Faculties of 1Nursing and 2Medicine and 5Center for Research in Medical Sciences, Autonomous University of Mexico State, Toluca, Mexico; 3Faculty of Medicine, Universidad de la Sabana, Chía, Colombia; 4Coordination of High Specialty Hospitals, Ministry of Health, Toluca, Mexico *Corresponding Author’s e-mail: mezh_74@yahoo.com العالقة بني َمْنِسب تقييم منوذج االستباب ومستويات األديبونيكنت واللبتني واألنسولني ومنسب كتلة اجلسم املرتبط بتعدد األشكال اجلينية عند املراهقني ماريا دي لو�ص أنجليس مارتينيز-مارتينيز، هوجو منديتا-زيرون، لوي�ص �شيلي�ص، كري�شتيان ليتون-توفار، روكيو توريه-جار�شيا، لورا قوتريز-بليقو، انيدا كاملريو-رومريو، هوزي دي جي�شي�شقارديونو-قار�شيا، ماريا كاملريو-رومريو abstract: Objectives: This study aimed to describe correlations between glucose, insulin and adipokine levels and the homeostasis model assessment (HOMA) index with regards to the presence/absence of fat mass and obesity- associated (FTO) rs9939609 and peroxisome proliferator-activated receptor (PPAR)-y rs1801282 single nucleotide polymorphisms (SNPs) as indicators of body mass index in adolescents. Methods: This cross-sectional study was conducted between September and December 2016 in Toluca, Mexico. A total of 71 students between 14–18 years old were included. Various anthropometric and laboratory measurements were collected, including lipid profile, glucose, insulin and adipokine levels and HOMA index. The degree of association between variables was evaluated with regards to the presence/absence of the SNPs. Results: Leptin levels were significantly higher among female students (P = 0.001), although adiponectin levels did not differ significantly (P = 0.060). There were significant positive correlations between insulin levels and HOMA index with FTO (r = 0.391; P = 0.007 and r = 0.413; P = 0.005, respectively) and PPARγ (r = 0.529; P = 0.007 and r = 0.537; P = 0.007, respectively) SNPs. Leptin showed a significant positive correl- ation in the presence of PPARγ (r = 0.483; P = 0.007) or in the absence of both SNPs (r = 0.627; P = 0.039). However, adiponectin was significantly negatively correlated in the presence of FTO, either alone (r = −0.333; P = 0.024) or in combination with PPARγ (r = −0.616; P = 0.043). Conclusion: The presence of FTO and/or PPARγ SNPs might be related to a genetic predisposition to metabolic syndrome. Keywords: Obesity; Body Mass Index; Single Nucleotide Polymorphisms; Fat Mass and Obesity Associated Protein, Human; Peroxisome Proliferator-Activated Receptor gamma; Adipokines. ال�شتباب منوذج تقييم وَمْن�ِشب والديبونكتني، والأن�شولني اجللوكوز م�شتويات بني العالقات الدرا�شة هذه ت�شف الهدف: امللخ�ص: )FTO rs9939609 و PPARγ rs1801282( ملعرفة وجود اأو عدم وجود تعدد اأ�شكال النوكليوتيدات املفردة ملورثات كتلة الدهن وال�شمنة بح�شبانها موؤ�رسات لكتلة اجل�شم عند املراهقني. الطريقة: اأجريت هذه الدرا�شة امل�شتعر�شة ما بني �شبتمرب ودي�شمرب عام 2016م يف تولو�شا باملك�شيك، و�شارك فيها 71 طالبا يف عمر ما بني 18–14 عاما. ومت اإجراء عدد من القيا�شات الأنرثوبومرتية واملختربية �شملت م�شتويات الدهون واجللكوز والأن�شولني والأديبونيكنت وَمْن�ِشب تقييم منوذج ال�شتباب. ومت تقييم درجة العالقة بني تلك املتغريات ن�شبة ً اإىل وجود ،)P = 0.001( اأو غياب تعدد يف اأ�شكال النوكليوتيدات املفردة. النتائج: كان م�شتوى تركيز اللبتني اأعلى ب�شورة ُمْعَتدٌّة عند الطالبات الإناث غري اأن م�شتوى الديبونكتني مل يتغري ب�شورة ُمْعَتدٌّة )P = 0.060(. وكانت هنالك عالقات اإيجابية بني م�شتويات الن�شولني وَمْن�ِشب تقييم منوذج ال�شتباب وبني اأ�شكال النوكليوتيدات املفردة ملورثات كتلة الدهن وال�شمنة )r = 0.413; P= 0.005 و r = 0.391; P = 0.007، على التوايل(، و PPARγ )r = 0.537; P = 0.007 و r = 0.529; P = 0.007، على التوايل(، وجد هناك عالقة طردية إيجابية لهرمون الليبتني بوجود PPARγ (r = 0.483; P = 0.007) اأو يف غياب �شكلي النوكليوتيدات املفردة (P ;r = 0.627 = 0.039). غري اأن م�شتوى الديبونكتني كان .)r = -0.616; P = 0.043( PPARγ اأو يف وجود )r = -0.333; P = 0.024( يتنا�شب �شلبيا مع وجود مورثات كتلة الدهن وال�شمنة، اإما مبفرده الوراثي بال�شتعداد عالقة PPARγ ل املفردة النوكليوتيدات اأ�شكال و/اأو وال�شمنة الدهن كتلة مورثات لوجود يكون اأن ميكن اخلال�صة: لالإ�شابة باملتالزمة الأي�شية )ال�شتقالبية(. الكلمات املفتاحية: ال�شمنة؛ موؤ�رس كتلة اجل�شم؛ تعدد اأ�شكال النوكليوتيدات املفردة؛ الربوتني املرتبط بكتله الدهن وال�شمنة، اإِْن�شان؛ PPARγ؛ الأديبوكاينز. Correlation of the Homeostasis Model Assessment Index and Adiponectin, Leptin and Insulin Levels to Body Mass Index-Associated Gene Polymorphisms in Adolescents María D. Martínez-Martínez,1 *Hugo Mendieta-Zerón,2 Luis Celis,3 Cristian F. Layton-Tovar,4 Rocío Torres-García,5 Laura E. Gutiérrez-Pliego,5 Eneida Camarillo-Romero,5 José D. Garduño-García,5 María D. Camarillo-Romero5 clinical & basic research Sultan Qaboos University Med J, August 2018, Vol. 18, Iss. 3, pp. e291–298, Epub. 19 Dec 18 Submitted 31 Jan 18 Revision Req. 25 Feb 18; Revision Recd. 13 Mar 18 Accepted 5 Apr 18 doi: 10.18295/squmj.2018.18.03.005 Advances in Knowledge - Certain single nucleotide polymorphisms (SNPs) have been associated with obesity and insulin resistance. However, current data are conflicting regarding the roles of the fat mass and obesity-associated (FTO) rs9939609 and peroxisome proliferator-activated receptor (PPAR)-y rs1801282 SNPs in this regard. Correlation of the Homeostasis Model Assessment Index and Adiponectin, Leptin and Insulin Levels to Body Mass Index-Associated Gene Polymorphisms in Adolescents e292 | SQU Medical Journal, August 2018, Volume 18, Issue 3 Obesity is a multifactorial disease deter- mined by a complex interaction between genetic and environmental factors. Previous research has associated an obesogenic phenotype with the presence of specific polymorphisms also linked to the development of insulin resistance, diabetes mellitus and metabolic syndrome.1 Moreover, pancreatic function may be altered by mutations that cause changes in the activity or expression of proteins involved in the regul- ation of basal energy expenditure; the latter phenomenon is explained in part by the various mechanisms of oxid- ative phosphorylation. Although the effect of each indiv- idual gene or combination of different genetic variants on metabolism and thermogenesis is uncertain, this may explain why certain individuals have a greater tendency to develop metabolic disorders.2 In recent decades, efforts have intensified in the search for single nucleotide polymorphisms (SNPs) caus- ing observed changes in the signalling pathways that regulate metabolic processes, leading to failures in energy homeostasis and predisposing individuals to diabetes and obesity.3 Peroxisome proliferator-activated receptors (PPARs) are a group of nuclear receptor proteins that function as transcription factors. These receptors are present in different metabolic pathways related to energy homeostasis, in addition to the lipid route. So far, three PPAR isoforms have been identified; the PPARγ isoform, which is highly expressed in white adipose tissue, is involved in lipid storage and energy dissipation and is recognised to be the master regulator of adipogenesis.4 The fat mass and obesity-associated (FTO) gene is comp- osed of nine exons on chromosome 16 (16q12.2).5 It was the first gene to be associated with obesity in genome- wide association studies.6 Frayling et al. observed that adults with the FTO rs9939609 SNP had a 1.67-fold incr- eased risk of obesity and weighed an average of 3–4 kg more than those without this polymorphism.7 In Mexico, genomic studies have demonstrated several genetic ancestries for the local population.8 How- ever, this implies that there may be discrepancies in the role of some SNPs in the presence of obesity-related