Dissecting the role of micro-RNAs as a diagnostic marker for polycystic ovary syndrome: a systematic review and meta-analysis.

OBJECTIVE: To investigate the clinical diagnostic value and role of micro-RNAs (miRNAs) in the pathogenesis of polycystic ovary syndrome (PCOS). DESIGN: Systematic review and meta-analysis. SETTING: Not applicable. PATIENT(S): Patients were women of reproductive age with PCOS and controls. INTERVENTION(S): Summary odds ratio was calculated using a random effects model. MAIN OUTCOME MEASURE(S): Association of micro-RNAs with PCOS. METHOD(S): An electronic literature search was conducted using PubMed, Scopus, and Google Scholar databases to identify all relevant studies up to May 2019. A random effects model was used to conduct a meta-analysis. Fold change and P values were used to pool effect size. A funnel plot was used to assess publication bias. Quality score was calculated using the QUADAS scale. Subgroup analysis was based on tissue type. Odds ratios, 95% confidence intervals, and P values were estimated using meta-analysis. Metaregression was performed for correlating covariates with effect size. Area under the curve and receiver operating characteristic analysis was done to assess diagnostic performance accuracy of miRNAs in PCOS. RESULT(S): Twenty-one studies with a total of 79 miRNAs were included initially. Only three miRNAs (miR-29a-5p, miR-320, miR-93) are reported in more than three studies as of December 2018, so 12 studies were finally included in the quantitative analysis of meta-analysis and 21 studies were involved in the systematic review. The micro-RNAs miR-29a-5p and miR-320 were found to be significantly associated with PCOS. Funnel plot revealed an absence of publication bias for miR-29a-5p and miR-320. Receiver operating characteristic analysis with an area under the curve value of 0.95 proved miR-29a-5p to be the better diagnostic marker of PCOS. CONCLUSION(S): Aberrant expression of various miRNAs plays an important role in PCOS pathogenesis. Micro-RNAs hold potential diagnostic value for PCOS. These findings may offer new insights for PCOS pathogenesis research. PROSPERO REGISTRATION NUMBER: CRD42018106198.

The Prevalence of Polycystic Ovary Syndrome: A Brief Systematic Review.

BACKGROUND: Polycystic ovary syndrome (PCOS), the major endocrinopathy among reproductive-aged women, is not yet perceived as an important health problem in the world. It affects 4%-20% of women of reproductive age worldwide. The prevalence, diagnosis, etiology, management, clinical practices, psychological issues, and prevention are some of the most confusing aspects associated with PCOS. AIM: The exact prevalence figures regarding PCOS are limited and unclear. The aim of this review is to summarize comprehensively the current knowledge on the prevalence of PCOS. MATERIALS AND METHODS: Literature search was performed through PubMed, ScienceDirect, Cochrane Library, and Google Scholar (up to December 2019). All relevant articles published in English language were identified following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS: Our analysis yielded 27 surveys with a pooled mean prevalence of 21.27% using different diagnostic criteria. The proportion of women with PCOS also increased in the last decade. CONCLUSION: The current review summarizes and interprets the results of all published prevalence studies and highlights the burden of the syndrome, thereby supporting early identification and prevention of PCOS in order to reverse the persistent upward trend of prevalence.

Single nucleotide polymorphisms in treatment of polycystic ovary syndrome: a systematic review.

As 15-20% of reproductive aged females are suffering from polycystic ovary syndrome (PCOS), a large number of pharmacological preparations are frequently available in the market for the treatment of PCOS; however, they seem to be ineffective and cause undesirable side effects. This has emphasized the need to optimize dosage regimens for individualized treatment. The objective of this systematic review is to review single nucleotide polymorphisms (SNPs) associated with drugs used for the treatment of PCOS to understand pharmacogenetics variability of patients to drug response there by helping clinicians in designing tailored treatments and possibly reducing adverse drug reactions. A comprehensive electronic literature search was conducted to highlight some clinically relevant SNPs that act to influence PCOS and associated co-morbidities. A total of 16 studies were included in this review. These genetic variations can be used as a potential target for pharmacotherapy and pharmacogenetic clinical trials for better diagnosis, management, and treatment planning.

