Literature DB >> 32154826

Genetic variants in the fat mass and obesity-associated (FTO) gene confer risk for extreme obesity and modulate adiposity in a Brazilian population.

Ana Carolina Proença da Fonseca1, Bruna Marchesini1, Verônica Marques Zembrzuski1, Danielle Dutra Voigt2, Vivianne Galante Ramos2, João Regis Ivar Carneiro3, José Firmino Nogueira Neto4, Giselda Maria Kalil de Cabello1, Pedro Hernán Cabello1,2.   

Abstract

Obesity is a major public health problem worldwide. It has a complex etiology, influenced by environmental and genetic factors. FTO has been recognized as an important genetic factor for obesity development. This study evaluated the contribution of FTO polymorphisms (rs9939609 and rs17817449) for extreme obesity in terms of the period of obesity onset, anthropometric, and biochemical parameters. The haplotype and the combined effects of FTO risk alleles on obesity susceptibility were evaluated. We investigated 169 normal-weight subjects (body mass index, BMI: 22.8 [21.0; 24.0] kg/m2) and 123 extremely obese individuals (BMI: 47.6 [44.1; 53.1] kg/m2). Genotyping was performed by real time PCR. Our results showed a strong association between FTO variants and extreme obesity. Carriers of the AT haplotype had an increased risk for extreme obesity. Gene scores suggested that the risk of developing extreme obesity was increased 1.37-fold per risk allele added. Both polymorphisms also influenced BMI and body weight. Additionally, rs17817449 influenced triglyceride levels. No effect of FTO variants on the period of obesity onset was found. In conclusion, the FTO polymorphisms showed a strong association with development of extreme phenotype of obesity and adiposity modulation in a Brazilian population.

Entities:  

Year:  2020        PMID: 32154826      PMCID: PMC7197983          DOI: 10.1590/1678-4685-GMB-2018-0264

Source DB:  PubMed          Journal:  Genet Mol Biol        ISSN: 1415-4757            Impact factor:   1.771


Introduction

Obesity (body mass index, BMI ≥ 30 kg/m2) is defined as an increase in body fat mass that is sufficient to cause adverse health effects. Over the last three decades, the prevalence of obesity has increased rapidly, affecting low-, middle-, and high-income countries. Recent data estimate that there are at least 600 million obese people in the world. In Brazil, 20% of the population was obese in 2015 (WHO, 2018). Epidemiological studies have shown that subjects with severe obesity and morbid obesity (BMI ≥ 35 kg/m2 and BMI ≥ 40 kg/m2, respectively) have a substantial increase in the risk of comorbidities and mortality. Furthermore, this elevated BMI was associated with 6.5–13.7 years lost in life expectancy (Kitahara ). The prevalence of severe obesity in women is three times higher than men in Brazil. There are 6.7 million women with this disease, whereas only 2.2 million men. Currently, the prevalence of morbid obesity is nearly 1.1% in the world (NCD Risk Factor Collaboration, 2016). Obesity is a multifactorial disease, influenced by environmental and genetic factors (Grundy, 1998). Researchers have been making a continuous effort to identify genes and variants that predispose individuals to common forms of obesity (Rankinen ; Fonseca ). Nowadays, over 291 loci were found associated with obesity, involved in different biological pathways, including adipocyte differentiation, lipid metabolism, thermogenesis, and food intake control (Wu ). Among the genes, the association of fat mass and obesity-associated gene (FTO) with obesity susceptibility was confirmed. Different groups identified that common variants in the first intron of FTO are associated with an increased body fat mass in humans (Dina ; Frayling ; Scuteri ). Besides the association with obesity, FTO variants have also been correlated to body composition and obesity-related traits (Scuteri ; Shabana and Hasnain, 2015). FTO encodes a Fe(II)- and 2-oxoglutarate (OG)-dependent nucleic acid demethylase that is localized in the cell nucleus. The highest levels of FTO mRNA are found in the hypothalamus, particularly in the arcuate nucleus. This area of the brain has an important role in controlling food intake, which suggests that FTO may act in the management of energy balance (Gerken ). Located in chromosome 16, the FTO gene spans for more than 400 kb and has nine exons. Despite the large size of this gene, most of the variations that were associated with obesity are found in the first intron (Loos and Bouchard, 2008). The influence of FTO variants on the risk of obesity is consistent in Caucasian studies (Dina ). However, apparently it is not relevant in African Americans, Chinese Han, and Native Oceanic populations (Ohashi ; Scuteri ; Li ). In Brazil, few studies have analyzed the relationship between FTO rs9939609 polymorphism and obesity susceptibility. Reuter studied the association between this polymorphism and overweight/obesity risk in a sample of youths from the South of Brazil. They observed that the rs9939609 was associated with BMI and waist circumference. Pereira have performed a similar study with children; however, they did not find this association. Ramos investigated the contribution of this polymorphism in morbid obesity risk. They analyzed 126 morbidly obese individuals and 113 controls from Minas Gerais, in the southeastern region of Brazil. Their result suggested that presence of the rs9939609(A) allele increased the risk for obesity. These divergent results may be explained by differences in the inclusion criteria of participants, as well as environmental and genetic backgrounds. Therefore, more studies are needed to elucidate the association of FTO rs9939609 and obesity development in Brazil. In addition, we also selected the FTO rs17817449 polymorphism for analysis. To date, no study was performed with this polymorphism in the Brazilian population. The aim of our study was to evaluate the role of the FTO rs9939609 and rs17817449 polymorphisms in the risk of extreme obesity, period of obesity onset, and in relation to anthropometric and biochemical parameters. We also investigated the influence of haplotype and the combined effect of FTO variants on extreme obesity development.

