Risk Factor For Polycystic Ovary Syndrome Research Articles

Association of SOGPI in mediating the effect of Phosphatidylcholine on polycystic Ovary Syndrome

Background Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in women of reproductive age, marked by hormonal imbalances and disruptions in glucose and lipid metabolism. Emerging research has indicated a correlation between lipids and PCOS, yet the specific lipid profiles or associated genes identified in various studies vary, and observational data alone cannot establish causation. Therefore, our study seeks to establish a causal association between lipidome and PCOS. Methods Data from genome-wide association studies, liposomes, metabolites, and PCOS-related information were collected. Four rounds of double-sample bidirectional intermediate Mendelian Randomization analyses including liposomes to disease, liposomes to metabolites, metabolites to disease, and reverse Mendelian Randomization analysis of lipids, total effect values and intermediary effect values were calculated. The proportion mediated by the intermediary effect was determined by dividing the intermediary effect value by the total effect value. Results The analyses revealed that three liposomes and nine metabolites were causally associated with PCOS. Specifically, phosphatidylcholine and 1-Stearoyl-2-Oleoyl-Glycosylphosphatidylinositol were identified as independent risk factors for PCOS through further Mendelian Randomization analysis. The risk of developing PCOS increased by 32% for every one standard deviation increase in phosphatidylcholine and by 17% for every one standard deviation increase in 1-Stearoyl-2-Oleoyl-Glycosylphosphatidylinositol. Furthermore, the study revealed that phosphatidylcholine can influence the development of PCOS with 1-Stearoyl-2-Oleoyl-Glycosylphosphatidylinositol acting as a mediator, explaining 4.97% of the effect. Conclusions This study confirmed a causal relationship between phosphatidylcholine and 1-Stearoyl-2-Oleoyl-Glycosylphosphatidylinositol with PCOS, where phosphatidylcholine can influence the occurrence of PCOS with 1-Stearoyl-2-Oleoyl-Glycosylphosphatidylinositol as a mediator.

Outdoor Artificial Light at Night and Reproductive Endocrine and Glucose Homeostasis and Polycystic Ovary Syndrome in Women of Reproductive Age.

Artificial light at night, a well-recognized circadian clock disrupter, causes disturbances in endocrine homeostasis. However, the association of artificial light at night with polycystic ovary syndrome (PCOS) is still unknown. This study examines the effects of outdoor artificial light at night on sex hormones, glucose homeostasis markers, and PCOS prevalence in Anhui Province, China. We recruited 20,633 women of reproductive age from Anhui Medical University Reproductive Medicine Center. PCOS was diagnosed according to Rotterdam criteria. We estimated long-term (previous year) and short-term (previous month) artificial light at night values for residential addresses using 500 m resolution satellite imagery. We fitted multivariable models, using both linear and logistic regression, to estimate the association of artificial light at night with sex hormones, glucose homeostasis markers, and PCOS prevalence. Both long-term and short-term exposure to outdoor artificial light at night were negatively associated with follicle-stimulating hormone and luteinizing hormone levels, while positively associated with testosterone, fasting insulin, homeostasis model assessment-insulin resistance, and homeostasis model assessment-insulin resistance-β levels. The second-highest quintile of artificial light at night was associated with increased PCOS prevalence (odds ratio [OR long-term ] = 1.4; 95% confidence interval [CI] = 1.2, 1.6 and OR short-term = 1.3; 95% CI = 1.1, 1.5) compared with the lowest quintile. In addition, prevalence of PCOS was linearly associated with long-term exposure to artificial light at night, but nonlinearly associated with short-term exposure. This association was more evident in younger, obese or overweight, moderately educated, rural women, and for the summer and fall seasons. Outdoor artificial light at night may be a novel risk factor for PCOS.

Causal relationships between modifiable risk factors and polycystic ovary syndrome: a comprehensive Mendelian randomization study.

