Abstract
Background and Aims:
The polymorphisms in fat mass and obesity-associated gene (FTO) have been implicated in metabolic dysregulation. This study aimed to investigate the associations between the FTO rs9939609 and rs17817449 polymorphisms and MetS risk, and to assess whether glucolipid parameters mediate these associations.
Methods:
A hospital-based cross-sectional study involving 701 adults was conducted. MetS was diagnosed according to the criteria of the International Diabetes Federation (2005). Clinical data were collected for all participants. Genotyping of rs9939609 and rs17817449 was performed via polymerase chain reaction-restriction fragment length polymorphism. Logistic regression and mediation analysis were used to evaluate genetic associations and mediating effects.
Results:
The MetS group showed higher frequencies of rs9939609 A allele (14.01% vs. 6.09%, P < 0.001) and rs17817449 G allele (16.94% vs. 12.18%, P = 0.012) compared to controls. Rs9939609 AA genotype carriers had the highest MetS risk (OR = 3.58, 95% CI: 1.08–11.88) and exhibited allelic dose-dependent worsening of triglycerides, high-density lipoprotein cholesterol (HDL-C), and fasting blood glucose (FBG) (all P < 0.05). Similarly, rs17817449 G allele was linked to elevated triglycerides, reduced HDL-C, higher FBG, and increased systolic blood pressure (all P < 0.05). Mediation analysis revealed triglycerides, HDL-C, and FBG as significant mediators for the associations of rs9939609 and rs17817449 with MetS (all P < 0.001).
Conclusion:
FTO rs9939609 and rs17817449 polymorphisms are strongly associated with MetS risk, primarily by increasing triglyceride and glucose levels and decreasing HDL-C. These findings highlight the pivotal role of FTO variants in metabolic dysregulation and suggest potential targets for early intervention of MetS.
Introduction
Metabolic syndrome (MetS) is a cluster of interrelated cardiometabolic risk factors, including abdominal obesity (increased waist circumference, WC), hypertension (elevated systolic/diastolic blood pressure, SBP/DBP), dyslipidemia (high triglycerides; low high-density lipoprotein cholesterol, HDL-C), and impaired glucose metabolism (elevated fasting blood glucose, FBG). Diagnostic criteria vary across guidelines: the NCEP ATP III defines MetS as the presence of ≥3 abnormal components, whereas the International Diabetes Federation (IDF) requires central obesity (based on ethnicity-specific WC cutoffs) plus ≥2 additional components (; ; ). MetS substantially elevates the risk of cardiovascular disease, type 2 diabetes mellitus (T2DM), metabolic dysfunction-associated steatotic liver disease, and chronic kidney disease (; ; ; ). Its global prevalence ranges from 25% to 33%, with regional variations: 25% in the United States, 30% in Bangladesh, 30.4% in Iran, 31.1% in China, 32.4% in Africa, and 33% in Brazil (; ; ; ; ; ). The pathogenesis of MetS is multifactorial, involving genetic predisposition, lifestyle factors (e.g., poor diet, physical inactivity), and environmental exposures (e.g., pollutants, endocrine disruptors) (; ). Recent advances in genomics have identified multiple susceptibility genes and polymorphic variants contributing to MetS susceptibility, highlighting its complex genetic architecture.
The fat mass and obesity-associated gene (FTO), which encodes an RNA N6-methyladenosine demethylase, has been implicated in regulating multiple components of MetS. Human studies have demonstrated tissue-specific associations between FTO expression and metabolic parameters. reported that subcutaneous adipose tissue FTO mRNA expression correlated positively with WC and FBG in patients undergoing abdominal surgery. Similarly, found that subcutaneous adipose FTO expression in Danish twins showed an inverse relationship with HDL-C levels, suggesting a role in lipid metabolism. Mouse models further reveal the diverse metabolic functions of FTO across tissues. demonstrated that adipose-specific FTO knockout mice exhibited enhanced triglyceride clearance and reduced serum triglyceride concentrations through mechanisms involving ANGPTL4 upregulation. In contrast, showed that smooth muscle cell-specific FTO deletion led to significantly reduced SBP and DBP without affecting body weight, revealing a novel role in vascular function regulation. These findings collectively highlight the pleiotropic effects of FTO across different tissues in modulating MetS components.