Materials and Methods

Subjects

This cross-sectional case-control study comprised 292 unrelated individuals (68.2% female and 31.8% male), aged 18 to 65 years (median, 33.0 [26.0; 43.0]), from Rio de Janeiro, southeast of Brazil. The participants were divided into two groups according to BMI (calculated by dividing weight [kilograms] by the height squared [meters]). The exclusion criteria were pregnancy, lactation, and the use of medication to lose or gain weight. The first group included 123 subjects with extreme obesity (BMI ≥ 40.0 kg/m2) recruited from a non-governmental organization called to Self-Esteem and Citizenship Rescue Group for the Obese (in Portuguese, “Grupo de Resgate à Autoestima e Cidadania do Obeso”). These patients were candidates for bariatric surgery. The period of obesity onset was self reported. The second group included 169 individuals with normal weight (18.5 ≤ BMI ≤ 24.9 kg/m2) that were volunteers in public hospitals in the same city. The study protocol was performed according to the Declaration of Helsinki (1964). All participants provided written consent prior to their inclusion in this study and the protocol was approved by Ethics Committee of the Oswaldo Cruz Foundation.

Anthropometric measurements

Height, weight, and waist and hip circumference were measured by a trained person. Waist circumference was measured at the midpoint between the iliac crest and the last costal arch. Hip circumference was measured at the level of the greater trochanters. BMI and waist to hip ratio (WHR) were then calculated for each subject.

Biochemistry

Serum samples were collected and clinical variables were measured after an overnight fast. Glucose, total cholesterol (TC), HDL-cholesterol (HDL-c), and triglyceride (TG) were measured by the oxidase-peroxidase method (BioSystems). LDL-cholesterol (LDL-c) was calculated by the Friedewald formula (LDL-c = TC – HDL-c – TG/5). Individuals using medication for these biochemical parameters had their levels excluded from statistical analysis.

Demographic characteristics

Practice of physical activity was categorized as “yes” or “no” according to the participant’s report of the last month. The classification of the Demographic Census conducted by the Brazilian Institute of Geography and Statistics was used to categorize the race/skin color of participants (white, brown, black, and others [yellow or indigenous]). All information was self reported and collected using standardized questionnaires.

Single nucleotide polymorphism (SNP) genotyping

Genomic DNA was extracted from peripheral white blood cells using a commercial DNA extraction kit (QIAamp Blood Kit, Qiagen, Valencia, CA, USA). FTO rs9939609 and rs17817449 polymorphisms were genotyped by real time PCR using TaqMan® assays (ThermoFisher, Carlsbad, CA, USA). Reactions were performed in 10 μL volumes, including 2–10 ng of DNA, Universal Master Mix 1X, and TaqMan Genotyping Assay 1X specific for each polymorphism studied. Amplification was carried out in a StepOne® Plus Real Time PCR System (ThermoFisher) using the number of cycles and temperatures according the manufacturer’s recommendations. All plates included a negative control (all components excluding DNA).

