, Davies MJ (2022) Type 2 diabetes. The Lancet 400(10365):1803-1820. https://doi.org/10.1016/S0140-6736(22)01655-5 \u003c/li\u003e\n\u003cli\u003eMisra S, Ke C, Srinivasan S, Goyal A, Nyriyenda MJ, Florez JC, Khunti K, Magliano DJ, Luk A (2023) Current insights and emerging trends in early-onset type 2 diabetes. Lancet Diabetes Endocrinol 11(10):768-782. https://doi.org/10.1016/S2213-8587(23)00225-5\u003c/li\u003e\n\u003cli\u003eDubey R, Prabhakar PK, Gupta J (2022). Epigenetics: Key to improve delayed wound healing in type 2 diabetes. Mol Cell Biochem 477, 371-383. https://doi.org/10.1007/s11010-021-04285-0\u003c/li\u003e\n\u003cli\u003eInternational Diabetes Federation. IDF Diabetes Atlas 2021. https://diabetesatlas.org/atlas/tenth-edition/ Accessed 29 October 2024\u003c/li\u003e\n\u003cli\u003eAmerican Diabetes Association Professional Practice Committee (2024) 2. Diagnosis and classification of diabetes: standards of care in diabetes\u0026mdash;2024. Diabetes Care 47(Supplement_1):S20-S42. https://doi.org/10.2337/dc24-S002\u003c/li\u003e\n\u003cli\u003eDornas W, Silva M (2024) Modulation of the antioxidant enzyme paraoxonase-1 for protection against cardiovascular diseases. Nutr Metab Cardiovasc Dis 34(12), 2611\u0026ndash;2622. https://doi.org/10.1016/j.numecd.2024.04.005\u003c/li\u003e\n\u003cli\u003eTaler-Verčič A, Goličnik M, Bavec A (2020) The structure and function of paraoxonase-1 and its comparison to paraoxonase-2 and-3. Molecules (Basel, Switzerland) 25(24), 5980. https://doi.org/10.3390/molecules25245980\u003c/li\u003e\n\u003cli\u003eKhalaf FK, Connolly J, Khatib-Shahidi B, Albehadili A, Tassavvor I, Ranabothu M, Eid N, Dube P, Khouri SJ, Malhotra D (2023) Paraoxonases at the Heart of Neurological Disorders. Int J Mol Sci 24(8):6881. https://doi.org/10.3390/ijms24086881\u003c/li\u003e\n\u003cli\u003eKunachowicz D, Ściskalska M, Kepinska M (2023) Modulatory effect of lifestyle-related, environmental and genetic factors on paraoxonase-1 activity: a review. Int J Environ Res Public Health 20(4):2813. https://doi.org/10.3390/ijerph20042813\u003c/li\u003e\n\u003cli\u003eJakubowski H (2023). Proteomic Exploration of Paraoxonase 1 Function in Health and Disease. Int J Mol Sci \u003cem\u003e24\u003c/em\u003e(9), 7764. https://doi.org/10.3390/ijms24097764 \u003c/li\u003e\n\u003cli\u003eMahrooz A, Mackness M, Bagheri A, Ghaffari-Cherati M, Masoumi P (2019) The epigenetic regulation of paraoxonase 1 (PON1) as an important enzyme in HDL function: The missing link between environmental and genetic regulation. Clin Biochem 73:1-10. https://doi.org/10.1016/j.clinbiochem.2019.07.010\u003c/li\u003e\n\u003cli\u003eZhou M, Liu X-H, Liu Q-Q, Chen M, Bai H, Guan L-B, Fan P (2020) Lactonase activity, status, and genetic variations of paraoxonase 1 in women with gestational diabetes mellitus. J Diabetes Res 2020(1):3483427. https://doi.org/10.1155/2020/3483427\u003c/li\u003e\n\u003cli\u003eMedina-D\u0026iacute;az IM, Ponce-Ru\u0026iacute;z N, Rojas-Garc\u0026iacute;a AE, Zambrano-Zargoza JF, Bernal-Hern\u0026aacute;ndez YY, Gonz\u0026aacute;lez-Arias CA, Barr\u0026oacute;n-Vivanco BS, Herrera-Moreno JF (2022) The relationship between cancer and paraoxonase 1. Antioxidants 11(4):697. https://doi.org/10.3390/antiox11040697\u003c/li\u003e\n\u003cli\u003eHashemi MM, Mousavi E, Arab-Bafrani Z, Nezhadebrahimi A, Marjani A (2019) The most effective polymorphisms of paraoxonase-1 gene on enzyme