HDL Cholesterol Levels and Pancreatic Cancer Risk: Protective Effects Revealed.

IF 2.3 4区 医学 Q3 ONCOLOGY
Yiming Shao, Rui Hao, Si Si Lin, Ba-Fang Ma, Jun-Nan Ye, Mayila Maimaiti, Yasen Maimaitiyiming
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Abstract

Background: The causal relationship between lipoprotein traits and the risk of pancre-atic cancer (PC) remains unclear. In this study, we employed a two-sample Mendelian randomiza-tion (MR) approach to explore the untangled relationship between lipoprotein traits and PC.

Methods: Univariable MR analyses were used to determine the causal connection between lipo-protein traits and PC. Instrumental variables corresponding to lipoprotein traits were taken from the Global Lipids Genetics Consortium (GLGC) (n = 188,578). The outcome dataset was created from PC summary-level data (n case = 1896, n control = 1939) from a genome-wide association study of European ancestry. Causal effects were evaluated using the inverse variance weighted (IVW) method. For sensitivity analysis, both the weighted median (WM) and MR-Egger methods, among others, were utilized. We also conducted multivariable MR analyses to examine potential confounders.

Results: In univariable MR, IVW methods supported evidence that HDL cholesterol (OR = 0.463, 95% CI: 0.313-0.685; P = 1.10×10-4) was linked with a decreased risk of PC. These findings were consistent across other MR methods, including MR-Egger (OR = 0.340, 95% CI: 0.182-0.638; P = 1.30×10-3) and WM (OR = 0.367, 95% CI: 0.195-0.692; P = 1.90×10-3). Our results displayed no significant heterogeneity or horizontal pleiotropy. Furthermore, these associations persisted in the multivariable MR analysis after adjusting for confounding factors such as smok-ing, alcohol consumption, and body mass index (BMI).

Conclusions: Our comprehensive MR analyses consistently demonstrate a protective association between higher HDL cholesterol levels and decreased PC risk, even after adjustments for key life-style factors and BMI.

高密度脂蛋白胆固醇水平与胰腺癌风险:保护作用揭示。
背景:脂蛋白特征与胰腺癌(PC)风险之间的因果关系尚不清楚。在这项研究中,我们采用双样本孟德尔随机化(MR)方法来探索脂蛋白性状与PC之间的关系。方法:采用单变量磁共振分析确定脂蛋白性状与PC之间的因果关系。与脂蛋白性状对应的工具变量来自全球脂质遗传学联合会(GLGC) (n = 188,578)。结果数据集是根据欧洲血统全基因组关联研究的PC汇总数据(n例= 1896,n对照= 1939)创建的。采用反方差加权(IVW)方法评价因果效应。敏感性分析采用加权中位数法(WM)和MR-Egger等方法。我们还进行了多变量磁共振分析,以检查潜在的混杂因素。结果:在单变量MR中,IVW方法支持高密度脂蛋白胆固醇(OR = 0.463, 95% CI: 0.313-0.685;P = 1.10×10-4)与降低患PC的风险有关。这些发现在其他MR方法中是一致的,包括MR- egger (OR = 0.340, 95% CI: 0.182-0.638;P = 1.30×10-3)和WM (OR = 0.367, 95% CI: 0.195-0.692;P = 1.90×10-3)。我们的结果显示没有显著的异质性或水平多效性。此外,在调整了诸如吸烟、饮酒和体重指数(BMI)等混杂因素后,这些关联在多变量MR分析中仍然存在。结论:我们的综合MR分析一致表明,即使在调整了关键的生活方式因素和BMI后,较高的HDL胆固醇水平与降低的PC风险之间存在保护性关联。
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来源期刊
Current cancer drug targets
Current cancer drug targets 医学-肿瘤学
CiteScore
5.40
自引率
0.00%
发文量
105
审稿时长
1 months
期刊介绍: Current Cancer Drug Targets aims to cover all the latest and outstanding developments on the medicinal chemistry, pharmacology, molecular biology, genomics and biochemistry of contemporary molecular drug targets involved in cancer, e.g. disease specific proteins, receptors, enzymes and genes. Current Cancer Drug Targets publishes original research articles, letters, reviews / mini-reviews, drug clinical trial studies and guest edited thematic issues written by leaders in the field covering a range of current topics on drug targets involved in cancer. As the discovery, identification, characterization and validation of novel human drug targets for anti-cancer drug discovery continues to grow; this journal has become essential reading for all pharmaceutical scientists involved in drug discovery and development.
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