Original Article

Genetic association of FTO gene polymorphisms with obesity and its related phenotypes: A case-control study

Introduction

Obesity is a common multifactorial disorder characterized by the accretion of excess body fat. Obesity has been increasing at an alarming rate in low- and middle-income countries during the last three decades.¹ Obesity and overweight are the main risk factors for many non-communicable diseases considering 44% of diabetes, 23% of ischaemic heart disease and 7-41% of certain cancers.^2,3 Various factors contribute to obesity like binge eating, a sedentary lifestyle, lack of physical activity, alcohol consumption, and consumption of a high-calorie-rich diet. BMI, or Body Mass Index, which is calculated as the ratio of Weight in Kg to height in m² is a globally employed measure for evaluating overweight and obesity.

According to WHO, individuals with a body mass index (BMI) greater than 25 kg/m² are considered overweight, while those with a BMI exceeding 30 kg/m² are classified as obese.⁴ However, it has always been contentious for Asian and South Asian populations. Despite having a lower BMI of 25 kg/m², they exhibit a high incidence of cardiovascular disease, abdominal obesity, trunk subcutaneous fat and a notable difference in percent body fat. This challenges the conventional BMI cutoffs.^5,6 The recommended BMI cut-off points for the Asian population were as follows: the normal range is 18.5-22.9, overweight is defined as > 23.0 to 24.9, obese class I is ≥ 25.0 to 29.9, and obese class II is ≥ 30.0.⁷ It has been found that by the year 2040, the prevalence of overweight among adults in India is anticipated to undergo a twofold escalation, while the incidence of obesity is expected to undergo a threefold amplification.⁸ Numerous genes contribute to obesity predisposition, with various single nucleotide polymorphisms (SNPs) in these genes linked to the disease across diverse populations. However, these positive associations are not found in every population possibly due to differences in various factors like lifestyle, ethnic background, eating behaviour etc.^9-13

The FTO (Fat mass and obesity-associated) gene is present on chromosome no. 16q12.2 and comprises 9 exon counts. This gene spans about 417,979 bp. The variants of the FTO SNPs are present in 47 kb linkage disequilibrium blocks covering the portion of 1^st two introns and exon 2 of the FTO gene that is related to obesity and high body mass index. The FTO gene cipher a Fe II 2-oxoglutarate dependent demethylase enzyme that cuts the methyl group present in various positions of DNA as well as RNA and it is expressed in the arcuate nucleus of the hypothalamus playing a key role in the mechanism of energy intake and energy expenditure.¹⁴ Several studies have examined a remarkable correlation between obesity risk and polymorphisms of the FTO gene.^15-19 The current study depicts two intronic variants of the FTO gene 30685T/G (rs17817449) and -23525T/A (rs9939609).

An intronic variant 30685T/G substitution shows a significant relation with obesity and its related phenotypes.^16,20-24 The FTO 30685T/G variant is linked to the consumption of high-fat-rich foods and refined starches.²⁵ Moreover, an association has been observed with increased triglyceride levels for the 30685T/G variant.²⁶ Another intronic variant in the FTO gene having T to A substitution (-23525T/A) shows an association with high BMI in obese individuals.^26-29 Several studies have explored the association between the FTO gene polymorphism and metabolic syndrome, revealing contradictory findings. While some studies have established a connection, others have not found any association between FTO gene polymorphisms and obesity or overweight.

Obesity is influenced by genetic variations and ethnicity, with known polymorphisms showing varied associations across different ethnic populations. The population of Punjab, India has a unique genetic profile and extensive diversity. The study aims to assess the connection between SNPs in the FTO gene and obesity susceptibility in this population due to the high prevalence of overweight and obesity in the region.

Materials and Methods

Study Subjects

The present population-based case-control study included 671 unrelated adult individuals recruited from different districts of Punjab, an Indian state. Out of 671 subjects 333 were obese caseswith a mean age of 39.65 ± 10.25 years and a mean BMI of 27.57 ± 1.37 kg/m² for obese I, and 34.03 ± 4.28 kg/m² for obese II.Whereas, 338 were non-obese healthy controlswith a mean age of 37.46 ± 11.56 years and a mean BMI of 21.01 ± 1.89 kg/m². To minimize the selection bias in the present case-control study, the controls were randomly collected from the same population with matching ages and a 1:1 ratio to improve the statistical power of the study. The inclusion criteria for obese cases were adult individuals (≥ 18 years) with a BMI exceeding 25 kg/m², categorized as Obese I (25-29.9 kg/m²) and Obese II (≥ 30 kg/m²). Controls were individuals with a BMI ranging from ≥ 18.5 to 22.9.⁷ The exclusion criteria were pregnant and lactating females, individuals with big muscles, diabetes, kidney disease and other cardiovascular disease. All the subjects were interviewed and their ethnographic information, drug intake, anthropometric measurements, socio-economic lifestyle patterns, and family history were noted down.

The present study protocol was according to the Declaration of Helsinki (1964). All participants submitted written consent before their inclusion in this study and the study was agreed upon by the Institutional ethics committee of Guru Nanak Dev University.

Sample size calculation

The determination of the sample size for the present case-control study was conducted using the CaTS power software, specifically designed for genetic association studies.³⁰ The calculation of the sample size involved following specific assumptions. Firstly, a two-stage sample design was employed. The accepted significance level, denoted as Type II error, was set at 0.05. The prevalence rate of obesity in the Punjab region was considered25% according to Tripathy et al³¹ To identify an association with an effective size, the odds ratio of genotype-related risk was established at 1.50. Additionally, an additive model was utilized to ensure a statistical power exceeding 90%, along with a 95% confidence interval. Based on these calculations, the final sample size arrived at 333 obese cases and 338 healthy controls by increasing it by 10% to account for statistical correction, adjustment/design effect, and improved statistical power and level of significance for both cases and controls.