Cross-sectional study of the prevalence of polycystic ovary syndrome in rural and urban populations.

OBJECTIVE: To assess the prevalence and risk factor profile of polycystic ovary syndrome (PCOS) in Haryana, India. METHODS: A large-scale cross-sectional study was conducted among women of reproductive age in Haryana between December 2015 and May 2017. A random multi-stage stratified sampling method was adopted. PCOS screening was based on questionnaires. Blood samples for hormonal analysis were collected from those with probable and definitive PCOS cases. Women with menstrual irregularities (MI), hyperandrogenism (HA), and polycystic ovaries (PCO) (Rotterdam criteria) were included. Females with thyroid disease, hyperprolactinemia, and adrenal hyperplasia were excluded. RESULTS: Among total 2400 women screened, 94 (4.21%) had PCOS. The PCOS phenotypes were 30% clinical HA (hirsutism, H), 64% biochemical HA, 35% PCO, 16% H+MI, 10% MI+PCO, 52% MI+HA, 14% PCO+H, and 19% PCO+H+HA. Overall, 67 (71%) of the women with PCOS resided in urban regions and 27 (29%) in rural regions. CONCLUSION: Among the women with PCOS, a considerably higher proportion resided in urban regions of Haryana. The difference may be attributed to lifestyle and dietary factors. Ignoring PCOS may put women at risk of serious long-term health consequences that are difficult to manage. Lifestyle changes and continuous surveys should be promoted for better management.

Quantitative analysis of sarcosine with special emphasis on biosensors: a review.

The quantitative determination of sarcosine is of great importance in clinical chemistry, food and fermentation industries. Elevated sarcosine levels are associated with Alzheimer, dementia, prostate cancer, colorectal cancer, stomach cancer and sarcosinemia. This review summarizes the various methods for quantitative analysis of sarcosine with special emphasis on various strategies of biosensors and their analytical performance. The current bio sensing methods have overcome the drawbacks of conventional methods. Sarcosine biosensors work optimally at pH 7.0 to 8.0 in the linear range of 0.1 to 100 µM within 2 to 17 s and between 25 and 37 °C, within a limit of detection (LOD) between 0.008 and 500 mM. The formulated biosensors can be reused within a stability period of 3-180 days. Future research could be focused to modify existing sarcosine biosensors, leading to simple, reliable, and economical sensors ideally suited for point-of-care treatment. Clinical significance Elevated sarcosine levels are associated with prostate and colorectal cancer, Alzheimer, dementia, stomach cancer and sarcosinemia. Quantitative determination of sarcosine is of great importance in clinical chemistry as well as food and fermentation industries. Attempts made in development of sarcosine biosensors have been reviewed with their advantages and disadvantages, so that scientist and clinicians can improvise the methods of developing more potent sarcosine biosensor applicable in multitudinous fields. This is the first comprehensive review which compares the various immobilization methods, sensing principles, strategies used in biosensors and their analytical performance in detail.

Association of Luteinizing hormone and LH receptor gene polymorphism with susceptibility of Polycystic ovary syndrome.