conditions, such as metabolic syndrome. This study aimed to identify correlations between glucose, insulin and adipokine levels and the homeostasis model assess- ment (HOMA) index with regards to the presence or absence of FTO rs9939609 and PPARy rs1801282 SNPs as indicators of body mass index (BMI) in Mexican adolescents. Methods This cross-sectional study was conducted from Sept- ember to December 2016 at the Autonomous University of Mexico State (UAEM) in Toluca, Mexico. All adolesc- ents between 14–18 years old attending the Lic. Adolfo López Mateos Preparatory School in Toluca were invited to participate in the study. The exclusion criteria incl- uded a history of smoking, being pregnant or having been diagnosed with a chronic or acute disease. The sample size was calculated as follows:9 where n is the infinite population of available partic- ipants (981 adolescents), z is the 95% confidence level (1.96), p is the estimated percentage of the studied poly- morphisms in the total population (30%), ε is the margin of error set at 11% with a replacement rate of 9%, n' is the required finite sample size and N is the population size. Based on this, the required sample size was set at 68 adolescents. A body composition monitor was used to measure the subjects’ weight (BC-533 InnerScan Body Comp- osition Monitor®, Tanita Corp., Tokyo, Japan), while a standard stadiometer was used to measure height. BMI was calculated as weight in kg divided by height in m2. According to gender- and age-specific World Health Organization BMI classifications for adolescents, the participants were categorised as either normal, over- weight (≥1 standard deviation [SD] of the z score) or obese (≥2 SD of the z score).10 Waist and hip circumfer- ences were measured using a fibreglass tape to the nearest 0.1 cm and waist-to-height and waist-to-hip ratios calcul- ated accordingly. Blood pressure was checked by auscult- ation using a sphygmomanometer with an appropriately sized cuff. Systolic and diastolic hypertension was det- ermined according to the criteria for high blood pressure in children and adolescents from the National High Blood Pressure Education Program Working Group.11 After a fasting period of 8 hours, 3 mL of venous blood were drawn from participants and collected into BD Vacutainer® tubes (Becton, Dickinson and Co., Fran- klin Lakes, New Jersey, USA). Using enzymatic methods, concentrations of glucose, uric acid, total cholesterol, - The current study found that certain adipokines were significantly correlated with FTO and PPARγ expression. Application to Patient Care - Determining the presence or absence of FTO and PPARy SNPs among adolescents might help in the design and implementation of more intensive obesity prevention strategies in this population. z2 × p(1-p) n z2 × p(1-p) ε2 N n = n’ = ε2 1 + María D. Martínez-Martínez, Hugo Mendieta-Zerón, Luis Celis, Cristian F. Layton-Tovar, Rocío Torres-García, Laura E. Gutiérrez-Pliego, Eneida Camarillo-Romero, José D. Garduño-García and María D. Camarillo-Romero Clinical and Basic Research | e293 high-density lipoproteins (HDLs), low-density lipoproteins (LDLs) and triglycerides were determined according to the manufacturer’s instructions for each reagent assay kit (Randox Laboratories Ltd., Crumlin, County Antrim, UK). The participants’ thyroid profiles were measured by radioimmunoassay, whereas adiponectin, insulin and leptin levels were determined using the 900 series Invitr- ogen® enzyme-linked immunosorbent assay (Thermo Fisher Scientific Inc., Pittsburgh, Pennsylvania, USA). One sample remained frozen at -70 °C until DNA extr- action. The atherogenic index of plasma (AIP) was calcul- ated as total cholesterol divided by HDL. The HOMA index for insulin resistance was calculated as follows:12 where fPI is fasting