The human FTO gene is located on chromosome 16q12.2 and consists of 9 exons interspersed with 8 introns. Two obesity-associated single-nucleotide polymorphisms (SNPs), rs9939609 and rs17817449, reside within intron 1 of FTO. The rs9939609 variant, a thymine-to-adenine transversion (g.53786615T>A), has been functionally linked to allele-specific expression differences. quantified FTO mRNA in subcutaneous adipose tissue from 31 Mexican women, revealing 1.65-fold higher expression in A allele carriers of rs9939609 compared to TT homozygotes. extended these findings through transcript quantification in peripheral blood mononuclear cells and skin biopsies, showing A allele carriers exhibited 1.38-fold and 1.31-fold higher FTO mRNA levels than TT genotypes, respectively. These expression differences were further corroborated in leukocyte samples by , who observed 1.22-fold increased FTO transcription in AA homozygotes compared to T-allele carriers. The rs17817449 variant (g.53779455T>G), positioned approximately 7.2 kb upstream of rs9939609 within the same intronic region, may influence FTO expression through cis-regulatory mechanisms. This variant was associated with elevated risks of T2DM and dyslipidemia in a Chinese Han population (), suggesting its potential role in modulating metabolic phenotypes via FTO dysregulation.
This retrospective case-control study aims to evaluate whether FTO rs9939609 and rs17817449 polymorphisms are associated with MetS susceptibility, and to elucidate the pathways through which these polymorphisms influence MetS susceptibility.
Subjects and methods
Study subjects
This cross-sectional study consecutively enrolled 701 adults (aged ≥18 years) from the Health Management Center at the Clinical Medical College & Affiliated Hospital of Chengdu University between January and December 2024. Eligible participants met the following inclusion criteria: 1) provision of written informed consent; 2) completion of standardized assessments: anthropometry, fasting blood tests (glucose, lipid profile), and blood pressure measurements; 3) availability of complete demographic/lifestyle data (smoking, alcohol drinking). Exclusion criteria included: 1) chronic liver disease such as viral/autoimmune hepatitis, and cirrhosis; 2) endocrine disorders such as Cushing’s syndrome, hypothyroidism, and untreated hyperthyroidism; 3) genetic/metabolic diseases such as hemochromatosis, Wilson’s disease, and glycogen storage disorders; 4) acute conditions such as recent infection, hospitalization, or surgery; 5) current use of glucocorticoids, antipsychotics, or immunomodulators; 6) incomplete biochemical/clinical records. The study was approved by the Ethics Committee of the Clinical Medical College & Affiliated Hospital of Chengdu University.
MetS diagnosis
MetS was diagnosed according to the IDF criteria (2005) (), requiring the presence of: 1) WC as an essential component, ≥90 cm for men, and ≥80 cm for women; 2) plus any two of the following four components: triglycerides ≥1.7 mmol/L (150 mg/dL), HDL-C <1.03 mmol/L (40 mg/dL) for men or <1.29 mmol/L (50 mg/dL) for women, SBP/DBP ≥130/85 mmHg or antihypertensive treatment, FBG ≥5.6 mmol/L (100 mg/dL) or T2DM diagnosis. WC was measured at the midpoint between the lower rib and iliac crest. SBP and DBP were measured twice after 5 min rest using a calibrated sphygmomanometer. Triglycerides and HDL-C were analyzed from venous blood samples after 8-h fasting.
Epidemiological survey and biochemical measurements
All participants answered standardized questionnaires about age, sex, medical history, lifestyle behaviors of smoking and alcohol drinking. Body mass index (BMI) was calculated as weight (in kilograms) divided by height (in meters) squared. Blood samples were tested by laboratory physicians, including measurements of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (APOA1), apolipoprotein B (APOB), lipoprotein (a), [Lp(a)], FBG, hemoglobin A1c (HbA1c), uric acid (UA), and hypersensitive C-reactive protein (hsCRP).
Genomic DNA extraction and genotyping
Genomic DNA was isolated from EDTA-anticoagulated peripheral blood samples using the TIANamp Blood DNA Kit (TIANGEN, Beijing, China) according to the manufacturer’s protocol. DNA concentration and purity were verified by spectrophotometry (NanoDrop2000, Thermo Fisher Scientific), with all samples having A260/A280 ratios between 1.7 and 1.9. The rs9939609 and rs17817449 polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism analysis. Each 25 μL PCR reaction contained: 1 μL genomic DNA (50–100 ng),12.5 μL 2× Taq PCR Master Mix (containing Taq DNA polymerase, dNTPs, and reaction buffer), 1 μL each of forward and reverse primers (10 μM), and 9.5 μL nuclease-free water. Restriction digestion was performed by incubating 3 μL PCR product with 5 units of appropriate restriction endonuclease. The digested fragments were resolved by electrophoresis on 2.5% agarose gels stained with GoldView nucleic acid dye and visualized under UV transillumination. The primer sequences, expected product sizes, restriction enzymes, and genotype-specific fragment patterns are detailed in Table 1. Supplementary Figure S1 displays the gel electrophoresis patterns of PCR amplification products for the rs9939609 and rs17817449 polymorphisms. Supplementary Figure S2 presents the gel electrophoresis patterns of restriction enzyme digestion products for the rs9939609 polymorphism, while Supplementary Figure S3 shows the corresponding gel electrophoresis patterns of restriction enzyme digestion products for the rs17817449 polymorphism.
