The relationship between serum galectin-3 level and echocardiographic findings in patients with polycystic ovary syndrome

Abstract

Aim

In the our study, we examined the relationship between galectin-3 levels and global longitudinal strain (GLS) and aortic intima-media thickness (A-IMT) in patients with polycystic ovary syndrome (PCOS). We evaluated the potential of this molecule as a biomarker in the early stages of atherosclerosis and heart failure.

Material and method

A total of 80 participants, 40 newly diagnosed PCOS patients and 40 healthy controls, were included in the Health Sciences University Adana City Training and Research Hospital between 01.06.2021 and 31.03.2022. Galectin-3 level was measured by using Human galectin-3 kits and Enzyme-Linked Immuno Sorbent Assay method. A-IMT and GLS measurements were performed by using ultrasonography and echocardiography.

Results

When both study groups were evaluated, a statistically significant difference was found between the PCOS patient and the control groups in terms of blood glucose (93.6 ± 9.82 mg/dL to 87.7 ± 8.42 mg/dL; p = 0.006) HOMA-IR (Homeostatic Model Assessment of Insulin Resistance) Index (2.55 ± 0.49 to 2.05 ± 0.61; p < 0.001), galectin-3 (13.7 ± 0.98 ng/mL to 12.2 ± 2.08 ng/mL; p < 0.001), A-IMT (1.41 ± 0.008 mm to 1.25 ± 0.16 mm; p < 0.001), and GLS (-16.7 ± 1.75% to -18.8 ± 1.37%; p < 0.001) values A correlation analysis was conducted, resulting in the identification of a robust association between galectin-3 levels and GLS (r = 0.747, p < 0.001). Additionally, weaker yet statistically significant correlations were observed between galectin-3 levels and A-IMT (r = 0.327, p = 0.006) and HOMA-IR (r = 0.446, p < 0.001). Multivariate analysis revealed that GLS was the only independent predictor of galectin-3 levels (B = 0.395; p < 0.001). Conversely, A-IMT and HOMA-IR were not significant predictors (p = 0.340 and p = 0.887, respectively).

Conclusion

Galectin-3 levels were significantly associated with markers of subclinical atherosclerosis and early cardiac dysfunction in patients with PCOS. Galectin-3 demonstrated potential utility as a biomarker for the early identification of subclinical atherosclerosis and heart failure risk in this population. Notably, this study is the first to evaluate the association of galectin-3 with both A-IMT and GLS in patients with PCOS, providing novel insights into their cardiovascular risk profile.

Introduction

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age, affecting approximately 8–10% of this population [1]. The World Health Organization (WHO) has classified women with infertility into three groups. According to the WHO, PCOS, classified in Group 2, is a complex syndrome with chronic anovulation and hyperandrogenism in its pathogenesis [2]. This condition has been demonstrated to exert a detrimental effect on the secretion of numerous hormones. These include hypothalamic-pituitary dysfunction, insulin resistance, hyperinsulinism, obesity, menstrual irregularities, anovulation, infertility, hirsutism, voice changes, acne, and alopecia. Moreover, PCOS has been linked to elevated levels of stress in women, which can result in limitations in social, professional, and sexual domains [3]. Hyperlipidaemia, hypertension (HT), glucose metabolism disorders, and cardiovascular diseases (CVD) are more prevalent in patients with PCOS than in those without PCOS within the same age group [4, 5]. Consequently, the management of PCOS necessitates a multidisciplinary approach, encompassing the domains of cardiology, internal medicine, endocrinology, gynaecology and psychiatry, thereby underscoring the requirement for a well-coordinated treatment strategy [6, 7].

Studies have shown that increased and decreased levels of galectin-3 can be used to detect CVD and to predict the development of heart failure (HF) [8]. Atherosclerosis is an important parameter underlying many developmental pathological operations. Early detection of atherosclerosis and determination of therapeutic targets is an increasingly important situation. Therefore, researchers seek to develop non-invasive and widely used procedures. One of these is the measurement of aortic intima-media thickness (A-IMT) in the arterial wall [9–12]. The measure of deformation in a material against force is expressed as strain. Evaluation of myocardial deformation with new generation echocardiography two-dimensional speckle tracking echocardiography (2D-STE) ) devices provides valuable information about ventricular functions. Visualizing the deformation with this method can detect even the smallest functional differences and help us detect them at an early stage. Recent studies have shown that many patients with normal ejection fraction (EF) have a decrease in systolic functions by measuring global longitudinal strain (GLS) [13–15].

