Circulating FTO Protein Levels and β-Cell Function in Individuals with Different Metabolic Profiles: A Cross- Sectional Study

Abstract

Background

Obesity and type 2 diabetes mellitus are characterized by insulin resistance and progressive impairment of β-cell function. Fat mass and obesity-associated (FTO) protein, an m6A demethylase involved in metabolic regulation, has been linked to obesity. However, the relationship between circulating FTO protein levels and β-cell function among individuals with different metabolic profiles remains unclear. This study aimed to investigate circulating FTO levels and their relationship with β-cell function, assessed by (HOMA-β), in individuals with newly diagnosed T2D, obese individuals without diabetes, and normal-weight individuals without diabetes.

Patients and Methods

This cross-sectional observational study included 82 participants: 39 individuals newly diagnosed with T2D, 23 obese individuals without diabetes, and 20 normal-weight individuals without diabetes. Anthropometric and biochemical parameters, including fasting blood glucose, glycated hemoglobin, fasting insulin, HOMA-IR, and HOMA-β, were assessed. Serum FTO levels were measured using ELISA. Correlation and multiple linear regression analyses were performed to examine the relationship between circulating FTO levels and (HOMA-β).

Results

Serum FTO protein levels differed significantly among the three groups (P = 0.002), with the highest levels observed in obese individuals without diabetes. In this group, FTO protein levels were positively correlated with body mass index, fasting insulin, and HOMA-β (P = 0.018, P = 0.040, and P = 0.033, respectively). HOMA-β was also positively correlated with FTO, fasting insulin, and HOMA-IR. However, the positive association between FTO levels and HOMA-β was not statistically significant after adjustment for age, sex, and metabolic status.

Conclusions

Circulating FTO levels were highest in obese individuals without diabetes and were positively correlated with HOMA-β in this group. However, this relationship was not independently significant after adjustment for potential confounders. These findings provide preliminary evidence of a relationship between circulating FTO and β-cell function in the context of obesity, while the cross-sectional design precludes causal or temporal inferences.

Introduction

Obesity, defined as a Body Mass Index (BMI) ≥30 kg/m², is a major risk factor for insulin resistance and type 2 diabetes (T2D).¹ In obese individuals without diabetes, pancreatic β-cells undergo adaptive changes to meet increased insulin demand. These adaptations include increased insulin secretion, increased β-cell mass, and increased β-cell excitability, which are partly mediated by reduced K_ATP channel density. Human studies have shown that β-cell mass increases by approximately 20–90% in obese individuals, reflecting a compensatory response to insulin resistance.² Despite these adaptations, persistent metabolic stress may eventually overwhelm β-cell compensatory capacity, leading to progressive β-cell dysfunction and the development of T2D. By the time of diagnosis, approximately 40–50% of β-cell function has already been lost, highlighting the pivotal role of β-cell failure in disease progression.³

Genome-wide association studies (GWAS) have identified the fat mass and obesity-associated (FTO) gene as one of the strongest genetic loci linked to obesity.^4,5 The FTO protein is the first identified N6-methyladenosine (m6A) RNA demethylase and plays a key role in regulating energy homeostasis, adipogenesis, gluconeogenesis, and lipid metabolism.⁶ FTO is abundantly expressed in pancreatic β-cells,⁷ and experimental studies suggest it may regulate β-cell survival, proliferation, and insulin secretion.⁸ Although most evidence regarding FTO function has focused on intracellular FTO expression,^8,9 the detection of FTO protein in circulation may reflect systemic metabolic alterations associated with changes in FTO expression or release from metabolically active tissues. Given the high expression of FTO in pancreatic β-cells and the increased metabolic demand imposed by insulin resistance, circulating FTO levels may provide an indirect indicator of metabolic adaptations involving β-cell function. However, the extent to which circulating FTO reflects tissue-specific FTO activity remains unclear.