Anthropometric and Physiometric measurements

Various parameters like height, weight, waist circumference (WC), hip circumference (HC), and skinfold measurements were noted. The height of the subject was measured to the nearest 0.5 cm whereas the weight of the subject was measured to the nearest 0.1 kg and these measurements were taken with bare feet and light clothing. Waist, arm, calf and hip circumference were measured in cm. BMI was calculated by the given formula- the ratio of weight in kg to height in m². WHR was calculated by the ratio of waist circumference to the hip circumference whereas, WHtR was calculated by the ratio of waist circumference to that of height. Skinfold measurements of triceps, bicep, supra-iliac and sub-scapular were taken in mm by Lange skinfold caliper. For physiometric measurements such as systolic and diastolic blood pressures were measured by a mercury sphygmomanometer. Mean arterial blood pressure (MBP) was also calculatedby the given formula³²:

MBP = Diastolic Blood Pressure (DBP) + 1/3 [Systolic Blood Pressure (SBP)- DBP]

Biochemical Analysis

Serum was obtained from venous blood samples after an overnight fast to measure lipid variables, including total cholesterol (TC), triglyceride (TG) and high-density lipoprotein (HDL) by using Erba- Mannheim kit (Trans Sasia Bio-medicals Ltd., Solan, India). The calculation of low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) was done by Friedewald formula.³³

Genetic analysis

Genomic DNA was isolated by the Phenol/chloroform (PCA) method which was then diluted to a working concentration of 50ng/ml and stored at -20ºc for further use. Genotyping for both polymorphisms of the FTO gene was done by Polymerase chain reaction-based Restriction fragment length polymorphism (PCR-RFLP) and the Sanger sequencing method. The DNA was amplified by following set of primers: F: 5’-CGGTGAAGAGGAGGAGATTG-3’ and R: 5’-CATCTCTGCCCCAGTTTCTC-3’ for 30685T/G; F: 5’- AACTGGCTCTTGAATGAAATAGGATTCAGA-3’ and R: 5’- AGAGTAACAGAGACTATCCAAGTGCAGT AC-3’ for -23525T/A.^34,35

The PCR was performed by taking 50ng of DNA, 200µM of each dNTP, 4µM of each primer, 1x PCR buffer and 0.3U/ml of Taq DNA polymerase in a total reaction volume of 15µl. The conditions of the PCR cycle were: initial denaturation of 5 min at 95ºc followed by 30 cycles of denaturation for 45sec at 95ºc, annealing of 1min at 58ºc (for 30685T/G), 30 sec at 58ºc (for -23525T/A) extension of 1 min at 72ºc and a final extension of 10 min at 72ºc. To investigate contamination in PCR, a negative control without a DNA template was run with each reaction. The PCR products were checked in 2% agarose gel stained with ethidium bromide (10mg/ml) (Genei^TM).

The amplified PCR products (223bp for 30685T/G and 182bp for -23525T/A) were digested with restriction enzyme AlwNI and ScaI (New England Biolabs, USA) for both the polymorphisms 30685T/G and -23525T/A, respectively for 12-16 hours at 37ºc with 1x Neb buffer in a final reaction volume of 15µl followed by heat inactivation at 65ºc for 20min. The digested PCR products were resolved in 2.5% agarose gel stained with ethidium bromide against a 100 bp ladder and viewed under a UV transilluminator.

In 30685T/G, the homozygous wildtype allele was digested and resulted in 2 fragments of 123 bp and 100 bp i.e., the mutant allele remains undigested (Figure 1a). On the contrary, in -23525T/A the homozygous wildtype allele remains undigested whereas, the mutant allele gave 2 fragments of 154 bp and 28bp on digestion (Figure 1b).

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Figure 1.

Ethidium bromide-stained 2.5% agarose gel pictures showing PCR-RFLP digested products of the FTO gene polymorphisms (a) 30685T/G; M: 100bp DNA ladder, Lane 2,3,6,7 represents wild genotype (TT), Lane 1, 10 represents mutant genotype (GG), Lane 4,5,8,9,11 represents heterozygous genotype (TG) (b) -23525T/A; M: 100bp DNA ladder, Lane 1,2,6,9 represents wild genotype (TT), Lane 3,4,5,7,8 represents heterozygous genotype (TA)

Figure 1.

Ethidium bromide-stained 2.5% agarose gel pictures showing PCR-RFLP digested products of the FTO gene polymorphisms (a) 30685T/G; M: 100bp DNA ladder, Lane 2,3,6,7 represents wild genotype (TT), Lane 1, 10 represents mutant genotype (GG), Lane 4,5,8,9,11 represents heterozygous genotype (TG) (b) -23525T/A; M: 100bp DNA ladder, Lane 1,2,6,9 represents wild genotype (TT), Lane 3,4,5,7,8 represents heterozygous genotype (TA)

Sequencing

Genotyping of 50% of the samples for each polymorphism was performed by the Sanger sequencing method. Figures 2 and 3 demonstrate the sequencing chromatograms for the genotypes of 30685T/G and -23525T/A polymorphism. Individual sequence traces were examined, and alignments were compared to GenBank sequences using the NCBI blast program.

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Figure 2.

Sequencing chromatograms demonstrating the genotypes for polymorphism 30685T/G (a) Homozygous TT (b) Heterozygous TG (c) Homozygous GG

Figure 2.

Sequencing chromatograms demonstrating the genotypes for polymorphism 30685T/G (a) Homozygous TT (b) Heterozygous TG (c) Homozygous GG

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Figure 3.