Polycystic Ovary Syndrome (PCOS) is a complex clinical manifestation involving critical hormonal disturbances in its pathogenesis, and numerous biomolecular studies have been conducted in the literature to predict long-term outcomes in the early stages of the disease. A significant portion of these studies specifically focused on insulin resistance and ovarian dysfunction [16]. For example, some research has provided insights into the disease progression by examining the restorative effects of the alpha-lipoic acid molecule on insulin sensitivity and oxidative stress [17]. Based on this scientific accumulation, our study aimed to investigate the relationship between serum galectin-3 levels, considered an important biomarker for detecting heart failure and atherosclerosis; GLS, which is a valuable parameter for predicting left ventricular EF; and A-IMT, accepted as an early indicator of atherosclerosis in PCOS patients.

Materials and methods

Patient population

The study was planned as a single-center, cross-sectional and prospective. 40 PCOS patients and healthy individuals between the ages of 18–40 who applied to the internal medicine and endocrinology outpatient clinics of Adana City Training and Research Hospital between 01.06.2021 and 31.03.2022 were included in the study. An a priori power analysis was performed using the G*Power software, assuming a two-sided alpha level of 0.05, a statistical power of 80%, and a moderate effect size. For the control group, healthy volunteers with similar age, gender and body mass index (BMI) were selected. The diagnosis of PCOS was stated according to the 2003 Rotterdam criteria.

In the study, the exclusion criteria were malignancy, chronic inflammatory disease, pregnancy, breastfeeding, kidney and liver disease, type 1 diabetes mellitus (DM), type 2 DM, HF, valve disease, thyroid disease, HT, cerebrovascular disease, and a history of infection in the last month. The study was approved by the Çukurova University Faculty of Medicine Non-Invasive Clinical Research Ethics Committee. Informed consent form was signed by those who wanted to be included in the study. Detailed anamnesis of all patients and individuals in the healthy control group were taken, physical examinations were performed. Age, gender, medical histories, physical examination findings and laboratory measurements were recorded in their files. The study was conducted in accordance with the Declaration of Helsinki.

Laboratory measurements

Laboratory analyses were performed in the hospital’s biochemistry laboratory, which adheres to the International Organization for Standardization quality control system and the standards of the International Federation of Clinical Chemistry and Laboratory Medicine. After at least 8 h of overnight fasting, venous blood samples were drawn from the antecubital vein of both patients and controls. Measurements were performed using automated laboratory procedures (Abbott Aeroset, Minneapolis, MN) and validated commercial kits (Abbott). After 5 min of rest in a quiet environment, blood pressure was measured bilaterally using an appropriate cuff, and heart rate was recorded. Anthropometric measurements of body weight and height were obtained. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared (kg/m²). The index was calculated using the formula: the product of fasting blood glucose (mg/dL) and fasting insulin (uIU/mL) is divided by 405.

Galectin-3 measurements

In the course of routine medical assessments, a procedure was carried out in which blood samples were obtained from subjects, comprising both patients and designated control groups. An additional set of samples was collected into specialized gel tubes, identified by their distinctive yellow capsules. After the samples were centrifuged for 10 min at 4000 rpm without wasting time, the serum part was separated and stored at -80 °C until the time to be studied by putting them in an Eppendorf tube. After the study was completed, the samples were sent to Istanbul Bezmiâlem Vakif University Medical Microbiology Laboratory under appropriate conditions. The study was carried out using Human Galectin-3 kits (eBioscience, Europe/International, Austria) and ELISA (Enzyme-Linked Immunosorbent Assay) method.

For the ELISA assay, 100 µL of serum was added to each well, and samples were analyzed without dilution. Subsequently, the microplate was subjected to an incubation period at a temperature of 37 °C for a duration of 60 min. This was done to facilitate the binding of the pre-coated capture antibodies. Subsequent to the execution of the washing steps in accordance with the manufacturer’s protocol, a biotin-conjugated detection antibody and subsequently a streptavidin–horseradish peroxidase (HRP) conjugate were applied. The color development process was facilitated by employing a tetramethylbenzidine (TMB) substrate, and the reaction was subsequently terminated with the addition of a stop solution. Absorbance was measured at a wavelength of 450 nanometers (nm) using a microplate reader, a specialized instrument that allows for the quantitative analysis of colored samples in a manner analogous to that of a spectrophotometer. Serum galectin-3 concentrations were calculated from a standard curve generated using the recombinant galectin-3 standards provided in the kit. This ELISA-based method has been previously applied in studies assessing serum galectin-3 levels in women with polycystic ovary syndrome [18].