Statistical analysis

Normality of continuous variables was tested by Kolmogorov-Smirnov and Shapiro Wilk tests. All continuous parameters had a non-normal distribution. Differences of clinical, biochemical, and anthropometric parameters between case and control groups were compared by Mann Whitney and χ2 tests. Genotype and allele frequencies were estimated by gene counting. Hardy-Weinberg equilibrium (HWE) was tested for each polymorphism using the χ2 test. Logistic regression was carried out in order to analyze the association between FTO polymorphisms and the risk for extreme obesity. All analyses were adjusted for age and gender (model 1) and then for race/skin color and physical activity practice (model 2). Anthropometric and biochemical variables were log-transformed before linear regression. All linear regression analyses were adjusted by model 1 and 2. We also included BMI as covariate, excepted for BMI and body weight. Both logistic and linear regressions were carried out in additive, recessive, and dominant models. Haplotypes were obtained and their associations with obesity were verified by χ2 test (OR was calculated). A pairwise linkage disequilibrium analysis between rs9939609 and rs17817449 polymorphisms was carried out. Furthermore, gene score + was used to calculate the combined risk alleles. Individuals were encoded as 0 (homozygous protective), 1 (heterozygous), and 2 (homozygous risk) for each variant studied (Shabana and Hasnain, 2015; Shabana ). Then, the number of risk alleles was calculated from the sum of the codes for both rs9939609 and rs17817449 polymorphisms. The mean of risk alleles was compared between the groups using Student’s t-test. Logistic regression was also used to calculate the extreme obesity risk per unit allele increased. Finally, period of obesity onset was obtained from individuals with extreme obesity phenotype. The Mann-Whitney test was used to calculate BMI differences between subjects with early and late-onset obesity. Finally, the association of FTO polymorphisms with the period of obesity onset was tested using logistic regression. Since different polymorphisms were analyzed, a Bonferroni’s correction was used and a p-value of 0.025 was applied as a significant cutoff. All data analyses were performed using the SPSS statistical package, Haploview, and PHASE. Sample size calculation was performed using an iterative process to compute the minimum number of individuals necessary to test the difference between two groups of a qualitative variable according to Zar (1999). In this study, rs9939609 and rs17817449 polymorphisms were analyzed, and thus a conservative and convenience sample was chosen (80% of statistic power).

Results

Basic characteristics of the study population

Clinical characteristics from the 292 subjects, stratified into case and controls by BMI status, are shown in Table 1. As expected, anthropometric and biochemical data were significantly increased in individuals with extreme obesity when compared to the control group. Exceptions were in HDL-cholesterol and height, in which the control individuals had higher values. We also observed that the control group practiced more physical activities and exhibited a higher proportion of subjects with white race/skin color.
Table 1

Characteristics of study population.

VariablesNAllnControlnCase p
Age (years)29233 (26; 43)16929 (24; 38)12339 (31; 49)<0.001
Gender (female/male)292199/93169100/6912399/24<0.001
Race/ Skin color       
White291163 (56.0)169114 (67.5)12249 (40.2)<0.001
Brown 84 (28.9) 44 (23) 40 (32.8) 
Black 42 (14.4) 11 (6.5) 31 (25.4) 
Others 2 (0.7) 0 (0) 2 (1.6) 
Physical Activity Practice       
Yes289116 (40.1)16988 (52.1)12028 (23.3)<0.001
No 173 (59.9) 81 (47.9) 92 (76.7) 
Weight (kg)29274.1 (61.3; 126.2)16963.0 (57.0; 70.3)123131.5 (115.5; 146.5)<0.001
Height (m)2921.65 (1.60; 1.73)1691.69 (1.62; 1.74)1231.62 (1.58; 1.69)<0.001
BMI (kg/m2)29224.6 (22.4; 46.61)16922.8 (21.0; 24.0)12347.6 (44.1; 53.1)<0.001
Waist circumference (cm)29298.0 (83.0; 134.0)16984.0 (76.0; 91.0)122138.3 (128.0; 148.3)<0.001
Hip circumference (cm)292103.0 (92.5; 141.0)16995.0 (85.3; 100.3)122144.0 (134.0; 154.3)<0.001
WHR2920.92 (0.83; 1.01)1690.86 (0.80; 1.04)1220.97 (0.91; 1.01)<0.001
Glucose (mg/dL)25992.0 (86.0; 102 5)16388.0 (84.0; 95.0)96103.0 (94.0; 115.8)<0.001
Total cholesterol (mg/dL)259182.0 (159.0; 209 0)163178.0 (156.0; 198.0)96192.0 (168.0; 220.8) 0.003
HDL cholesterol (mg/dL)25952.0 (44.0; 63.0)16358.0 (47.0; 68.0)9647.0 (41.0; 53.8)<0.001
LDL cholesterol (mg/dL)255108.0 (88.0; 127 0)162102.0 (86.8; 122.3)93116.0 (95.5; 137.0) 0.002
Triglycerides (mg/dL)25988.0 (68.0; 131.0)16376.0 (61.0; 102.0)96128.0 (93.8; 185.0)<0.001

FTO frequencies and Hardy-Weinberg equilibrium

All subjects were genotyped for FTO rs9939609 and rs17817449 variants. Both were polymorphic in our sample. The details about the genotypic and allelic frequencies are presented in Table 2. Genotypes of rs9939609 and rs17817449 polymorphisms were in HWE (p > 0.05) for both case and control groups.
Table 2

Genotypic and allelic frequencies of FTO rs9939609 and rs17817449 polymorphisms.