Sequencing chromatograms demonstrating the genotypes for polymorphism 30685T/G (a) Homozygous TT (b) Heterozygous TA (c) Homozygous AA

Figure 3.

Sequencing chromatograms demonstrating the genotypes for polymorphism 30685T/G (a) Homozygous TT (b) Heterozygous TA (c) Homozygous AA

Statistical analysis

The data were analyzed using Statistical Package for Social Sciences (SPSS) for Windows Version 21.0. Continuous variables were represented as means ± SD and were compared by the student’s t-test, and quantitative data of the three groups were compared by one-way ANOVA. Binary logistic regression was performed to test the association of studied variants, under presumed genetic models after adjusting for various confounding factors. Allelic and genotypic frequencies were compared between obese cases and non-obese controls using the chi-square test (χ²). The influence of clinical variables and polymorphisms in the risk of obesity was examined with multiple linear regression analysis. To assess the effect of FTO gene variants on traits defining obesity, linear Regression analysis was performed.

The construction of a linkage disequilibrium map and haplotype blocks within variants of the FTO gene was based on genotypes and utilized Haploview software (version 4.1). Haplotype frequencies, odds ratios (ORs), two-tailed p-values and 95% confidence interval (CI) were calculated as the measure of association of the SNPs and the presence of obesity. A two-tailed p-value < 0.05 was considered statistical standard significant.

Results

Clinical and Biochemical characteristics of the study population

Table 1 summarizes the comparison of various anthropometric, clinical, and biochemical data among the obese I, obese II and control groups. The statistical analysis revealed that the mean values for height, weight, hip circumference (HC), waist circumference (WC), calf circumference (CC), arm circumference (AC), body mass index (BMI), triceps skinfold (TSF), biceps skinfold (BSF), subscapular skinfold (SSSF), suprailiac skinfold (SISF), waist-to-height ratio (WHtR), systolic blood pressure (SBP), pulse pressure (PP), total cholesterol (TC), triglyceride (TG), and low-density lipoprotein (LDL) were significantly higher in both obese I and obese II groups compared to the non-obese group (P < 0.001).

Association between genotypes with clinical parameters

The analysis of clinical and biochemical parameters across the genotypes among both studied polymorphisms has been presented in Table 2. The risk genotypes of both the variants i.e., 30685GG and -23525AA genotypes had significantly higher BMI (P = 0.00001 and P = 0.00001); WC (P = 0.00450 and 0.00358); SBP (P = 0.00003 and 0.0002); diastolic blood pressure DBP (P = 0.00001 and 0.0019); TC (P = 0.01478 and 0.02598) and TG (P = 0.03346 and 0.00005), respectively. However, the high-density lipoprotein HDL (P = 0.00145 and 0.04254) was found to be significantly higher in individuals harboring 30685TT and -23525TT genotypes respectively. Furthermore, the genetic variant 30685T/G demonstrated a significant association with HC, WHR, BSF, SISF and pulse rate (PR) (P < 0.05). Similarly, the variant -23525T/A showed significant associations with weight, very low-density lipoprotein (VLDL) andLDL (P < 0.05).

Distribution of FTO genotypes and alleles in obese and non-obese groups

The genotype and allele frequency distributions for FTO 30685T/G(rs17817449) and -23525T/A(rs9939609) polymorphisms in the total study population, obese and non-obese groups are presented in Table 3. The overall genotype (P = 0.00001; 30685T/G and P = 0.0005; -23525T/A, respectively) and allele frequencies (P = 0.0063; 30685T/G and P = 0.0001;-23525T/A) differed significantly between the obese and non-obese groups for both polymorphisms. The homozygous recessive genotype 30685GG was more prevalent in the obese group (20.42%) compared to the non-obese group (10%); (P = 0.0001). The 30685GG exhibited a twofold higher risk for the development of obesity [OR(95%CI): 2.30 (1.39-3.79); P = 0.001]. Similarly, the frequency of the homozygous recessive genotype -23525AA was significantly higher in the obese group (15.01%) compared to the non-obese group (3.25%) (P = 0.0001). The -23525AA genotype conferred an almost threefold higher risk for the progression of obesity [OR (95%CI): 2.78 (1.37-5.64); P = 0.0046].

Association of genetic models with obesity

The results of logistic regression analysis using different genetic models to assess the association between FTO gene polymorphisms with obesity are shown in Table 4. The 30685T/G and -23525T/A polymorphismsconferred a huge risk for obesity by conferring it 2-fold and 5 folds under the recessivemodel of inheritance [OR (95%CI): 2.29 (1.47-3.57); P = 0.0007; OR (95%CI): 5.25 (2.68-10.28); P = 0.0001, respectively].

Haplotype analysis

The haplotype distribution and the pattern of LD in both FTO polymorphisms in the total study population, obese and non-obese groups are presented in Table 5. The haplotype frequencies were significantly different between obese and non-obese subjects (P = 0.0001). The TT haplotype (both wild-type alleles) exhibited a higher frequency in the control group, signifying a significant protective effect against obesity development [OR (95%CI): 0.64 (0.52-0.79); P = 0.0001]. On the contrary, the GT and TA haplotypes were more frequent in obese subjects. The high-risk GA haplotype (30685G and -23525A) was considered as the baseline haplotype. When compared to this baseline haplotype, the G-T haplotype significantly elevated the risk of obesity [OR (95%CI): 3.1 (2.20-4.36); P = 0.0001]. Similarly, the TA haplotype, comprised of low-risk 30685T and high-risk -23525A significantly increased the obesity risk [OR (95%CI): 4.87 (2.96-7.99); P = 0.0001]. Based on the measure of LD, it has been observed the two SNPs (30685T/G and -23525T/A) were in strong LD in the total study population (D’ = 0.644, r² = 0.323) whereas, in moderate LD among obese and non-obese groups (D’ = 0.351, r² = 0.091; D’ = 0.517, r² = 0.218, respectively (Figure 4).