TABLE 1
| Polymorphisms | FTO rs9939609 | FTO rs17817449 |
|---|---|---|
| Forward primer | 5′-CTAGGTTCCTTGCGACTGCTGTGAACT-3′ | 5′-GGAGTCTCCCCTTAACTGGTC-3′ |
| Reverse primer | 5′-TTCAAGTCACACTCAGCCTCTCTACCA-3′ | 5′-CACAGCAGGCATTTACAAGCG-3′ |
| Location | Intron | Intron |
| Product size | 215 bp | 430 bp |
| Amplification conditions | 95 °C 7 min; 95 °C 30 s, 60 °C 30 s, 72 °C 30 s, 35 cycles; 72 °C 8 min | 95 °C 7 min; 95 °C 30 s, 60 °C 30 s, 72 °C 40 s, 35 cycles; 72 °C 10 min |
| Restriction endonucleases | DdeI C↓TNAG | AlwNI CAGNNN↓CTG |
| Digested fragments | TT: 215 bp TA: 215 bp, 189 bp and 26 bp AA: 189 bp and 26 bp | GG: 430 bp GT: 430 bp, 357 bp and 73 bp TT: 357 bp and 73 bp |
Primer sequences, restriction endonucleases, and digested fragments.
FTO, fat mass and obesity-associated gene.
Statistical analysis
Continuous variables are presented as mean ± standard deviation, and categorical variables as frequencies (percentages). Group comparisons (MetS vs. control) for continuous and categorical variables were performed using independent samples t-tests and chi-square tests, respectively. The associations between FTO polymorphisms (rs9939609 and rs17817449) and MetS risk were assessed using binary logistic regression, with results reported as odds ratios (ORs) with 95% confidence intervals (CIs). These analyses were adjusted for potential confounding variables, including age, sex, and BMI. Linkage disequilibrium (LD) between the two SNPs (rs9939609 and rs17817449) was assessed by calculating the squared correlation coefficient (r2) and Lewontin’s D-prime (D′) in the overall population, as well as separately in the MetS and control groups. LD strength was classified as follows: weak (r2 < 0.2), moderate (r2 = 0.2–0.8), or strong (r2 > 0.8). Mediation analysis was performed using the “Storm Stats” platform (https://zstats.medsta.cn/mediator/), which utilizes the well-established mediation package in R. We employed a simulation-based bootstrap approach with 1,000 iterations to estimate the indirect effects and generate robust 95% CIs. A significant mediation effect was inferred if the 95% CI for the indirect effect did not include zero. The mediation models were specified with the genotypes of rs9939609 and rs17817449 as independent variables. The serum levels of TG, HDL-C, and FBG were evaluated as potential mediators, and the presence of MetS was designated as the dependent variable. All models were adjusted for key covariates, including age, sex, and BMI. All statistical analyses were conducted using R statistical software (version 4.2.0) and EmpowerStats (version 4.2). A two-tailed P value <0.05 was considered statistically significant.
Results
Characteristics of the study population
The clinical characteristics of the study participants, stratified by the presence of MetS, are presented in Table 2. Compared to the control group, individuals with MetS exhibited a higher prevalence of hypertension (63.52% vs. 17.01%, P < 0.001) and T2DM (25.73% vs. 7.11%, P < 0.001). Lifestyle behaviors also differed significantly, with a greater proportion of smokers in the MetS group (51.14% vs. 39.09%, P = 0.001). Clinically, the MetS group demonstrated markedly elevated SBP and DBP (P < 0.001 for both), higher BMI (P < 0.001), and increased WC (P < 0.001). Metabolic parameters further highlighted significant differences, including elevated triglycerides (P < 0.001), reduced HDL-C (P < 0.001), and higher FBG (P = 0.03). Additionally, the MetS group showed increased levels of ALT (P = 0.001), UA (P < 0.001) and hsCRP (P < 0.001), indicating pronounced systemic inflammation. No significant differences were observed between groups for age, gender distribution, alcohol consumption, or multiple other biochemical parameters including AST, TC, LDL-C, APOA1, APOB, Lp(a), and HbA1c (all P > 0.05). These findings collectively underscore the multifaceted metabolic and cardiovascular risk profile associated with MetS.