activity and concentration of paraoxonase-1 protein in type 2 diabetes mellitus patients and non-diabetic individuals: A systematic review and meta-analysis. Diabetes Res Clin Pract 152:135-145. https://doi.org/10.1016/j.diabres.2019.05.007\u003c/li\u003e\n\u003cli\u003eShokri Y, Variji A, Nosrati M, Khonakdar-Tarsi A, Kianmehr A, Kashi Z, Bahar A, Bagheri A, Mahrooz A (2020) Importance of paraoxonase 1 (PON1) as an antioxidant and antiatherogenic enzyme in the cardiovascular complications of type 2 diabetes: Genotypic and phenotypic evaluation. Diabetes Res Clin Pract 161:108067. https://doi.org/10.1016/j.diabres.2020.108067\u003c/li\u003e\n\u003cli\u003eMackness M, Sozmen EY (2021) A critical review on human serum Paraoxonase-1 in the literature: truths and misconceptions. Turk J Biol 46(1):3-8. https://doi.org/10.1515/tjb-2020-0186\u003c/li\u003e\n\u003cli\u003eKaur S, Bhatti GK, Vijayvergiya R, Singh P, Mastana SS, Tewari R, Bhatti JS (2019) Paraoxonase 1 gene polymorphisms (Q192R and L55M) are associated with coronary artery disease susceptibility in Asian Indians. Dubai Diabetes and Endocrinology Journal 24(1-4):38-47. https://doi.org/10.1159/000494508\u003c/li\u003e\n\u003cli\u003eAshiq S, Ashiq K (2021) The role of paraoxonase 1 (PON1) gene polymorphisms in coronary artery disease: a systematic review and meta-analysis. Biochem Genet 59(4):919-939. https://doi.org/10.1007/s10528-021-10043-0\u003c/li\u003e\n\u003cli\u003eLuo JQ, Ren H, Liu MZ, Fang PF, Xiang DX (2018) European versus Asian differences for the associations between paraoxonase‐1 genetic polymorphisms and susceptibility to type 2 diabetes mellitus. J Cell Mol Med 22(3):1720-1732. https://doi.org/10.1111/jcmm.13453\u003c/li\u003e\n\u003cli\u003eWu D, Wu C, Zhong Y (2018) The association between paraoxonase 1 activity and the susceptibilities of diabetes mellitus, diabetic macroangiopathy and diabetic microangiopathy. J Cell Mol Med 22(9):4283-4291. https://doi.org/10.1111/jcmm.13711\u003c/li\u003e\n\u003cli\u003eWamique M, Ali W, Himanshu D (2020) Association of SRB1 and PON1 gene polymorphisms with type 2 diabetes mellitus: A case control study. Int J Diabetes Dev Ctries 40:209-215. https://doi.org/10.1007/s13410-019-00787-2\u003c/li\u003e\n\u003cli\u003edel Carmen Xotlanihua-Gervacio M, Herrera-Moreno JF, Medina-D\u0026iacute;az IM, Bernal-Hern\u0026aacute;ndez YY, Rothenberg SJ, Barr\u0026oacute;n-Vivanco BS, Rojas-Garc\u0026iacute;a AE (2019) Relationship between internal and external factors and the activity of PON1. Environ Sci Pollut Res Int 26(24):24946-24957. https://doi.org/10.1007/s11356-019-05696-9\u003c/li\u003e\n\u003cli\u003eMahrooz A, Mackness M (2020) Epigenetics of paraoxonases. Curr Opin Lipidol 31(4):200-205. https://doi.org/10.1097/MOL.0000000000000687\u003c/li\u003e\n\u003cli\u003eSirca TB, Mureșan ME, Pallag A, Marian E, Jurca T, Vicaș LG, Tunduc IP, Manole F, Ștefan L (2024) The Role of Polyphenols in Modulating PON1 Activity Regarding Endothelial Dysfunction and Atherosclerosis. Int J Mol Sci 25(5):2962. https://doi.org/10.3390/ijms25052962\u003c/li\u003e\n\u003cli\u003eDavies MJ, Aroda VR, Collins BS, Gabbay RA, Green J, Maruthur NM, Rosas SE, Del Prato S, Mathieu C, Mingrone G, Rossing P, Tankova T, Tsapas A, Buse JB. Management of Hyperglycemia in Type 2 Diabetes, 2022. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care \u003cem\u003e45\u003c/em\u003e(11):2753\u0026ndash;2786. https://doi.org/10.2337/dci22-0034\u003c/li\u003e\n\u003cli\u003eKhanna D, Peltzer C, Kahar P, Parmar MS (2022) Body mass index (BMI): a screening tool analysis. Cureus 14(2):e22119. https://doi.org/10.7759/cureus.22119\u003c/li\u003e\n\u003cli\u003eErel O (2004) A novel automated direct measurement method for total antioxidant capacity using a new generation, more stable ABTS radical cation. Clin Biochem 37(4):277-285. https://doi.org/10.1016/j.clinbiochem.2003.11.015\u003c/li\u003e\n\u003cli\u003eErel O (2005) A new automated colorimetric method for measuring total oxidant status. Clin Biochem 38(12):1103-1111. https://doi.org/10.1016/j.clinbiochem.2005.08.008\u003c/li\u003e\n\u003cli\u003eAl-Kuraishy HM, Sami OM, Hussain NR, Al-Gareeb AI (2020) Metformin and/or vildagliptin mitigate type II diabetes mellitus induced-oxidative stress: the intriguing effect. J Adv Pharm Technol Res 11(3):142. https://doi.org/10.4103/japtr.JAPTR_18_20\u003c/li\u003e\n\u003cli\u003eSaglam M, Arikan H, Savci S, Inal-Ince D, Bosnak-Guclu M, Karabulut E, Tokgozoglu L (2010) International physical activity questionnaire: reliability and validity of the Turkish version. Percept Mot Skills 111(1):278-284. https://doi.org/10.2466/06.08.PMS.111.4.278-284\u003c/li\u003e\n\u003cli\u003eRakıcıoğlu N, Tek A, Ayaz A, Pekcan G (2020). Photograph catalog of food and dishes: portion sizes and amounts. 7th ed. Ata Ofset Pub, Ankara, Turkey.\u003c/li\u003e\n\u003cli\u003eIstanbul Beslenme Bilgi Sistemi (BEB_IS) nutrition data base software version 9. Data base: the German food code and nutrient data base (BLS) with additions from USDA-sr and other sources. Stuttgart, Germany: Hohenhim University; 2018. Avaliable from: https://bebis.com.tr/anasayfa.\u003c/li\u003e\n\u003cli\u003eShunmoogam N, Naidoo P, Chilton R (2018) Paraoxonase (PON)-1: a brief overview on genetics, structure, polymorphisms and clinical relevance. Vasc Health Risk Manag 14:137-143. https://doi.org/10.2147/VHRM.S165173\u003c/li\u003e\n\u003cli\u003eGallego PH, Craig ME, Duffin AC, Bennetts B, Jenkins AJ, Hofer S, Lam A, Donaghue KC (2008) Association between p. Leu54Met polymorphism at the paraoxonase-1 gene and plantar fascia thickness in young subjects with type 1 diabetes. Diabetes care 31(8):1585-1589. https://doi.org/10.2337/dc07-2236\u003c/li\u003e\n\u003cli\u003eMoasser E, Azarpira N, Ghorbani dalini A, Shirazi B (2018) Paraoxonase 1 (PON1) gene polymorphism and haplotype analysis in type 2 diabetes mellitus: a case\u0026ndash;control study in the south Iranian population.\u003cem\u003e Int J Diabetes Dev Ctries\u003c/em\u003e 38:62-68. https://doi.org/10.1007/s13410-016-0544-z\u003c/li\u003e\n\u003cli\u003eJiang X, Ding C, Wang C, Yu J, Hua Z, Chen X, Ma J, Chen W (2020) Association of paraoxonase 1 gene polymorphisms and polycystic ovarian syndrome susceptibility: a systematic review and meta-analysis. Gynecol Obstet Invest 85(2):167-177. https://doi.org/10.1159/000505452\u003c/li\u003e\n\u003cli\u003eFlekač M, \u0026Scaron;krha J, Zidkova K, Lacinova Z, Hilgertova J (2008) Paraoxonase 1 gene polymorphisms and enzyme activities in diabetes mellitus. Physiol Res 57(5):717-726. https://doi.org/10.33549/physiolres.931285\u003c/li\u003e\n\u003cli\u003eElattar N, Swelam E, Hamed E, Elnahal A, Mostafa E (2012) Paraoxonase 1 gene polymorphism relationship with type 2 diabetes mellitus. Life Sci J 9(3):1742-1751\u003c/li\u003e\n\u003cli\u003eAltuner D, Ates