European Journal of Cardiovascular Medicine

Polycystic ovary syndrome (PCOS) is one of the most prevalent endocrine and metabolic disorders affecting women of reproductive age, with a reported prevalence ranging from 6% to 20%, depending on the criteria used for diagnosis. ^[1] The global prevalence of PCOS ranges from 4% to 21%, while in India, it varies from 2% to 35%. ^[2] It is characterised by a combination of clinical, biochemical, and morphological abnormalities, including hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. Women with PCOS often experience menstrual irregularities, infertility, hirsutism, and acne, which can significantly affect their quality of life. Beyond reproductive concerns, PCOS is also associated with severe metabolic complications such as insulin resistance (IR), obesity, dyslipidemia, type 2 diabetes mellitus (T2DM), and an increased risk of cardiovascular disease (CVD). ^{[3] [4][5]}

Insulin resistance, a key feature of PCOS, occurs in both obese and lean individuals, underscoring its role in the syndrome's pathophysiology. It results from impaired insulin receptor function, leading to hyperinsulinemia, exacerbating androgen overproduction by ovarian theca cells. This process creates a vicious cycle that contributes to metabolic imbalances and reproductive dysfunction. ^[6] Despite extensive research, the precise molecular mechanisms driving IR in PCOS remain incompletely understood, necessitating further exploration into potential biomarkers and therapeutic targets. ^[7]

Fetuin-A, also known as alpha-2-Heremans-Schmid glycoprotein (AHSG), is a glycoprotein primarily produced by the liver and secreted into the bloodstream. It has been implicated in various physiological processes, including regulating calcium-phosphorus balance, bone metabolism, and inflammation. ^{[8] [9]} Recent research highlights its role as a negative regulator of insulin signalling by inhibiting insulin receptor autophosphorylation. ^[10] Elevated levels of Fetuin-A have been linked to metabolic conditions such as obesity, T2DM, and non-alcoholic fatty liver disease (NAFLD). ^[11][12] Fetuin-A’s interaction with inflammatory pathways and lipid metabolism further strengthens its association with metabolic syndrome and related disorders. ^[13]

While numerous studies have explored the relationship between Fetuin-A and metabolic diseases, its role in the development and progression of PCOS remains controversial. Some research suggests that increased Fetuin-A levels may contribute to IR and metabolic dysregulation in PCOS, while other studies report inconsistent or negligible associations. These discrepancies highlight the need for further investigation into the potential of Fetuin-A as a biomarker for IR and metabolic disturbances in PCOS patients.

Given the critical role of insulin resistance (IR) in the pathophysiology of PCOS and the emerging evidence linking Fetuin-A to metabolic abnormalities, this study aims to evaluate serum Fetuin-A levels in women with PCOS compared to healthy controls. While some data suggest a potential association, few studies have comprehensively explored this relationship, highlighting the need for further investigation. The findings are expected to provide a deeper understanding of Fetuin-A’s involvement in the metabolic dysregulation seen in PCOS and its potential as a predictive biomarker for metabolic risk assessment in affected women.

This comparative study was conducted from January 2021 to June 2022 at a Tertiary care centre. The study included 180 women of reproductive age, comprising 90 women diagnosed with polycystic ovary syndrome (PCOS) based on the Rotterdam criteria and 90 women in a control group. Women with chronic medical disorders or those receiving treatment for dyslipidemia or insulin resistance were excluded. Informed consent was obtained in both Hindi and English, following an explanation of the study's purpose and protocol.

Participants underwent detailed clinical evaluation, including a comprehensive history and systemic examination. Anthropometric parameters such as height, weight, and BMI were measured. Laboratory investigations included a complete blood count, fasting and postprandial blood glucose, lipid profile, and markers of metabolic syndrome (fasting insulin, HOMA-IR). Advanced biochemical parameters such as serum levels of fetuin-A were analysed using ELISA kits following standardised procedures.

Data was managed using Microsoft Excel and analysed with SPSS software (version 25). Quantitative data were compared using the student’s t-test, qualitative data using the Chi-square test, and Pearson’s correlation was applied to evaluate associations between biochemical markers and clinical/metabolic parameters. Statistical significance was set at p < 0.05.

The demographic characteristics of the study population, including 90 cases of women with PCOS and 90 healthy controls, were comparable across age and BMI categories, with no statistically significant differences observed (p > 0.05). Most participants were aged between 21 and 30 years, and more than half had a BMI ≥ 25 in both groups. These findings confirm a balanced distribution of participants across key demographic variables, minimising confounding effects due to age and BMI. (Table 1).