TABLE 2
| Variables | Control group (N = 394) | MetS group (N = 307) | P value |
|---|---|---|---|
| Demographic variables | |||
| Age, years | 53.66 ± 10.54 | 58.04 ± 11.99 | 0.20 |
| Male/female | 266/128 | 225/82 | 0.10 |
| Medical history | |||
| Hypertension, n (%) | 67 (17.01%) | 195 (63.52%) | <0.001 |
| Diabetes, n (%) | 28 (7.11%) | 79 (25.73%) | <0.001 |
| Lifestyle behaviors | |||
| Smoking, n (%) | 154 (39.09%) | 157 (51.14%) | 0.001 |
| Alcohol drinking, n (%) | 200 (50.76%) | 171 (55.70%) | 0.19 |
| Clinical variables | |||
| SBP, mmHg | 121.42 ± 7.77 | 144.85 ± 18.19 | <0.001 |
| DBP, mmHg | 76.16 ± 3.97 | 90.39 ± 24.36 | <0.001 |
| BMI, kg/m2 | 23.69 ± 3.99 | 27.48 ± 2.26 | <0.001 |
| WC, cm | 85.37 ± 6.82 | 91.16 ± 7.12 | <0.001 |
| ALT, U/L | 28.58 ± 19.28 | 35.89 ± 21.44 | 0.001 |
| AST, U/L | 26.99 ± 18.28 | 28.86 ± 12.72 | 0.76 |
| Triglycerides, mmol/L | 1.43 ± 0.23 | 2.34 ± 0.60 | <0.001 |
| TC, mmol/L | 4.78 ± 1.23 | 4.95 ± 0.98 | 0.054 |
| LDL-C, mmol/L | 2.69 ± 0.49 | 2.84 ± 0.34 | 0.38 |
| HDL-C, mmol/L | 1.66 ± 0.27 | 1.26 ± 0.22 | <0.001 |
| APOA1, g/L | 1.45 ± 0.27 | 1.26 ± 0.3 | 0.31 |
| APOB, g/L | 0.86 ± 0.22 | 0.83 ± 0.26 | 0.80 |
| Lp(a), nmol/L | 199.78 ± 29.91 | 228.59 ± 19.02 | 0.52 |
| FBG, mmol/L | 5.51 ± 1.46 | 6.77 ± 1.82 | 0.03 |
| HbA1c | 5.97 ± 0.43 | 6.67 ± 0.93 | 0.10 |
| UA, μmol/L | 386.13 ± 85.79 | 527.95 ± 283.05 | <0.001 |
| hsCRP, mg/L | 0.79 ± 1.18 | 3.49 ± 1.62 | <0.001 |
Clinical characteristics of the study population.
MetS, metabolic syndrome; SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; WC, waist circumference; ALT, alanine aminotransferase; AST, aspartate aminotransferase; TC, total cholesterol; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; APOA1, apolipoprotein A1; APOB, apolipoprotein B; Lp(a), lipoprotein (a); FBG, fasting blood glucose; HbA1c, hemoglobin A1c; UA, uric acid; hsCRP, hypersensitive C-reactive protein.
Association of FTO rs9939609 and rs17817449 polymorphisms with MetS risk
The analysis of the rs9939609 and rs17817449 polymorphisms revealed significant associations with MetS risk (Table 3). For rs9939609, the MetS group exhibited a markedly higher frequency of the TA genotype (20.85% vs. 10.15%) and AA genotype (3.58% vs. 1.02%) compared to controls (both P < 0.001). The combined TA + AA genotypes were also more prevalent in MetS patients (24.43% vs. 11.17%, P < 0.001), with the A allele significantly enriched in the MetS cohort (14.01% vs. 6.09%, P < 0.001). Similarly, for rs17817449, the GT genotype (28.01% vs. 19.29%) and GG genotype (2.93% vs. 2.54%) were more frequent in MetS patients, with the combined GT + GG genotypes showing a significant difference (30.94% vs. 21.83%, P = 0.006). The G allele was also more prevalent in the MetS group (16.94% vs. 12.18%, P = 0.012). These findings suggest that both rs9939609 and rs17817449 polymorphisms are strongly associated with an increased risk of MetS, highlighting the potential role of FTO gene variants in metabolic dysregulation.