Intima media thickness measurements

The abdominal aorta was examined with a new generation high resolution USG system (Philips EPIQ 7) equipped with a linear and convex high resolution transducer (Philips HealthCare, Bothell, WA, USA). All arteries were scanned longitudinally to visualize intima-media thickness (IMT) in the distal or posterior wall of the artery. All measurements were made on frozen images, with the two best quality images selected for analysis in each run. IMT was defined as the distance from the leading edge of the first echogenic line to the anterior edge of the second echogenic line. The first line represents the intima-lumen interface and the second line represents the upper layer of the adventitia. All IMT values ​​were calculated as the mean of six measurements, and were measured by two independent and double-blind observers. The patients were placed in the supine position and the abdominal aorta was examined in the segment from the renal artery bifurcation to the iliac artery bifurcation. IMT measurement viewed from the posterior wall of the abdominal aorta was accepted as A-IMT.

Echocardiographic evaluation

Evaluation was performed with the EPIQ 7 C (Philips Healthcare 3000 Minuteman Road, Andover, MA USA) device with a 2.5–3.5 MHz transducer. Echocardiographic analyses were independently performed by two experienced cardiologists who were blinded to each other’s assessments and to clinical and treatment data. All the participants were evaluated in the left lateral decubitus position with blood pressure monitoring. All the images were taken from standard parasternal long and short axis, apical 4-chamber, 5-chamber and 2-chamber views with at least 3 repetitive cycles in accordance with the recommendations of the American Society of Echocardiography. All patients were in sinus rhythm during the procedure. Left atrium and ventricular myocardial deformation parameters were performed using two-dimensional gray-scale images by a speckle tracking echocardiography device. Cardiac loops with segments and premature beats with poor image quality were excluded from the measurement. QLAB version 10.5 (Philips, Andover, MA, USA) software was used for left atrium and ventricular analysis. The left ventricular endocardium was processed frame by frame from two-dimensional images with manual tracking, and the software automatically followed the wall movements throughout the entire cardiac cycle. Left ventricular GLS values ​​were calculated using 2D-STE images. After manually marking 2 basal and 1 apical parts of the left ventricle, the remaining endocardial borders were automatically marked by the software and appropriate epicardial borders were drawn automatically. When these automatic drawings were not suitable for analysis, the borders were manually corrected so that correct analysis could be performed. Post-analysis software divided the left ventricular apical 2, 3, 4 chamber recordings into six segments, and an 18-segment model was used to calculate left ventricular GLS.

Statistical analysis

All analyses were performed using the SPSS 26.0 (Chicago, IL, USA) statistical software package. Whether the distribution of continuous variables was normal or not was evaluated with the Kolmogorov-Smirnov test. Continuous variables in group data were expressed as mean ± standard deviation. Categorical variables were expressed as numbers and percentages. Student’s t-test or Mann-Whitney U were used to compare continuous variables between groups. The chi-square (χ2) test was used to compare categorical variables. To determine the parameters related to Galectin-3 level, GLS and A-IMT, univariate correlation analysis was performed with the Pearson-Spearman correlation method. Linear regression analysis was performed with statistically significant parameters in a multivariate model. Independent factors affecting Galectin-3 level, GLS and A-IMT were determined. The results were evaluated within the 95% confidence interval and the statistical significance level was accepted as p < 0.05.

Results

When the demographic characteristics of the PCOS patient and control groups were evaluated, there were no significant differences between the groups in terms of age (years) (29.2 ± 4.64 to 28.0 ± 4.71; p = 0.255), BMI (26.9 ± 7.70 kg/m² to 24.7 ± 3.58 kg/m²; p = 0.207), pulse (78.5 ± 9.51 /minute to 75.6 ± 6.25 /dk), systolic blood pressure (125.1 ± 3.94 mmHg to 122.7 ± 13.84 mmHg), and diastolic blood pressure (77.1 ± 5.36 mmHg to 75.6 ± 6.06 mmHg).