β-cell function is estimated via the Homeostasis Model Assessment of β-cell function (HOMA-β), which is derived from fasting plasma glucose and insulin concentration.³ The relationship between circulating FTO protein levels and β-cell function assessed by (HOMA-β) has not been extensively investigated. Therefore, the present study aimed to investigate circulating FTO protein levels and their associations with β-cell function in individuals with different metabolic states, including obese without diabetes, type 2 diabetes, and normal-weight without diabetes controls.

Materials and Methods

Study Design

This cross-sectional observational study included individuals with newly diagnosed T2D, obese without diabetes participants, and normal-weight without diabetes controls. The T2D group was recruited from the Endocrinology Clinic at Damascus National Hospital in Damascus, Syria, and the obese without diabetes and normal-weight without diabetes groups were recruited from hospital staff and relatives of patients. Sample collection was conducted between February 2024 and March 2025. A total of 5120 individuals were screened for eligibility. After applying the inclusion and exclusion criteria, 82 participants aged 38–63 years were enrolled in the study.

The study population consisted of 39 individuals with newly diagnosed T2D, who were diagnosed for the first time; 23 obese individuals without diabetes, as defined by the World Health Organization (BMI ≥30 kg/m²); and 20 healthy normal-weight controls, as defined by the World Health Organization (BMI<25 kg/m²). Fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) were measured to assess glycemic status, and participants were classified into three groups: patients with type 2 diabetes, obese without diabetes, and normal-weight without diabetes controls. For the purposes of this study, newly diagnosed T2D was defined by FBG ≥126 mg/dL and HbA1c ≥6.5% according to the American Diabetes Association (ADA) criteria.¹⁰ Obese individuals without diabetes were defined as those with BMI ≥30 kg/m²,¹¹ FBG ≤100 mg/dL, and HbA1c ≤6.0%, whereas normal-weight controls were defined as those with BMI <25 kg/m²,¹¹ FBG ≤100 mg/dL, and HbA1c <5.7%.¹⁰

The exclusion criteria included treatment with insulin or oral antihyperglycemic agents, lipid-lowering medications, loop or thiazide diuretics, cardiovascular disease, thyroid disorders, hepatic or renal disease, autoimmune disorders, infectious diseases, or malignancies. Women with polyendocrine metabolic ovarian syndrome (PMOS), pregnant women, and breastfeeding mothers were also excluded. The study protocol was approved by the Biomedical Research Ethics Committee of Damascus University (Approval No. PH-210224-210; February 2024).¹² Written informed consent was obtained from all participants before blood sample collection.

Data Collection and Measurement

Individuals with newly diagnosed T2D underwent a comprehensive clinical evaluation by endocrinologists. Relevant research data, including demographic characteristics, medical history, and anthropometric measurements, were collected. Eligibility for inclusion in the obese without diabetes and normal weight without diabetes groups was determined on the basis of glycemic assessment, including FBG and HbA1c, together with other relevant biochemical parameters and medical history. Body weight and height were measured for all participants via a standardized scale, with participants wearing light clothing and no shoes. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m²).

After a 12-hour overnight fast with water permitted during the fasting period, 5 mL of venous blood was collected from each participant through sterile venipuncture and divided into two tubes. A 2 mL blood sample was transferred into an EDTA tube for the measurement of HbA1c, expressed as a percentage of total hemoglobin, via a turbidimetric inhibition immunoassay (TINIA) kit provided by Roche Diagnostics, Switzerland.¹³ The remaining 3 mL of blood was collected into a clot activator tube. After clot formation, the samples were centrifuged at 3000 × g for 15 minutes. A portion of the obtained serum was used for immediate measurement of FBG via an enzymatic colorimetric assay with a Roche diagnostic kit (Switzerland).¹⁴ The remaining serum samples were stored at −80°C until further analysis of FINS and serum FTO protein levels. Serum insulin concentrations were measured via an electrochemiluminescence immunoassay (ECLIA) with a Roche Diagnostics kit (Switzerland).¹⁵ Serum FTO protein levels were determined in singlet via a commercially available Enzyme-Linked Immunosorbent Assay (ELISA) kit (Cat No: MBS3800553 My BioSource, USA),¹⁶ according to the manufacturer’s instructions. The intra-assay and inter-assay coefficients of variation (CVs) were less than 15%.