plasma insulin and fPG is fasting plasma glucose. A diagnosis of metabolic syndrome was based on the criteria of the International Diabetes Feder- ation (IDF) and adjusted for age.13 DNA extraction was performed using the MagNA Pure LC 2.0 Instrument and MagNA Pure LC DNA Isolation Kit 1 (Roche Diagnostics GmbH, Manheim, Germany). Results were quantified using the N60 Nano- Photometer® (Implen GmbH, Munich, Germany), rep- orting the concentration (in μg/mL) and purity (the ratio of the absorbance of 260/280 nm). Genotyping was performed by polymerase chain reaction analysis in a Life ECO® thermal cycler (Bioer Technology Co. Ltd., Hangzhou, China). The primers and conditions for each polymorphism are listed in Table 1.14 Oligo- nucleotides were designed using the PrimerQuest® web tool (Integrated DNA Technologies Inc., Skokie, Illinois, USA) and synthesised at the Institute of Bio- technology, National Autonomous University of Mexico, Cuernavaca, Morelos, Mexico. The Basic Local Align- ment Search Tool® (National Library of Medicine, Bethesda, Maryland, USA) was used to verify the correct hybridisation. The final products were visualised in 2% agarose gel, stained with ethidium bromide and digitally documented using an ultraviolet transillum- inator system (Gel Logic 212 Pro, Carestream Health, Rochester, New York, USA) [Figure 1]. Sequencing was performed at the National Institute of Genomic Medicine in Mexico City to confirm the detection of polymorphisms as per previously described methods.14 Statistical analyses were performed using the Stat- istical Package for the Social Sciences (SPSS), Version 19 (IBM Inc., Armonk, New York, USA). Descriptive continuous data were presented as means and SDs while qualitative variables were expressed as percentages. Either the Student’s t-test or Mann-Whitney U test were used, depending on whether the variables were normally distributed. Using Pearson’s correlation coeff- icient, the degree of association between glucose, insulin and adipokine levels, AIP and HOMA index were eval- uated in two different settings, the first being the absence of either SNP and the second being the presence of either or both SNPs. Multivariate linear modelling was perf- ormed to establish the possible effect of the presence of polymorphisms and gender on lipid profile. A linear regression model weighted by gender was used to det- ermine whether very-low-density lipoprotein (VLDL), LDL, HDL and triglyceride levels were predictors of HOMA index. A linear regression analysis was also used fPI × fPGHOMA index = 22.5 Figure 1: Agarose gel electrophoresis image of poly- merase chain reaction amplification products showing the presence of a fat mass and obesity-associated (FTO) polymorphism. Lane one contains the molecular marker, lanes 2–8 contain amplified FTO gene DNA fragments, lane nine contains the positive control and lane 10 contains the negative control. Table 1: Primers and polymerase chain reaction cond- itions for the studied polymorphisms14 Polymorphism FTO PPARγ Accession number* NG_012969.1 XM_011533843.2 Variant rs9939609 rs1801282 Forward primer tggctcttgaatgaatag- gattcagaa ccaattcaagcccagtcctttc Reverse primer agcctctctaccatcttat- gtccaaaca cagtgaaggaatcgctttccg PCR conditions Denaturation - 10 minutes at 95 °C 15 seconds at 95 °C 30 seconds at 60 °C 30 seconds at 72 °C Extension end cycle - 5 minutes at 72 °C FTO = fat mass and obesity-associated; PPAR = peroxisome proliferator-activated receptor; PCR = polymerase chain reaction. *From the National Center for Biotechnology Information database. }× 40 cycles Correlation of the Homeostasis Model Assessment Index and Adiponectin, Leptin and Insulin Levels to Body Mass Index-Associated Gene Polymorphisms in Adolescents e294 | SQU Medical Journal, August 2018, Volume 18, Issue 