Altered folliculogenesis and reproductive anomalies in polycystic ovary syndrome (PCOS) suggest that variations of genes involved in folliculogenesis might influence etiopathogenesis of this syndrome. The objective of this study was to assess the association of LHß (rs1056917) and lutropin receptor (LHR) (rs61996318) polymorphism with polycystic ovarian syndrome and to interrelate the levels of luteinizing hormone (LH) with severity of clinical manifestations of PCOS. Three hundred women of reproductive age were enrolled in this retrospective case-control study. Rotterdam Criteria was used to diagnose PCOS patients. Nucleotide mutations of LH and LHR gene was analyzed using polymerase chain reaction-restriction fragment length polymorphism. High LH levels were found in 88% of PCOS patients. LHß TC and CC genotypes were significantly associated with PCOS risk (OR [odds ratio] 13.95, CI [confidence interval] 6.30-30.86, p < 0.0001 and OR 3.31, CI 1.30-8.41, p = 0.01). The frequency of the C allele was 0.31 in PCOS and 0.02 in controls (OR 18.80, CI 8.54-41.37, p < 0.0001). LHR CA and AA genotype conferred a significant risk in development of PCOS (OR 5.07, CI 2.50-10.31, p < 0.0001). The frequency of the A allele was 0.51 in PCOS and 0.03 in controls (OR 26.62, CI 13.99-50.65, p < 0.0001). The results show an association between polymorphism of LHß, LHR and PCOS, indicating that variants of these genes may affect the metabolic pathways involved in this syndrome. Majority of the affected women were found to have elevated LH levels. This study sheds new light in the diagnosis, treatment and management of PCOS syndrome. Abbreviations: AUC: area under curve; BMI: body mass index; C: cholesterol; CI: confidence interval; DBP: diastolic blood pressure; DHEAS: dehydroepiandrosterone sulfate; FG: Ferriman-Gallway; FSH: follicle stimulating hormone; GHQ: general health questionnaire; HA: hyperandrogenism; HDL-C: high-density lipoprotein cholesterol; HOMA-IR: homeostatic model assessment for insulin resistance; HWR: hip waist ratio; LDL-C: low-density lipoprotein cholesterol; LH: luteinizing hormone; LH: luteinizing hormone; LHR: lutropin receptor; O: oligomenorrhea; OR: odds ratio; PCO: polycystic ovaries; PCO: polycystic ovary; PCOS: polycystic ovary syndrome; PCR: polymerase chain reaction; ROC: receiver operating curve; SBP: systolic blood pressure; SE: standard error of coefficient; SNP: single nucleotide polymorphism; TG: triglycerides; TSH: thyroid stimulating hormone; VD: vitamin D.

Cholesterol biosensors: A review.

Cholesterol is the most important sterol synthesized by most of the human cells majorly in the liver. It is a necessary constituent of cell membranes, it acts as a precursor for the synthesis of steroid hormones, vitamin D, and bile acids. Cholesterol is transported in plasma primarily in the form of low-density lipoproteins (LDL), the principal route for its removal from tissues to the liver is in high-density lipoproteins (HDL), followed by excretion in the bile. Cholesterol level is less than 200 mg/dL in healthy persons. 200 and 239 mg/dL is considered borderline high and 240 mg/dL and above is considered a biomarker for cardiovascular diseases, heart attack, strokes, peripheral arterial disease, type 2 diabetes and high blood pressure. Several methods are available for detection of cholesterol, among them, most are burdensome, time-consuming, require sample pre-treatment, high-cost instrumental set-up, and experienced personnel to operate. Biosensing approach overcomes these disadvantages, as these are highly specific, fast, easy, cost-effective, and highly sensitive. The review describes the various cholesterol biosensors. Cholesterol biosensors work ideally within 1 to 300 s, in pH range, 7.0-8.6, temperature 25-37 °C and cholesterol concentration range, 0.000025-700 mM, the detection limits being in the range, 0.000002-4 mM, with working potential -0.05 to 0.65 V. These biosensors measured cholesterol level in fruit juices, beverages, sera and urine samples and reused up to 200 times over a period of 15 to 50 days, while stored dry at 4 °C (Table 1). Future perspective for further improvement and commercialization of cholesterol biosensors are discussed.

Quantitative analysis of hydrogen peroxide with special emphasis on biosensors.