Polycystic Ovary Syndrome (PCOS) is a heritable condition with an as yet unclear etiology. Various factors, such as genetics, lifestyle, environment, inflammation, insulin resistance, hyperandrogenism, iron metabolism, and gut microbiota, have been proposed as potential contributors to PCOS. Nevertheless, a systematic assessment of modifiable risk factors and their causal effects on PCOS is lacking. This study aims to establish a comprehensive profile of modifiable risk factors for PCOS by utilizing a two-sample Mendelian Randomization (MR) framework. After identifying over 400 modifiable risk factors, we employed a two-sample MR approach, including the Inverse Variance Weighted (IVW) method, Weighted Median method, and MR-Egger, to investigate their causal associations with PCOS. The reliability of our estimates underwent rigorous examination through sensitivity analyses, encompassing Cochran's Q test, MR-Egger intercept analysis, leave-one-out analysis, and funnel plots. We discovered that factors such as smoking per day, smoking initiation, body mass index, basal metabolic rate, waist-to-hip ratio, whole body fat mass, trunk fat mass, overall health rating, docosahexaenoic acid (DHA) (22:6n-3) in blood, monounsaturated fatty acids, other polyunsaturated fatty acids apart from 18:2 in blood, omega-3 fatty acids, ratio of bisallylic groups to double bonds, omega-9 and saturated fatty acids, total lipids in medium VLDL, phospholipids in medium VLDL, phospholipids in very large HDL, triglycerides in very large HDL, the genus Oscillibacter, the genus Alistipes, the genus Ruminiclostridium 9, the class Mollicutes, and the phylum Tenericutes, showed a significant effect on heightening genetic susceptibility of PCOS. In contrast, factors including fasting insulin interaction with body mass index, sex hormone-binding globulin, iron, ferritin, SDF1a, college or university degree, years of schooling, household income, the genus Enterorhabdus, the family Bifidobacteriaceae, the order Bifidobacteriales, the class Actinobacteria, and the phylum Actinobacteria were determined to reduce risk of PCOS. This study innovatively employs the MR method to assess causal relationships between 400 modifiable risk factors and the susceptibility of PCOS risk. It supports causal links between factors like smoking, BMI, and various blood lipid levels and PCOS. These findings offer novel insights into potential strategies for the management and treatment of PCOS.

Plasma Corin: A New Biochemical Marker for Polycystic Ovary Syndrome.

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder. Atrial natriuretic peptide (ANP) is a risk factor for PCOS. Corin protein has an essential role in ANP synthesis. This study aimed to evaluate corin as a sensitive biomarker for PCOS. A case-control study was conducted with 70 PCOS patients and 70 healthy females. Plasma Corin levels were quantified using enzyme-linked immunosorbent assay. The median plasma corin levels in PCOS patients and controls were 1785 and 822.5 pg/mL, respectively. Plasma corin levels were significantly elevated in PCOS patients than in the controls (p < 0.001). The optimal cut-off value was set at 1186 pg/mL. The sensitivity and specificity of Corin were 100% and 97.1%, respectively. Plasma corin levels were surrogate predictors for infertility in women with PCOS. It had an odds ratio of 5.9 (95% confidence interval: 1.1-32.7) (p = 0.04). Plasma corin levels were more highly detected in patients with PCOS than in the controls. Plasma corin level has reasonable diagnostic interpretation for PCOS. Corin appears as a worthy distinct predictor of infertility in PCOS women. Therefore, Corin may be a substantial biomarker for PCOS.

Genome-wide association study (GWAS) identified PCOS susceptibility variants and replicates reported risk variants.

Genetic predisposition and environmental factors are considered risk factors for polycystic ovary syndrome (PCOS). Genome-wide association studies (GWAS) have been reported from various subpopulations to evaluate SNPs associated with PCOS risk. No PCOS-associated GWAS study has been reported from India so far. The current study was conducted to identify the PCOS-susceptible loci among the North Indian population and to validate the significant loci reported by previous GWAS studies. A total of 272 participants with 134 PCOS patients and 138 age-matchedhealthy controls were recruited. Genomic DNA was isolated and genotyped by using Infinium Global Screening Array v3.0 microchip considering HWE 10e-5 statistically significant. A total of fifteen markers have been identified as candidate PCOS risk factors. Only two SNPs, namely rs17186366 and rs11171739 have been identified through replication analysis while comparing the previously reported PCOS GWAS data. In-silico analysis was performed to study the functional impact of identified significant genes for gene ontology, pathways related to gene set, and cluster analysis to determine protein-protein interaction among genes or gene products. The study suggests that multiple variants play an important role in PCOS pathogenesis and emphasizes the importance of further genetic studies among Indian subpopulations.The study also validates two previously reported SNPs in the Indian population. What this study adds to clinical work Study summarizes the importance of candidate gene markers validated by replication and in-silico functional study, significantly involved in PCOS pathogenesis in the studied population. These markers can be used in the future as diagnostic markers for clinical phenotype identification.

