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Updated: Jun 14, 2025

A Hyperandrogenic Mouse Model to Study Polycystic Ovary Syndrome
Published on: October 2, 2018
The impact of sex hormones on metabolic syndrome: univariable and multivariable Mendelian randomization studies
Siyuan Liu1, Zhuosong Mu2, Xinyi Chen1
1The Third Clinical Medical College of Zhejiang, University of Traditional Chinese Medicine, Hangzhou, Zhejiang, China.
Background:
Observational studies have found associations between sex hormones and metabolic syndrome(Mets), but the causal relationships remains unclear. This study utilizes univariable and multivariable Mendelian randomization (MR) to elucidate the associations between sex hormones (including sex hormone-binding globulin(SHBG), estradiol(E2), testosterone(T)) and Mets and its subtypes (including waist circumference(WC), fasting blood glucose(FBG), high blood pressure(HBP), high-density lipoprotein(HDL-C), triglycerides(TG)).
Methods:
We utilized summary data from large-scale genome-wide association studies. Univariable Mendelian randomization (UMVMR) analysis was primarily conducted using the inverse variance weighted method (IVW), with secondary analyses employing the weighted median, MR-Egger regression, simple mode method, and weighted mode method. Subsequently, multivariable Mendelian randomization (MVMR) was employed to assess the causal relationships between SHBG, T, E2, and MetS and its components: WC, FPG, HBP, HDL-C, and TG. Sensitivity analyses were conducted to assess result reliability.
Results:
Genetically predicted SHBG was significantly negatively associated with MetS (UMVMR: β=-0.72; 95% CI = 0.41 to 0.57; P = 1.28e-17; MVMR: β=-0.60; 95% CI=-0.83 to -0.38; P < 0.001). Positive causal relationships were observed between SHBG and WC(MVMR: β = 0.10; 95% CI = 0.03 to 0.17; P = 0.01) and HDL-C (MVMR: β = 0.41; 95% CI = 0.21 to 0.60; P < 0.001), while negative causal relationships were found between SHBG and HBP (MVMR: β=-0.02; 95% CI=-0.04 to -0.00; P = 0.02), TG (MVMR: β=-0.48; 95% CI=-0.70 to -0.26; P < 0.001). Genetically predicted E2 exhibited a negative association with TG (MVMR: β=-1.49; 95% CI=-2.48 to -0.50; P = 0.003). Genetically predicted T was negatively associated with TG (MVMR: β=-0.36; 95% CI=-0.71 to -0.00; P = 0.049) and WC (MVMR: β=-0.13; 95% CI=-0.24 to -0.02; P = 0.02), with inconsistent sensitivity analyses. Additionally, No other causal associations were found.
Conclusion:
Our study indicates that SHBG is a protective factor for MetS, potentially delaying its onset and progression through improvements in HBP and TG. Furthermore, T and E2 may improve TG levels, with T also reducing WC levels. Importantly, our study provides new insights for the prevention and treatment of MetS.
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