TABLE 3
| Polymorphisms | Control group (N = 394) | MetS group (N = 307) | P Value |
|---|---|---|---|
| FTO rs9939609 | |||
| TT, n (%) | 350 (88.83%) | 232 (75.57%) | <0.001 |
| AT, n (%) | 40 (10.15%) | 64 (20.85%) | |
| AA, n (%) | 4 (1.02%) | 11 (3.58%) | |
| AT + AA, n (%) | 44 (11.17%) | 75 (24.43%) | <0.001 |
| T allele, n (%) | 740 (93.91%) | 528 (85.99%) | <0.001 |
| A allele, n (%) | 48 (6.09%) | 86 (14.01%) | |
| FTO rs17817449 | |||
| TT, n (%) | 308 (78.17%) | 212 (69.06%) | 0.014 |
| GT, n (%) | 76 (19.29%) | 86 (28.01%) | |
| GG, n (%) | 10 (2.54%) | 9 (2.93%) | |
| GT + GG, n (%) | 86 (21.83%) | 95 (30.94%) | 0.006 |
| T allele, n (%) | 692 (87.82%) | 510 (83.06%) | 0.012 |
| G allele, n (%) | 96 (12.18%) | 104 (16.94%) | |
Genotype and allele frequencies of FTO rs9939609 and rs17817449 polymorphisms in control and MetS groups.
FTO, fat mass and obesity-associated gene; MetS, metabolic syndrome.
Figure 1 presents the forest plots of the association between the rs9939609 and rs17817449 polymorphisms and MetS risk based on binary logistic regression analysis with adjustments for age, sex, smoking, and alcohol consumption. For rs9939609 (Panel A), compared to the TT reference genotype, the heterozygous AT genotype showed a significantly increased MetS risk (OR = 2.11, 95% CI: 1.33–3.34). A more pronounced effect was observed in the AA genotype group (OR = 3.58, 95% CI: 1.08–11.88). The combined AT + AA genotypes further confirmed this association (OR = 2.25, 95% CI: 1.45–3.48), underscoring a strong genetic predisposition. In contrast, rs17817449 (Panel B) exhibited a weaker association with MetS risk. The GT genotype (OR = 1.45, P = 0.097), GG genotype (OR = 1.37, P = 0.55), and combined GT + GG genotypes (OR = 1.44, P = 0.087) all failed to reach significance.
FIGURE 1
Linkage disequilibrium between rs9939609 and rs17817449
The LD was evaluated between the two FTO SNPs, rs9939609 and rs17817449, which are located approximately 7.2 kb apart within intron 1. In the overall study population, the LD measures were r2 = 0.24 and D' = 0.61, indicating a moderate level of LD. Stratified analysis revealed stronger LD in the MetS group (r2 = 0.37, D' = 0.73) compared to the control group (r2 = 0.11, D' = 0.48), suggesting a potential difference in haplotype structure between the two groups. These results confirm that while the two SNPs are in moderate LD, they are not in complete linkage, supporting their independent analysis in this study.
Association of FTO rs9939609 genotypes with MetS components
Analysis of FTO rs9939609 genotypes revealed significant associations with key components of MetS (Table 4). In the MetS group, the AA genotype exhibited the most severe metabolic disturbances, with significantly higher triglycerides and lower HDL-C compared to the AT and TT genotypes (all P < 0.05). A dose-dependent trend was evident, with stepwise increases in triglycerides and decreases in HDL-C across TT, TA, and AA genotypes (all P < 0.05 for trend). Additionally, FBG levels were significantly higher in the AA and AT genotypes compared to the TT genotype (both P < 0.001). In the control group, similar but less pronounced patterns were observed. Individuals with the AA or AT genotype had higher triglycerides and lower HDL-C compared to the TT genotype (all P < 0.05). No significant differences were noted for WC, SBP, or DBP across genotypes in either group (P > 0.05). These findings highlight the graded influence of the rs9939609 variant on dyslipidemia and hyperglycemia, key features of MetS pathogenesis. The AA genotype, in particular, is associated with more severe metabolic abnormalities, underscoring its potential role in MetS susceptibility.
TABLE 4
| Genotypes | WC (cm) | SBP (mmHg) | DBP (mmHg) | Triglycerides (mmol/L) | HDL-C (mmol/L) | FBG (mmol/L) |
|---|---|---|---|---|---|---|
| Control group | ||||||
| TT genotype | 85.24 ± 6.32 | 121.39 ± 16.89 | 75.99 ± 10.82 | 1.34 ± 0.52 | 1.67 ± 0.19 | 5.49 ± 0.35 |
| AT genotype | 86.14 ± 4.85 | 122.82 ± 14.58 | 77 ± 10.60 | 1.74 ± 0.53a | 1.43 ± 0.08a | 5.60 ± 0.89 |
| AA genotype | 89.29 ± 7.54 | 110.25 ± 7.77 | 81.25 ± 10.6 | 2.14 ± 0.59a | 1.20 ± 0.01a | 5.62 ± 1.54 |
| P | 0.34 | 0.36 | 0.57 | 0.04 | <0.001 | 0.90 |
| MetS group | ||||||
| TT genotype | 90.36 ± 4.61 | 145.61 ± 19.55 | 90.67 ± 12.45 | 2.33 ± 0.52 | 1.31 ± 0.85 | 6.41 ± 2.92 |
| AT genotype | 91.05 ± 6.37 | 142.5 ± 21.45 | 89.09 ± 11.87 | 2.66 ± 0.62a | 1.16 ± 0.33a | 7.74 ± 1.91a |
| AA genotype | 92.36 ± 4.64 | 142.45 ± 19.64 | 93.14 ± 15.86 | 3.09 ± 0.79ab | 1.01 ± 0.25ab | 8.56 ± 4.08a |
| P | 0.61 | 0.87 | 0.95 | <0.001 | 0.001 | <0.001 |
MetS components of the subjects according to FTO rs9939609 genotypes.
