Triglycerides, independent of Ferriman Gallwey Score, is a main determinant of free testosterone index in PCOS

Optimizing Dietary Habits in Adolescents with Polycystic Ovary Syndrome: Personalized Mediterranean Diet Intervention via Clinical Decision Support System-A Randomized Controlled Trial

The hypothesis of this randomized controlled trial was that a clinical decision support system (CDSS) would increase adherence to the Mediterranean diet (MD) among adolescent females with polycystic ovary syndrome (PCOS). The objective was to assess the impact of personalized MD plans delivered via a CDSS on nutritional status and psychological well-being. Forty adolescent females (15-17 years) with PCOS were randomly assigned to the MD group (n = 20) or the Control group (n = 20). The MD group received personalized MD plans every 15 days via a CDSS, while the Control group received general nutritional advice. Assessments were conducted at baseline and after 3 months. Results showed significantly increased MD adherence in the MD group compared to the Control group (p < 0.001). The MD group exhibited lower intakes of energy, total fat, saturated fat, and cholesterol, and higher intakes of monounsaturated fat and fiber (p < 0.05). Serum calcium and vitamin D status (p < 0.05), as well as anxiety (p < 0.05) were improved. In conclusion, tailored dietary interventions based on MD principles, delivered via a CDSS, effectively manage PCOS in adolescent females. These findings highlight the potential benefits of using technology to promote dietary adherence and improve health outcomes in this population. ClinicalTrials.gov registry: NCT06380010.

Clinical and laboratory features in women with different phenotypes of polycystic ovary syndrome

BACKGROUND

Misdiagnosis is still an obstacle in the workup of polycystic ovary syndrome. We compared patients' characteristics among phenotypes of the syndrome and assessed the association of the characteristics with oligo-anovulation, hyperandrogenism, and polycystic ovary.

METHODS

In the infertility department of a teaching hospital, we performed a cross-sectional study. Based on the Rotterdam Criteria, we included 136 patients with polycystic ovary syndrome and 46 healthy controls.

RESULTS

The most common phenotype was A (N.=45;33%). Overall, A and C had larger Body Mass Index (P=0.019 and 0.030, respectively) and waist circumference (P=0.005 and 0.003) than control. Also, A and D had higher serum anti-mullerian hormone than control (both P<0.001) or phenotype C (P<0.001 and 0.01). Phenotypes A and C had higher insulin than control (both P=0.004). The highest level of estradiol was for control and the lowest for B. The lowest high-density lipoprotein was for C; and A to C phenotypes had higher triglyceride than control (P=0.002, <0.001, and 0.041). Larger body mass was associated with hyperandrogenism (adjusted Odds Ratio 95% CI=1.11 [1.01, 1.23], P=0.034); higher anti-mullerian hormone and high-density lipoprotein were related to oligo-anovulation (1.2 [1.07, 1.37], P=0.004; 1.1 [1.00, 1.13], P=0.041). Higher insulin and lower high-density lipoprotein were associated with polycystic ovary (1.11 [1.03, 1.21], P=0.013; 0.9 [0.82, 0.97], P=0.014).

CONCLUSIONS

There are potentials in Body Mass Index, waist circumference, serum anti-mullerian hormone, insulin, estradiol, high-density lipoprotein, and triglyceride concentration for differentiating the phenotypes of polycystic ovary syndrome and for more precise diagnosis of hyperandrogenism, oligo-anovulation, and polycystic ovary morphology.

Reference range of testosterone and dehydroepiandrosterone sulfate levels in women during reproductive age in the Iranian population

Backgrounds

To determine the average cutoff values of serum-free and total testosterone (FT, TT) and dehydroepiandrosterone sulfate (DHEAS) among healthy premenopausal women.

Materials and Methods

Participants were women aged 18-55 years without signs and symptoms of hyperandrogenism (n = 489). Participants if Ferriman-Gallwey (FG) scores between 6 and 8 were considered a group located in the upper spectrum related to the normal hirsutism score (n = 30). DHEAS, TT, and FT levels were compared between different populations. Upper limits of 97.5 and 95 and lower limits of 5 and 2.5 percentiles were calculated to provide the reference intervals for DHEA, TT, and FT in the total sample and in the population with FG 6-8.

Results

In the total population, the mean ± standard deviation (SD) serum FT, TT, and DHEAS levels were 1.40 ± 0.63 pg/mL, 0.42 ± 0.17 ng/mL, and 1.5 ± 0.97 µg/ml, respectively. The cutoff values of FT at 1.35 and TT at 0.49 were obtained for differentiating the patients with FG 6-8 scores from the normal population, with the corresponding specificity of 0.60, the sensitivity of 0.67, and area under the ROC curve (AUC) (confidence interval 95%) of 0.63 (0.52-0.73), P = 0.01 and 0.68 (0.58-0.78) P = 0.001, respectively.

Conclusions

In our study, the mean ± SD serum FT level was 1.40 ± 0.63 pg/mL, the TT level was 0.42 ± 0.17 ng/mL, and the DHEAS level was 1.5 ± 0.97 µg/ml, in premenopausal women between 18 and 49 years of age. Furthermore, in a population with FG 6-8 score, a cutoff value of FT at 1.35 and TT at 0.49 was obtained. Although the irregular menstrual cycle did not change the reference range when compared with the normal group.

Analysis of Methylome, Transcriptome, and Lipid Metabolites to Understand the Molecular Abnormalities in Polycystic Ovary Syndrome

Purpose

This study aimed to identify differentially methylated genes (DMGs) and differentially expressed genes (DEGs) to investigate new biomarkers for the diagnosis and treatment of polycystic ovary syndrome (PCOS).

