Andrology · 2021 · 27 citations · 29 references
MedicineEndocrinologyUrologyEpidemiologic MethodsEpidemiologyRisk Factor AnalysisDiabetes MellitusErectile DysfunctionMendelian RandomizationMetabolic SyndromeSexual DysfunctionCausal Effects Of Genetic VariantsDiabetes-related Erectile DysfunctionGenome-wide Association Study DesignMendelian Risk FactorsMetabolic Syndrome EpidemiologyUnivariate Analysis
BACKGROUND: The causal effects of individual risk factors of metabolic syndrome on erectile dysfunction (ED) are still unclear. OBJECTIVES: To evaluate the causal effect of risk factors of metabolic syndrome on ED through Mendelian randomization (MR). MATERIALS AND METHODS: Data for risk factors were obtained from multiple databases with 173,082-757,601 individuals, and that for ED were collected from a genome-wide association study including 223,805 Europeans. We performed univariate MR analysis using inverse-variance weighted, MR-Egger, weighted-median, weighted mode methods and multivariable MR analysis to evaluate the total and direct causal effects. RESULTS: The univariable MR supported that type 2 diabetes mellitus (odds ratios [OR] = 1.14, 95% confidence intervals [CI]: 1.08-1.21, p < 0.001) and body mass index (BMI) (OR = 1.27, 95% CI: 1.12-1.44, p < 0.001) were associated with ED. After excluding the SNPs associated with BMI and other risk factors, the results of multivariable MR for T2D (OR = 1.15, 95% CI: 1.05-1.25, p = 0.001) remained consistent. However, the results of multivariable MR provided limited evidence for the causality between BMI and ED (OR = 1.06, 95% CI: 0.88-1.29, p = 0.532). For systolic blood pressure and lipid components (low-density lipoprotein, high-density lipoprotein and triglycerides), both univariable and multivariable MR failed to offer sufficient evidence to confirm their causal effect on ED. CONCLUSION: T2D showed a direct causal effect on ED independent of obesity and dyslipidemia.
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Harmonizing the Metabolic Syndrome
K. G. M. M. Alberti, Robert H. Eckel, Scott M. Grundy et al. · Circulation · 2009 · 14.7K citations · Full text
The MR-Base platform supports systematic causal inference across the human phenome
Gibran Hemani, Jie Zheng, Benjamin Elsworth et al. · eLife · 2018 · 8.4K citations · Full text