When the laboratory characteristics of PCOS patients and control groups were examined, there were no significant differences between the groups in terms of WBC (6.56 ± 1.48 10³/µL to 6.36 ± 1.41 10³/µL; p = 0.549), Hb (13.2 ± 2.47 g/dL to 13.3 ± 1.70 g/dL; p = 0.834), platelet (288.9 ± 31.6 10³/µL to 292.2 ± 36.3 10³/µL; p = 0.664) were similar between the groups. Similarly, AST (20.4 ± 8.81 u/L to 19.6 ± 8.02 u/L; p = 0.666), ALT (19.3 ± 4.48 u/L to 17.3 ± 5.86 u/L; p = 0.096), triglyceride (120.6 ± 74.2 mg/dL to 105.6 ± 40.4 mg/dL; p = 0.270), LDL (122.8 ± 36.0 mg/dL to 119.0 ± 26.1 mg/dL; p = 0.596), HDL (53.0 ± 12.0 mg/dL to 55.3 ± 14.5 mg/dL; p = 0.447), sodium (138.9 ± 1.19 mmol/L to 138.7 ± 3.38 mmol/L; p = 0.809), potassium (4.36 ± 0.32 mmol/L to 4.31 ± 0.35 mmol/L; p = 0.533), creatinine (0.59 ± 0.09 mg/dL to 0.58 ± 0.13 mg/dL; p = 0.829), calcium (9.51 ± 0.47 mg/dL to 9.41 ± 0.49 mg/dL; p = 0.322), TSH (2.05 ± 1.01 mIU/L to 1.83 ± 0.80 mIU/L; p = 0.306) were similar between the two groups.

The participants in the study were divided into two groups as patients with PCOS and a healthy controls. Glucose (93.6 ± 9.82 mg/dL to 87.7 ± 8.42 mg/dL; p = 0.006), DHEAS (331.3 ± 148.4 ug/dL to 101.8 ± 41.5; p < 0.001), total testosterone (72.6 ± 12.2 ng/mL to 43.6 ± 12.8; p < 0.001), LH/FSH ratio (1.18 ± 0.89 to 0.63 ± 0.23; p = 0.002), HOMA-IR Index (2.55 ± 0.49 to 2.05 ± 0.61; p < 0.001), galectin-3 (13.7 ± 0.98 ng/ml to 12.2 ± 2.08 ml; p < 0.001), A-IMT (1.41 ± 0.008 mm to 1.25 ± 0.16 mm; p < 0.001), GLS (-16.7 ± 1.75% to -18.8 ± 1.37%; p < 0.001) measurements were statistically significantly higher in the patient group than in the control group (Table 1; Figs. 1 and 2).

Table 1.

Clinical, demographic and laboratory findings of the patients with polycystic ovarian syndrome group and healthy control group

Variables	Patient group with PCOS, n = 40	Healthy control group n = 40	P
Age (year)	29.2 ± 4.64	28.0 ± 4.71	0.255
Body mass index (kg/m2 )	26.9 ± 7.70	24.7 ± 3.58	0.107
Basal heart rate (pulse/minute)	78.5 ± 9.51	75.6 ± 6.25	0.114
Systolic blood pressure (mmHg)	125.1 ± 3.94	122.7 ± 13.84	0.297
Diastolic blood pressure (mmHg)	77.1 ± 5.36	75.6 ± 6.06	0.229
White blood cell (10³/ µL)	6.56 ± 1.48	6.36 ± 1.41	0.549
Hemoglobin (g/dL)	13.2 ± 2.47	13.3 ± 1.70	0.834
Platelet (10³/ µL)	288.9 ± 31.6	292.2 ± 36.3	0.664
Glucose (mg/dL)	93.6 ± 9.82	87.7 ± 8.42	0.006
AST (u/L)	20.4 ± 8.81	19.6 ± 8.02	0.666
ALT (u/L)	19.3 ± 4.48	17.3 ± 5.86	0.096
Triglyceride (mg/dL)	120.6 ± 74.2	105.6 ± 40.4	0.270
LDL (mg/dL)	122.8 ± 36.0	119.0 ± 26.1	0.596
HDL (mg/dL)	53.0 ± 12.0	55.3 ± 14.5	0.447
Sodium (mmol/L)	138.9 ± 1.19	138.7 ± 3.38	0.809
Potassium (mmol/L)	4.36 ± 0.32	4.31 ± 0.35	0.533
Creatinine (mg/dL)	0.59 ± 0.09	0.58 ± 0.13	0.829
Calcium (mg/dL)	9.51 ± 0.47	9.41 ± 0.49	0.322
TSH (mIU/L)	2.05 ± 1.01	1.83 ± 0.80	0.306
hs-CRP (mg/L)	0.41 ± 0.28	0.30 ± 0.28	0.077
HOMA-IR Index	2.55 ± 0.49	2.05 ± 0.61	< 0.001
DHEAS (µg/dL)	331.3 ± 148.4	101.8 ± 41.5	< 0.001
LH/FSH	1.18 ± 0.89	0.63 ± 0.23	0.002
Total Testosterone (ng/ml)	72.6 ± 12.2	43.6 ± 12.8	< 0.001
Galectin-3 (ng/mL)	13.7 ± 0.98	12.2 ± 2.08	< 0.001
A-IMT (mm)	1.41 ± 0.08	1.25 ± 0.16	< 0.001
GLS (%)	-16.7 ± 1.75	-18.8 ± 1.37	< 0.001