FTO polymorphismsControlCaseModel 1Model 2
 n=169 (%)n=123 (%)OR (95% CI) P OR (95% CI) p
rs9939609       
Genotype       
TT64 (37.9)27 (22.0)1.00 (Ref.)-1.00 (Ref.)-
TA72 (42.6)59 (48.0)1.97 (1.06 - 3.66)0.0321.90 (0.99 - 3.66)0.054
AA33 (19.5)37 (30.1)2.88 (1.41 - 5.89) 0.004 2.51 (1.17 - 5.35) 0.017
Dominant Model       
TT64 (37.9)27 (22.0)1.00 (Ref.)-1.00 (Ref.)-
TA+AA105 (62.1)96 (78.0)2.25 (1.26 - 4.01) 0.006 2.09 (1.14 - 3.84) 0.016
Recessive Model       
TT+TA136 (80.5)86 (69.9)1.00 (Ref.)-1.00 (Ref.)-
AA33 (19.5)37 (30.1)1.91 (1.05 - 3.48)0.0351.74 (0.90 - 3.33)0.097
Allele       
T200 (59.2)113 (45.9)1.00 (Ref.)-1.00 (Ref.)-
A138 (40.8)133 (54.1)1.70 (1.19 - 2.43) 0.003 1.60 (1.10 - 2.33) 0.014
rs17817449       
Genotype       
G/G64 (37.9)33 (26.8)1.00 (Ref.)-1.00 (Ref.)-
G/T91 (53.8)60 (48.8)1.41 (0.78-2.52)0.3651.21 (0.65-2.26)0.531
T/T14 (8.3)30 (24.4)4.74 (2.04 - 11.01) 0.0003 3.89 (1.56 – 9.38) 0.003
Dominant Model       
GG64 (37.9)33 (26.8)1.00 (Ref.)-1.00 (Ref.)-
GT+TT105 (62.1)90 (73.2)1.83 (1.05 - 3.19)0.0341.57 (0.87 - 2.82)0.130
Recessive Model       
GG+GT155 (91.7)93 (75.6)1.00 (Ref.)-1.00 (Ref.)-
TT14 (8.3)30 (24.4)3.83 (1.80 - 8.17) 0.001 3.41 (1.50 - 7.74) 0.003
Allele       
G219 (64.8)126 (51.2)1.00 (Ref.)-1.00 (Ref.)-
T119 (35.2)120 (48.8)1.98 (1.33 - 2.96) 0.001 1.75 (1.15 - 2.67) 0.009

Influence of FTO variants on extreme obesity risk

The distribution of genotypes and alleles for rs9939609 and rs17817449 polymorphisms was compared between case and control groups (Table 2). Our results showed that the genotypic and allelic frequencies of both polymorphisms differed significantly between the groups. The frequency of the rs9939609(AA) genotype was significantly higher in the extremely obese group when compared to the control group. Allelic analysis showed that the prevalence of the rs9939609(A) allele was higher in subjects with extreme obesity (0.54 vs. 0.41; p = 0.003). Individuals carrying the rs9939609(A) allele had a 1.7 times higher risk for developing this phenotype. The frequency of the rs17817449(TT) genotype was higher in the case than in the control group. Furthermore, subjects carrying the TT genotype had a 4.5-fold increased risk for extreme obesity. In addition, carriers of at least one rs17817449(T) allele were 1.98 times more likely to develop this extreme phenotype. All these associations remained after adjusting for covariates (model 2).

Haplotype and linkage disequilibrium

Haplotype group analyses were performed using FTO rs9939609 and rs17817449. In the whole sample, the most common haplotypes were TG (50%) and AT (39.5%). The distribution of haplotypes between the case and control groups is shown in Table 3. Our results demonstrated that carriers of the AT haplotype had a 1.87-fold increased risk for extreme obesity development when compared to individuals with TG haplotype.
Table 3

Association of FTO haplotypes with obesity susceptibility.

HaplotypeControlExtremely obeseOR (95% CI) p
 n=169 (%)n=123 (%)  
T/G187 (55.3)110 (44.7)1.00 (Ref.)-
T/T13 (3.8)3 (1.2)0.44 (0.14 - 1.40)0.156
A/G32 (9.5)16 (6.5)0.86 (0.46 - 1.62)0.639
A/T106 (31.4)117 (47.6)1.87 (1.32 - 2.66) 0.0005
The polymorphisms studied are located in the first intron of FTO, and the distance from one another is about 7.2 kb. Our analysis demonstrated that FTO rs9939609 and rs17817449 are in linkage disequilibrium (D’ = 0.78; r2 = 0.583; LOD = 52.63).