Association between Perfluoroalkyl Substances in Follicular Fluid and Polycystic Ovary Syndrome in Infertile Women.

In recent years, perfluoroalkyl substances (PFASs), a family of fluorinated organic com pounds, have garnered much attention due to their reproductive and developmental toxicity in humans. Polycystic ovary syndrome (PCOS) is a prevalent endocrine disease that affects women of reproductive age and is a significant contributor to female infertility. A previous study suggested that PFASs play a possible role in PCOS. We conducted a clinical study investigating the relationship between PCOS and PFAS in follicular fluid. A total of 73 infertile patients with PCOS and 218 controls were recruited from the International Peace Maternity and Child Health Hospital, affiliated with the Shanghai Jiao Tong University School of Medicine. The concentrations of 12 PFASs in follicular fluid samples and sex hormones in serum were measured. Correlation analysis and multiple linear regression revealed a positive relationship between perfluorooctanoic acid (PFOA) and testosterone (T) concentrations. The adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for each PFAS were estimated using multivariable logistic regression and quantile-based g-computation (QGC). The PFOA concentrations in follicular fluid were correlated with increased odds of PCOS (second vs. first quartile: OR = 3.65, 95% CI: 1.47-9.05, p = 0.005; third vs. first quartile: OR = 2.91, 95% CI: 1.17-7.26, p = 0.022; fourth vs. first quartile: OR = 3.13, 95% CI: 1.21-8.09, p = 0.019; P for trend = 0.032). This association was confirmed with QGC. Mediation analysis suggested that the mediation effect of T in association with PFOA and PCOS was not statistically significant. Our study suggests that PFOA may be a risk factor for PCOS.

Correlation between chronic low-grade inflammation and glucose and lipid metabolism indicators in polycystic ovary syndrome

Objective The purpose of this study was to explore the correlation between inflammatory indicators and blood lipids and to further provide a theoretical basis for the diagnosis and treatment of clinical polycystic ovary syndrome (PCOS). Methods Whole-blood cell counts and hormone and blood lipid levels were measured in 110 patients with PCOS and 126 healthy women. The differences in the above levels and the correlation between inflammation and blood lipid levels in the two groups were determined, and classified according to BMI. Differences in inflammatory indices were also analyzed. The independent risk factors for PCOS were analyzed by binary logistic regression. Results The PCOS group had greater BMI and greater body weight than the control group. The inflammatory indicators WBC, neutrophil, lymphocyte, monocyte counts and the NLR were significantly higher than those of the control group. It had higher testosterone (TSTO), triglyceride (TG) and total cholesterol (TC) levels. Correlation analysis showed that leukocyte and neutrophil counts were positively correlated with TSTO and TG levels and negatively correlated with HDL. In the BMI ≥ 24 and BMI < 24 groups, WBC was higher in PCOS patients than in healthy controls. Logistic regression showed that TSTO, TG and FSH were independent risk factors for PCOS. Conclusion Inflammatory markers are correlated with blood lipids in PCOS. During the treatment of PCOS, blood lipids and serum inflammatory factors should be monitored.

Alteration of Plasma Indoles in Polycystic Ovary Syndrome.