FTO, fat mass and obesity-associated gene; MetS, metabolic syndrome; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; FBG, fasting blood glucose.
p < 0.05 compared with the TT, genotype in control or MetS group.
p < 0.05 compared with the AT, genotype in control or MetS group.
Association of FTO rs17817449 genotypes with MetS components
Analysis of the rs17817449 genotypes revealed distinct associations with MetS components (Table 5). In the MetS group, individuals with the GG genotype showed the most severe metabolic disturbances, exhibiting higher triglyceride levels compared to the GT and TT genotypes (P ≤ 0.003), lower HDL-C versus the TT genotype (P < 0.05), and elevated FBG relative to GT and TT genotypes (P ≤ 0.02). A clear allelic dosage effect was observed for glucolipid parameters, with progressive worsening from TT to GT to GG genotypes (all P ≤ 0.01 for trend). The GT genotype displayed intermediate metabolic alterations, with significantly higher triglycerides and lower HDL-C compared to the TT genotype (both P < 0.05). In the control group, similar trends emerged but with milder effects. The GG or GT genotype had higher triglycerides than the TT genotype (both P < 0.05). The GG genotype had lower HDL-C than the GT or TT genotype (both P < 0.05). Notably, SBP was significantly higher in the GG genotype compared to the GT or TT (both P < 0.05), suggesting early blood pressure dysregulation. No significant differences were observed for WC or DBP across genotypes in either group (P > 0.05). These results underscore the GG genotype’s robust association with dyslipidemia and hyperglycemia, mirroring the FTO rs17817449 variant’s impact but with additional links to elevated SBP in controls. The consistency of dose-dependent effects highlights FTO’s broader role in metabolic dysregulation.
TABLE 5
| Genotypes | WC (cm) | SBP (mmHg) | DBP (mmHg) | Triglycerides (mmol/L) | HDL-C (mmol/L) | FBG (mmol/L) |
|---|---|---|---|---|---|---|
| Control group | ||||||
| TT genotype | 78.98 ± 22.48 | 120.37 ± 15.79 | 75.98 ± 10.69 | 1.36 ± 0.52 | 1.67 ± 0.43 | 5.48 ± 1.56 |
| GT genotype | 82.51 ± 17.95 | 123.56 ± 12.69 | 76.35 ± 9.37 | 1.63 ± 0.57a | 1.56 ± 0.29 | 5.54 ± 1.35 |
| GG genotype | 89.78 ± 6.53 | 136.11 ± 20.83ab | 79.44 ± 15.34 | 1.67 ± 0.32a | 1.34 ± 0.18ab | 5.83 ± 1.03 |
| P | 0.18 | 0.01 | 0.66 | <0.001 | 0.01 | 0.75 |
| MetS group | ||||||
| TT genotype | 90.72 ± 8.11 | 142.03 ± 19.24 | 90.82 ± 12.33 | 2.22 ± 0.50 | 1.33 ± 0.36 | 6.60 ± 1.82 |
| GT genotype | 92.14 ± 7.58 | 141.06 ± 20.63 | 88.62 ± 11.67 | 2.57 ± 0.66a | 1.24 ± 0.31a | 6.99 ± 1.63 |
| GG genotype | 92.78 ± 6.80 | 145.11 ± 20.41 | 95.11 ± 16.00 | 3.16 ± 0.68ab | 1.09 ± 0.10a | 8.47 ± 2.66ab |
| P | 0.68 | 0.85 | 0.32 | <0.001 | <0.001 | 0.007 |
MetS components of the subjects according to FTO rs17817449 genotypes.
FTO, fat mass and obesity-associated gene; MetS, metabolic syndrome; WC, waist circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; FBG, fasting blood glucose.
p < 0.05 compared with the TT, genotype in control or MetS group.
p < 0.05 compared with the GT, genotype in control or MetS group.
