Background. Polycystic ovary syndrome (PCOS) and hypothyroidism are the most common endocrinological disorders among women of reproductive age. Since hypothyroidism occurs more frequently in PCOS patients, it is vital to explain its clinical impact. Aim. To evaluate the impact of subclinical hypothyroidism (SCH) and its treatment on the metabolic profile of patients with PCOS. Methods. 190 women with PCOS phenotype A were enrolled in the case-control study. They were divided into three groups: 38 women with PCOS and subclinical hypothyroidism, 76 women with PCOS and SCH under thyroid replacement therapy, and 76 women with PCOS and normal thyroid function (control group). Serum lipids, fasting glucose, and insulin, as well as oral glucose tolerance tests were performed. Results. In the analyzed parameters, there were no statistic differences between the groups in relation to thyroid function. BMI turned out to be the main factor dividing the patients in terms of serum lipids, fasting glucose, fasting insulin, and oral glucose tolerance test. TSH was associated with total cholesterol and LDL cholesterol levels, whereas BMI has a dominant impact on HDL cholesterol, triglycerides, glucose, and insulin resistance. Conclusions. SCH is associated with mild lipid serum alterations in women with PCOS, but it is BMI to have a dominant impact on glucose and insulin. It seems that treatment of SCH in PCOS does not significantly alter lipid and glucose metabolism.

We investigated the relationship between selected body composition (BC) parameters and included 55 women diagnosed with PCOS and 29 women in which PCOS was excluded. Hormone concentration and BC parameters were assessed during hospitalization. Women with PCOS had higher concentration of luteinizing hormones, total testosterone, androstenedione, and Anti-Müllerian hormones compared to women that were not diagnosed with PCOS. We did not observe any significant differences in the BC parameters between both groups as well as between four PCOS phenotype subgroups. Only in the group of women with PCOS was the concentration of sex hormone binding globulin and free testosterone correlated with all investigated BC parameters. Correspondence analysis did not confirm unambiguously associations between phenotypes of PCOS and the value of BC parameters, while logistic regression revealed that increased Anti-Müllerian hormone concentration and the value of body mass index could be useful parameters in differentiating women with PCOS and women with other disorders. The ROC analysis performed on the entire group of women also confirmed that the concentration of Anti-Müllerian hormones could be a powerful parameter to categorize women as suffering from PCOS.

Objectives: The aim of this study is to analyze correlation between vitamin D level and BMI in polycystic ovary syndrome (PCOS) women. Material and methods: The study group consisted of 311 patients with PCOS. Patients were categorized according to four phenotypes. All of the women participating in the study had their blood tested in the appropriate phase of the menstrual cycle and after proper preparation for the tests. The ultrasound examination and anthropometric measurements were performed. Results: Vitamin D concentration was assessed in all study subgroups. The majority of patients had vitamin D deficiency or insufficient level. Variables included in the study, such as level of vitamin D, low density lipoprotein (LDL), sex hormone binding globulin (SHBG), testosterone, androstenedione, Anti-Müllerian Hormone (AMH) and BMI were correlated. A negative correlation was observed with the the level of SHBG, vitamin D and AMH. Subsequently, positive correlations were shown with testosterone, LDL and free testosterone level. An analysis of the correlation between BMI and vitamin D concentration showed that in phenotype I of PCOS this correlation was statistically significant and in the remaining PCOS phenotypes the correlation was close to statistical significance. Conclusions: Most PCOS patients have a deficiency or insufficient level of vitamin D. Women with PCOS have shown a significant negative correlation between BMI and SHBG serum level and between BMI and AMH level. A positive correlation exists between BMI and total and free testosterone and LDL. There is a negative correlation between BMI and vitamin D level in PCOS patients and in phenotype I this correlation was statistically significant. Objectives: The aim of this study is to analyze correlation between vitamin D level and BMI in polycystic ovary syndrome (PCOS) women. Material and methods: The study group consisted of 311 patients with PCOS. Patients were categorized according to four phenotypes. All of the women participating in the study had their blood tested in the appropriate phase of the menstrual cycle and after proper preparation for the tests. The ultrasound examination and anthropometric measurements were performed. Results: Vitamin D concentration was assessed in all study subgroups. The majority of patients had vitamin D deficiency or insufficient level. Variables included in the study, such as level of vitamin D, low density lipoprotein (LDL), sex hormone binding globulin (SHBG), testosterone, androstenedione, Anti-Müllerian Hormone (AMH) and BMI were correlated. A negative correlation was observed with the the level of SHBG, vitamin D and AMH. Subsequently, positive correlations were shown with testosterone, LDL and free testosterone level. An analysis of the correlation between BMI and vitamin D concentration showed that in phenotype I of PCOS this correlation was statistically significant and in the remaining PCOS phenotypes the correlation was close to statistical significance. Conclusions: Most PCOS patients have a deficiency or insufficient level of vitamin D. Women with PCOS have shown a significant negative correlation between BMI and SHBG serum level and between BMI and AMH level. A positive correlation exists between BMI and total and free testosterone and LDL. There is a negative correlation between BMI and vitamin D level in PCOS patients and in phenotype I this correlation was statistically significant.