AST Aspartate Aminotransferase, ALT Alanine Aminotransferase, LDL Low-Density Lipoprotein, HDL High-Density Lipoprotein, TSH Thyroid Stimulating Hormone, hs-CRP high sensitivity C-Reactive Protein, HOMA-IR Homeostatic Model Assessment for Insulin Resistance, DHEAS Dehydroepiandrosterone sulfate, LH/FSH Luteinizing Hormone (LH), the Follicle Stimulating Hormone (FSH) ratio, A-IMT Aortic İntima-Media Thickness, GLS Global Longitudinal Strain

Boldfaces are used for parameters where the p-value is significant

Fig. 1.

Aortic intima media thickness measurements of healthy control (A) and patient with acromegaly (B)

Fig. 2.

Global longitudinal strain measurements of healthy control (A) and patient with acromegaly (B)

In PCOS patients and control groups; Correlation analysis was performed between galectin-3 level, GLS, A-IMT measurements and HOMA-IR Index and other demographic, clinical and laboratory parameters. İn univariate analiysis, GLS showed strong and significant assosiation with galectin-3 levels (r = 0.747; p < 0.001). A-IMT was also significantly assosiated with galectin-3, althoug with a weaker correlation (r = 0.327; p = 0.006). Similarly, the HOMA-IR index demonstrated a moderate but significant correlation with galectin-3 levels (r = 0.446; p < 0.001). in multivariate linear regression analysis including GLS, A-IMT and HOMA-IR index, only GLS remained independently assosiated with galectin-3 levels (B = 0.395; p < 0.001), whereas A-IMT (B = 1.275; p = 0.340) and HOMA-IR index (B = 0.038; p = 0.887) were not significant predictors. The final model explained a substantial proportion of the variance in galectin-3 levels (adjusted R² =0.534)(Table 2) (Fig. 3).

Table 2.

Parameters associated with galectin-3 level

Variables	Univariate Analysis		Multivariate Analysis
	p	r	p	Β
GLS	< 0.001	0.747	< 0.001	0.395
A-IMT	0.006	0.327	0.340	1.275
HOMA-IR Index	< 0.001	0.446	0.887	0.038

R² Adjusted: 0.534

Boldfaces are used for parameters where the p-value is significant

Fig. 3.

Scatter plot diagram between galectin-3 and global longitidunal strain

Discussion

Studies have shown that the frequency of traditional cardiovascular risk factors increases in PCOS patients, and endothelial dysfunction and structural vascular changes develop in the early stage of the disease. It has been shown that Galectin-3 may play an important role in the formation and progression of CVD through inflammation and fibrosis and atherosclerosis, and may be a new diagnostic, prognostic biomarker and a new promising therapeutic target for CVD [19].

In our study, it was found that galectin-3, which has a role in the atherosclerotic process and development of HF, was higher in the PCOS patient group than in the control group. In the correlation analysis, galectin-3 was found to be associated with GLS, A-IMT and HOMA-IR Index. In the linear regression analysis, galectin-3 was independently associated with GLS. In literature review, there is no study showing the relationship between galectin-3 level and GLS and A-IMT measurements in PCOS.