I, Suzen SH, Koc GV, Aral Y, Karakaya A (2011) The relationship of PON1 QR 192 and LM 55 polymorphisms with serum paraoxonase activities of Turkish diabetic patients. Toxicol Ind Health 27(10):873-878. https://doi.org/10.1177/0748233711399317\u003c/li\u003e\n\u003cli\u003eG\u0026ouml;k\u0026ccedil;en S, Cengiz M, \u0026Ouml;zaydın A (2013) Serum paraoxonase levels and PON1 (192) polymorphism in type 2 diabetes mellitus patients. Gazi Med J 24(3):70-73. doi:http://dx.doi.org/10.12996/gmj.2013.20\u003c/li\u003e\n\u003cli\u003eKoren-Gluzer M, Aviram M, Meilin E, Hayek T (2011) The antioxidant HDL-associated paraoxonase-1 (PON1) attenuates diabetes development and stimulates \u0026beta;-cell insulin release. Atherosclerosis 219(2):510-518. https://doi.org/10.1016/j.atherosclerosis.2011.07.119\u003c/li\u003e\n\u003cli\u003eYu W, Liu X, Feng L, Yang H, Yu W, Feng T, Wang S, Wang J, Liu N (2017) Glycation of paraoxonase 1 by high glucose instigates endoplasmic reticulum stress to induce endothelial dysfunction in vivo. Sci Rep 7(1):45827. https://doi.org/10.1038/srep45827\u003c/li\u003e\n\u003cli\u003eNawaka N, Pansang P, Saniwa A, Chaibut N, Jeenduang N (2021) Paraoxonase 1 (PON1) L55M and Q192R polymorphisms are not associated with chronic kidney disease in Thai individuals with type 2 diabetes. Int J Clin Pract 75(12):e14982. https://doi.org/10.1111/ijcp.14982\u003c/li\u003e\n\u003cli\u003eArpaci A, Yalın S, Ecevit H, Comelekoglu U, Mete T (2020) Enzyme activity and genetic polymorphisms in patients with type II diabetes mellitus. Adv Clin Exp Med 29(9):1057-1063. https://doi.org/10.17219/acem/125397\u003c/li\u003e\n\u003cli\u003eJeelani H, Ganie MA, Amin S, Fatima Q, Kawa IA, Manzoor S, Parvez T, Ahmad DN, Rashid F (2019) Effect of Paraoxonase1 (PON1) gene polymorphisms on PON1 activity, HDL, LDL and MDA levels in women with polycystic ovary syndrome (PCOS): A case-control study. Meta Gene 20:100552. https://doi.org/10.1016/j.mgene.2019.100552\u003c/li\u003e\n\u003cli\u003eRainwater DL, Rutherford S, Dyer TD, Rainwater ED, Cole SA, VandeBerg JL, Almasy L, Blangero J, MacCluer JW, Mahaney MC (2009) Determinants of variation in human serum paraoxonase activity. Heredity 102(2):147-154. https://doi.org/10.1038/hdy.2008.110\u003c/li\u003e\n\u003cli\u003eMeneses MJ, Silvestre R, Sousa-Lima I, Macedo MP (2019) Paraoxonase-1 as a regulator of glucose and lipid homeostasis: impact on the onset and progression of metabolic disorders. Int J Mol Sci 20(16):4049. https://doi.org/10.3390/ijms20164049\u003c/li\u003e\n\u003cli\u003eDeakin S, Leviev I, Nicaud V, Meynet M-CB, Tiret L, James RW, Group EarS (2002) Paraoxonase-1 L55M polymorphism is associated with an abnormal oral glucose tolerance test and differentiates high risk coronary disease families. J Clin Endocrinol Metab 87(3):1268-1273. https://doi.org/10.1210/jcem.87.3.8335\u003c/li\u003e\n\u003cli\u003eSarıkaya U, Meydan S, Selek Ş, Sarıkaya A, Demirel M, G\u0026uuml;l AZ, Yıldız T (2023) Could the PON1 phenotype play a key role in insulin resistance? Int J Diabetes Dev Ctries 43(3):476-481. https://doi.org/10.1007/s13410-022-01096-x\u003c/li\u003e\n\u003cli\u003eFridman O, Gariglio L, Riviere S, Porcile R, Fuchs A, Potenzoni M (2016) Paraoxonase 1 gene polymorphisms and enzyme activities in coronary artery disease and its relationship to serum lipids and glycemia. Arch Cardiol Mex 86(4):350-357. https://doi.org/10.1016/j.acmx.2016.08.001\u003c/li\u003e\n\u003cli\u003ePappa