Associations of Leptin Receptor and Peroxisome Proliferator-Activated Receptor Gamma Polymorphisms with Polycystic Ovary Syndrome: A Meta-Analysis

2019 ◽  
Vol 75 (1) ◽  
pp. 1-8
Author(s):  
Jialang Liang ◽  
Jiarong Lan ◽  
Min Li ◽  
Fang Wang
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Leptin Receptor ◽  
Genetic Model ◽  
Polycystic Ovary ◽  
Meta Analysis ◽  
Peroxisome Proliferator ◽  
Ovary Syndrome ◽  
Peroxisome Proliferator Activated Receptor ◽  
Subgroup Analyses ◽  
The Relationship

Background: Previous studies on associations of leptin receptor (LEPR) and peroxisome proliferator-activated receptor gamma (PPARG) polymorphisms with polycystic ovary syndrome (PCOS) yielded conflicting results. Objectives: In this meta-analysis, we aimed to better analyze the relationship between LEPR/PPARG polymorphisms and PCOS in a larger pooled population. Methods: We performed a systematic search of PubMed, Web of Science, Embase and CNKI. We calculated pooled ORs and 95% CIs to estimate associations between LEPR/PPARG polymorphisms and PCOS. Results: Totally, 33 eligible studies were included. A significant association with susceptibility to PCOS was observed for LEPR rs1137101 polymorphism under recessive genetic model (p = 0.002, OR 1.88, 95% CI 1.26–2.78, I2 = 42%) and for PPARG rs1801282 polymorphism under dominant (p = 0.007, OR 1.20, 95% CI 1.05–1.36, I2 = 49%), overdominant (p = 0.02, OR 0.85, 95% CI 0.74–0.97, I2 = 48%), and allele (p = 0.006, OR 1.18, 95% CI 1.05–1.33, I2 = 47%) genetic models in overall population. Further subgroup analyses by ethnicity revealed that LEPR rs1137101 and PPARG rs3856806 polymorphisms were both significantly associated with susceptibility to PCOS in Asians. No any positive results were detected in overall and subgroup analyses. Conclusions: Our meta-analysis suggested that LEPR rs1137101, PPARG rs1801282, and rs3856806 polymorphisms were all significantly associated with individual susceptibility to PCOS in certain populations.

scholarly journals Association of Estrogen Receptor Genes Polymorphisms With Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis Based on Observational Studies

2021 ◽  
Vol 12 ◽  
Author(s):  
Siyu Zhou ◽  
Shu Wen ◽  
Yongcheng Sheng ◽  
Meina Yang ◽  
Xiaoyang Shen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Estrogen Receptor ◽  
Polycystic Ovary Syndrome ◽  
Publication Bias ◽  
Polycystic Ovary ◽  
Meta Analysis ◽  
Genetic Models ◽  
Cochrane Library ◽  
Ovary Syndrome ◽  
Subgroup Analyses

PurposeControversial results existed in amounts of studies investigating the authentic association of estrogen receptor genes (ESR1 and ESR2) polymorphisms with the occurrence and progression of polycystic ovary syndrome (PCOS). The inconsistency might result from different loci, sample sizes, and ethnicities. To find the potential correlations between ESR1/ESR2 polymorphisms and PCOS risk, we conducted the first systematic review and meta-analysis to comprehensively summarize current studies in a large combined population.MethodsEligible studies were retrieved from PubMed, MEDLINE, EMBASE, Cochrane Library, CBM, CNKI, WANFANG, and VIP up to February 28, 2021. The quality of studies was assessed using the Newcastle–Ottawa Scale (NOS) scoring system. Odds ratios (ORs) and 95% confidence intervals (95%CIs) were calculated to synthesize data in five genetic models. Subgroup analyses were conducted by ethnicity. Heterogeneity and publication bias were also assessed. The protocol was registered in PROSPERO under the number CRD42021239200.ResultsA total of 8 studies involving 1,522 PCOS patients and 4,198 controls were included. No evidence demonstrated the association of ESR1 rs2234693 (OR=1.07 95%CI 0.98–1.18), ESR1 rs9340799 (OR=0.99 95%CI 0.69–1.43), or ESR2 rs4986938 (OR=1.06 95%CI 0.81–1.38) polymorphisms and PCOS risk in five genetic models. According to stratified subgroup analyses, ethnicity was considered the major source of heterogeneity. No publication bias was found in eligible studies.ConclusionThe present meta-analysis found no significant associations between the variants of ESR1 rs2234693, ESR1 rs9340799, ESR2 rs4936938, and individual PCOS susceptibility, even if ethnicity was taken into account.Systematic Review RegistrationThe protocol was registered in PROSPERO (available from https://www.crd.york.ac.uk/PROSPERO) with the ID number CRD42021239200.

scholarly journals Association of the Pro12Ala Polymorphism with the Metabolic Parameters in Women with Polycystic Ovary Syndrome

2017 ◽  
Vol 5 (3) ◽  
pp. 275-280 ◽  
Author(s):  
Moushira Zaki ◽  
Naglaa Hassan ◽  
Hala T. El-Bassyouni ◽  
Sanaa Kamal ◽  
Walaa Basha ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Polycystic Ovary ◽  
Fasting Blood Glucose ◽  
Metabolic Parameters ◽  
Peroxisome Proliferator ◽  
Pro12ala Polymorphism ◽  
Ovary Syndrome ◽  
Metabolic Complications ◽  
Peroxisome Proliferator Activated Receptor ◽  
Significant Difference

AIM: To investigate the association of peroxisome proliferator-activated receptor gamma (PPARG) Pro12Ala polymorphism with polycystic ovary syndrome (PCOS) and its effect on the metabolic parameters in PCOS women.METHODS: The study used PCR to identify the presence of the PPARG Pro12Ala polymorphism in 100 PCOS women and 120 age-matched healthy women. All participants were subjected to anthropometry, biochemical and metabolic evaluation.RESULTS: Significant difference in the genotypes distributions of PPARG Pro12Ala polymorphism was observed among PCOS women and controls (p = 0.03). The frequency of the polymorphic allele Ala was significantly higher in PCOS cases than that in the controls (OR = 2.01, p = 0.01). The carries of the variant allele Ala in PCOS women showed significant higher values in body mass index (BMI), systolic and diastolic blood pressure, waist circumference, waist to hip ratio, sum of skin folds, fasting blood glucose, fasting blood insulin, HOMA-IR, fasting triglycerides, total cholesterol and low-density lipoprotein than non-carriers.CONCLUSION: The PPARG Pro12Ala polymorphism might contribute to the risk of PCOS and abnormal metabolic parameters and could be considered as a biomarker for early diagnosis and clinic prediction of metabolic complications.

Sign in / Sign up

Export Citation Format

Share Document