3 to test BMI as the dependent variable and age as the independent variable according to gender and weighted by the presence of polymorphisms. A P value of ≤0.050 was considered statistically significant. This study was approved by the Institutional Review Board of the Medical Sciences Research Center at UAEM (#2015/14). All subjects and their parents/guardians provided informed consent prior to participation in the study. All of the study procedures were in line with the ethical standards of the revised Declaration of Helsinki as well as the Mexican Standard for the Implementation of Projects of Research for Health in Humans (#NOM-012-SSA3-2012). Results A total of 71 adolescents were included in the study, of which 40 (56.3%) were female and 31 (43.7%) were male. The mean age was 15.7 ± 0.7 years and the mean BMI was 24.5 ± 3.8 kg/m2. Based on the IDF criteria, 21.1% of the subjects had metabolic syndrome.13 Never- theless, 56 adolescents (78.8%) were positive for at least one diagnostic criterion of metabolic syndrome, with high triglyceride levels being most frequently observed (52%). In terms of family history, 14 (19.7%) and 16 (22.5%) adolescents had a mother or father, respectively, with metabolic disease. Interesting, 39 adol- escents (54.9%) had relatives affected by chronic disease; however, none of these individuals had been diagnosed with hypothyroidism. According to gender, there was a statistically signif- icant difference among the participants in terms of weight, height, waist-to-hip ratio and cholesterol, HDL, leptin and uric acid levels (P <0.050 each) [Table 2]. Age and leptin levels showed a non-parametric distribution. Although FTO SNPs were more frequent among females, this difference was not statistically significant (χ2 = 2.4671; P = 0.116). Similarly, there was a non-significant incr- ease in PPARγ SNP frequency among males (χ2 = 1.2884; P = 0.256). There was no difference according to gender in terms of the presence of both SNPs (χ2 = 0.2819; P = 0.595) [Table 3]. According to a linear regression analysis weighted by gender, VLDL, HDL, LDL and tri- glyceride levels significantly influenced HOMA index (P ≤0.001). Similar results were observed among adol- escents with FTO or PPARγ SNPs (P = 0.002) as well as those without PPARγ polymorphisms (P = 0.035). Table 2: Anthropometric and laboratory variables according to gender among adolescents in Toluca, Mexico (N = 71) Variable Mean ± SD P value Total Females (n = 40) Males (n = 31) Age in years 15.7 ± 0.7 15.7 ± 0.7 15.8 ± 0.7 0.525 Height in m 1.63 ± 0.09 1.57 ± 0.06 1.70 ± 0.07 ≤0.001 Weight in kg 65.8 ± 13.8 59.4 ± 9.6 74.0 ± 14.2 ≤0.001 BMI in kg/m2 24.5 ± 3.8 23.9 ± 3.8 25.3 ± 3.7 0.111 WHR 0.86 ± 0.06 0.84 ± 0.0 0.88 ± 0.06 0.006 Adiponectin in µg/nL 12.9 ± 4.4 13.8 ± 4.2 11.8 ± 4.4 0.060 Glucose in mg/dL 91.9 ± 6.4 90.7 ± 4.9 93.4 ± 7.8 0.079 Insulin in IU/mL 14.6 ± 8.3 14.5 ± 8.2 14.8 ± 8.5 0.899 HOMA index 3.03 ± 1.83 2.96 ± 1.7 3.11 ± 1.92 0.743 Cholesterol in mg/dL 168.9 ± 37.9 179.3 ± 40.2 156.0 ± 30.7 0.010 HDL in mg/dL 42.5 ± 10.7 45.7 ± 11.1 38.67 ± 8.9 0.006 Leptin in ng/mL 18.0 ± 1.6 23.3 ± 15.7 11.0 ± 14.0 0.001 LDL in mg/dL 107.1 ± 31.8 112.0 ± 34.0 100.9 ± 28.2 0.149 Triglycerides in mg/dL 131.8 ± 72.1 131.2 ± 63.3 132.5 ± 82.9 0.939 Uric acid in mg/dL 4.4 ± 1.4 3.6 ± 1.0 5.3 ± 1.3 ≤0.001 VLDL in mg/dL 19.2 ± 12.2 21.5 ± 12.5 16.3 ± 11.3 0.080 AIP 4.0 ± 0.9 4.0 ± 1.0 4.1 ± 0.8 0.743 SD = standard deviation; BMI = body mass index; WHR = waist-to-hip ratio; HOMA = homeostatic model assessment; HDL = high-density lipoprotein; LDL = low-density lipoprotein; VLDL = very-low-density lipoprotein; AIP = atherogenic index of plasma. María D. Martínez-Martínez, Hugo Mendieta-Zerón, Luis Celis, Cristian F. Layton-Tovar, Rocío Torres-García, Laura E. Gutiérrez-Pliego, Eneida