KI, Gazouli M, Anastasiou E, Loutradis D, Anagnou NP (2017) The Q192R polymorphism of the paraoxonase-1 (PON1) gene is associated with susceptibility to gestational diabetes mellitus in the Greek population. Gynecol Endocrinol 33(8):617-620. https://doi.org/10.1080/09513590.2017.1302419\u003c/li\u003e\n\u003cli\u003eSumi A, Nakamura U, Iwase M, Fujii H, Ohkuma T, Ide H, Jodai-Kitamura T, Komorita Y, Yoshinari M, Hirakawa Y (2017) The gene\u0026ndash;treatment interaction of paraoxonase-1 gene polymorphism and statin therapy on insulin secretion in Japanese patients with type 2 diabetes: Fukuoka diabetes registry. BMC Med Genet 18(1):146. https://doi.org/10.1186/s12881-017-0509-1\u003c/li\u003e\n\u003cli\u003eGupta N, Binukumar B, Singh S, Sunkaria A, Kandimalla R, Bhansali A, Gill KD (2011) Serum paraoxonase-1 (PON1) activities (PONase/AREase) and polymorphisms in patients with type 2 diabetes mellitus in a North-West Indian population. Gene 487(1):88-95. https://doi.org/10.1016/j.gene.2011.07.011\u003c/li\u003e\n\u003cli\u003eGupta N, Singh S, Maturu VN, Sharma YP, Gill KD (2011) Paraoxonase 1 (PON1) polymorphisms, haplotypes and activity in predicting cad risk in North-West Indian Punjabis. PLoS One 6(5):e17805. https://doi.org/10.1371/journal.pone.0017805\u003c/li\u003e\n\u003cli\u003eGomathi P, Iyer AC, Murugan PS, Sasikumar S, Raj NBAJ, Ganesan D, Nallaperumal S, Murugan M, Selvam GS (2018) Association of paraoxonase-1 gene polymorphisms with insulin resistance in South Indian population. Gene 650:55-59. https://doi.org/10.1016/j.gene.2018.01.094\u003c/li\u003e\n\u003cli\u003eVaisar T, Kanter JE, Wimberger J, Irwin AD, Gauthier J, Wolfson E, Bahnam V, Wu I-H, Shah H, Keenan HA (2020) High concentration of medium-sized HDL particles and enrichment in HDL paraoxonase 1 associate with protection from vascular complications in people with long-standing type 1 diabetes. Diabetes Care 43(1):178-186. https://doi.org/10.2337/dc19-0772\u003c/li\u003e\n\u003cli\u003eMahrooz A, Khosravi-Asrami OF, Alizadeh A, Mohmmadi N, Bagheri A, Kashi Z, Bahar A, Nosrati M, Mackness M (2023) Can HDL cholesterol be replaced by paraoxonase 1 activity in the prediction of severe coronary artery disease in patients with type 2 diabetes? Nutr Metab Cardiovasc Dis 33(8), 1599\u0026ndash;1607. https://doi.org/10.1016/j.numecd.2023.05.020\u003c/li\u003e\n\u003cli\u003eGrzegorzewska AE, Ostromecka K, Adamska P, Mostowska A, Warchoł W, Jagodziński PP (2020) Paraoxonase 1 gene polymorphisms concerning non-insulin-dependent diabetes mellitus nephropathy in hemodialysis patients. J Diabetes Complications 34(11):107687. https://doi.org/10.1016/j.jdiacomp.2020.107687\u003c/li\u003e\n\u003cli\u003eYounis NN, Durrington PN (2012) HDL functionality in diabetes mellitus: potential importance of glycation. Clin Lipidol 7(5):561-578. https://doi.org/10.2217/clp.12.60\u003c/li\u003e\n\u003cli\u003eKuet O, Kilit T, Kocak E (2022) Comparison of oxidative stress status and quality of life in participants with type 2 diabetes mellitus according to treatment modality. Niger J Clin Pract 25(2):130-136. https://doi.org/10.4103/njcp.njcp_92_20\u003c/li\u003e\n\u003cli\u003eAlu SN, Los EA, Ford GA, Stone WL (2022) Oxidative stress in type 2 diabetes: The case for future pediatric redoxomics studies. Antioxidants 11(7):1336. https://doi.org/10.3390/antiox11071336\u003c/li\u003e\n\u003cli\u003e\u0026Ouml;ztaş