Polycystic ovary syndrome (PCOS) is one of the most common endocrinopathies in reproductive-aged women. The occurrence of PCOS was reported to be associated with the alteration of gut microbiota. Microbiota-derived indoles may possibly play a key role in glycemic control. The purpose of this work is to reveal the alteration of plasma indoles in PCOS patients and to investigate the correlation between indoles levels and glucose metabolism. Sixty-five patients with PCOS and twenty-eight age-matched women were enrolled in this work. The concentrations of plasma indoles, including indoxyl sulfate (IS), indole-3-acetic acid (IAA), indole-3-propionate (IPA), indole (IND), and 3-methylindole (3-MI), were measured by HPLC with the fluorescence detection. The plasma levels of IS, IAA, and IND were significantly elevated in patients with PCOS compared to those in the control group (p < 0.05). Furthermore, the plasma levels of IS, IAA, and IND were positively correlated with fasting glucose, fasting insulin, and the homeostatic model of insulin resistance index (HOMA-IR) (p < 0.05). Besides, the 3-MI level in the plasma was positively correlated with the fasting glucose level, whereas plasma levels of IS, IAA, IND, and 3-MI were negatively correlated with glucagon-like peptide 1 (p < 0.05). Moreover, IS and IND were considered to be risk factors for PCOS after age, BMI, T, LH, and HOMA-IR adjustment. The area under the receiver-operating characteristic curve of the combined index of five indoles was 0.867 for PCOS diagnosis. Additionally, plasma indoles altered in PCOS, which was closely associated with the glucose metabolism.

Frequency of Hypovitaminosis D in Obese Adolescent with Polycystic Ovary Syndrome

Background: Polycystic ovary syndrome (PCOS) is one of the most common female endocrine disorders affecting the reproductive age group and is thought to be one of the leading cause of female infertility. Many patients with polycystic ovary syndrome (PCOS) also have features of the metabolic syndrome, including insulin resistance, obesity, and dyslipidemia. Vitamin D affects insulin and glucose metabolism, and a low vitamin D status maybe a risk factor for PCOS. Aim: To determine vitamin D status among the obese adolescent with Polycystic Ovary Syndrome (PCOS) and to compare the vitamin D level among obese and nonobese adolescent with PCOS. Methods: This cross sectional study was done at the out-patient department of Obstetrics and Gynecology in Bangabandhu Sheikh Mujib Medical University (BSMMU) during November 2017 to October 2018 but the patients enrollment was started after 16 July 2018. The study comprises of 80 adolescent girls diagnosed as PCOS according to Rotterdam criteria, in the age range of 9 to 18 years, out of which 50 obese adolescent girls was considered as group I and 30 non obese adolescent girls was considered as group II. The biochemical parameters measured in the study includes fasting blood sugar, fasting insulin level and serum 25-hydroxy vitamin D level. Serum 25 (OH) D level less than 20 ng/ml was classified as vitamin D deficiency. Results: In this study it was observed that maximum patients were vitamin D deficient in both groups. In group I, 76% and in group II, 60% were vitamin D deficient. Again in group I, 14% and 33.3% in group II were vitamin D insufficient. Only 10% in group I and 6.7% in group II were found to have sufficient level of vitamin D. The mean Vitamin D was found 18.25±5.51 ng/ml in group I and 19.66±5.21 ng/ml in group II. The mean difference of vitamin D level between two groups was statistically not significant. There is a negative significant correlation between vitamin D and BMI which indicates level of vitamin D decreases with increase of BMI of the participants. Conclusion: Vitamin D deficiency was predominant in both groups. Though the difference of vitamin D level was not significant between two groups but the mean level of vitamin D is lower in group I than in group II. There is a negative significant correlation between vitamin D and BMI which indicates that higher BMI levels were associated with lower vitamin D levels.

Pediatric Features of Genetic Predisposition to Polycystic Ovary Syndrome.

Polycystic ovary syndrome (PCOS) has historically been conceptualized as a disorder of the reproductive system in women. However, offspring of women with PCOS begin to show metabolic features of PCOS in childhood, suggestive of childhood manifestations. To identify childhood manifestations of genetic risk for PCOS. We calculated a PCOS polygenic risk score (PRS) for 12 350 girls and boys in 4 pediatric cohorts-ALSPAC (UK), COPSAC (Denmark), Project Viva (USA), and The HOLBÆK Study (Denmark). We tested for association of the PRS with PCOS-related phenotypes throughout childhood and with age at pubarche and age at peak height velocity and meta-analyzed effects across cohorts using fixed-effect models. Higher PRS for PCOS was associated with higher body mass index in midchildhood (0.05 kg/m2 increase per 1 SD of PRS, 95% CI 0.03, 0.07, P = 3 × 10-5) and higher risk of obesity in early childhood (OR 1.34, 95% CI 1.13, 1.59, P = .0009); both persisted through late adolescence (P all ≤.03). Higher PCOS PRS was associated with earlier age at pubarche (0.85-month decrease per 1 SD of PRS, 95% CI -1.44, -0.26, P = .005) and younger age at peak height velocity (0.64-month decrease per 1 SD of PRS, 95% CI -0.94, -0.33, P = 4 × 10-5). Genetic risk factors for PCOS are associated with alterations in metabolic, growth, and developmental traits in childhood. Thus, PCOS may not simply be a condition that affects women of reproductive age but, rather, a possible manifestation of an underlying condition that affects both sexes starting in early life.