The coexistence of polycystic ovary syndrome (PCOS) and liver steatosis has been studied for years. The gold standards for the diagnosis of liver steatosis are liver biopsy and magnetic resonance imaging (MRI), which are invasive and expensive methods. The main aim of this study is to check the usefulness of lipid accumulation product (LAP) and free androgen index (FAI) in the diagnosis of liver steatosis. The Ideal IQ MRI was performed in 49 women with PCOS phenotype A to assess the degree of liver steatosis, which was expressed with the proton density fat fraction (PDFF). Anthropometric examination and laboratory tests were performed, and the LAP and FAI were calculated. The correlation between MRI results and LAP, FAI, and one of the FAI components, sex hormone binding globulin (SHBG), was checked using statistical tests. There is a statistically significant correlation between PDFF and LAP and also between PDFF and FAI. LAP = 70.25 and FAI = 5.05 were established as cut-offs to diagnose liver steatosis. The SHBG is not a statistically significant parameter to predict liver steatosis. The study showed that especially LAP, but also FAI, can be used to predict liver steatosis with high specificity and sensitivity.

Polycystic ovary syndrome (PCOS) is a hormonal disorder with complex, multifactorial and still not fully explained etiopathogenesis. It is believed that the cause is a combination of genetic and environmental factors. Background: With the aim to better understand PCOS etiology, the study examines body composition and compares the occurrence of lipid disorders and visceral adipose tissue depending on the adopted Rotterdam phenotypes. Methods: The study included 242 patients classified into four classic Rotterdam phenotypes. Clinical data from patients were collected and carefully analyzed to determine the relationship between the occurrence of lipid disorders and the visceral adiposity index (VAI). Results: The results obtained after assessing the differences between the Rotterdam phenotypes were not statistically significant. Differences in the levels of coefficients included in the VAI equation in the given phenotypes were also analyzed, as follows: waist circumference (p-value = 0.3415), BMI (p-value = 0.7112), TG [mmol/L] (p-value = 0.5341) and HDL [mmol/L] (p-value = 0.2302). None of the differences were statistically significant. Conclusions: Although the results did not show a clear association between VAI and the individual Rotterdam PCOS phenotypes, this coefficient can be used in the assessment of cardiometabolic risk in women with PCOS regardless of the adopted classification.

The aim of present study was to investigate the association between serum calcium, iron, magnesium, copper levels and insulin resistance in women with full blown phenotype of polycystic ovary syndrome (PCOS) compared to women with not-full blown phenotype. 104 women, aged 18–39, in the first phase of menstrual cycle, diagnosed with PCOS based on the Rotterdam Criteria, were qualified for the study. Patients were divided into two groups: group I contained women with full blown PCOS (phenotype A) and group II contained women with not-full blown PCOS (phenotypes B, C and D). Whole study population was divided on group X containing women with proper insulin sensitivity and group Y containing women with insulin resistance. The study found that women with full blown PCOS had lower level of magnesium compared with not-full blown phenotypes. Also, the level of copper was lower in group with proper insulin sensitivity compared to group with insulin resistance. Serum cooper content showed a negative correlation with Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) in group with full blown phenotype. Magnesium level showed positive correlation with level of calcium and cooper in group with proper insulin sensitivity. Level of iron content showed a negative correlation with sex hormone binding globulin (SHBG) and HOMA-IR showed a positive correlation with age and body mass index (BMI) in group with insulin resistance. Either level of calcium showed positive correlation with iron and cooper in group with insulin resistance. Keywords: insulin resistance polycystic ovary syndrome phenotypes micronutrients