Insulin resistance was estimated via the Homeostasis Model Assessment of insulin resistance (HOMA-IR), which was calculated via the following formula: HOMA-IR = fasting glucose (mg/dL) × fasting insulin (μU/mL)/405. β-cell function was estimated via the Homeostasis Model Assessment of β-cell function (HOMA-β), which was calculated via the following formula: HOMA-β (%) = [360 × fasting insulin (µU/mL)] / [fasting glucose (mg/dL)-63]. The laboratory work was conducted at the National University Hospital Laboratory in Damascus.

Statistical Analysis

The data were manually entered into Microsoft Excel and analyzed via IBM SPSS Statistics (version 27.0). Continuous variables are expressed as the mean ± standard deviation (SD) for normally distributed data and as medians with interquartile ranges (IQRs) for non-normally distributed data. Data normality was assessed before analysis to select the appropriate statistical tests. This study was designed as an exploratory study using a convenience sample. Therefore, no formal a priori sample size calculation was performed. The final sample size was determined by the number of eligible participants available during the study recruitment period who met the predefined inclusion and exclusion criteria and had complete data for the study variables. The relatively small sample size may have limited the statistical power to detect modest associations and may have reduced the precision of the estimates, particularly in subgroup analyses. Therefore, the findings should be considered exploratory and interpreted with appropriate caution. All participants included in the final analysis had complete data for the study variables. Intergroup comparisons were performed via One-Way analysis of variance (ANOVA) for normally distributed variables and the Kruskal–Wallis test for non-normally distributed variables. Categorical variables were evaluated via the chi-square test. Correlations between FTO levels and the studied variables were assessed via Pearson’s correlation coefficient for normally distributed data. Associations involving HOMA-β were evaluated via either Pearson’s or Spearman’s correlation coefficients, depending on the normality of the distribution. Given the exploratory nature of the study, correlation analyses were considered exploratory, and no adjustment for multiple comparisons was applied. Multiple linear regression analysis was performed to determine the independent association between HOMA-β and serum FTO protein levels after adjusting for potential confounding variables. Independent variables included in the multiple linear regression model were selected a priori based on their clinical relevance and biological plausibility as potential determinants of β-cell function. Serum FTO protein levels were included as the primary predictor of interest, while age, sex, diabetes status, and obesity status were included as potential confounding variables. Diabetes status and obesity status were entered as binary dummy variables, with normal-weight non-diabetic participants serving as the reference group. Statistical significance was defined as a P-value < 0.05.

Results

Participant Recruitment and Study Population

During the study period, 5120 individuals were screened for eligibility. After applying the predefined inclusion and exclusion criteria (Figure 1), 82 participants were included in the final analysis. All variables were available for all 82 participants.

Figure 1.

Flow diagram showing participant selection and inclusion in the study.

Demographic and Anthropometric Characteristics of the Study Groups

The study included three groups: individuals with newly diagnosed type 2 diabetes mellitus (T2D), obese individuals without diabetes, and normal-weight individuals without diabetes. No statistically significant differences in age, height, and sex were observed among the three groups (P > 0.05). However, significant differences were observed in weight and BMI among the groups (P < 0.05). The demographic and anthropometric characteristics of the study groups are presented in Table 1.

Table 1.

Demographic and Anthropometric Characteristics of the Study Groups

Variable	The T2D Group (n=39)	The Obese Without Diabetes Group (n=23)	The Normal Weight Without Diabetes Group (n=20)	P	P1	P2	P3
Age	49.79±6.47	47.75±6.44	47.38±6.87	0.304a	0.550	1	0.759
Sex	–	–	–	0.195b	–	–	–
Male	25(64.1%)	13(56.52%)	9(45%)	–
Female	14(35.89%)	10(43.48%)	11(55%)	–
Weight (kg)	88.1±17.71	100.1±15.96	57.90±6.11	0.001a	0.018	0.001>	0.001>
Heigh(m)	167.90±10.6	166.36±11.9	164.62±9.34	0.606a	1	1	1
BMI (kg/m2)	29.60±6.2	34.78±4.4	21.50±2.8	0.001c	0.003	0.001>	0.001>

Notes: ^a One-Anova Test, ^b Chi-square, ^c Kruskal-wails Test, Statistical significance (P < 0.05). P1 between the T2D and obese groups. P2 between the obese without diabetes and the normal weight without diabetes groups. P3 between the T2D and normal weight without diabetes groups.