Table 1: Demographic Characteristics in Cases and Controls

The investigation of metabolic parameters revealed significant differences between cases and controls. Women with PCOS exhibited higher fasting blood sugar (98.8 ± 21.4 vs. 90.1 ± 13.7 mg/dL; p = 0.001), postprandial blood sugar (137.2 ± 41.6 vs. 115.3 ± 20 mg/dL; p < 0.001), fasting insulin (20.8 ± 30.9 vs. 14.8 ± 19.1 µU/mL; p = 0.019), and postprandial insulin (52.4 ± 46.6 vs. 37.4 ± 22.8 µU/mL; p = 0.007). They also showed elevated HbA1c levels (5.6 ± 0.8% vs. 4.8 ± 0.4%; p < 0.001) and HOMA-IR (11.03 ± 5.40 vs. 3.03 ± 4.62, P<0.001), indicating insulin resistance. Dyslipidemia was evident with significantly higher cholesterol levels (167.3 ± 34.2 vs. 126.7 ± 20.3 mg/dL; p < 0.001), Triglyceride levels (127.4 ± 55.8 vs. 112.3 ± 41.4 mg/dL; p = 0.004) and LDL levels (98.5 ± 30.7 vs. 93.6 ± 28.4 mg/dL; p = 0.006) in cases compared to controls, though no significant differences were found for HDL. (Table 2).

Table 2: Comparison of Investigations in Cases and Controls

Figure 1: Bar chart showing Serum Fetuin-A levels in Cases and Controls

Serum Fetuin-A levels were significantly elevated in women with PCOS compared to controls (8.3 ± 4.3 vs. 3.1 ± 3.2 µg/mL; p < 0.001). (Figure 1) In women with PCOS, significant positive correlations were found between serum fetuin-A levels and fasting blood sugar (p=0.001), postprandial blood sugar (p=0.014), fasting insulin (p=0.031), postprandial insulin (p=0.045), HOMA-IR (p=0.001), cholesterol (p=0.028), triglycerides (p=0.031), and LDL (p=0.021). These findings suggest that serum fetuin-A is positively associated with metabolic abnormalities in women with PCOS. In contrast, the control group showed no significant correlations between fetuin-A levels and most of these parameters. These results highlight the strong association between fetuin-A and metabolic dysfunction in women with PCOS, particularly about insulin resistance and lipid abnormalities. (Table 3).

Table 3: Correlation of Serum Fetuin-A with study variables in cases and Controls

In the present study, the age distribution between PCOS cases and controls showed no significant difference (p = 0.848), with most participants being between 21-30 years. This finding aligns with Liu et al. ^[14] who reported a similar age range of 19-37 years in PCOS patients and 19-32 years in controls. However, Gulhan et al. ^[6] observed a statistically significant age difference (p = 0.002), with younger PCOS patients (mean age 25.5 ± 4.1 years) compared to controls (mean age 28.61 ± 5.0 years). Similarly, Sak et al. ^[15] found no significant age difference (p = 0.688), with mean ages of 23.45 ± 3.76 years in PCOS patients and 23.77 ± 3.82 years in controls. ElSirgany et al. ^[8] also reported no significant age difference (p = NS), with PCOS patients averaging 31.35 ± 4.85 years and controls 33.2 ± 5.43 years. Overall, these findings highlight that age distribution was comparable across most studies, supporting the reliability of the age-matching approach in PCOS research. The present study observed no significant difference in BMI distribution between PCOS cases and controls (p = 0.692). The majority of participants in both groups had a BMI ≥ 25 kg/m², indicating a high prevalence of overweight or obesity among participants. Comparatively, Liu et al. ^[14] found a statistically significant higher BMI in PCOS patients (24.4 ± 4.4 kg/m²) compared to controls (21.6 ± 2.9 kg/m², p < 0.001), highlighting obesity's strong association with PCOS. In contrast, Sak et al. ^[15] reported no significant difference (p = 0.257), with slightly higher BMI values in PCOS patients (29.50 ± 3.65 kg/m²) than in controls (28.61 ± 3.86 kg/m²). Similarly, Gulhan et al. and ElSirgany et al. observed no significant BMI differences (p = NS). Gulhan et al. ^[6] reported BMI averages of 24.7 ± 3.6 kg/m² in PCOS patients and 23.6 ± 3.8 kg/m² in controls, while ElSirgany et al. ^[8] noted a higher, though non-significant, BMI in PCOS patients (27.04 ± 5.74 kg/m²) compared to controls (24.26 ± 3.97 kg/m²). While some studies reported significant BMI differences, others found no association. This inconsistency highlights the variability in BMI's role in PCOS and the importance of considering other metabolic and hormonal factors in PCOS research.

In the present study, PCOS patients had significantly higher fasting (98.8 ± 21.4 mg/dL vs. 90.1 ± 13.7 mg/dL, p = 0.001) and postprandial blood sugar levels (137.2 ± 41.6 mg/dL vs. 115.3 ± 20 mg/dL, p < 0.001) compared to controls. Similarly, Liu et al. ^[14] and ElSirgany et al. ^[8] found higher fasting blood glucose in PCOS patients (p < 0.01 and p < 0.05, respectively). In contrast, Sak et al. ^[15] and Gulhan et al. reported no significant differences, highlighting variability in glucose metabolism findings across studies. These variations could be attributed to differences in study populations, diagnostic criteria, and glycemic control indicators. The consistent association in the present study highlights the importance of monitoring glucose metabolism in PCOS management.