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Figure 4.

LD plot showing the position of the two FTO polymorphisms and pair-wise D’ values observed in the study population with respect to (a) Study population (b) Obese cases (c) non-obese controls

Figure 4.

LD plot showing the position of the two FTO polymorphisms and pair-wise D’ values observed in the study population with respect to (a) Study population (b) Obese cases (c) non-obese controls

Interaction analysis of FTO 30685T/G and -23525T/A polymorphism

The interaction analysis of different combinations of two polymorphisms has been presented in Table 6. The combination of dominant homozygous (TT) of 30685T/G and risk genotype (AA) of -23525T/A [OR (95%CI): 0.16 (0.05-0.49); P = 0.0004]; heterozygous TG of 30685T/G and risk genotype (AA) of -23525T/A [OR (95%CI): 0.19 (0.07-0.51); P = 0.0004]; risk genotype (GG) of 30685T/G and dominant homozygous (TT) of -23525T/A [OR (95%CI): 0.48 (0.24-0.95); P = 0.033]; risk genotype (GG) of 30685T/G and heterozygous (TA) of -23525T/A [OR (95%CI): 0.33 (0.17-0.69); P = 0.003] have exhibited protection against the development of obesity, respectively.

Association of FTO polymorphisms with obesity indices

Multiple linear regression analysis was performed to investigate the impact of 30685T/G (rs17817449) and -23525T/A (rs9939609) polymorphisms in elucidating the variation in obesity-related traits Table 7. The results revealed that the 30685G allele contributed with 29.59 (P = 0.0001), -0.188 (P = 0.013), 4.22 (P = 0.01), 13.45 (P = 0.012), -0.083 (P = 0.002), -275 (P = 0.035) and 0.02 (P = 0.001) increase in BMI, WC, WHR, waist to height ratio (WHtR), SBP, DBP and TG concentration, respectively. Furthermore, -23525A contributed with 20.13 (P = 0.0001), 0.031 (P = 0.030), 6.62 (P = 0.004), -0.014 (P = 0.0001), 0.02 (P = 0.009) and 0.007 (P = 0.0001) increase in BMI, WC, WHtR, SBP, DBP and TG, respectively. The 30685T/G polymorphism and the selected covariates were shown to be significant and independent predictors of the BMI, WC, WHR, WHtR, SBP, DBP and TG among obese subjects explaining the 55.5%, 49.1%, 13.3%, 42.3%, 34.7%, 31.1% and 22.3% of the variance, respectively. Similarly, the -23525T/A polymorphism also contributed 98%, 82.1%, 54%, 59.1%, 71.8% and 84.7% of the variability in the BMI, WC, WHtR, SBP, DBP and TG, respectively.

Discussion

We designed this case-control study to evaluate the association of two FTO variants 30685T/G (rs17817449) and -23525T/A (rs9939609) with obesity risk in the population of Punjab. Obesity is a complex phenotype and is contributed by genetic and environmental factors.^3,6 Among the genetic factors, the FTO gene has been considered one of the primary contributors to the development of the risk of polygenic obesity. Despite this fact, the impact of FTO variants has been a subject of controversy among oceanic, Egyptian, Portuguese, Iranian, Brazilian and other multi-ethnic populations.^{9,12,13,26,36,37} The present investigation has reported a significant association of 30685GG and -23525AA genotypes with the risk of obesity and its related parameters in the studied population. Individuals carrying 30685GG and -23525AA genotypes have twice more risk for developing obesity than non-carriers suggesting that FTO 30685GG and -23525AA might be a good predictor for obesity in this population.

The present findings align with numerous previous studies conducted among various populations, including Saudi, Thai, Spanish, Indian, South African and Mexican, confirming the interaction of these two polymorphisms with obesity.^16,21,38-41 However, the present results contrast with numerous previous studies conducted in oceanic, Chinese, Egyptian, Mexican and Latin American populations.^{9,10,12,35,42} The possible reason for these conflicting results could be that FTO gene products play a role in regulating food intake, with individuals carrying the risk allele tending to opt for food with higher energy content and increased fat.⁴³ In the Egyptian population, the two FTO gene polymorphisms exhibited no association with obesity. This could be attributed to the significant role of ethnicity variations in influencing the genetic component of individuals and their susceptibility to obesity.¹² Li et al reported significant differences in FTO risk allele frequencies and gene linkage patterns among the Chinese population, with risk alleles being common in Europeans but not in the Chinese.¹⁰ These differences suggest an evolutionary divergence that might reflect a history of negative selection against the FTO risk alleles in the Chinese population. Additionally, the potential variance in the genetic architecture of different ethnic groups may contribute to the distinct actions of these SNPs in different populations. Similarly, a study conducted on an oceanic population has elucidated that the FTO gene experienced negative selection following the divergence of mouse and human lineages.⁹ A study on Latin Americans revealed that communities have experienced a substantial nutrition transition, where socioeconomic factors such as urbanization and income were likely major contributors to the significant interpersonal variability in BMI. This suggests that the impact of FTO genetic polymorphisms on obesity susceptibility might be mitigated by socioeconomic variables.⁴²

The specific biological process through which the FTO polymorphisms contribute to the heightened susceptibility to obesity remains largely unidentified.⁴⁴ Clarifying how the FTO gene polymorphisms influence fat mass could enhance our comprehension of the origins of obesity. The FTO primarily contributes to weight gain by elevating energy intake and reducing the sensation of satiety. The FTO gene’s intronic region, highly sensitive to DNase, binds various transcription factors associated with obesity, particularly showing robust signals with glucocorticoid receptors.⁴⁵ FTO gene polymorphisms impact RNA-level gene regulation through catalytic demethylation leading to the development of obesity, ultimately contributing to insulin resistance.¹⁴