Abbreviations: BMI: Body Mass Index.

Differences in Laboratory Parameters and Calculated Indices Among the Study Groups

Significant differences in FBG, HbA1c, FINS, HOMA-IR, HOMA-β, and serum FTO protein levels were detected among the three groups (P < 0.05). Serum FTO protein levels differed significantly among the three study groups (P=0.002), with a large effect size (η2=0.16), indicating that approximately 16% of the variance in FTO protein levels was attributable to differences among the study groups. A comparison of laboratory parameters among the study groups is presented in Table 2.

Table 2.

Comparison of Laboratory Parameters Among the Three Study Groups

Variable	The T2D Group (n=39)	The Obese Without Diabetes Group (n=23)	The Normal-weight Without Diabetes Group (n=20)	P		P1	P2	P3
FBG (mg/dl)	182.77±54.16	92.41±4.32	88.74±7.42	0.001a		0.001>	1	0.001>
HbA1c (%)	8.7±3.8	5.75±0.53	5.6±0.48	0.001b		0.001	1	0.001
FINS (uU/ml)	10.6±11	12±9.98	5.79±3.16	0.001>b		1	0.001>	0.001>
HOMA-B (%)	38.53±45.63	157.20±109.77	78.1±32.75	0.001b		0.001>	0.024	0.047
HOMA-IR	6.1±4.44	2.78±2.41	1.27±0.78	<0.001b		<0.001	0.022	<0.001
FTO (Pg/ml)	16.41±5.6	20.83±5.97	14.35±4.52	0.002a	η2=0.16	0.007	0.004	0.961

Notes: P1 between T2D and obese groups. P2 between the obese without diabetes and the normal-weight without diabetes groups. P3 between the T2D and normal-weight without diabetes groups. ^aOne-way ANOVA test, ^bKruskal–Wallis Test, Statistical significance (P < 0.05).

Abbreviations: FBG, Fasting Blood Glucose; FINS, Fasting insulin; HOMA-IR, Homeostasis Model Assessment for Insulin Resistance; HOMA-β, Homeostasis Model Assessment of β-Cell Function; FTO, Fat Mass and Obesity-associated protein.

Correlations Between FTO Protein Levels and Various Parameters in the Groups

In the newly diagnosed T2D group, FTO protein expression was significantly positively correlated with age (P < 0.05). In the obese group, FTO was significantly positively correlated with BMI, FINS, and HOMA-β (P < 0.05). In the normal weight without diabetes group, FTO protein expression was significantly positively correlated with weight (P < 0.05). The results of the correlation analyses between FTO and the studied parameters are presented in Table 3.

Table 3.

Correlation Analyses Between FTO and the Studied Parameters

Variable	The T2D Group (n=39)		The Obese Without Diabetes (n=23)		The Normal Weight Without Diabetes Group (n=20)
	r	P	r	P	r	P
Age	0.490	0.002	−0.384	0.077	0.321	0.258
Weight	−0.303	0.06	0.355	0.105	0.595	0.032
BMI	−0.224	0.171	0.497	0.018	−0.124	0.687
FBG (mg/dl)	0.056	0.735	−2.28	0.308	0.489	0.090
FINS (uU/ml)	−0.234	0.151	0.441	0.040	−0.107	0.728
HOMA-B (%)	−0.208	0.206	0.457	0.033	−0.494	0.086
HOMA-IR	−0.165	0.315	0.420	0.052	0.029	0.926

Notes: Pearson correlation test, r; correlation coefficient, bold values indicate statistical significance (P<0.05).