Camarillo-Romero, José D. Garduño-García and María D. Camarillo-Romero Clinical and Basic Research | e295 Overall, the PPARγ SNP was present in 25 adol- escents (35.2%) and the FTO SNP was present in 46 (64.8%), including 11 cases (15.5%) in which both PPARγ and FTO SNPs were present. Neither SNP was present in 11 individuals (15.5%). Insulin levels and HOMA index were statistically correlated with the presence of FTO (P = 0.007 and 0.005, respectively), PPARγ (P = 0.007 each) and both SNPs combined (P = 0.039 and 0.029, respectively). While leptin showed a positive significant correlation in the presence of PPARγ (r = 0.483; P = 0.014) and in the absence of either SNP (r = 0.627; P = 0.039), adiponectin was significantly negatively correlated with FTO, either alone (r = −0.333; P = 0.024) or in combin- ation with PPARγ (r = −0.616; P = 0.043) [Table 4]. A multivariate linear model showed that the presence of the SNPs were not determinants of BMI and lipid profile. However, the effect of gender was significant (P <0.050), particularly in the setting of both SNPs together (P = 0.021) [Table 5]. Discussion Worldwide, various studies of different ethnic popul- ations have shown conflicting results regarding the relationship between body weight and FTO and PPARγ polymorphisms. For example, the PPARγ Pro12Ala rs1801282 polymorphism has been associated with obesity and insulin resistance among Asian Indians; however, in a Chinese sample, it was reported to be a protective factor against type 2 diabetes and obesity.15,16 Huang et al. found that the presence of the rs2282440- SDC3T/T genotype alongside the rs1801282 PPARγ2 carrier genotype was strongly associated with obesity.17 On the other hand, Queiroz et al. found that PPARγ rs1801282 conferred a higher risk of altered insulin levels and HOMA index for insulin resistance among overweight adolescents.18 To some extent, the latter obs- ervation is consistent with the results of the present study. A previous study demonstrated that circulating lipids in Mexican children modified the association between the PPARγ2 rs1801282 genotype and insulin resistance.19 In the current study, significant associations were noted between HOMA index and the presence of FTO or PPARγ polymorphisms, taking into account the role of lipids and weighted by gender. In Asiatic populations, FTO has been associated with an increased risk of obesity and type 2 diabetes.20 Saldaña-Alvarez et al. found that FTO SNPs made differential contributions to obesity risk, supporting the hypothesis that mechanisms involving these variants are gender-dependent and that these changes may contribute to disease development.21 Although the researchers evaluated different FTO SNPs (rs1121980, rs17817449, rs3751812, rs9930506 and rs17817449) to that of the present study (rs9939609), such findings confirm the possibility that gender is a risk Table 4: Correlations between glucose, insulin and adipokine levels and homeostasis model assessment index with body mass index-related polymorphisms among adolescents in Toluca, Mexico (N = 71) Variable Polymorphisms Neither FTO nor PPARγ (n = 11) FTO (n = 46)* PPARγ (n = 25)* Both FTO and PPARγ (n = 11) r P value r P value r P value r P value Glucose 0.303 0.365 0.272 0.070 0.090 0.675 0.292 0.413 Insulin 0.600 0.051 0.391 0.007 0.529 0.007 0.627 0.039 HOMA index 0.600 0.051 0.413 0.005 0.537 0.007 0.685 0.029 Leptin 0.627 0.039 0.248 0.096 0.483 0.014 0.221 0.513 Adiponectin −0.323 0.332 −0.333 0.024 −0.110 0.599 −0.616 0.043 AIP 0.721 0.012 0.463 0.001 0.192 0.368 0.487 0.154 FTO = fat mass and obesity-associated; PPAR = peroxisome proliferator-activated receptor; HOMA = homeostasis model assessment; AIP = ather- ogenic index of plasma. *Including the 11 adolescents with both polymorphisms. Table 3: Frequency