Additive effects of FTO risk alleles on obesity

The combined effect of risk alleles was performed in order to study their influence on extreme obesity development. Our results showed that the average number of risk alleles was different between the groups (cases = 2.05 ± 1.34; controls = 1.52 ± 1.34; p = 0.001). Furthermore, the risk of being obese increased 1.37-fold for each risk allele added (OR = 1.37 [1.14 – 1.66]; p = 0.001).

Association of FTO variants with biochemical and anthropometric parameters

The influence of both FTO polymorphisms on biochemical and anthropometric measurements was analyzed by linear regression. FTO rs9939609 was associated with body weight in the additive model. Moreover, it was associated with BMI in the additive, dominant, and recessive models (Table 4). However, the association with BMI in the recessive model did not remain after correcting for covariates (model 2). FTO rs17817449 was associated with body weight in the additive and recessive models. This variant was also related with BMI in the additive, dominant, and recessive models. Furthermore, FTO rs17817449 influenced the triglycerides levels in the recessive model (Table 5). Our results indicated no significant effects of rs9939609 and rs17817449 variants on fasting glucose levels, total cholesterol, HDL-cholesterol, LDL-cholesterol, WHR, and waist and hip circumferences.
Table 4

Association of FTO rs9939609 with anthropometric and biochemical parameters.

ParametersTTTAAAAdditiveDominantRecessive
 nValuesNValuesnValues p a p b p a p b p a p b
Weight (kg)9169.5 (57.2 - 81.2)13170.5 (59.0 - 117.6)7070.0 (60.1 - 126.3) 0.008 0.021 0.0280.0410.0270.079
BMI (kg/m2)9123.4 (21.2 - 24.9)13124.1 (21.8 - 44.9)7024.5 (22.9 - 46.0) 0.003 0.009 0.011 0.016 0.017 0.055
Waist circumference (cm)9187.5 (82.0 - 102.5)13096.5 (81.8 - 128.1)7091.0 (80.0 - 126.5)0.9960.8130.5970.7030.5610.409
Hip circumference (cm)9198.5 (90.0 - 106.75)130102.5 (88.0 - 136.8)7099.5 (91.0 - 138.5)0.2340.2070.6970.6360.1030.095
WHR910.91 (0.82 - 1.04)1300.92 (0.82 - 1.03)700.90 (0.83 - 1.04)0.2520.2550.5760.5560.1720.184
Glucose (mg/dL)7697.0 (88.0 - 116.8)10596.0 (88.0 - 109.3)4699.0 (90.5 - 113.5)0.8280.8500.9380.9330.6330.663
Total cholesterol (mg/dL)82180.5 (154.0 - 199.3)119183.5 (16.8 - 200.3)58180.0 (155.0 - 210.0)0.0630.0730.0900.1040.1790.191
HDL cholesterol (mg/dL)8254.0 (45.3 - 63.0)11952.0 (43.0 - 63.3)5853.0 (44.5 - 67.5)0.0850.1100.3690.3650.0780.077
LDL cholesterol (mg/dL)82106.5 (84.3 - 126.0)117109.0 (89.8 - 129.3)56102.0 (86.5 - 125.0)0.2400.2610.2210.2450.4960.509
Triglycerides (mg/dL)8283.5 (66.0 - 125.8)11986.0 (65.5 - 120.3)5885.0 (67.5 - 127.5)0.4600.5510.8380.6990.1300.142
Table 5

Association of FTO rs17817449 with anthropometric and biochemical parameters.

ParametersGGGTTTAdditiveDominantRecessive
 nValuesNValuesnValues p a p b p a p b p a p b
Weight (kg)9769.5 (57.4 - 80.9)15170.5 (59.0 - 117.3)4470.0 (60.2 - 124.8) 0.0005 0.003 0.0320.077 0.0003 0.001
BMI (kg/m2)9723.4 (21.3 - 24.9)15124.1 (21.9 - 44.8)4424.5 (22.9 - 42.4) 0.0003 0.002 0.017 0.041 0.0003 0.002
Waist circumference (cm)9787.5 (82.0 - 102.0)15096.5 (82.0 - 128.0)4491.0 (80.0 - 126.0)0.7120.9130.6240.7770.9700.859
Hip circumference (cm)9798.5 (90.0 - 106.5)150102.5 (88.0 - 136.0)4499.5 (92.0 - 136.0)0.3400.3150.7870.7770.1510.127
WHR970.91 (0.82 - 1.04)1500.92 (0.82 - 1.03)440.90 (0.83 - 1.03)0.2960.3130.6630.7050.1670.161
Glucose (mg/dL)8097.0 (88.0 - 116.5)12496.0 (88.0 - 109.0)2399.0 (92.0 - 113.0)0.6640.7090.6360.6700.8610.926
Total cholesterol (mg/dL)86180.5 (154.0- 198.5)138183.5 (161.0 - 200.0)35180.0 (156.0 - 209.0)0.4240.4080.7350.7200.2880.278
HDL cholesterol (mg/dL)8654.0 (45.5 - 63.0)13852.0 (43.0 - 63.0)3553.0 (45.0 - 67.0)0.8080.8110.5180.5220.1680.173
LDL cholesterol (mg/dL)86106.5 (84.5 - 126.0)136109.0 (90.0 - 129.0)33102.0 (87.0 - 124.0)0.9900.9500.9690.9500.9750.975
Triglycerides (mg/dL)8683.5 (67.0 - 125.5)13886.0 (66.0 - 120.0)3585.0 (68.0 - 125.0)0.1450.1220.8510.813 0.011 0.008