Mediation effects of glucolipid parameters on FTO rs9939609 and rs17817449 polymorphisms and MetS risk
Mediation analysis revealed that triglycerides, HDL-C, and FBG significantly mediated the associations between rs9939609 or rs17817449 and MetS risk (all mediation P < 0.001) (Figure 2). Triglycerides exhibited a strong positive mediation effect, accounting for 86.21% (rs9939609) and 73.08% (rs17817449) of the total effect. HDL-C showed a significant negative mediation effect, explaining 62.42% (rs9939609) and 73.67% (rs17817449) of the association. FBG also significantly mediated the relationship positively, though to a lesser extent (45.76% and 45.06%, respectively).
FIGURE 2
Discussion
This study provides robust evidence that the FTO polymorphisms rs9939609 and rs17817449 significantly increase MetS risk in a Chinese population, primarily through detrimental effects on glucose and lipid metabolism. Key findings include: 1) The A allele of rs9939609 and G allele of rs17817449 were significantly enriched in MetS patients; 2) Both variants demonstrated allele dose-dependent worsening of MetS components; and 3) Dyslipidemia and hyperglycemia work as the primary pathways linking FTO variants to MetS susceptibility. While large-scale GWAS have primarily established FTO’s link to obesity (), our results refine and extend this paradigm by demonstrating that its metabolic impact is substantially mediated through glucolipid pathways. Our findings not only align with prior evidence linking FTO to general metabolic dysregulation (; ; ; ), but, more importantly, quantify the substantial mediating role (45%–86%) of these metabolites—a relationship suggested but not rigorously established in previous, smaller-scale studies.
Our findings extend prior research on FTO and metabolic traits while also revealing important distinctions. While earlier large-scale GWAS and meta-analyses have primarily and robustly linked FTO variants to elevated BMI and obesity risk (; ), our mediation analysis demonstrates that a substantial portion of MetS risk is attributable to dyslipidemia and hyperglycemia, partially independent of absolute adiposity measures. Given that these glucolipid abnormalities are not fully explained by adiposity, our data suggest that FTO’s metabolic effects may operate through parallel pathways: one influencing energy balance (appetite/adiposity) and another more directly perturbing hepatic lipid metabolism and insulin signaling. Notably, the rs17817449 G allele showed stronger associations with elevated SBP in controls, an observation that, while not aligning with the primary metabolic profile of FTO, parallels its broader association with cardiovascular risk factors. Although such direct associations with blood pressure are uncommon for FTO variants, isolated reports exist, underscoring the need for further investigation (). Finally, discrepancies with studies predominantly conducted in European populations (; ) may reflect ethnic-specific genetic architectures or gene-environment interactions, as suggested by trans-ethnic meta-analyses which have noted heterogeneity in FTO effect sizes across ancestries (). Furthermore, the LD analysis revealed a moderate linkage between rs9939609 and rs17817449 in the overall population (r2 = 0.24), which was notably stronger in the MetS group (r2 = 0.37) than in controls (r2 = 0.11). This differential LD pattern may reflect distinct haplotype structures contributing to MetS susceptibility, or could be a consequence of the disease-associated allele distribution.
Our mediation analysis identified triglycerides, HDL-C, and FBG as the significant mediators linking FTO polymorphisms to MetS, while BP did not emerge as a primary pathway. This finding aligns with the predominant metabolic function of FTO. The gene’s role as an RNA m6A demethylase places it squarely within pathways governing hepatic lipogenesis (; ; ), adipocyte differentiation (), and insulin signaling (; ), thereby directly impacting circulating lipid and glucose levels. Conversely, hypertension pathogenesis is largely driven by separate mechanisms, such as renal sodium handling, vascular resistance, and the renin-angiotensin system (), in which FTO does not play a well-established central role. This mechanistic divergence is corroborated by our genotype-phenotype analysis (Tables 4 and 5), where both rs9939609 and rs17817449 exhibited clear, dose-dependent effects on triglyceride and FBG levels, but not on SBP or DBP. Therefore, the contribution of these specific FTO variants to MetS appears to be channeled predominantly through the dysregulation of glucolipid metabolism, rather than through direct effects on blood pressure.