Studies suggest that plasma adiponectin and satiety hormones like leptin, released from adipose tissue, are affected byFTO gene polymorphisms.⁴⁶ These genetic variants of the FTO gene are responsible for reducing post-prandial satiety consequently increasing hunger.⁴⁶ Similarly, adiponectin is vital for glucose uptake and fatty acid metabolism. Although the mechanism explaining the potential connection between FTO and adiponectin is not clearly defined, individuals with obesity or elevated BMI often show reduced levels of adiponectin.⁴⁷

Adipose tissue also produces high-sensitive C-reactive protein (hsCRP), recognized as a pro-inflammatory cytokine linked to obesity-related inflammation. The FTO gene polymorphisms contribute not only to increased adiposity but also potentially amplify inflammation within adipose tissue, leading to heightened systemic inflammation regardless of adiposity levels.⁴⁸ Additionally, CRP binds with leptin, hindering its signalling and diminishing its physiological effects.⁴⁹

The present study reported that both FTO variants were in moderate linkage disequilibrium and were associated with obesity in the Punjabi population. The present study has also suggested that common forms of obesity could be explained by the combined effects of variants located in the same gene or different genes than a single isolated variant. We also tested the influence of these polymorphisms on anthropometric and biochemical parameters in the present samples. The results revealed that 30685T/G (rs17817449) and -23525T/A (rs9939609) variants may increase the susceptibility to adiposity metabolic syndrome with increased total cholesterol (TC), waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), and triglyceride (TG). These results confirm the findings from other investigations in various ethnic groups and populations, including Mexican, Indian, Chinese, Brazilian, South African, Pakistani, Kuwaiti, Turkish and Italian.^{15,20,21,26,39,50-53}

The present results suggested that FTO 30685T/G (rs17817449) and -23525T/A (rs9939609) are the risk factors for obesity with regulation of body mass and composition. However, these two polymorphisms are not situated in an encoding region, still, they may exert functional effects through altered levels of FTO mRNA or in linkage disequilibrium with another genetic variant.⁵⁴ In addition to that it has been observed that the variants located in non-coding sequences (intron1 and 2) within the FTO geneinteract with the promoter region of another gene IRX3 inthe neighborhood. Therefore, FTO polymorphisms association with obesity alters the expression of the IRX3 gene in the human brain which is closely related to the regulation of obesity and its risk factors.⁵⁵ However, more functional studies are required to confirm the role of FTO protein in obesity which is not completely elucidated whereas, the animal studies suggested that FTO expression is regulated by fasting and feeding habits.⁵⁴

Multiple linear regressions revealed 55%, 49%, 42%, 34%, 31% and 22% variance in BMI, WC, WHtR, SBP, DBP and TG levels respectively due to the 30685T/G variant. In relation to -23525T/A polymorphism, the results have shown statistically significant association with BMI, WC, TG, TC, DBP, SBP and WHtR accounting for 98%, 82%, 84%, 76%, 71%, 59% and 54% variability respectively. It indicates that these two variants are relevant markers for adiposity and its related metabolic indices in this population.

The robustness of this study stems from the meticulous sampling design of our participants, who form a distinct and uniform population in terms of geographical, dietary, and cultural factors. This design is resilient to the influence of population stratification, substantially reducing the potential for false positive associations. The present study marks the initial attempt to examine the correlation between these two genetic variants and the prevalence of obesity in this particular population of Punjab. These results hold significance as the prevalence of overweight and obesity is on a rapid rise in the Indian population especially in the state of Punjab. Therefore, identifying and comprehending the mechanisms underlying the connection between the FTO gene and obesity will aid in developing rational strategies for personalized management of obesity.

The present study’s sample size, particularly after BMI stratification, was insufficient for conclusive results. Therefore, it is imperative to replicate these findings in future studies with larger samples for validation.Serum levels of FTO were not measured in this study, preventing the conduct of genotype-phenotype correlation studies.The study sample lacks national representativeness, with significant implications mainly applicable to North Indian ethnic groups. As a result, the generalizability of these findings to other ethnicities remains uncertain. Hence, further assessments of diverse ethnic groups are necessary.

Conclusion

In this study, we tried to find out the impact of FTO variants 30685T/G (rs17817449) and -23525T/A (rs9939609) on the development of obesity risk. The results have suggested a strong association between FTO 30685T/G and -23525T/A polymorphisms with obesity and related phenotypes in the studied population.

Acknowledgments

We are highly acknowledged to all the participants for their involvement, cooperation and contribution towards this research study. The current study was assisted by departmental financial assistance from Guru Nanak Dev University, Amritsar, Punjab, India.

Competing Interests

The authors declare no conflict of interest.

Ethical Approval

The present study protocol was performed according to the Declaration of Helsinki (1964). The current study was also agreed upon by the institutional ethics committee(ethics no.1609/HG)constituted by Guru Nanak Dev University, Amritsar, Punjab, India.