Association of FTO variants with onset of obesity

We divided the case group according to the period of obesity onset, stratifying in early-onset obesity (childhood and adolescence) and late-onset obesity (adulthood). Of the 123 individuals with extreme obesity, 70 subjects developed obesity during childhood/adolescence (56.9%), and 53 individuals developed obesity during adulthood (43.1%). Our results showed no relation between BMI and period of obesity onset, in which both early-onset (BMI = 48.84 [44.65; 55.05] kg/m2) and late-onset (BMI = 46.92 [43.11; 52.87] kg/m2) had similar median values (p = 0.376). We also analyzed whether those polymorphisms influence the period of obesity onset. However, no association was found for both variants (data not shown).

Discussion

Obesity is a complex phenotype influenced by genetic and environmental factors. In the last decades, individuals have changed the lifestyle, resulting in energy imbalance caused by excessive food intake and diminished physical activity. Regarding genetic factors, the FTO gene has been recognized as one of the main contributors to polygenic obesity. However, the influence of FTO variants has been controversial among different populations (Ohashi ; Scuteri ; Li ; Ramos ; Pereira ). Moreover, there are only few studies associating FTO variants and extreme obesity, since sample selection is difficult and requires considerable effort. The strategy of using an extreme phenotype sample probably increases the power for detecting genetic associations in a median sample size (Price ; Castro ). In this study, we observed a strong association between the FTO rs9939609 and rs17817449 polymorphisms and risk for extreme obesity in a Brazilian population sample. These polymorphisms are located in the first intron of FTO, which is a region that has been consistently associated with adiposity in humans (Dina ; Frayling ; Scuteri ). Interestingly, the rs9939609 and rs17817449 polymorphisms were associated with extreme obesity in different populations (Price ; Villalobos-Comparán ). Price found that the rs9939609(A) and rs17817449(G) alleles were risk factors for extreme obesity in women from Spain. However, González reported that only rs17817449(T) was associated with extreme obesity in individuals from Western Spain when a single analysis was performed. Ramos observed that presence of the rs9939609(A) allele increased the risk for morbid obesity in a Brazilian population. Furthermore, Villalobos-Comparán reported that both FTO variants were in strong linkage disequilibrium and were associated with extreme obesity in Mexican mestizos subjects, which was corroborated by our results. Different studies have analyzed the contribution of single nucleotide polymorphisms for obesity risk. However, common forms of obesity have a complex etiology and could be explained by combined effects of variants located in the same or different genes (Shabana and Hasnain, 2015). Our study showed that the mean values of FTO risk alleles were higher in the case group. We also found that the risk of developing extreme obesity increased for each risk allele added. Only few previous studies had performed such an analysis. Nevertheless, it is a robust approach when the genetic study has a small or median sample size (Rouskas ; Lazopoulou ; Shabana and Hasnain, 2015). Shabana and Hasnain (2015) performed this analysis using the rs9939609 polymorphism and other different variants in the same gene. Interestingly, they reported that the mean of risk alleles was elevated in an obese group from Pakistan. Our results are in accordance with earlier studies that reported that the homozygote risk variants for both polymorphisms are strongly associated with obesity susceptibility (Price ; Villalobos-Comparán ). We also tested the influence of these polymorphisms on anthropometric and biochemical parameters. Our results showed that rs9939609 and rs17817449 were associated with BMI and body weight. Furthermore, the rs17817449 polymorphism was also associated with triglycerides levels. A variety of studies has investigated the effect of rs9939609 and rs17817449 variants on metabolic and anthropometric measurements, and these reported divergent results (Sentinelli ; Lazopoulou ; Shabana ). These different results may be explained by the effect of these two FTO variants that depend on environmental factors and ethnicity of the population. Additionally, we investigated the influence of FTO variants on the period of obesity onset. No association was found in our population. Previous studies have reported that the rs9939609 polymorphism was associated with body weight according to age. Sentinelli suggested that individuals carrying the rs9939609(A) risk allele had an increased body size earlier in life. Another study investigated the longitudinal pattern of the relationship between the rs9939609 variant and BMI during childhood, adolescence, and adulthood. This polymorphism was strongly associated with increased BMI during childhood, adolescence, and early adulthood (Hardy ). Reasons for the discrepancies in these results may be explained by a different methodology design, since we have performed a cross-sectional study. Furthermore, the period of obesity onset was self reported in our study, whereas Sentinelli used the age of individuals at the moment of sample collection. The role of FTO protein in obesity is not completely elucidated. However, high levels of FTO mRNA were detected in a hypothalamus region that is involved in energy homeostasis. Animal studies suggested that Fto expression is regulated by feeding and fasting (Gerken ). Church also reported that loss of function or expression of Fto is associated with an increased energy expenditure and a lean phenotype; otherwise, the overexpression induced an increased food intake and resulted in obesity. Even though the two polymorphisms are not located in an encoding region, they may exert functional effects through altered levels of FTO mRNA (Gerken ), or they are in linkage disequilibrium with another causative genetic variant (Prakash ). Additionally it has been suggested that the polymorphisms located in noncoding sequences (intron 1 and 2) within FTO interact with the promotor region of another gene in the neighborhood, called IRX3. Consistent with this, FTO polymorphisms associated with obesity alter the expression of IRX3 in human brains, which is related with regulation of body mass and composition (Smemo ). Therefore, our results suggest that FTO rs9939609 and rs17817449 are risk factors for obesity; however, more functional studies are required to confirm these results.