Are ABO/Rh blood groups A risk factor for polycystic ovary syndrome?

This study goaled to evaluate the ABO/Rh blood group distribution and its relationship with clinical and biochemical factors in polycystic ovary syndrome (PCOS) patients. ABO/Rh blood group distribution of the patients and the healthy individuals were compared. In addition, the features of clinical and biochemical factors were compared according to the ABO/Rh blood groups. Two hundred and sixty-five patients were involved in the study. At the time of diagnosis, hirsutism (86%) and oligomenorrhea (80.9%) were the most prevalent symptoms. There were 166 (62.6%) patients with baseline ultrasonography results consistent with PCOS. In 111 (41.9%) patients, insulin resistance was found. ABO blood group distributions in the patient (42.6% A, 17% B, 9.4% AB, 30.9% O) and control (42% A, 16% B, 8% AB, 34% O) groups were found to be similar (P = .9). There was no difference between oligomenorrhea, hirsutism, hair loss, acne, obesity, high androgen level, insulin resistance, and ultrasound characteristics according to ABO/Rh blood groups. In this study, ABO/Rh blood group distribution in individuals with PCOS was found to be similar to healthy individuals, and it was determined that ABO/Rh blood group was not a risk factor for PCOS. In addition, no correlation was found between the clinical and biochemical characteristics of the patients at the time of diagnosis and the ABO/Rh blood group.

The association between gut microbiome and PCOS: evidence from meta-analysis and two-sample mendelian randomization.

Increasing evidence from observational studies and clinical experimentation has indicated a link between the gut microbiotas (GMs) and polycystic ovary syndrome (PCOS), however, the causality and direction of causality between gut microbiome and PCOS remains to be established. We conducted a comprehensive search of four databases-PubMed, Cochrane Library, Web of Science, and Embase up until June 1, 2023, and subjected the results to a meta-analysis. In this study, a bidirectional two-sample Mendelian randomization (MR) analysis was employed to investigate the impact of gut microbiota on polycystic ovary syndrome (PCOS). The genome-wide association study (GWAS) data for PCOS comprised 113,238 samples, while the GWAS data for gut microbiota were derived from the MiBioGen consortium, encompassing a total sample size of 18,340 individuals. As the largest dataset of its kind, this study represents the most comprehensive genome-wide meta-analysis concerning gut microbiota composition to date. Single nucleotide polymorphisms (SNPs) were selected as instrumental variables at various taxonomic levels, including Phylum, Class, Order, Family, and Genus. The causal associations between exposures and outcomes were assessed using four established MR methods. To correct for multiple testing, the false discovery rate (FDR) method was applied. The reliability and potential biases of the results were evaluated through sensitivity analysis and F-statistics. The meta-analysis incorporated a total of 20 studies that met the criteria, revealing a close association between PCOS and specific gut microbiota species. As per the results from our MR analysis, we identified six causal associations between the gut microbiome and polycystic ovary syndrome (PCOS). At the genus level, Actinomyces (ORIVW = 1.369, FDR = 0.040), Streptococcus (ORIVW = 1.548, FDR = 0.027), and Ruminococcaceae UCG-005 (ORIVW = 1.488, FDR = 0.028) were identified as risk factors for PCOS. Conversely, Candidatus Soleaferrea (ORIVW = 0.723, FDR = 0.040), Dorea (ORIVW = 0.580, FDR = 0.032), and Ruminococcaceae UCG-011 (ORIVW = 0.732, FDR = 0.030) were found to be protective factors against PCOS. Furthermore, the MR-PRESSO global test and MR-Egger regression indicated that our study results were not affected by horizontal pleiotropy (p > 0.05). Finally, the leave-one-out analysis corroborated the robustness of the MR findings. Both our meta-analysis and MR study indicates that there is a causal relationship between the gut microbiome and PCOS, which may contribute to providing novel insights for the development of new preventive and therapeutic strategies for PCOS.