Ilhan et al. as a result of the study, waist/hip ratio, blood pressure, triglyceride, HOMA-IR Index, glucose, free androgen index and galectin-3 levels were found to be statistically significantly higher in the patient group with metabolic syndrome compared to the control group. Galectin-3 has been found to be positively correlated with blood pressure and triglycerides in women with PCOS. Galectin-3 may be a promising biomarker when evaluating long-term metabolic and cardiovascular risks in women with PCOS; it was concluded that it can identify patients in the high-risk group in the early period and reduce long-term negative outcomes [20]. Glucose, HOMA-IR Index, and galectin-3 were found to be significantly higher in the patient group. Unlike Ilhan et al.’s study, since patients with similar BMI were involved in the study and HT was an exclusion criterion, blood pressure may not have been statistically significant.

Yilmaz et al. found that individuals diagnosed with PCOS were found to have higher galectin-3 levels compared to healthy individuals. Galectin-3 level was found to be positively correlated with progesterone, hirsutism scoring, insulin level, HOMA-IR Index, DHEAS, testosterone and free testosterone level. It was concluded that Galectin-3 may be a new mediator through insulin resistance and hyperandrogenism in PCOS patients [18]. Galectin-3 level and HOMA-IR Index, Similarly to Yılmaz et al. it was statistically significant. In addition, in the study, GLS with echocardiography was checked and it was statistically significant with galectin-3 level. The reason for this may be that galectin-3 level triggers fibrosis over myofibroblasts and plays a role in the pathogenesis of heart failure.

When the results of Alves et al. were evaluated, the level of galectin-3 was similar in PCOS patients and the control group. However, in the PCOS group, galectin-3 levels were positively correlated with glucose level in OGTT, BMI, insulin level and HOMA-IR Index. As a result, it was concluded that galectin-3 may play a role in the pathophysiology of insulin resistance and obesity in the PCOS group [21]. Since people in similar BMI and age groups were included in the study, BMI was not statistically significant. Since fasting plasma glucose was evaluated in our study, it was found to be statistically significant. Alves et al. Similarly, galectin-3 level and HOMA-IR Index were statistically significant. This may be because galectin-3 level is associated with insulin resistance.

Demirelli et al. waist/hip ratio, HOMA-IR Index, fasting insulin and TG levels were higher in the PCOS group compared to the control group and were statistically significant. Left ventricular GLS and left ventricular global longitudinal tension velocity evaluated with 2D-STE were lower in the PCOS group than in the patient group and were statistically significant. In this study, a decrease in left ventricular functions was detected using 2D-STE. Therefore, it seems useful for early detection of subclinical left ventricular dysfunction in patients with PCOS [22]. Erdogan et al. found that in the echocardiographic evaluation of PCOS and control group patients, there was no comparable left ventricular EF, left ventricular volumes and left ventricular dysfunction in both groups. In the study, GLS evaluated with 2D-STE was significantly reduced in the PCOS group compared to the control group and was statistically significant. It was concluded that the GLS assessment with STE may be an early indicator of cardiac involvement in this patient population [23]. Both Demirelli et al. both Erdogan et al.’s studies were examined, heart failure was an exclusion criterion, as in the study, and the EFs of the patients were normal. Besides, GLS was lower in the PCOS group compared to the control group and was statistically significant. In the study, Edogan et al. and Demirelli et al. stated in his studies that it was thought that GLS may be useful in predicting heart failure in the early period.

No study examining the relationship between galectin-3 molecule and GLS in the PCOS patient group in the literature review could be found, but there are also studies examining GLS with galectin-3 and other diseases. In the study by Kotwica et al. galectin-3 was increased and GLS decreased in psoriasis patients compared to the control group. Multiregression analysis revealed that GLS was independently associated with galectin-3 in patients with psoriasis. In this study, it was shown that GLS decreased in psoriasis patients, that subclinical systolic disorder was associated with inflammation and increased galectin-3 level mediated this [24]. In the study, chronic inflammatory diseases were the exclusion criteria as they may affect the results. Additionally, it was found that galectin-3 increased and GLS decreased in the patient group.