Conclusion

In this study, we investigated the association between FTO polymorphisms (rs9939609 and rs17817449) and the risk for extreme obesity development. We identified that FTO rs9939609 and rs17817449 polymorphisms have a strong association with extreme obesity and adiposity modulation in a Brazilian population sample.
  28 in total

1.  The combined effect of MC4R and FTO risk alleles on childhood obesity in Greece.

Authors:  Natalia Lazopoulou; Eleana Gkioka; Ioanna Ntalla; Panagiota Pervanidou; Alexandra-Maria Magiakou; Eleftheria Roma-Giannikou; George P Chrousos; Ioannis Papassotiriou; George Dedoussis; Christina Kanaka-Gantenbein
Journal:  Hormones (Athens)       Date:  2015 Jan-Mar       Impact factor: 2.885

2.  Common variants in FTO, MC4R, TMEM18, PRL, AIF1, and PCSK1 show evidence of association with adult obesity in the Greek population.

Authors:  Konstantinos Rouskas; Anastasia Kouvatsi; Konstantinos Paletas; Dimitrios Papazoglou; Apostolos Tsapas; Stéphane Lobbens; Vincent Vatin; Emmanuelle Durand; Yann Labrune; Jérôme Delplanque; David Meyre; Philippe Froguel
Journal:  Obesity (Silver Spring)       Date:  2011-06-30       Impact factor: 5.002

Review 3.  The human obesity gene map: the 2005 update.

Authors:  Tuomo Rankinen; Aamir Zuberi; Yvon C Chagnon; S John Weisnagel; George Argyropoulos; Brandon Walts; Louis Pérusse; Claude Bouchard
Journal:  Obesity (Silver Spring)       Date:  2006-04       Impact factor: 5.002

4.  Life course variations in the associations between FTO and MC4R gene variants and body size.

Authors:  Rebecca Hardy; Andrew K Wills; Andrew Wong; Cathy E Elks; Nicholas J Wareham; Ruth J F Loos; Diana Kuh; Ken K Ong
Journal:  Hum Mol Genet       Date:  2009-10-31       Impact factor: 6.150

5.  FTO polymorphism, cardiorespiratory fitness, and obesity in Brazilian youth.

Authors:  Cézane Priscila Reuter; Andréia Rosane De Moura Valim; Anelise Reis Gaya; Tássia Silvana Borges; Elisa Inês Klinger; Lia Gonçalves Possuelo; Silvia Isabel Rech Franke; Lívia Kmetzsch; Marilene Henning Vainstein; Daniel Prá; Miria Suzana Burgos
Journal:  Am J Hum Biol       Date:  2015-10-12       Impact factor: 1.937

6.  Effect of six type II diabetes susceptibility loci and an FTO variant on obesity in Pakistani subjects.

Authors:  Saleem Ullah Shahid; Ka Wah Li; Jayshree Acharya; Jackie A Cooper; Shahida Hasnain; Stephen E Humphries
Journal:  Eur J Hum Genet       Date:  2015-09-23       Impact factor: 4.246

Review 7.  Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants.