of body mass index-related polymor- phisms according to gender among adolescents in Toluca, Mexico (N = 71) Polymorphism n (%) P value Total Females (n = 40) Males (n = 31) Neither FTO nor PPARγ 11 (15.5) 4 (10) 7 (22.6) 0.146 FTO alone 35 (49.3) 23 (57.5) 12 (38.7) 0.116 PPARγ alone 14 (19.7) 6 (15) 8 (25.8) 0.256 Both FTO and PPARγ 11 (15.5) 7 (17.5) 4 (12.9) 0.595 FTO = fat mass and obesity-associated; PPAR = peroxisome proliferator -activated receptor. Correlation of the Homeostasis Model Assessment Index and Adiponectin, Leptin and Insulin Levels to Body Mass Index-Associated Gene Polymorphisms in Adolescents e296 | SQU Medical Journal, August 2018, Volume 18, Issue 3 factor for obesity.17 Similarly, these results are supported by those of Huđek et al., who found a statistically signif- icant positive correlation between frequencies of high- risk FTO genotypes in obese women (AA rs9939609, CC rs1421085 and GG rs17817449).22 Díaz-Anzaldúa et al. reported that differences in mean BMI levels among Mexican patients with bipolar disorder were explained by the presence of FTO rs8050136 and rs9939609 genotypes.23 Another study showed that the locus of the FTO gene was significantly associated with increased BMI in indigenous Mexican populations.24 Muñoz-Yáñez et al. found that FTO rs9939609 polymorphisms were associated with obesity- related traits, including elevated BMI, cholesterol and LDL levels, tricep skinfolds and an increased waist circumference and waist-to-height ratio.25 In the present study, an extremely high percentage of adolescents had FTO SNPs (64.8%). Given a population of approxim- ately nine million Mexicans aged 15–20 years old, there are an estimated 5,830,200 young people with FTO rs9939609 polymorphisms and, therefore, a corresp- onding risk of obesity.26 Such findings are alarming for the local healthcare system. Fortunately, despite a genetic predisposition influenced by polymorphisms, obesity is a modifiable condition, even with a positive genetic profile risk score.27 In the PREDIMED-NAVARRA randomised trial, PPARγ Pro12Ala rs1801282 carriers exhibited lower telomere shortening compared to those with the Pro/Pro geno- type after five years of adherence to a Mediterranean- style diet.28 Unfortunately, the molecular effects of a traditional Mexican diet have yet to be fully elucidated. In the current study, mean HDL levels were significantly higher among females. However, this may be because the mean level for males was below recomm- endations reported for the Mexican population.29 In addition, female students also had significantly higher leptin levels. Although leptin is a significant predictor of carotid intima media thickness, previous research has confirmed that men suffer from higher cardiovascular- related mortality compared to women.30,31 Such findings undermine the epidemiological evidence for utilising leptin as a prognostic tool for cardiovascular disease in adolescents. As in previous research, females in the current study also demonstrated significantly higher cholesterol levels.32 A strong correlation has been established bet- ween cholesterol and visceral adipose tissue as quantified by dual-energy X-ray absorptiometry.33 Unfortunately, this technique was not utilised in the present study. Finally, the frequency of metabolic disease among the parents of the studied adolescents was lower than exp- ected; instead, students’ relatives were found to have a high rate of chronic disease. However, it is unclear whether these individuals had lipid-related abnormalities. It is worth noting that various researchers have recommended lowering BMI cut-off values for over- Table 5: Multivariate linear model for body mass index- related polymorphisms and gender as determinants for body mass index and lipid profile Variable Statistical