In the present study, fasting insulin levels were significantly higher in PCOS cases (20.8 ± 30.9 µIU/mL) compared to controls (14.8 ± 19.1 µIU/mL, p = 0.019), indicating insulin resistance in PCOS patients. Similarly, Liu et al. ^[14] reported significantly elevated fasting insulin levels in PCOS patients (18.00 mU/L) compared to controls (7.40 mU/L, p < 0.001), and ElSirgany et al. ^[8] observed similar results (26.7 ± 6.04 IU/mL in PCOS vs. 11.4 ± 2.8 IU/mL in controls, p < 0.05). In contrast, Gulhan et al. ^[6] found no significant difference in fasting insulin levels between PCOS patients (11.37 ± 7.1 µIU/mL) and controls (10.71 ± 5.8 µIU/mL, p = NS). Overall, most studies, including the present one, demonstrated higher fasting insulin levels in PCOS patients, supporting the association between PCOS and insulin resistance. In the present study, postprandial insulin levels were significantly higher in PCOS cases (52.4 ± 46.6 µIU/mL) compared to controls (37.4 ± 22.8 µIU/mL, p = 0.007). Additionally, HbA1c levels were notably elevated in PCOS patients (5.6 ± 0.8%) versus controls (4.8 ± 0.4%, p < 0.001), indicating impaired glucose metabolism and a higher risk of insulin resistance in PCOS individuals.

In the present study, HOMA-IR values were significantly higher in PCOS cases (11.03 ± 5.40) compared to controls (3.03 ± 4.62, p < 0.001), indicating marked insulin resistance. Similarly, Liu et al. ^[14] (HOMA-IR: 3.85 vs. 1.15, p < 0.001) and ElSirgany et al. ^[8] (5.5 vs. 2.24, p < 0.05) reported elevated HOMA-IR in PCOS patients, while Gulhan et al. ^[6] found no significant difference. Regarding lipid profiles, PCOS cases in the present study had significantly higher total cholesterol (167.3 ± 34.2 mg/dL vs. 126.7 ± 20.3 mg/dL, p < 0.001), triglycerides (127.4 ± 55.8 mg/dL vs. 112.3 ± 41.4 mg/dL, p = 0.004), and LDL (98.5 ± 30.7 mg/dL vs. 93.6 ± 28.4 mg/dL, p = 0.006), with no significant difference in HDL levels (p = 0.912). These findings align with Liu et al. ^[14], who reported similar dyslipidemia trends in PCOS patients. This pattern underscores the metabolic disturbances commonly observed in PCOS.

The present study revealed significantly elevated Fetuin-A levels in PCOS cases compared to controls (8.3 ± 4.3 vs. 3.1 ± 3.2; p < 0.001), aligning with findings from Liu S et al. ^[14] (437.9 ± 119.3 vs. 313.8 ± 60.5 µg/L; p < 0.001) and Sak S et al. ^[15] (210.26 ± 65.06 vs. 182.68 ± 51.20 µg/mL; p = 0.024). These consistent results support the hypothesis that increased Fetuin-A may play a role in PCOS pathophysiology. However, Gulhan I et al. ^[6] found no significant difference in Fetuin-A levels (255.4 ± 37.2 vs. 253.0 ± 43.2 ng/mL; NS), suggesting possible variability due to different sample sizes, measurement techniques, or population characteristics. Similarly, ElSirgany S et al. ^[8] reported minimal differences between groups (521 ± 7.1 vs. 505 ± 50.5 ng/mL), though statistical significance was not specified. Most studies support a positive association between elevated Fetuin-A levels and PCOS, indicating its potential as a biomarker. Inconsistencies highlight the need for standardised measurement protocols and larger sample sizes in future research.

The present study demonstrated significant positive correlations of Fetuin-A with BMI (r=0.560, p=0.021), fasting blood sugar (r=0.675, p=0.001), postprandial blood sugar (r=0.455, p=0.014), fasting insulin (r=0.509, p=0.031), postprandial insulin (r=0.461, p=0.045), and HOMA-IR (r=0.584, p=0.001) in PCOS cases, consistent with findings from Liu S et al. ^[14] (BMI: r=0.294, p<0.001; HOMA-IR: r=0.511, p<0.001) and ElSirgany S et al. ^[8] (fasting insulin: r=0.470, p=0.002; HOMA-IR: r=0.474, p=0.002).

In contrast, Sak S et al. ^[15] reported a weaker, non-significant correlation between Fetuin-A and BMI (r=0.181, p=0.082). No significant associations were observed in controls in the present study. These findings suggest that Fetuin-A is strongly linked to metabolic parameters related to insulin resistance in PCOS, reinforcing its potential role as a biomarker for metabolic dysfunction.

Fetuin-A levels were significantly elevated in PCOS cases compared to controls, with strong positive correlations observed with BMI, fasting and postprandial blood glucose, insulin levels, and HOMA-IR, indicating a link to insulin resistance and metabolic dysfunction. These findings align with prior studies, reinforcing Fetuin-A's potential as a biomarker for metabolic disturbances in PCOS. Standardised measurement protocols and larger, multi-centred studies are recommended to validate its clinical utility.

Conflict of Interest: None declared

Acknowledgement: None

Funding: None

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