scholarly journals Skeletal Muscle Immunometabolism in Women With Polycystic Ovary Syndrome: A Meta-Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Maria Manti ◽  
Elisabet Stener-Victorin ◽  
Anna Benrick
Keyword(s):  
Skeletal Muscle ◽  
Polycystic Ovary Syndrome ◽  
Polycystic Ovary ◽  
Meta Analysis ◽  
Ovary Syndrome

scholarly journals Molecular Mechanisms of Insulin Resistance in Polycystic Ovary Syndrome: Unraveling the Conundrum in Skeletal Muscle?

2019 ◽  
Vol 104 (11) ◽  
pp. 5372-5381 ◽  
Author(s):  
Nigel K Stepto ◽  
Alba Moreno-Asso ◽  
Luke C McIlvenna ◽  
Kirsty A Walters ◽  
Raymond J Rodgers
Keyword(s):  
Insulin Resistance ◽  
Skeletal Muscle ◽  
Polycystic Ovary Syndrome ◽  
Molecular Mechanisms ◽  
Current Knowledge ◽  
Polycystic Ovary ◽  
Evidence Synthesis ◽  
Basic Research ◽  
Future Research ◽  
Ovary Syndrome

Abstract Context Polycystic ovary syndrome (PCOS) is a common endocrine condition affecting 8% to 13% of women across the lifespan. PCOS affects reproductive, metabolic, and mental health, generating a considerable health burden. Advances in treatment of women with PCOS has been hampered by evolving diagnostic criteria and poor recognition by clinicians. This has resulted in limited clinical and basic research. In this study, we provide insights into the current and future research on the metabolic features of PCOS, specifically as they relate to PCOS-specific insulin resistance (IR), that may affect the most metabolically active tissue, skeletal muscle. Current Knowledge PCOS is a highly heritable condition, yet it is phenotypically heterogeneous in both reproductive and metabolic features. Human studies thus far have not identified molecular mechanisms of PCOS-specific IR in skeletal muscle. However, recent research has provided new insights that implicate energy-sensing pathways regulated via epigenomic and resultant transcriptomic changes. Animal models, while in existence, have been underused in exploring molecular mechanisms of IR in PCOS and specifically in skeletal muscle. Future Directions Based on the latest evidence synthesis and technologies, researchers exploring molecular mechanisms of IR in PCOS, specifically in muscle, will likely need to generate new hypothesis to be tested in human and animal studies. Conclusion Investigations to elucidate the molecular mechanisms driving IR in PCOS are in their early stages, yet remarkable advances have been made in skeletal muscle. Overall, investigations have thus far created more questions than answers, which provide new opportunities to study complex endocrine conditions.

scholarly journals Non‐alcoholic fatty liver disease in premenopausal women with polycystic ovary syndrome: A systematic review and meta‐analysis

JGH Open ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 434-445
Author(s):  
Mohamed Shengir ◽  
Tianyan Chen ◽  
Elena Guadagno ◽  
Agnihotram V Ramanakumar ◽  
Peter Ghali ◽  
...  
Keyword(s):  
Systematic Review ◽  
Liver Disease ◽  
Polycystic Ovary Syndrome ◽  
Fatty Liver Disease ◽  
Polycystic Ovary ◽  
Meta Analysis ◽  
Premenopausal Women ◽  
Ovary Syndrome ◽  
Alcoholic Fatty Liver ◽  
Alcoholic Fatty Liver Disease

scholarly journals Effects of probiotic and synbiotic supplementation on insulin resistance in women with polycystic ovary syndrome: a meta-analysis

2021 ◽  
Vol 49 (7) ◽  
pp. 030006052110317
Author(s):  
Chenyun Miao ◽  
Qingge Guo ◽  
Xiaojie Fang ◽  
Yun Chen ◽  
Ying Zhao ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Polycystic Ovary Syndrome ◽  
Confidence Interval ◽  
Polycystic Ovary ◽  
Serum Insulin ◽  
Meta Analysis ◽  
Mean Difference ◽  
Model Assessment ◽  
Ovary Syndrome ◽  
Synbiotic Supplementation

Objective This meta-analysis evaluated the effect of probiotics and synbiotics on insulin resistance in patients with polycystic ovary syndrome (PCOS). Methods A systematic search was performed to identify all relevant publications listed on the electronic databases (PubMed®, Web of Science, Embase® and China National Knowledge Infrastructure) between inception and 30 October 2020. All statistical analyses were performed on randomized controlled trials (RCTs) using RevMan version 5.3 software provided by the Cochrane Collaboration. Results A total of 486 patients from seven RCTs were included in the meta-analysis. Probiotic and synbiotic supplementation appeared to improve levels of homeostatic model assessment of insulin resistance (mean difference = –0.37; 95% confidence interval –0.69, –0.05) and serum insulin (standardized mean difference = –0.66; 95% confidence interval –1.19, –0.12). The results failed to show any influence of probiotic and synbiotic supplementation on body mass index, waist circumference, hip circumference and fasting blood sugar. Conclusions Probiotics and synbiotics appear to have a partially beneficial effect on indices of insulin resistance in patients with PCOS.