When the literature was reviewed, no study was found between PCOS and A-IMT. Many studies are between PCOS and carotid IMT, and the study will be an original study on this subject. Jabbour et al. found that increased carotid IMT in the PCOS patient group was positively correlated with the negative metabolic risk panel. It has been concluded that it is possible for PCOS patients to show systemic atherosclerosis at an early age, and it may be beneficial to detect atherosclerosis in these patients [25]. In the study, it was found that A-IMT, which was shown to be valuable in detecting subclinical atherosclerosis, was significantly higher in the PCOS group. It was also observed that A-IMT was significantly higher in patients with negative metabolic parameters.

In the study by Bahat et al. carotid IMT, LDL, waist/hip ratio, HbA1c, Ferriman-Gallwey score and free androgen index were significantly higher in the PCOS group [26]. In our study, it was found A-IMT, fasting blood glucose and HOMA-IR Index to be significantly higher in the PCOS group. High Ferriman-Gallwey score in PCOS patients is a natural result. It may be possible that atherosclerosis will progress more rapidly, as the adverse clinical consequences of hyperandrogenism will be further increased in patients with excessively increased atherosclerosis. Early screening for subclinical atherosclerosis in this patient group may provide useful data on managing long-term adverse outcomes.

Meyer et al. in his meta-analysis found that 1123 PCOS patients and 923 control groups were examined. Carotid IMT measurements were evaluated. The results show that women with PCOS have a risk of early atherosclerosis and it is important to screen and monitor cardiovascular disease risk factors in this patient group [27].

Recent findings indicate that nutraceutical approaches targeting metabolic and inflammatory pathways, such as inositols and alpha-lipoic acid, may improve insulin resistance, oxidative stress, and cardiometabolic risk factors in women with PCOS. These findings further support the hypothesis that chronic low-grade inflammation and metabolic dysregulation play a central role in the development of subclinical atherosclerosis in this population [16]. In this context, Galectin-3 may serve as a potential biomarker, reflecting the inflammatory and metabolic milieu associated with early atherosclerotic changes in PCOS. However, further prospective studies are necessary to elucidate its clinical significance.

Limitations

The limitations of our study were the low number of patients and the fact that our study was conducted in a single center. There is a need for multicenter studies with a larger number of patients. In addition, PCOS is a heterogeneous disease with various phenotypes. The patients were not divided into groups within themselves. In the future, patients can be divided and classified by taking these phenotypes into consideration. Although BMI, lipid parameters, and androgen levels are clinically relevant factors in PCOS and may influence cardiovascular risk, they were not included in the final multivariable model, which may result in residual confounding. Accordingly, the findings related to independent associations should be interpreted cautiously.

Conclusion

PCOS is associated with adverse short- and long-term outcomes, in which inflammation plays a key role, and the findings of the present study suggest that galectin-3 may serve as a potential biomarker reflecting increased cardiometabolic risk in women with PCOS, thereby aiding in the early identification of high-risk individuals.

Authors’ contributions

Conceptualization: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Cigdem Erhan, Hilmi Erdem SumbulMethodology: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Dilan Damla Ozturk, Merve Saracoglu Sumbul, Hilmi Erdem SumbulFormal analysis: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Cigdem Erhan, Dilan Damla Ozturk, Merve Saracoglu Sumbul, Hilmi Erdem SumbulInvestigation: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Cigdem Erhan, Dilan Damla Ozturk, Hilmi Erdem SumbulData Curation: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Hilmi Erdem SumbulWriting - Original Draft: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Cigdem Erhan, Dilan Damla Ozturk, Merve Saracoglu Sumbul, Hilmi Erdem SumbulWriting - Review & Editing: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Cigdem Erhan, Dilan Damla Ozturk, Merve Saracoglu Sumbul, Hilmi Erdem SumbulVisualization: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Hilmi Erdem SumbulSupervision: Ibrahim Erdem, Huseyin Ali Ozturk, Erdinc Gulumsek, Fatih Necip Arici, Begum Seyda Avci, Dilan Damla Ozturk, Merve Saracoglu Sumbul, Hilmi Erdem Sumbul.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

The dataset can be provided upon request from the authors.

Declarations

Ethics approval and consent to participate

The ethics committee of the Adana City Training and Research Hospital approved the study.

The study was performed according to the recommendations set by the The Declaration of Helsinki on Medical Research involving Human Subjects.

Informed consent was obtained from all individual participants included in the study.

Competing interests

The authors declare no competing interests.