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代谢综合征、脂肪因子、凝血因子与静脉血栓栓塞症:一项两步孟德尔随机化研究

Metabolic syndrome, adipokines, coagulation factors, and venous thromboembolism: a two-step Mendelian randomization study.

作者信息

Chen Zhenzhen, Shuai Qi, Jiang Xia, Chen Wenci, Ruan Pingping, Li Ruohe, Ji Jing, Chen Shixuan

机构信息

Department of Rehabilitation Medicine, Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine affiliated to Zhejiang Chinese Medical University, No.75, Jinxiu Road, Lucheng District, Wenzhou City, Zhejiang Province, China.

Operating Room, Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine affiliated to Zhejiang Chinese Medical University, Wenzhou City, Zhejiang Province, China.

出版信息

Diabetol Metab Syndr. 2025 Jun 4;17(1):190. doi: 10.1186/s13098-025-01763-z.

DOI:10.1186/s13098-025-01763-z
PMID:40462212
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12135247/
Abstract

OBJECTIVE

The relationship between metabolic syndrome (MetS) and venous thromboembolism (VTE) remains controversial. To clarify this, we conducted a two-step Mendelian randomization (MR) study to elucidate these independent causal associations and to investigate the potential mediating effects of circulating adipokines and coagulation factors.

METHODS

Two-sample MR was employed to explore the causal associations between MetS components and VTE and its subtypes, including pulmonary embolism (PE) and deep vein thrombosis (DVT). Multivariable MR (MVMR) assessed independent effects, while mediation analyses evaluated the mediating roles of adipokines and coagulation factors. The random-effects inverse-variance weighting was adopted as the primary method, and MR-Egger and weighted median methods were used as supplementary analyses. Cochran's Q test was used to assess heterogeneity, and both the MR-Egger intercept test and Bayesian colocalization analysis were performed to detect horizontal pleiotropy.

RESULTS

In the two-sample MR analysis, we found that genetically predicted elevated systolic blood pressure (SBP) is associated with a reduced risk of VTE (OR = 0.99, p = 6.28e-06), PE (OR = 0.99, p = 4.97e-04), and DVT (OR = 0.98, p = 1.15e-08), while higher waist circumference (WC) increases the risk of VTE (OR = 1.65, p = 4.11e-10), PE (OR = 1.74, p = 1.99e-07), and DVT (OR = 1.76, p = 2.20e-08). MVMR analysis showed that both SBP and WC were independently associated with VTE, PE, and DVT. Further mediation analysis revealed that coagulation factor VIII (FVIII) mediated 18.97% of the effect of SBP on VTE, 12.95% on PE, and 14.14% on DVT. Leptin was found to mediate 50.69% of the effect of WC on VTE, 58.12% on PE, and 51.93% on DVT. These findings were replicated in independent samples. Sensitivity analyses excluded the possibility of horizontal pleiotropy and reverse causation.

CONCLUSION

Our MR analysis suggests that SBP among the components of MetS is negatively causally associated with VTE and its subtypes, while WC shows a positive causal association. Furthermore, FVIII and leptin play a key mediating role in these relationships. These findings illuminate the mechanisms linking metabolic factors to thrombotic risks, offering novel insights for targeted interventions.

摘要

目的

代谢综合征(MetS)与静脉血栓栓塞症(VTE)之间的关系仍存在争议。为阐明这一点,我们进行了一项两步孟德尔随机化(MR)研究,以阐明这些独立的因果关联,并研究循环脂肪因子和凝血因子的潜在中介作用。

方法

采用两样本MR来探索MetS各组分与VTE及其亚型(包括肺栓塞(PE)和深静脉血栓形成(DVT))之间的因果关联。多变量MR(MVMR)评估独立效应,而中介分析评估脂肪因子和凝血因子的中介作用。采用随机效应逆方差加权作为主要方法,MR-Egger法和加权中位数法作为补充分析。采用Cochran's Q检验评估异质性,并进行MR-Egger截距检验和贝叶斯共定位分析以检测水平多效性。

结果

在两样本MR分析中,我们发现遗传预测的收缩压(SBP)升高与VTE风险降低相关(OR = 0.99,p = 6.28×10⁻⁶)、PE风险降低相关(OR = 0.99,p = 4.97×10⁻⁴)和DVT风险降低相关(OR = 0.98,p = 1.15×10⁻⁸),而腰围(WC)增加与VTE风险增加相关(OR = 1.65,p = 4.11×10⁻¹⁰)、PE风险增加相关(OR = 1.74,p = 1.99×10⁻⁷)和DVT风险增加相关(OR = 1.76,p = 2.20×10⁻⁸)。MVMR分析表明,SBP和WC均与VTE、PE和DVT独立相关。进一步的中介分析显示,凝血因子VIII(FVIII)介导了SBP对VTE作用的18.97%、对PE作用的12.95%和对DVT作用的14.14%。发现瘦素介导了WC对VTE作用的50.69%、对PE作用的58.12%和对DVT作用的51.93%。这些发现已在独立样本中得到重复。敏感性分析排除了水平多效性和反向因果关系的可能性。

结论

我们的MR分析表明,MetS各组分中的SBP与VTE及其亚型呈负因果关联,而WC呈正因果关联。此外,FVIII和瘦素在这些关系中起关键中介作用。这些发现阐明了将代谢因素与血栓形成风险联系起来的机制,为靶向干预提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/5b9638442621/13098_2025_1763_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/80c6fa6f708c/13098_2025_1763_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/fabc40a96de7/13098_2025_1763_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/055d62a9203d/13098_2025_1763_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/5b9638442621/13098_2025_1763_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/80c6fa6f708c/13098_2025_1763_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/fabc40a96de7/13098_2025_1763_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/055d62a9203d/13098_2025_1763_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b954/12135247/5b9638442621/13098_2025_1763_Fig4_HTML.jpg

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