Correlations Between HOMA-β and Various Parameters in the Groups

In the newly diagnosed T2D group, HOMA-β was significantly positively correlated with weight, FINS, and HOMA-IR (P < 0.05) and significantly negatively correlated with BMI, FBG, and HbA1c (P < 0.05). In the obese without diabetes group, HOMA-β was significantly positively correlated with weight, FINS, FTO, and HOMA-IR (P < 0.05) and significantly negatively correlated with FBG (P<0.05). In the normal-weight without diabetes group, HOMA-β was significantly positively correlated with FINS (P < 0.05) and significantly negatively correlated with FBG (P < 0.05). The results of the correlation analyses between HOMA-β and the studied parameters are presented in Table 4.

Table 4.

Correlations Between HOMO-β and the Studied Parameters in the Study Groups

Variable	The T2D Group (n=39)		The Obese Without Diabetes (n=23)		The Normal Weight Without Diabetes Group (n=20)
	r/ρ	P	r/ρ	P	r/ρ	P
Age	−0.198	0.226a	−0.288	0.194a	−0.359	0.228a
Weight	0.566	0.001a	0.461	0.031a	−0.276	0.361a
BMI	−0.481	0.002b	0.369	0.091b	−0.08	0.795b
FBG (mg/dl)	−0.666	0.001a	−0.478	0.025a	−0.626	0.022a
HbA1c	−0.691	0.001b	−0.161	0.475b	−0.064	0.835b
FINS (uU/ml)	0.749	0.001b	0.948	0.001b	0.648	0.017b
FTO(Pg/ml)	−0.208	0.206a	0.457	0.033a	−0.494	0.086a
HOMA-IR	0.335	0.037b	0.911	0.001b	0.522	0.067b

Notes: ^aPearson correlation test, ^bSpearman correlation test, bold values indicate statistical significance (P < 0.05).

Multiple Linear Regression Analysis

A multiple linear regression analysis was performed to identify factors independently associated with β-cell function, assessed by HOMA-β. The model included age, sex, serum FTO protein levels, and metabolic group, with normal-weight without diabetes participants serving as the reference category. Age was negatively associated with HOMA-β (B = −2.478, 95% CI: −4.489, −0.466, P = 0.016), while obese without diabetes participants had significantly higher HOMA-β values than normal-weight without diabetes participants (B = 71.597, 95% CI: 30.589–112.605, P = 0.001). Serum FTO protein levels were positively associated with HOMA-β, but the association did not reach statistical significance (B = 1.36, P = 0.176). Neither sex or type 2 diabetes status was significantly associated with HOMA-β (P = 0.823 and P = 0.098, respectively). The results of the multiple linear regression analysis are presented in Table 5.

Table 5.

Multiple Linear Regression Analysis of Factors Associated with HOMA-β

Dependent	Variable	B(SE)	95% CI	P	P
HOMA-β	Age	−2.478(1.009)	−4.489, −0.466	0.016	<0.001a
	Sex	−2.938(13.054)	−28.955, 23.079	0.823
	Levels of FTO protein	1.360(0.995)	−0.623, 3.343	0.176
	T2D	−30.415(18.14)	−66.568, 5.738	0.098
	Obese without diabetes	71.597(20.576)	30.589, 112.605	0.001

Notes: ^aMultiple linear regression test. Observations: Reference category: normal weight without diabetes. bold values indicate statistical significance (P < 0.05).

Abbreviations: B, adjusted unstandardized coefficient; CI, confidence interval; SE, standard error.

Discussion

Obesity is a complex, relapsing, chronic disease characterized by excessive or abnormal fat accumulation that may impair health, according to the World Health Organization (WHO).¹⁷ It has a significant inflammatory component that is associated with alterations in insulin sensitivity and the development of insulin resistance.¹⁸ When obesity persists, progressive β-cell dysfunction may occur, contributing to the development of type 2 diabetes mellitus (T2D).¹⁹

