Evidence map›Paper›PMID 39223618›Full record

ArticleDiabetology & metabolic syndrome2024

The impact of sex hormones on metabolic syndrome: univariable and multivariable Mendelian randomization studies.

Siyuan Liu, Zhuosong Mu, Xinyi Chen, Yingying Xu

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Article in Diabetology & metabolic syndrome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Siyuan Liu *The Third Clinical Medical College of Zhejiang, University of Traditional Chinese Medicine, Hangzhou, Zhejiang, China.
Zhuosong Mu *Jiangnan Hospital Affiliated to Zhejiang, Chinese Medical University (Hangzhou Xiaoshan Hospital of Traditional Chinese Medicine), Hangzhou, Zhejiang, China.
Xinyi ChenThe Third Clinical Medical College of Zhejiang, University of Traditional Chinese Medicine, Hangzhou, Zhejiang, China.
Yingying XuThe Third Affiliated Hospital of Zhejiang, University of Traditional Chinese Medicine, Hangzhou, Zhejiang, China. haoke@com.hz.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObservational 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)).

methodsWe 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.

resultsGenetically 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.

conclusionOur 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.

Indexed as

Mendelian randomizationMetabolic syndromeSex hormone binding proteinSex hormones

Identifiers

PMID39223618
PMCPMC11370018

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.