The mechanisms by which FTO rs9939609 and rs17817449 polymorphisms contribute to MetS likely involve epigenetic regulation of metabolic genes and disruption of energy homeostasis, mirroring findings from related obesity-associated FTO variants. First, these intronic variants may exert their metabolic effects by modulating FTO expression, thereby altering RNA methylation (m6A) patterns of downstream targets critical for lipid and glucose metabolism. Previous studies have consistently shown that the A allele carriers of rs9939609 exhibit elevated FTO mRNA levels in subcutaneous adipose tissue (; ), skin biopsies (), and peripheral blood cells (). This upregulation disrupts the expression of key metabolic regulators including sterol regulatory element binding protein-1c (; ; ), peroxisome proliferator-activate receptor-alpha (), peroxisome proliferator-activated receptor-gamma (), peroxisome proliferator-activated receptor gamma coactivator-1 alpha (), and carbohydrate responsive element binding protein (). These transcription factors collectively govern critical metabolic processes such as lipogenesis, adipogenesis, and insulin sensitivity. Notably, the pivotal role of FTO in lipid metabolism is supported by large-scale genetic studies that link its risk variants to altered blood lipid profiles, particularly elevated triglycerides, independently of BMI (; ). Second, FTO variants may influence appetite regulation and energy intake through ghrelin signaling (). The A allele of rs9939609 has been linked to decreased m6A methylation of ghrelin mRNA, leading to elevated circulating ghrelin levels. This epigenetic dysregulation promotes increased hunger and caloric intake, providing a mechanistic explanation for the allele dose-dependent deterioration in triglycerides, HDL-C, and FBG observed in our study. Together, these mechanisms suggest that FTO-associated MetS risk arises from a combination of direct effects on glucolipid metabolism and indirect effects on feeding behavior. This molecular model directly explains our clinical findings, providing a plausible foundation for the prominent mediating effects of triglycerides, HDL-C, and FBG, and thereby bridging the gap between the FTO genotype and systemic metabolic dysfunction.
The strong associations between FTO polymorphisms and MetS risk, particularly through dyslipidemia and hyperglycemia, have important clinical and public health implications. Our findings suggest that genetic screening for FTO variants could help identify high-risk individuals before overt metabolic dysfunction develops. Given the allelic dose-dependent worsening of triglycerides, HDL-C, and FBG, carriers of risk genotypes may benefit from early lifestyle interventions or pharmacological strategies targeting lipid and glucose metabolism. Additionally, the high mediation proportions of triglycerides and HDL-C suggest that lipid-lowering therapies might be particularly effective in attenuating genetic risk in this population. These results align with emerging precision medicine approaches for MetS, where genetic profiling could guide risk stratification and tailored prevention strategies.
Several limitations of this study should be acknowledged. First, the cross-sectional design precludes causal inferences regarding the temporal relationship between FTO polymorphisms and MetS development. Second, while we adjusted for major confounders, residual confounding from unmeasured factors (e.g., dietary patterns, physical activity intensity, or environmental exposures) may persist. Third, this was a candidate-gene study focusing on two specific FTO polymorphisms (rs9939609 and rs17817449) based on our previous research findings (; ; ). A genome-wide association study might reveal additional genetic variants associated with MetS in this population. These limitations highlight the need for longitudinal, multi-ethnic studies incorporating comprehensive omics approaches to validate and extend our findings.
In conclusion, the polymorphisms in the first intron of FTO are associated with high risk of MetS, which is strongly modulated by triglycerides, HDL-C and FBG. These findings highlight the necessity for population-specific approaches in genetic risk assessment for MetS.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by the Ethics Committee of the Clinical Medical College and Affiliated Hospital of Chengdu University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
YS: Conceptualization, Funding acquisition, Writing – original draft. TW: Data curation, Investigation, Methodology, Writing – original draft. MS: Data curation, Investigation, Methodology, Writing – review and editing. XW: Data curation, Investigation, Methodology, Writing – review and editing. YZ: Supervision, Validation, Writing – review and editing. JP: Supervision, Validation, Writing – review and editing. YW: Supervision, Validation, Writing – review and editing. JY: Conceptualization, Funding acquisition, Writing – original draft.
Funding
The authors declare that financial support was received for the research and/or publication of this article. This work was supported by the Natural Science Foundation of Sichuan, China [2022NSFSC0740]; the Chengdu Medical Research Project [2025609].
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2025.1659460/full#supplementary-material
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Summary
Keywords
FTO, polymorphism, rs9939609, rs17817449, metabolic syndrome
Citation
Song Y, Wang T, Su M, Wang X, Zhang Y, Pan J, Wang Y and Yang J (2025) FTO rs9939609 and rs17817449 polymorphisms contribute to metabolic syndrome risk by increasing triglyceride and glucose levels. Front. Genet. 16:1659460. doi: 10.3389/fgene.2025.1659460
Received
04 July 2025
Revised
17 October 2025
Accepted
07 November 2025
Published
19 November 2025
Volume
16 - 2025
Edited by
S. Hong Lee, University of South Australia, Australia
Reviewed by
Young Jun Park, Seoul National University College of Medicine, Republic of Korea
Tiar Masykuroh Pratamawati, Swadaya Gunung Djati University, Indonesia
Updates
Copyright
© 2025 Song, Wang, Su, Wang, Zhang, Pan, Wang and Yang.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jin Yang, yangjin@cdu.edu.cn
† These authors have contributed equally to this work and share first authorship
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.