Determination of hydrogen peroxide (H2O2) has become essential in pharmaceutical, biological, clinical and environmental studies. The conventional detection methods of H2O2 such as colourimetry, titration, chromatography, spectrophotometry, fluorimetry, chemiluminescence have limited success, due to their poor selectivity and sensitivity, long analysis time and lack of long-term reliability and reproducibility. The biosensors overcome these limitations because of their simplicity, rapidity, selectivity and high sensitivity. This review describes the principle, analytic parameters, merits and demerits of various methods of H2O2 determination with special emphasis on biosensors. The classification of biosensors based on various materials/nanomaterials and electrodes have been described in detail. The recent advances in vivo sensing and bio-sensing of H2O2 by hemoglobin nanoparticles are also presented. The significant challenges and future perspective for highly selective H2O2 detection are discussed.

Sex hormone binding globulin - an important biomarker for predicting PCOS risk: A systematic review and meta-analysis.

Sex hormone-binding globulin (SHBG) is a glycoprotein which regulates bioavailability of sex steroid hormones. Interest in SHBG has escalated in recent years because of its inverse association with polycystic ovary syndrome (PCOS), obesity, insulin resistance, metabolic syndrome, and diabetes type II. This meta-analysis was performed to examine the associations of SHBG with PCOS and to correlate serum SHBG levels with various PCOS associated endocrine and metabolic dysregulation as well as to determine the effects of various therapeutic agents on serum SHBG levels in PCOS patients in order to assess the true accuracy of SHBG in the prediction of PCOS. A literature search was performed using Pub-Med, Science direct, google scholar, EMBASE, and Cochrane library. A total of 675 relevant records were identified, of which 62 articles were included. Meta-analysis using a random-effects model was performed using STATA version 13 to calculate standardized mean difference (SMD) with 95% confidence intervals (95 % CIs). SHBG levels in controls were significantly higher than that of PCOS patients (SMD= -0.83, 95%CI = -1.01, -0.64), with significant heterogeneity across studies (I2= 93.9% and p=0.000). Our results suggest that the lower serum SHBG levels are associated with the risk of PCOS. SHBG may also play an important role in various metabolic disturbances in PCOS patients. Therapeutic interventions improved SHBG levels in PCOS women which further reduced PCOS associated complications. Therefore, SHBG levels may prove to be a useful biomarker for the diagnosis and treatment of PCOS. Systematic review registration: PROSPERO CRD42017057972 Abbreviations: PCOS: polycystic ovary syndrome; SHBG: sex hormone-binding globulin.

Unveiling the association between Vitamin D Receptor and Poly Cystic Ovary Syndrome - a systematic review and meta-analysis.

Background: Low Vitamin D status observed in the populations globally and its associations with diverse systems have kindled the interest for Vitamin D in medical literature in last two decades. Accumulating evidence manifest that deficiency of Vitamin D might be a causal factor in the pathogenesis of various features of Poly Cystic Ovary Syndrome (PCOS). This notion is supported by the fact that > 3 % of the human genome is regulated by vitamin D receptor (VDR). Therefore, this meta-analysis was carried out to quantify the magnitude of risk associated with VDR polymorphisms (BsmI, TaqI, FokI and ApaI) and PCOS susceptibility. Methods: Pub-med, EMBASE, Cochrane database, Science direct, Scirus, ISI web of knowledge and Google scholar were searched for all years until July 2016. The case control studies related to VDR polymorphism and PCOS risk were selected according to inclusion and exclusion criteria. Nine studies of the initial 553 hits reporting VDR polymorphism in PCOS were included. All statistical analysis was performed using the STATA 11.0 software and odd ratio with 95 % confidence intervals was used as effect size to assess the strength of associations. Results: Nine studies comprising 1558 cases and 1033 controls were included in this meta-analysis. Significant association between VDR Fok1 polymorphisms and PCOS risk was observed. In further stratified analysis, an increased risks were observed among Asian and African populations for Taq1 polymorphism. Apa1 and Bsm1 polymorphism was found not to be a risk factor for PCOS susceptibility. Conclusion: The FokI polymorphism is found to be a significant risk factor for PCOS.