B, Eraldemir FC, Kır HM (2022) Serum Paraoxonase 1 as a Biomarker: Features and Applications in Type 2 Diabetes Mellitus. In: Patel, V.B., Preedy, V.R. (eds) Biomarkers in Diabetes. Biomarkers in Disease: Methods, Discoveries and Applications. Springer, Cham. pp 1-13. https://doi.org/10.1007/978-3-030-81303-1_22-1\u003c/li\u003e\n\u003cli\u003eGalicia-Garcia U, Benito-Vicente A, Jebari S, Larrea-Sebal A, Siddiqi H, Uribe KB, Ostolaza H, Mart\u0026iacute;n C (2020) Pathophysiology of type 2 diabetes mellitus. Int J Mol Sci 21(17):6275. https://doi.org/10.3390/ijms21176275\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Type 2 diabetes mellitus, PON1 gene, L55M, Q192R, PON1 activity","lastPublishedDoi":"10.21203/rs.3.rs-5920397/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5920397/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eParaoxonase-1 (PON1) plays a role in the prevention of lipid peroxidation and has been linked to type 2 diabetes mellitus, which is characterised by elevated oxidative stress. In this case-control study, 102 patients with T2DM and 102 healthy controls aged 30 to 60 were included. Anthropometric and body composition measurements of individuals were taken. Total antioxidant status (TAS), total oxidant status (TOS), PON1 activity, and metabolic parameters were analyzed in serum samples of all participants. These samples were genotyped by TaqMan. Dietary antioxidant capacity (DTAC) of individuals was assessed using 3-day food records. No statistically significant difference was observed between groups in the alleles and the genotype frequencies of SNPs. PON1 activity was significantly higher in controls compared to patients with T2DM. Furthermore, RR and LL genotypes were significantly associated with higher PON1 activity. In T2DM patients, HbA1c, fasting blood sugar (FBG), and LDL-cholesterol (LDL-c) were more elevated in all genotypes of the Q192R gene; triglyceride (TG) was higher in QQ and QR genotypes of the gene; TAS was higher in the RR genotype of the gene; and DTAC was lower in the QQ genotype of the gene compared to their respective controls. In controls, LDL-c and TG were lower in all genotypes of the L55M gene; HbA1c and FBG were lower in the LL and LM genotypes of the gene; total body fat was more down in MM genotype, but total body water, fat-free mass, and MET score were higher in MM genotype of the gene compared to their respective controls. Multiple linear regression analyses showed that several factors associated with the activity of PON1 were the PON1 genotypes, HDL-c, TAS, and TOS. Our study supports that the PON1 polymorphisms are associated with PON1 activity, glucose, and lipid metabolism parameters in patients with T2DM.\u003c/p\u003e","manuscriptTitle":"Enzyme Activity and Genetic Polymorphisms of Paraoxonase 1 in Patients With Type 2 Diabetes Mellitus: A Case-Control Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-31 18:05:05","doi":"10.21203/rs.3.rs-5920397/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b8578c67-eab3-47f6-85dd-2ce580039bef","owner":[],"postedDate":"January 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-18T05:54:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-31 18:05:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5920397","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5920397","identity":"rs-5920397","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}