Diabetes mellitus (DM) is a serious global health challenge. More than 90% of individuals with diabetes have type 2 diabetes mellitus (T2D). Persistent hyperglycemia can induce target-organ damage by increasing the risk of both microvascular complications and atherosclerotic macrovascular disease.¹ In this context, the FTO protein is an m6A demethylase, and its substrate is N6-methyladenosine (m6A). FTO is expressed in multiple tissues rather than being specific to a single organ.⁷ It regulates appetite, adipogenesis, and lipid and glucose metabolism.⁶ In the hypothalamus, dysregulation of FTO protein and the FTO locus contribute to leptin resistance, increased appetite, and hyperphagia in mice.²⁰ In the liver, FTO protein upregulation promotes maturation of Sterol Regulatory Element-Binding Protein-1c (SREBP1c) and Upregulates lipogenesis synthases in HepG2 cells;²¹ in addition, FTO protein upregulation increases expression of key gluconeogenic genes in zebrafish.²² In adipose cells, FTO expression increases adipogenesis, and the FTO locus may enhance white adipocyte formation.²³ In Skeletal muscle, FTO upregulation suppresses AMPK signaling, reducing fatty acid oxidation in C2C12 cells.²⁴ So, this effect may alter insulin signaling in peripheral tissues.

Previous studies have suggested a potential role for FTO in pancreatic β-cell function. Qi Fan et al²⁵ reported that increased FTO expression may contribute to pancreatic islet β-cell dysfunction and suggested that inhibiting FTO activity could be a potential therapeutic target for diabetes. Similarly, Taneera et al²⁶ demonstrated that reduced FTO expression in INS-1 cells was associated with decreased expression of genes involved in insulin production. In another study, Taneera et al⁸ suggested that FTO participates in the regulation of insulin production and vesicular docking, providing further insight into the molecular mechanisms underlying the involvement of FTO in β-cell biology. Later, our previous work²⁷ suggested that serum FTO levels may primarily reflect obesity rather than type 2 diabetes, and that FTO correlated with HOMA-IR and obesity indices. The present study extends this work by specifically investigating the association between circulating FTO protein and β-cell function, as estimated by the HOMA-β index, across different metabolic states. Unlike previous studies that investigated the role of FTO in β-cell function primarily using tissue- or cell-based approaches, the present study evaluates the relationship between circulating FTO protein levels and β-cell function using blood-based measurements. Our knowledge, this represents an evaluation of the relationship between circulating FTO protein levels and β-cell function across different metabolic states, extending our previous findings on the relationship between circulating FTO and type 2 diabetes.

In our study design, participants were recruited from individuals in different metabolic states, including individuals with newly diagnosed T2D, obese individuals without diabetes, and normal-weight individuals without diabetes. Our findings revealed significant differences in circulating FTO protein levels among the three study groups (P = 0.002) (Table 2), with a large effect size (η²=0.16). This difference was driven mainly by significant differences between the newly diagnosed T2D group and the obese without diabetes group (adjusted P1 = 0.007) and between the obese without diabetes group and the normal-weight group (adjusted P2 = 0.004). These findings are consistent with the study by Onalan E. et al,²⁸ which reported higher FTO mRNA expression levels in obese and T2D participants than in healthy controls. This alteration in FTO expression may be reflected in circulating FTO protein levels, and the observed differences were not only statistically significant but also substantial in magnitude.

In contrast, significant differences in HOMA-β and HOMA-IR were observed between the newly diagnosed T2D group and the obese without diabetes group (adjusted P1 = 0.001), whereas FINS did not differ significantly between these groups (P1 = 1.000) (Table 2). Although individuals with newly diagnosed T2D may present elevated insulin levels, this compensatory increase is insufficient to maintain glucose homeostasis due to impaired β-cell function. The significant difference in HOMA-β between the T2D and obese without diabetes groups reflects the progressive deterioration of β-cell function, which represents a key component in the pathogenesis of T2D.^3,29

In the correlation analysis, the obese without diabetes group demonstrated significant positive correlations between circulating FTO protein levels and BMI, fasting insulin (FINS), and HOMA-β (P = 0.018, P = 0.040, and P = 0.033, respectively) (Table 3). Previous studies have suggested that FTO plays important roles in β-cell survival, metabolism, and function. Taneera et al⁸ reported that FTO contributes to the regulation of β-cell function. In addition, HOMA-β was positively correlated with weight, FINS, and HOMA-IR in the obese without diabetes group (P= 0.031, P=0.001, P=0.001, respectively) (Table 4). Inaishi J. et al² demonstrated that β-cell mass increases by approximately 20% to 90% in obese individuals compared with that in normal-weight individuals without diabetes. Therefore, we proposed that the observed association between circulating FTO levels and HOMA-β in obese individuals may reflect the increased pancreatic demand for insulin secretion in response to obesity-related insulin resistance.