Risk factors for polycystic ovary syndrome among women of reproductive age in Egypt: A case control study.

Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder among women of reproductive age, associated with an increased risk of multiple diseases, and its pathogenesis is not fully understood. Purpose: identify risk factors for Polycystic Ovary Syndrome in reproductive-aged Egyptian women attending an outpatient gynecological clinic at a specialized hospital of Obstetrics and Gynecology in Port Said City, Egypt. The study population included 248 women; 124 women suffered from PCOS and 124 Non-PCOS. Methods: - Case-control study was conducted among women. PCOS women were diagnosed clinically by transvaginal ultrasound and laboratory investigations. Data were collected using; I) a structured interview questionnaire, including socio-demographic status, medical and family history, menstrual and obstetrical history and lifestyle habits, and clinical examination; II) anthropometric parameters; III) perceived stress scale. The mean age of cases was 26.18±0.45 years. The most common risk factors for PCOS were urban residence, high education, working, insufficient income, history of anemia, hypertension, cancer, and family history of PCOS and infertility, increasing body mass index, fast food, and drinking of coffee. The study concluded that the significant risk factors for polycystic ovarian disease in Egypt women included socio-demographic characteristics, medical and family history, increasing body mass index, and lifestyle habits. This study recommended that Polycystic Ovary Syndrome women follow a healthy diet and exercise regularly.

ANTHROPOMETRIC STUDY OF POLYCYSTIC OVARY SYNDROME (PCOS) IN WOMEN

The study focused on anthropometric measurements and their relationship with the increase in the incidence of polycystic ovary syndrome (PCOS) in women, where 61 samples were collected for women with the syndrome and 45 samples as a control group. The results showed that the body mass index (BMI) of the affected women group was higher than the control group at (p=0.05), the waist-hip ratio (WHR) of the affected women was higher than the control group at (p=0.003), and age was a major factor affecting On the levels of female hormones(estrogen and progesterone hormones), elderly women are usually more likely to develop Polycystic ovarian syndrome due to the increase in obesity around the abdominal area and the effect on the ovulation process with age. Finally, the study proved that Body mass index and Waist to Hips ratio are two new markers of increased risk factors for PCOS in women of different ages.

Assessment of serum fetuin-A and its gene polymorphism as a marker of insulin resistance in polycystic ovary syndrome

Background/aim Polycystic ovary syndrome (PCOS) is a prevalent endocrine condition affecting 5–10% of reproductive-aged women, the cause of which is unknown. Chronic anovulation, polycystic ovaries, and hyperandrogenism are symptoms of PCOS. It is linked to hirsutism, obesity, and increased probability of cardiovascular disease, metabolic syndrome, and diabetes mellitus. A risk factor for cardiovascular disease is PCOS that is undiagnosed or untreated. Our aim in this study is to investigate serum fetuin-A level and its gene as potential biomarkers for screening of insulin resistance in PCOS. Patients and methods This study involved 100 female participants from outpatient clinic, Department of Obstetrics and Gynecology, Zagazig University Hospital, Egypt. They were split into two groups (each 50). The first group included healthy fertile women without symptoms of hyperandrogenemia as a control. The second group included women with PCOS. Fasting blood sugar levels, cholesterol, high-density lipoprotein cholesterol and triglycerides have been estimated by enzymatic colorimetric technique while low-density lipoprotein cholesterol was calculated. Enzyme-linked immunosorbent assays have been used to measure serum concentrations of luteinizing hormone, follicular-stimulating hormone, testosterone, and fetuin-A, while PCR has been used to extract DNA and genotype common functional polymorphisms in fetuin-A. Results The present results revealed a considerable rise in glucose, insulin, Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), cholesterol, triglyceride, low-density lipoprotein cholesterol, luteinizing hormone, testosterone, and fetuin-A and significant decrease in follicular-stimulating hormone and high-density lipoprotein cholesterol in PCOS patients. Also, there was significant higher frequency of the fetuin-A gene variant rs1071592 AA genotype and A allele compared to controls. Conclusions Fetuin-A has a potential diagnostic value as a biomarker for insulin resistance in PCOS associated with metabolic syndrome. Additionally, ‘CG’ allele can be considered a risk factor for PCOS.