References

1. Endalifer ML, Diress G. Epidemiology, predisposing factors, biomarkers, and prevention mechanism of obesity: a systematic review. J Obes 2020; 2020:6134362. doi: 10.1155/2020/6134362 [Crossref] [ Google Scholar]
2. Saini S, Walia GK, Sachdeva MP, Gupta V. Genetics of obesity and its measures in India. J Genet 2018; 97(4):1047-71. doi: 10.1007/s12041-018-0987-8 [Crossref] [ Google Scholar]
3. Kaur H, Bains V, Sharma T, Badaruddoza Badaruddoza. Relationship between leptin gene variants (-2548G > A and 19A > G) and obesity among north Indian Punjabi population. J Genet 2023; 102(1):6. doi: 10.1007/s12041-022-01401-x [Crossref] [ Google Scholar]
4. World Health Organization (WHO). Obesity: preventing and managing the global epidemic Report of a WHO consultation. World Health Organ Tech Rep Ser 2000; 894:1-253. [ Google Scholar]
5. Low S, Chin MC, Ma S, Heng D, Deurenberg-Yap M. Rationale for redefining obesity in Asians. Ann Acad Med Singap 2009; 38(1):66-9. [ Google Scholar]
6. Kaur H, Badaruddoza B, Bains V, Kaur A. Genetic association of ADIPOQ gene variants (-3971A > G and + 276G > T) with obesity and metabolic syndrome in north Indian Punjabi population. PLoS One 2018; 13(9):e0204502. doi: 10.1371/journal.pone.0204502 [Crossref] [ Google Scholar]
7. Snehalatha C, Viswanathan V, Ramachandran A. Cutoff values for normal anthropometric variables in Asian Indian adults. Diabetes Care 2003; 26(5):1380-4. doi: 10.2337/diacare.26.5.1380 [Crossref] [ Google Scholar]
8. Luhar S, Timæus IM, Jones R, Cunningham S, Patel SA, Kinra S. Forecasting the prevalence of overweight and obesity in India to 2040. PLoS One 2020; 15(2):e0229438. doi: 10.1371/journal.pone.0229438 [Crossref] [ Google Scholar]
9. Ohashi J, Naka I, Kimura R, Natsuhara K, Yamauchi T, Furusawa T. FTO polymorphisms in oceanic populations. J Hum Genet 2007; 52(12):1031-5. doi: 10.1007/s10038-007-0198-2 [Crossref] [ Google Scholar]
10. Li H, Wu Y, Loos RJ, Hu FB, Liu Y, Wang J. Variants in the fat mass- and obesity-associated (FTO) gene are not associated with obesity in a Chinese Han population. Diabetes 2008; 57(1):264-8. doi: 10.2337/db07-1130 [Crossref] [ Google Scholar]
11. Hennig BJ, Fulford AJ, Sirugo G, Rayco-Solon P, Hattersley AT, Frayling TM. FTO gene variation and measures of body mass in an African population. BMC Med Genet 2009; 10:21. doi: 10.1186/1471-2350-10-21 [Crossref] [ Google Scholar]
12. Abdelmajed SS, Youssef M, Zaki ME, Abu-Mandil Hassan N, Ismail S. Association analysis of FTO gene polymorphisms and obesity risk among Egyptian children and adolescents. Genes Dis 2017; 4(3):170-5. doi: 10.1016/j.gendis.2017.06.002 [Crossref] [ Google Scholar]
13. Almeida SM, Furtado JM, Mascarenhas P, Ferraz ME, Ferreira JC, Monteiro MP. Association between LEPR, FTO, MC4R, and PPARG-2 polymorphisms with obesity traits and metabolic phenotypes in school-aged children. Endocrine 2018; 60(3):466-78. doi: 10.1007/s12020-018-1587-3 [Crossref] [ Google Scholar]
14. Han Z, Niu T, Chang J, Lei X, Zhao M, Wang Q. Crystal structure of the FTO protein reveals basis for its substrate specificity. Nature 2010; 464(7292):1205-9. doi: 10.1038/nature08921 [Crossref] [ Google Scholar]
15. Villalobos-Comparán M, Teresa Flores-Dorantes M, Teresa Villarreal-Molina M, Rodríguez-Cruz M, García-Ulloa AC, Robles L. The FTO gene is associated with adulthood obesity in the Mexican population. Obesity (Silver Spring) 2008; 16(10):2296-301. doi: 10.1038/oby.2008.367 [Crossref] [ Google Scholar]
16. Srivastava A, Mittal B, Prakash J, Srivastava P, Srivastava N, Srivastava N. Association of FTO and IRX3 genetic variants to obesity risk in north India. Ann Hum Biol 2016; 43(5):451-6. doi: 10.3109/03014460.2015.1103902 [Crossref] [ Google Scholar]
17. Zdrojowy-Wełna A, Bednarek-Tupikowska G, Zatońska K, Kolačkov K, Jokiel-Rokita A, Bolanowski M. The association between FTO gene polymorphism rs9939609 and obesity is sex-specific in the population of PURE study in Poland. Adv Clin Exp Med 2020; 29(1):25-32. doi: 10.17219/acem/111811 [Crossref] [ Google Scholar]
18. Quevedo Alves F, Reuter CP, Neumann I, Todendi PF, Brand C, Latosinski Matos W. Relationship between rs9939609 FTO polymorphism with waist circumference and body fat is moderated by ponderal index at birth in youth. Am J Hum Biol 2022; 34(1):e23575. doi: 10.1002/ajhb.23575 [Crossref] [ Google Scholar]
19. Gholamalizadeh M, Mirzaei Dahka S, Vahid F, Bourbour F, Badeli M, Javadi Kooshesh S. Does the rs9939609 FTO gene polymorphism affect fat percentage? A meta-analysis. Arch Physiol Biochem 2022; 128(6):1421-5. doi: 10.1080/13813455.2020.1773861 [Crossref] [ Google Scholar]