In the T2D group, correlation analysis revealed a significant positive correlation between circulating FTO protein levels and age (P = 0.002) (Table 3). Abd El Gayed et al³⁰ have not consistently reported similar findings regarding circulating FTO protein levels. This discrepancy may be related to differences in the study populations, as our study included newly diagnosed T2D patients without major comorbidities and excluded individuals receiving medications that could affect glucose and lipid metabolism. In addition, HOMA-β was positively correlated with FINS, HOMA-IR, and weight (P= 0.001, P=0.037, P=0.001, respectively) and negatively correlated with BMI, FBG, and HbA1c (P= 0.002, P=0.001, P=0.001, respectively) (Table 4). T2D patients exhibit β-cell dysfunction, and the amount of insulin used is insufficient to maintain glucose levels.

Multiple linear regression analysis showed that age was independently and negatively associated with β-cell function. In addition, obese individuals without diabetes had significantly higher HOMA-β values than normal-weight controls after adjustment for age, sex, and serum FTO protein levels (B = 71.597, 95% CI: 30.589–112.605, P = 0.001). In contrast, serum FTO protein levels showed a positive trend toward an association with HOMA-β; however, this association did not remain statistically significant after adjustment for other covariates (B = 1.36, P = 0.176). These findings suggest that the higher FTO levels observed in obese individuals without diabetes, together with their elevated HOMA-β values, may reflect a compensatory metabolic state characterized by increased insulin demand and preserved β-cell function. Interestingly, although a significant association between FTO and HOMA-β was observed within the obese non-diabetic group, this relationship was not maintained after adjustment for metabolic status in the overall population. This may indicate that circulating FTO is associated with β-cell adaptation under specific metabolic conditions rather than representing a universal independent marker of β-cell function (Table 5).

This study was designed as an exploratory investigation of the relationship between circulating FTO protein levels and β-cell function, estimated indirectly using HOMA-β, across different metabolic states. Collectively, our findings may provide a potential biological context for the observed differences in circulating FTO levels across metabolic profiles and for the unadjusted association between FTO and HOMA-β observed in the obese non-diabetic group (Table 3 and Table 4). One possible interpretation is that obesity represents a metabolic state characterized by insulin resistance and compensatory β-cell activity, which may provide a context in which an association between circulating FTO and HOMA-β becomes more apparent. Since FTO levels were highest in the obese without diabetes group (Table 2), this association may reflect the metabolic adaptations accompanying obesity. In contrast, the absence of a significant association in participants with established T2D may be related to differences in the underlying metabolic state and β-cell function. However, this interpretation remains hypothetical and cannot be established from the present data. Experimental studies have suggested that FTO may influence systemic metabolic homeostasis through tissue-specific mechanisms involving energy balance, lipid metabolism, glucose metabolism,³¹ and it may be related to insulin signaling. Evidence from hypothalamic, hepatic, adipose, and skeletal muscle models indicate that altered FTO activity may affect appetite regulation, lipogenesis, gluconeogenesis, adipogenesis, fatty acid oxidation, and metabolic signaling,^20–24 These findings provide a mechanistic context for a possible link between FTO and metabolic dysfunction; however, they were obtained from different cellular and animal models and cannot be directly extrapolated to circulating FTO or pancreatic β-cell function in humans.