Methods

To explore the potential biomarkers of PCOS diagnosis and treatment, we performed methyl-binding domain sequencing (MBD-seq) and RNA sequencing (RNA-seq) on ovarian granulosa cells (GCs) from PCOS patients and healthy controls. MBD-seq was also performed on the ovarian tissue of constructed prenatally androgenized (PNA) mice. Differential methylation and expression analysis were implemented to identify DMGs and DEGs, respectively. The identified gene was further verified by real-time quantitative PCR (RT-qPCR) and methylation-specific PCR (MSP) in clinical samples. Furthermore, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was carried out on PCOS patients and healthy controls to identify differential lipid metabolites.

Results

Compared to the control group, 13,526 DMGs related to the promoter region and 2429 DEGs were found. The function analysis of DMGs and DEGs showed that they were mainly enriched in glycerophospholipid, ovarian steroidogenesis, and other lipid metabolic pathways. Moreover, 5753 genes in DMGs related to the promoter region were screened in the constructed PNA mice. Integrating the DMGs data from PCOS patients and PNA mice, we identified the following 8 genes: CDC42EP4, ERMN, EZR, PIK3R1, ARHGEF18, NECTIN2, TSC2, and TACSTD2. RT-qPCR and MSP verification results showed that the methylation and expression of TACSTD2 were consistent with sequencing data. Additionally, 15 differential lipid metabolites were shown in the serum of PCOS patients. The differential lipids were involved in glycerophospholipid and glycerolipid metabolism.

Conclusion

Using integration of methylome and lipid metabolites profiling we identified 8 potential epigenetic markers and 15 potential lipid metabolite markers for PCOS. Our results suggest that aberrant DNA methylation and lipid metabolite disorders may provide novel insights into the diagnosis and etiology of PCOS.

Correlation of Body Mass Index with Anthropometric and Biochemical Parameters Among Polycystic Ovary Syndrome Phenotypes

This was a prospective observational study, conducted at a tertiary care health centre in Rajasthan. A total of 68 women with PCOS (Rotterdam criteria) attending OPD at Department of Obstetrics and Gynecology qualified as per inclusion and exclusion criteria were included in the study. Each participant was examined for anthropometric and biochemical parameters. The largest phenotypic group was phenotype A, (41.17%); followed by B (26.47%); C (20.58%), and D (P + O) phenotypes (11.76%). Hyperandrogenic phenotypes (A, B, C), had significantly higher prevalence of deranged serum glucose (fasting and postprandial), lipid profile and serum TSH than normoandrogenic phenotype D. BMI was strongly correlated with anthropometric (p < 0.001) and biochemical parameters (p < 0.05) in phenotype A among four phenotypes of PCOS. Phenotype A was the most common form of PCOS and a strong correlation of BMI with waist circumference (WC), dyslipidemia and Sub-clinical hypothyroidism (SCH) was observed in women of this phenotype of PCOS. These results indicate that phenotype A is at increased risk of CVD and diabetes and phenotype D has least metabolic risks.

The Associations between Sex Hormones and Lipid Profiles in Serum of Women with Different Phenotypes of Polycystic Ovary Syndrome

We aimed to evaluate the relationship between selected serum sex hormones and lipid profiles in a group of women with polycystic ovary syndrome (PCOS) dividing according to four phenotypes, value of body mass index (BMI), and presence of hyperlipidemia. The study included 606 Caucasian women. Lipids and selected hormones were estimated using commercially available procedures during hospitalization in 2017. Phenotype of PCOS, BMI value, and hyperlipidemia were significant factors that influenced androgen hormone concentrations, such as total and free testosterone and androstenedione as well as the value of free androgen index (FAI). Moreover, significant changes in concentrations of dehydroepiandrosterone sulphate and sex hormone binding globulin (SHBG) were found between those groups. Higher quartiles of triglyceride concentrations increased the odds ratio of decreased concentrations of SHBG or increased values of FAI, while an adverse relation was found in case of HDL-C. The concentration of estradiol in the blood of women with PCOS was not associated with lipid profile parameters in any investigated groups. Probably, irregularities in sex hormone concentrations during PCOS is not directly associated with lipid profile parameters but could be reflective of the concentration of SHBG or the ratio of SHBG and total testosterone and their association with lipids.

Dysbiosis of the Saliva Microbiome in Patients With Polycystic Ovary Syndrome

Significant differences in salivary microbiota communities between polycystic ovary syndrome (PCOS) patients and healthy controls have been reported, and interestingly, some salivary microbiota exhibit diurnal oscillation in healthy people. However, whether the diurnal oscillation of salivary microbiota is present in PCOS patients is unknown. In this study, we describe the differences in the saliva microbiome between the PCOS group and the control group at different time points over 24 h. 16S rRNA gene amplicon sequencing was performed on salivary and fecal samples from 10 PCOS patients and 10 healthy controls, and salivary samples were collected at 6-h intervals over 24 h (Zeitgeber (ZT)0, ZT6, ZT12, and ZT18). Among the salivary samples, those from the PCOS group showed significant differences from those of the control group at each time point. Differences were evident in taxa level and metabolic pathways. Interestingly, we found that PCOS disrupted the diurnal rhythm of the salivary microbiota abundance, as determined in the group of healthy women. In addition, no similar changes were found in PCOS patients and controls between the oral and fecal microbiota, including differential microbiota at the phylum level. In this study, significant differences in the composition of the salivary microbiota between PCOS and healthy women were detected at different time points. We also showed that the diurnal rhythm of relative abundance of the salivary microbiota was disrupted in patients with PCOS, which might be related to development of oral-related diseases and systematic metabolic disorders.