20. Prakash J, Srivastava N, Awasthi S, Agarwal CG, Natu SM, Rajpal N. Association of FTO rs17817449 SNP with obesity and associated physiological parameters in a north Indian population. Ann Hum Biol 2011; 38(6):760-3. doi: 10.3109/03014460.2011.614278 [Crossref] [ Google Scholar]
21. Chuenta W, Phonrat B, Tungtrongchitr A, Limwongse C, Chongviriyaphan N, Santiprabhob J. Common variations in the FTO gene and obesity in Thais: a family-based study. Gene 2015; 558(1):75-81. doi: 10.1016/j.gene.2014.12.050 [Crossref] [ Google Scholar]
22. Saldaña-Alvarez Y, Salas-Martínez MG, García-Ortiz H, Luckie-Duque A, García-Cárdenas G, Vicenteño-Ayala H. Gender-dependent association of FTO polymorphisms with body mass index in Mexicans. PLoS One 2016; 11(1):e0145984. doi: 10.1371/journal.pone.0145984 [Crossref] [ Google Scholar]
23. Younus LA, Algenabi AH, Abdul-Zhara MS, Hussein MK. FTO gene polymorphisms (rs9939609 and rs17817449) as predictors of type 2 diabetes mellitus in obese Iraqi population. Gene 2017; 627:79-84. doi: 10.1016/j.gene.2017.06.005 [Crossref] [ Google Scholar]
24. Barseem NF, Abou El Ella SS, Tawfik MA, El-Nehrawy RR. The potential implication of FTO rs17817449 gene polymorphism on BMI mediated risk for type2 diabetes among obese Egyptian children and adolescents. Endocr Metab Immune Disord Drug Targets 2019; 19(5):697-704. doi: 10.2174/1871530319666190101124751 [Crossref] [ Google Scholar]
25. Harbron J, van der Merwe L, Zaahl MG, Kotze MJ, Senekal M. Fat mass and obesity-associated (FTO) gene polymorphisms are associated with physical activity, food intake, eating behaviors, psychological health, and modeled change in body mass index in overweight/obese Caucasian adults. Nutrients 2014; 6(8):3130-52. doi: 10.3390/nu6083130 [Crossref] [ Google Scholar]
26. da Fonseca A, Marchesini B, Zembrzuski VM, Voigt DD, Ramos VG, Carneiro JR. Genetic variants in the fat mass and obesity-associated (FTO) gene confer risk for extreme obesity and modulate adiposity in a Brazilian population. Genet Mol Biol 2020; 43(1):e20180264. doi: 10.1590/1678-4685-gmb-2018-0264 [Crossref] [ Google Scholar]
27. Abdella HM, El Farssi HO, Broom DR, Hadden DA, Dalton CF. Eating behaviours and food cravings; influence of age, sex, BMI and FTO genotype. Nutrients 2019; 11(2):377. doi: 10.3390/nu11020377 [Crossref] [ Google Scholar]
28. Zhao NN, Dong GP, Wu W, Wang JL, Ullah R, Fu JF. FTO gene polymorphisms and obesity risk in Chinese population: a meta-analysis. World J Pediatr 2019; 15(4):382-9. doi: 10.1007/s12519-019-00254-2 [Crossref] [ Google Scholar]
29. Reuter ÉM, Reuter CP, de Castro Silveira JF, Carroll S, Hobkirk JP, Todendi PF. FTO gene polymorphism and longitudinal changes in nutritional/obesity status in children and adolescents: schoolchildren’s health cohort study. Eur J Pediatr 2021; 180(11):3325-33. doi: 10.1007/s00431-021-04120-0 [Crossref] [ Google Scholar]
30. Skol AD, Scott LJ, Abecasis GR, Boehnke M. Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet 2006; 38(2):209-13. doi: 10.1038/ng1706 [Crossref] [ Google Scholar]
31. Tripathy JP, Thakur JS, Jeet G, Chawla S, Jain S, Prasad R. Urban rural differences in diet, physical activity and obesity in India: are we witnessing the great Indian equalisation? Results from a cross-sectional STEPS survey. BMC Public Health 2016; 16(1):816. doi: 10.1186/s12889-016-3489-8 [Crossref] [ Google Scholar]
32. Crisafulli A, Scott AC, Wensel R, Davos CH, Francis DP, Pagliaro P. Muscle metaboreflex-induced increases in stroke volume. Med Sci Sports Exerc 2003; 35(2):221-8. doi: 10.1249/01.mss.0000048639.02548.24 [Crossref] [ Google Scholar]
33. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972; 18(6):499-502. doi: 10.1093/clinchem/18.6.499 [Crossref] [ Google Scholar]
34. Shahid A, Rana S, Saeed S, Imran M, Afzal N, Mahmood S. Common variant of FTO gene, rs9939609, and obesity in Pakistani females. Biomed Res Int 2013; 2013:324093. doi: 10.1155/2013/324093 [Crossref] [ Google Scholar]
35. Zermeño-Rivera JJ, Astocondor-Pérez JP, Valle Y, Padilla-Gutiérrez JR, Orozco-Castellanos R, Figuera LE. Association of the FTO gene SNP rs17817449 with body fat distribution in Mexican women. Genet Mol Res 2014; 13(4):8561-7. doi: 10.4238/2014.February.13.7 [Crossref] [ Google Scholar]
36. Mehrdad M, Fardaei M, Fararouei M, Eftekhari MH. The association between FTO rs9939609 gene polymorphism and anthropometric indices in adults. J Physiol Anthropol 2020; 39(1):14. doi: 10.1186/s40101-020-00224-y [Crossref] [ Google Scholar]
37. Ramos AV, Bastos-Rodrigues L, Resende BA, Friedman E, Campanha-Versiani L, Miranda DM. The contribution of FTO and UCP-1 SNPs to extreme obesity, diabetes and cardiovascular risk in Brazilian individuals. BMC Med Genet 2012; 13:101. doi: 10.1186/1471-2350-13-101 [Crossref] [ Google Scholar]
