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血脂谱、端粒长度与恶性肿瘤风险:孟德尔随机化和中介分析

Lipid Profiles, Telomere Length, and the Risk of Malignant Tumors: A Mendelian Randomization and Mediation Analysis.

作者信息

Liu Shupeng, Fu Zhengzheng, Liu Hui, Wang Yinghui, Zhou Meijuan, Ding Zhenhua, Feng Zhijun

机构信息

Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Radiation Medicine, School of Public Health, Southern Medical University, Guangzhou 510515, China.

出版信息

Biomedicines. 2024 Dec 25;13(1):13. doi: 10.3390/biomedicines13010013.

DOI:10.3390/biomedicines13010013
PMID:39857597
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11760878/
Abstract

The relationship between lipid profiles, telomere length (TL), and cancer risk remains unclear. This study employed two-sample Mendelian randomization (MR) with mediation analysis to investigate their causal relationships, examining lipid profiles as exposure, TL as mediator, and nine cancer types as outcomes. We conducted our analysis using two-stage least squares (2SLS) regression integrated with inverse variance weighted (IVW) methods to address potential endogeneity and strengthen our causal inference. we found that unfavorable lipid profiles were causally linked to increased TL ( < 0.05). TL showed positive causal associations with lung and hematologic cancers (OR > 1, < 0.05). Direct associations were observed between total and low-density lipoprotein (LDL) cholesterol and gastric cancer (OR < 1, < 0.05), and between remnant cholesterol and colorectal cancer (OR > 1, < 0.05). Mediation analysis revealed TL as a significant mediator in the pathway from lipid profiles to cancer development ( < 0.05). No horizontal pleiotropy was detected. Our findings suggest that lipid metabolism disorders may influence cancer development through telomere regulation, particularly in lung and hematologic cancers. This emphasizes the importance of lipid management in cancer prevention and treatment, especially for these cancer types.

摘要

血脂谱、端粒长度(TL)与癌症风险之间的关系仍不明确。本研究采用两样本孟德尔随机化(MR)和中介分析来探究它们之间的因果关系,将血脂谱作为暴露因素,TL作为中介变量,九种癌症类型作为结局变量。我们使用两阶段最小二乘法(2SLS)回归结合逆方差加权(IVW)方法进行分析,以解决潜在的内生性问题并加强因果推断。我们发现不良血脂谱与TL增加存在因果关联(<0.05)。TL与肺癌和血液系统癌症呈正因果关联(OR>1,<0.05)。总胆固醇和低密度脂蛋白(LDL)胆固醇与胃癌之间存在直接关联(OR<1,<0.05),残余胆固醇与结直肠癌之间也存在直接关联(OR>1,<0.05)。中介分析显示,TL在血脂谱到癌症发生的通路中是一个显著的中介变量(<0.05)。未检测到水平多效性。我们的研究结果表明,脂质代谢紊乱可能通过端粒调节影响癌症发生,尤其是在肺癌和血液系统癌症中。这强调了脂质管理在癌症预防和治疗中的重要性,特别是对于这些癌症类型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/41c348308d6c/biomedicines-13-00013-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/009d1a303128/biomedicines-13-00013-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/670aea577b80/biomedicines-13-00013-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/d75a1cfac767/biomedicines-13-00013-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/41c348308d6c/biomedicines-13-00013-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/009d1a303128/biomedicines-13-00013-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/670aea577b80/biomedicines-13-00013-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/d75a1cfac767/biomedicines-13-00013-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d14/11760878/41c348308d6c/biomedicines-13-00013-g004.jpg

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