Several limitations should therefore be considered when interpreting these findings. First, the cross-sectional design prevents establishing temporal or causal relationships between circulating FTO protein levels and β-cell function. It remains unclear whether altered circulating FTO levels contribute to metabolic or β-cell alterations or instead reflect the broader metabolic changes associated with obesity. Second, circulating FTO concentrations do not specifically represent pancreatic FTO expression or β-cell-specific activity, as circulating FTO may originate from multiple tissues. Accordingly, the observed relationship with HOMA-β should be interpreted as an association with systemic metabolic status rather than as direct evidence of altered pancreatic FTO activity. Third, HOMA-β is an indirect estimate of β-cell function based on fasting glucose and insulin concentrations and does not directly assess dynamic insulin secretion or β-cell secretory capacity.³ Moreover, because HOMA-β is mathematically derived from fasting glucose and fasting insulin, correlations involving HOMA-β may be partly influenced by mathematical coupling with its component variables. Universally established reference ranges for HOMA-β are also lacking, as its values may vary according to insulin assay characteristics.

Fourth, although the multivariable analysis adjusted for age, sex, diabetes status, and obesity status, the association between FTO and HOMA-β observed in the unadjusted analysis was not statistically significant after adjustment. Other metabolic characteristics may therefore contribute to the observed relationship, and residual confounding cannot be excluded. The relatively modest sample size and single-center design may further limit statistical power and generalizability, while the use of different recruitment sources for the study groups may have introduced selection bias. In addition, although sex distribution was reported for all study groups, sex-specific factors such as menopausal status were not collected and therefore could not be considered, potentially contributing to residual confounding among female participants.

Taken together, the present findings should be considered preliminary and hypothesis-generating rather than evidence of a causal role for circulating FTO in β-cell dysfunction. Larger, multicenter and longitudinal studies, together with mechanistic investigations using relevant cellular models, animal models, and human pancreatic islets, are warranted to determine whether and how FTO-mediated RNA methylation pathways may influence β-cell function and insulin secretion.

Conclusion

Serum FTO protein levels were highest among obese individuals and were significantly positively associated with β-cell function, as assessed by HOMA-β, but only in obese individuals before the development of overt type 2 diabetes. To the best of our knowledge, this study provides novel evidence regarding the association between circulating FTO protein levels and HOMA-β; we suggest that circulating FTO may represent a candidate biomarker associated with β-cell function among obese individuals without diabetes, while avoiding causal or temporal implications. Furthermore, this study represents the first investigation of circulating FTO protein levels in relation to obesity and type 2 diabetes in the Syrian population.

Funding Statement

No funding was received for this manuscript.

Abbreviations

ADA, American Diabetes Association; BMI, Body Mass Index; CI, confidence interval; EDTA, ethylenediaminetetraacetic acid; FBG, fasting blood glucose; FTO, Fat Mass and Obesity–associated; GWAS, Genome-Wide Association Study; HbA1c, glycated hemoglobin; T2DM, Type 2 diabetes mellitus; HOMA-IR, Homeostasis Model Assessment of Insulin Resistance; IDF, International Diabetes Federation; m6A, N6-methyladenosine; mRNA, messenger ribonucleic acid; HOMA-β, Homeostasis Model Assessment of β-cell function; ELISA, Enzyme-Linked Immunosorbent assay; TINIA, Turbidimetric Inhibition Immunoassay; WHO, World Health Organization; FINS, Fasting insulin; SD, standard deviation; SE, standard error; SPSS, Statistical Package for the Social Sciences; ANOVA, one-way analysis of variance.

Data Sharing Statement

The datasets generated and/or analyzed during the current study are included in this published article. The data are available upon request from the corresponding author.

Ethics Statement

Serum samples were obtained after approval of the study protocol by the Biomedical Research Ethics Committee (BMREC) at Damascus University (February −2024) (ID number: PH-210224-210). The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants before enrollment.

Author Contributions

Hadil Shams Aldeen Alsagher: formal analysis, investigation, resources, writing – original draft. Shaden Haddad: Conceptualization, investigation, methodology, supervision, writing – review and editing. All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no conflicts of interest.

A version of this study was made available as a preprint: https://www.researchsquare.com/article/rs-8321576/v1.