Performance Comparison of Neural Network-Based Models in the Classification of Polycystic Ovary Syndrome Disease

In this study, it was aimed to compare the performances of the above mentioned ANN, MLP and deep learning methods to determine polycystic ovary syndrome (PCOS) risk factors and predict PCOS diagnosis. In this study, the data set “Polycystic ovary syndrome” was used to determine PCOS risk factors and to compare the performances of ANN, MLP and deep learning methods for PCOS diagnosis prediction. The performance of the models was evaluated with accuracy, sensitivity, specificity, positive/negative predictive values. Factors associated with PCOS were estimated from the deep learning model that has the best performance. Accuracy, sensitivity, specificity, positive predictive value and negative predictive value obtained from the MLP method were 87.25%, 79.66%, 90.93%, 81.03%, and 90.19%. Accuracy, sensitivity, specificity, positive predictive value and negative predictive value obtained from the Neural Network method were 87.80%, 79.10%, 92.03%, 82.84%, and 90.05%. Accuracy, sensitivity, specificity, positive predictive value and negative predictive value obtained from the Deep Learning method were 89.09%, 81.92%, 92.58%, 84.30%, and 91.33%. According to the findings obtained from this study, the best classification result according to the performance metrics obtained from the artificial neural networks, MLP and deep learning methods used for the PCOS data set used in the study belongs to the deep learning method. As a result, PCOS was successfully classified in the light of the findings obtained from the study, and clinical findings were tried to be revealed by giving the risk factors associated with PCOS.

Serum uric acid/creatinine ratio and free androgen index are synergistically associated with increased risk of polycystic ovary syndrome in obese women

BackgroundFeatures of metabolic syndrome such as abdominal obesity, insulin resistance, hypertension and dyslipidemia are commonly encountered in polycystic ovary syndrome (PCOS). Recent evidence has suggested an association between high serum uric acid/creatinine (UA/Cr) ratio and metabolic syndrome however, no studies have investigated this association in PCOS. The current study was conducted to investigate the relationship between UA/Cr ratio and PCOS and to identify whether UA/Cr ratio and free androgen index (FAI) have an additive interaction for detection of PCOS risk in obese women.MethodsThis study enrolled 40 obese women with PCOS and 40 control women with regular menstrual cycles matched for age and body mass index (BMI). Anthropometric measurements, fasting glucose, fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), lipids profile, luteinizing hormone (LH), follicle stimulating hormone (FSH), estradiol, dehydroepiandrosterone sulfate (DHEAS), sex hormone binding globulin (SHBG), total testosterone, free androgen index (FAI), UA/Cr ratio were assessed.ResultsSerum UA/Cr ratio was significantly higher in obese women with PCOS than in non-PCOS women. UA/Cr ratio was correlated with BMI, waist and neck circumferences, blood pressure, fasting insulin, HOMA-IR, lipids, LH/FSH, estradiol, DHEAS, total testosterone, FAI and SHBG. UA/Cr ratio and FAI were independent risk factors for PCOS in obese women however, the addictive interaction between UA/Cr ratio and FAI had a higher fold risk (OR: 4.3, 95% CI, 3.4–7.58) and a more significance (P = 0.002) for determination of PCOS.ConclusionSerum UA/Cr ratio combined with FAI can exert an additive or synergistic impact on prediction of PCOS in obese women.

Is the Risk of Polycystic Ovary Syndrome among Working Women Higher and Vice Versa?

Introduction: Polycystic ovary syndrome (PCOS), an endocrine glands disorder, caused by hormonal imbalance, is featured by diverse potential effects for women; while individuals perpend to those that are affecting appearance and menstruation disorder. Our aim was to assess PCOS risk factors in working women. Materials and Methods: The study was carried out as a literature review work through searching databases including Scopus, PubMed, and ScienceDirect for papers published before December 2019. The databases were searched for the terms such as PCO, job stress, and risk factors of PCO. Risk factors for polycystic ovarian syndrome and occupational risk factors for working women were investigated. Results and Discussion: There are several reasons known for PCOS like obesity and insulin resistance along with the stressors that increase its risk. Working women tend to be exposed to several stressors and being in charge of home affairs creates a higher workload and intensified stresses. The risk of PCOS is higher in women with higher stressors at work. Conclusions: Working women experience many stressors and taking into account that stress is a precursor or intensifier of PCOS risk factors, working women are at a higher risk of PCOS compared with housewives.