Authors: 
Journal:  Lancet       Date:  2016-04-02       Impact factor: 79.321

8.  Association between class III obesity (BMI of 40-59 kg/m2) and mortality: a pooled analysis of 20 prospective studies.

Authors:  Cari M Kitahara; Alan J Flint; Amy Berrington de Gonzalez; Leslie Bernstein; Michelle Brotzman; Robert J MacInnis; Steven C Moore; Kim Robien; Philip S Rosenberg; Pramil N Singh; Elisabete Weiderpass; Hans Olov Adami; Hoda Anton-Culver; Rachel Ballard-Barbash; Julie E Buring; D Michal Freedman; Gary E Fraser; Laura E Beane Freeman; Susan M Gapstur; John Michael Gaziano; Graham G Giles; Niclas Håkansson; Jane A Hoppin; Frank B Hu; Karen Koenig; Martha S Linet; Yikyung Park; Alpa V Patel; Mark P Purdue; Catherine Schairer; Howard D Sesso; Kala Visvanathan; Emily White; Alicja Wolk; Anne Zeleniuch-Jacquotte; Patricia Hartge
Journal:  PLoS Med       Date:  2014-07-08       Impact factor: 11.069

9.  Obesity-associated variants within FTO form long-range functional connections with IRX3.

Authors:  Scott Smemo; Juan J Tena; Kyoung-Han Kim; Eric R Gamazon; Noboru J Sakabe; Carlos Gómez-Marín; Ivy Aneas; Flavia L Credidio; Débora R Sobreira; Nora F Wasserman; Ju Hee Lee; Vijitha Puviindran; Davis Tam; Michael Shen; Joe Eun Son; Niki Alizadeh Vakili; Hoon-Ki Sung; Silvia Naranjo; Rafael D Acemel; Miguel Manzanares; Andras Nagy; Nancy J Cox; Chi-Chung Hui; Jose Luis Gomez-Skarmeta; Marcelo A Nóbrega
Journal:  Nature       Date:  2014-03-12       Impact factor: 49.962

10.  The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase.

Authors:  Thomas Gerken; Christophe A Girard; Yi-Chun Loraine Tung; Celia J Webby; Vladimir Saudek; Kirsty S Hewitson; Giles S H Yeo; Michael A McDonough; Sharon Cunliffe; Luke A McNeill; Juris Galvanovskis; Patrik Rorsman; Peter Robins; Xavier Prieur; Anthony P Coll; Marcella Ma; Zorica Jovanovic; I Sadaf Farooqi; Barbara Sedgwick; Inês Barroso; Tomas Lindahl; Chris P Ponting; Frances M Ashcroft; Stephen O'Rahilly; Christopher J Schofield
Journal:  Science       Date:  2007-11-08       Impact factor: 47.728

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  3 in total

1.  Common BMI and diabetes-related genetic variants: A pilot study among indigenous people in the Brazilian Amazon.

Authors:  Isabela Guerreiro Diniz; Rosilene Reis Della Noce; Ana Paula Pereira; Aylla Núbia Lima Martins da Silva; Eliene Rodrigues Putira Sacuena; Renan Barbosa Lemes; Greice de Lemos Cardoso-Costa; Gilderlânio Santana Araújo; Jéssica Lígia Picanço Machado; Fernanda Andreza de Pinho Lott Figueiredo; Tábita Hümemeier; João Farias Guerreiro
Journal:  Genet Mol Biol       Date:  2022-05-11       Impact factor: 2.087

2.  FTO and ADRB2 Genetic Polymorphisms Are Risk Factors for Earlier Excessive Gestational Weight Gain in Pregnant Women with Pregestational Diabetes Mellitus: Results of a Randomized Nutrigenetic Trial.

Authors:  Karina Dos Santos; Eliane Lopes Rosado; Ana Carolina Proença da Fonseca; Gabriella Pinto Belfort; Letícia Barbosa Gabriel da Silva; Marcelo Ribeiro-Alves; Verônica Marques Zembrzuski; J Alfredo Martínez; Cláudia Saunders
Journal:  Nutrients       Date:  2022-03-01       Impact factor: 5.717

3.  Risk variants of obesity associated genes demonstrate BMI raising effect in a large cohort.

Authors:  Muhammad Saqlain; Madiha Khalid; Muhammad Fiaz; Sadia Saeed; Asad Mehmood Raja; Muhammad Mobeen Zafar; Tahzeeb Fatima; João Bosco Pesquero; Cristina Maglio; Hadi Valadi; Muhammad Nawaz; Ghazala Kaukab Raja
Journal:  PLoS One       Date:  2022-09-20       Impact factor: 3.752

  3 in total

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