scholarly journals Family-Based Quantitative Trait Meta-Analysis Implicates Rare Noncoding Variants in DENND1A in Polycystic Ovary Syndrome

2019 ◽  
Vol 104 (9) ◽  
pp. 3835-3850 ◽  
Author(s):  
Matthew Dapas ◽  
Ryan Sisk ◽  
Richard S Legro ◽  
Margrit Urbanek ◽  
Andrea Dunaif ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Quantitative Trait ◽  
Rare Variants ◽  
Polycystic Ovary ◽  
Association Studies ◽  
Meta Analysis ◽  
Premenopausal Women ◽  
Endocrine Disorders ◽  
Genome Wide Association Studies ◽  
Ovary Syndrome

AbstractContextPolycystic ovary syndrome (PCOS) is among the most common endocrine disorders of premenopausal women, affecting 5% to15% of this population depending on the diagnostic criteria applied. It is characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. PCOS is highly heritable, but only a small proportion of this heritability can be accounted for by the common genetic susceptibility variants identified to date.ObjectiveThe objective of this study was to test whether rare genetic variants contribute to PCOS pathogenesis.Design, Patients, and MethodsWe performed whole-genome sequencing on DNA from 261 individuals from 62 families with one or more daughters with PCOS. We tested for associations of rare variants with PCOS and its concomitant hormonal traits using a quantitative trait meta-analysis.ResultsWe found rare variants in DENND1A (P = 5.31 × 10−5, adjusted P = 0.039) that were significantly associated with reproductive and metabolic traits in PCOS families.ConclusionsCommon variants in DENND1A have previously been associated with PCOS diagnosis in genome-wide association studies. Subsequent studies indicated that DENND1A is an important regulator of human ovarian androgen biosynthesis. Our findings provide additional evidence that DENND1A plays a central role in PCOS and suggest that rare noncoding variants contribute to disease pathogenesis.

scholarly journals Relationships Between Biochemical Markers of Hyperandrogenism and Metabolic Parameters in Women with Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis

2019 ◽  
Vol 51 (01) ◽  
pp. 22-34 ◽  
Author(s):  
Mina Amiri ◽  
Fahimeh Tehrani ◽  
Razieh Bidhendi-Yarandi ◽  
Samira Behboudi-Gandevani ◽  
Fereidoun Azizi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Polycystic Ovary Syndrome ◽  
Biochemical Markers ◽  
Polycystic Ovary ◽  
Meta Analysis ◽  
Metabolic Parameters ◽  
High Density Lipoproteins ◽  
Total Testosterone ◽  
Ovary Syndrome ◽  
Increased Risk

AbstractWhile several studies have documented an increased risk of metabolic disorders in patients with polycystic ovary syndrome (PCOS), associations between androgenic and metabolic parameters in these patients are unclear. We aimed to investigate the relationships between biochemical markers of hyperandrogenism (HA) and metabolic parameters in women with PCOS. In this systematic review and meta-analysis, a literature search was performed in the PubMed, Scopus, Google Scholar, ScienceDirect, and Web of Science from 2000 to 2018 for assessing androgenic and metabolic parameters in PCOS patients. To assess the relationships between androgenic and metabolic parameters, meta-regression analysis was used. A total number of 33 studies involving 9905 patients with PCOS were included in this analysis. The associations of total testosterone (tT) with metabolic parameters were not significant; after adjustment for age and BMI, we detected associations of this androgen with low-density lipoproteins cholesterol (LDL-C) (β=0.006; 95% CI: 0.002, 0.01), high-density lipoproteins cholesterol (HDL-C) (β=–0.009; 95% CI: –0.02, –0.001), and systolic blood pressure (SBP) (β=–0.01; 95% CI: –0.03, –0.00). We observed a positive significant association between free testosterone (fT) and fasting insulin (β=0.49; 95% CI: 0.05, 0.91); this association remained significant after adjustment for confounders. We also detected a reverse association between fT and HDL-C (β=–0.41; 95% CI: –0.70, –0.12). There was a positive significant association between A4 and TG (β=0.02; 95% CI: 0.00, 0.04) after adjustment for PCOS diagnosis criteria. We also found significant negative associations between A4, TC, and LDL-C. Dehydroepiandrosterone sulfate (DHEAS) had a positive association with LDL-C (β=0.02; 95% CI: 0.001, 0.03) and a reverse significant association with HDL-C (β=–0.03; 95% CI: –0.06, –0.001). This meta-analysis confirmed the associations of some androgenic and metabolic parameters, indicating that measurement of these parameters may be useful for predicting metabolic risk in PCOS patients.

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