test Value* F value P value FTO Pillai’s trace 0.066 1.027 0.401 Wilks’ lambda 0.934 1.027 0.401 Lawley-Hotelling trace 0.071 1.027 0.401 Roy’s largest root 0.071 1.027 0.401 PPARγ Pillai’s trace 0.107 1.738 0.154 Wilks’ lambda 0.893 1.738 0.154 Lawley-Hotelling trace 0.120 1.738 0.154 Roy’s largest root 0.120 1.738 0.154 Gender Pillai’s trace 0.162 2.797 0.034 Wilks’ lambda 0.838 2.797 0.034 Lawley-Hotelling trace 0.193 2.797 0.034 Roy’s largest root 0.193 2.797 0.034 FTO × PPARγ Pillai’s trace 0.105 1.697 0.163 Wilks’ lambda 0.895 1.697 0.163 Lawley-Hotelling trace 0.117 1.697 0.163 Roy’s largest root 0.117 1.697 0.163 FTO × gender Pillai’s trace 0.040 0.607 0.659 Wilks’ lambda 0.960 0.607 0.659 Lawley-Hotelling trace 0.042 0.607 0.659 Roy’s largest root 0.042 0.607 0.659 PPARγ × gender Pillai’s trace 0.032 0.477 0.752 Wilks’ lambda 0.968 0.477 0.752 Lawley-Hotelling trace 0.033 0.477 0.752 Roy’s largest root 0.033 0.477 0.752 FTO × PPARγ × gender Pillai’s trace 0.178 3.143 0.021 Wilks’ lambda 0.822 3.143 0.021 Lawley-Hotelling trace 0.217 3.143 0.021 Roy’s largest root 0.217 3.143 0.021 FTO = fat mass and obesity-associated; PPARγ = peroxisome proliferator -activated receptor. *The degrees of freedom of hypothesis and error were 4.000 and 58.000, respectively, for each value. María D. Martínez-Martínez, Hugo Mendieta-Zerón, Luis Celis, Cristian F. Layton-Tovar, Rocío Torres-García, Laura E. Gutiérrez-Pliego, Eneida Camarillo-Romero, José D. Garduño-García and María D. Camarillo-Romero Clinical and Basic Research | e297 weight and obese categories in Mexican and Asiatic populations.34,35 Thus, if a BMI of ≥27 kg/m2 were cons- idered to indicate obesity, 31% of the adolescents in the current study would have been considered obese. Males were significantly heavier than females; this was accordingly reflected by slight elevations in glucose and insulin levels and HOMA index. However, these differences were not significant, possibly due to simil- arities in BMI in both genders. Therefore, further studies are recommended including other variables which could influence BMI in adolescents, such as physical activity and dietary habits.36 Another limitation of this study was the small sample size; nevertheless, investigations regarding associations between polymorphisms and clinical parameters for metabolic syndrome or obesity can be clinically significant in small samples.37 Conclusion The results of this study suggest significant positive correlations between insulin levels and HOMA index with BMI-related FTO rs9939609 and/or PPARγ rs180- 1282 polymorphisms. Future epidemiological studies are recommended to determine the net causative effect of such gene variants so as to halt the development of a pandemic of obesity-related health problems. Although the main causes of obesity, diabetes and metabolic syndr- ome are lifestyle factors, the role of such polymorphisms could help to explain why some individuals have a greater tendency to develop metabolic disorders and are more resistant to weight control interventions than others. c o n f l i c t o f i n t e r e s t The authors declare no conflicts of interest. f u n d i n g This study was funded with the aid of a grant from the Mexican Ministry of Education (grant #PROMEP/ 2013/CA-186/103105/13/9057). a c k n o w l e d g e m e n t s The preliminary version of this study was submitted as a M.Sc. thesis to the UAEM in 2016. This version is available on the university website. References 1. Kasim NB, Huri HZ, Vethakkan SR, Ibrahim L, Abdullah BM. Genetic polymorphisms associated with overweight and obesity in uncontrolled type 2 diabetes mellitus. Biomark Med 2016; 10:403–15. doi: 10.2217/bmm-2015-0037. 2. Kong X, Zhang X, Xing X, Zhang B, Hong J, Yang W. 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