38. Moselhy SS, Alhetari YA, Iyer A, Huwait EA, Al-Ghamdi MA, Al-Ghamdi S. Analysis of SNPs of MC4R, GNB3 and FTO gene polymorphism in obese Saudi subjects. Afr Health Sci 2017; 17(4):1059-69. doi: 10.4314/ahs.v17i4.14 [Crossref] [ Google Scholar]
39. Lombard Z, Crowther NJ, van der Merwe L, Pitamber P, Norris SA, Ramsay M. Appetite regulation genes are associated with body mass index in black South African adolescents: a genetic association study. BMJ Open 2012; 2(3):e000873. doi: 10.1136/bmjopen-2012-000873 [Crossref] [ Google Scholar]
40. Muñoz-Yáñez C, Pérez-Morales R, Moreno-Macías H, Calleros-Rincón E, Ballesteros G, González RA. Polymorphisms FTO rs9939609, PPARG rs1801282 and ADIPOQ rs4632532 and rs182052 but not lifestyle are associated with obesity related-traits in Mexican children. Genet Mol Biol 2016; 39(4):547-53. doi: 10.1590/1678-4685-gmb-2015-0267 [Crossref] [ Google Scholar]
41. Rodríguez-López R, González-Carpio M, Serrano MV, Torres G, García de Cáceres MT, Herrera T. [Association of FTO gene polymorphisms and morbid obesity in the population of Extremadura (Spain)]. Endocrinol Nutr 2010; 57(5):203-9. doi: 10.1016/j.endonu.2010.03.002.[Spanish] [Crossref] [ Google Scholar]
42. Ruiz-Díaz MS, Mena-Yi D, Gómez-Camargo D, Mora-García G. Interaction analysis of FTO and IRX3 genes with obesity and related metabolic disorders in an admixed Latin American population: a possible risk increases of body weight excess. Colomb Med (Cali) 2022; 53(2):e2044874. doi: 10.25100/cm.v53i2.4874 [Crossref] [ Google Scholar]
43. Timpson NJ, Emmett PM, Frayling TM, Rogers I, Hattersley AT, McCarthy MI. The fat mass- and obesity-associated locus and dietary intake in children. Am J Clin Nutr 2008; 88(4):971-8. doi: 10.1093/ajcn/88.4.971 [Crossref] [ Google Scholar]
44. Zhao J, Grant SF. Genetics of childhood obesity. J Obes 2011; 2011:845148. doi: 10.1155/2011/845148 [Crossref] [ Google Scholar]
45. Kar K, Munim MA, Fariha A, Roy AS, Rahman MI, Akter S. Association of an intronic SNP rs9939609 in FTO gene with type 2 diabetes mellitus among Bangladeshi population: a case–control study combined with updated meta-analysis. Hum Gene (Amst) 2023; 35:201133. doi: 10.1016/j.humgen.2022.201133 [Crossref] [ Google Scholar]
46. Speakman JR. The ‘fat mass and obesity related’ (FTO) gene: mechanisms of impact on obesity and energy balance. Curr Obes Rep 2015; 4(1):73-91. doi: 10.1007/s13679-015-0143-1 [Crossref] [ Google Scholar]
47. Bergmark BA, Cannon CP, White WB, Jarolim P, Liu Y, Bonaca MP. Baseline adiponectin concentration and clinical outcomes among patients with diabetes and recent acute coronary syndrome in the EXAMINE trial. Diabetes Obes Metab 2017; 19(7):962-9. doi: 10.1111/dom.12905 [Crossref] [ Google Scholar]
48. Fisher E, Schulze MB, Stefan N, Häring HU, Döring F, Joost HG. Association of the FTO rs9939609 single nucleotide polymorphism with C-reactive protein levels. Obesity (Silver Spring) 2009; 17(2):330-4. doi: 10.1038/oby.2008.465 [Crossref] [ Google Scholar]
49. Chen K, Li F, Li J, Cai H, Strom S, Bisello A. Induction of leptin resistance through direct interaction of C-reactive protein with leptin. Nat Med 2006; 12(4):425-32. doi: 10.1038/nm1372 [Crossref] [ Google Scholar]
50. Shabana Shabana, Hasnain S. Effect of the common fat mass and obesity associated gene variants on obesity in Pakistani population: a case-control study. Biomed Res Int 2015; 2015:852920. doi: 10.1155/2015/852920 [Crossref] [ Google Scholar]
51. Al-Serri A, Al-Bustan SA, Kamkar M, Thomas D, Alsmadi O, Al-Temaimi R. Association of FTO rs9939609 with obesity in the Kuwaiti population: a public health concern?. Med Princ Pract 2018; 27(2):145-51. doi: 10.1159/000486767 [Crossref] [ Google Scholar]
52. Inandiklioğlu N, Yaşar A. Association between rs1421085 and rs9939609 polymorphisms of fat mass and obesity-associated gene with high-density lipoprotein cholesterol and triglyceride in obese Turkish children and adolescents. J Pediatr Genet 2021; 10(1):9-15. doi: 10.1055/s-0040-1713154 [Crossref] [ Google Scholar]
53. Sentinelli F, Incani M, Coccia F, Capoccia D, Cambuli VM, Romeo S. Association of FTO polymorphisms with early age of obesity in obese Italian subjects. Exp Diabetes Res 2012; 2012:872176. doi: 10.1155/2012/872176 [Crossref] [ Google Scholar]
54. Gerken T, Girard CA, Tung YC, Webby CJ, Saudek V, Hewitson KS. The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science 2007; 318(5855):1469-72. doi: 10.1126/science.1151710 [Crossref] [ Google Scholar]
55. Smemo S, Tena JJ, Kim KH, Gamazon ER, Sakabe NJ, Gómez-Marín C. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature 2014; 507(7492):371-5. doi: 10.1038/nature13138 [Crossref] [ Google Scholar]