Predicting risk of obesity and meal planning to reduce the obese in adulthood using artificial intelligence.

BackgroundAn unhealthy diet or excessive amount of food intake creates obesity issues in human beings that further may cause several diseases such as Polycystic Ovary Syndrome (PCOS), Cardiovascular disease, Diabetes, Cancers, etc. Obesity is a major risk factor for PCOS, which is a common disease in women and is significantly correlated with weight gain.MethodsThis study is providing a one-step solution for predicting the risk of obesity using different Machine Learning (ML) algorithms such as Gradient Boosting (GB), Bagging meta-estimator (BME), XG Boost (XGB), Random Forest (RF), Support Vector Machine (SVM), and K Nearest Neighbour (KNN). A dataset is collected from the UCI ML repository having features of physical description and eating habits of individuals to train the proposed model.ResultsThe model has been experimented with different training and testing data ratios such as (90:10, 80:20, 70:30,60:40). At a data ratio of 90:10, the GB classifier achieved the highest accuracy i.e., 98.11%. Further, at the 80:20 ratio, the GB and XGB provide the same result i.e., 97.87%. For the 70:30 data ratio, XGB achieves the highest accuracy i.e., 97.79%. Further, the Nearest Neighbour (NN) learning method is applied to meal planning to overcome obesity.ConclusionThis method predicts the meal which includes breakfast, morning snacks, lunch, evening snacks, and dinner for the individual as per caloric and macronutrient requirements. The proposed research work can be used by practitioners to check obesity levels and to suggest meals to reduce the obese in adulthood.

Correlations between Obesity, Polycystic Ovary Syndrome, and Sleep Apnea: A Meta-Analysis

Background: Obesity is one of the biggest public health problems in the world. Obesity is associated with various health problems, decreased quality of life and death. Obesity is known to have an impact on women's lives, namely Polycystic Ovary Syndrome (PCOS) which if not treated immediately can cause sleep apnea. This study aims to analyze the relationship between obesity and PCOS and sleep apnea. Subjects and Method: This research is a systematic review and meta-analysis. Population = women, Intervention = obesity, Comparison = not obese, Outcomes = PCOS and sleep apnea. Article searches through journal databases include: PubMed, Science Direct, Google Scholar, and Springerlink. The keywords used are obesity OR obese AND PCOS OR “Polycystic Ovary Syn- drome” AND “sleep apnea” OR “Poor Sleep” OR “obstructive sleep apnea”. Articles were selected with the help of PRISMA flow diagrams. Inclusion criteria include full-text articles with obser- vational studies, multivariate analysis results in the form of aOR values and published from 2012- 2021. Eligible articles were analyzed using the Revman 5.3 application. Results: Eighteen articles from the United States, Brazil, China, Turkey, Iraq, Pakistan, Sri Lanka, Korea, West Africa, East Africa, Nigeria and the United Kingdom were included in the meta- analysis. A meta-analysis of the results of the case-control study design subgroup (4 articles) and the cross-sectional study (4 articles) showed that obese women had a 1.14-fold increased risk of developing PCOS compared to non-obese women (aOR = 1.14; 95% CI = 1.03 to 1.26; p= 0.010). A meta-analysis of 10 cross-sectional studies showed that obese women increased the risk of developing sleep apnea 4.66 times than non-obese women (aOR = 4.66; 95% CI = 3.23 to 6.71; p = &lt;0.001). Conclusion: Obesity is a risk factor for PCOS (Polycystic Ovary Syndrome) and sleep apnea in women. Keywords: obesity, PCOS, sleep apnea, meta-analysis. Correspondence: Saktryana Endang Ragil Jayanti. Master’s Program in Public Health, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta 57126, Central Java, Indonesia. Email: Saktryana.agil@gmail.com. Mobile: 082242154117.