Anna Ioannidou, Eleanor L Watts, Aurora Perez-Cornago, Elizabeth A Platz, Ian G Mills, Timothy J Key, Ruth C Travis, Konstantinos K Tsilidis, Verena Zuber
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This study aimed to identify the relationship between genetically predicted blood lipid concentrations and PCa.</p><p><strong>Methods and findings: </strong>Data for low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides (TG), apolipoprotein A (apoA) and B (apoB), lipoprotein A (Lp(a)), and PCa were acquired from genome-wide association studies in UK Biobank and the PRACTICAL consortium, respectively. We used a two-sample summary-level Mendelian randomisation (MR) approach with both univariable and multivariable (MVMR) models and utilised a variety of robust methods and sensitivity analyses to assess the possibility of MR assumptions violation. No association was observed between genetically predicted concentrations of HDL, TG, apoA and apoB, and PCa risk. Genetically predicted LDL concentration was positively associated with total PCa in the univariable analysis, but adjustment for HDL, TG, and Lp(a) led to a null association. Genetically predicted concentration of Lp(a) was associated with higher total PCa risk in the univariable (ORweighted median per standard deviation (SD) = 1.091; 95% CI 1.028 to 1.157; P = 0.004) and MVMR analyses after adjustment for the other lipid traits (ORIVW per SD = 1.068; 95% CI 1.005 to 1.134; P = 0.034). Genetically predicted Lp(a) was also associated with advanced (MVMR ORIVW per SD = 1.078; 95% CI 0.999 to 1.163; P = 0.055) and early age onset PCa (MVMR ORIVW per SD = 1.150; 95% CI 1.015,1.303; P = 0.028). Although multiple estimation methods were utilised to minimise the effect of pleiotropy, the presence of any unmeasured pleiotropy cannot be excluded and may limit our findings.</p><p><strong>Conclusions: </strong>We observed that genetically predicted Lp(a) concentrations were associated with an increased PCa risk. 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引用次数: 0
摘要
背景:许多流行病学研究都对血脂在前列腺癌(PCa)风险中的作用进行了调查,但至今仍无定论。正在进行的研究主要涉及观察性研究,而观察性研究往往容易受到混杂因素的影响。本研究旨在确定遗传预测血脂浓度与 PCa 之间的关系:低密度脂蛋白(LDL)胆固醇、高密度脂蛋白(HDL)胆固醇、甘油三酯(TG)、载脂蛋白A(apoA)和B(apoB)、脂蛋白A(Lp(a))和PCa的数据分别来自英国生物库和PRACTICAL联盟的全基因组关联研究。我们采用了双样本汇总级孟德尔随机化(MR)方法,同时使用单变量和多变量(MVMR)模型,并利用各种稳健方法和敏感性分析来评估违反 MR 假设的可能性。在高密度脂蛋白、总胆固醇、载脂蛋白A和载脂蛋白B的基因预测浓度与PCa风险之间未发现任何关联。在单变量分析中,基因预测的低密度脂蛋白浓度与总的 PCa 呈正相关,但对高密度脂蛋白、总胆固醇和脂蛋白(a)进行调整后发现两者之间的关系为空。在单变量分析(每标准差(SD)加权中位数 OR = 1.091;95% CI 1.028 至 1.157;P = 0.004)和 MVMR 分析(每标准差 ORIVW = 1.068;95% CI 1.005 至 1.134;P = 0.034)中,遗传预测的 Lp(a) 浓度与较高的 PCa 总风险相关。遗传预测的脂蛋白(a)也与晚期(MVMR ORIVW per SD = 1.078; 95% CI 0.999 to 1.163; P = 0.055)和早发 PCa(MVMR ORIVW per SD = 1.150; 95% CI 1.015,1.303; P = 0.028)相关。尽管我们采用了多种估计方法来尽量减少多效应的影响,但仍不能排除任何未测量的多效应的存在,这可能会限制我们的研究结果:我们观察到,基因预测的脂蛋白(a)浓度与 PCa 风险增加有关。未来的研究需要了解这一发现的潜在生物学途径,因为这可能为通过降低脂蛋白(a)策略预防 PCa 提供依据。
The relationship between lipoprotein A and other lipids with prostate cancer risk: A multivariable Mendelian randomisation study.
Background: Numerous epidemiological studies have investigated the role of blood lipids in prostate cancer (PCa) risk, though findings remain inconclusive to date. The ongoing research has mainly involved observational studies, which are often prone to confounding. This study aimed to identify the relationship between genetically predicted blood lipid concentrations and PCa.
Methods and findings: Data for low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides (TG), apolipoprotein A (apoA) and B (apoB), lipoprotein A (Lp(a)), and PCa were acquired from genome-wide association studies in UK Biobank and the PRACTICAL consortium, respectively. We used a two-sample summary-level Mendelian randomisation (MR) approach with both univariable and multivariable (MVMR) models and utilised a variety of robust methods and sensitivity analyses to assess the possibility of MR assumptions violation. No association was observed between genetically predicted concentrations of HDL, TG, apoA and apoB, and PCa risk. Genetically predicted LDL concentration was positively associated with total PCa in the univariable analysis, but adjustment for HDL, TG, and Lp(a) led to a null association. Genetically predicted concentration of Lp(a) was associated with higher total PCa risk in the univariable (ORweighted median per standard deviation (SD) = 1.091; 95% CI 1.028 to 1.157; P = 0.004) and MVMR analyses after adjustment for the other lipid traits (ORIVW per SD = 1.068; 95% CI 1.005 to 1.134; P = 0.034). Genetically predicted Lp(a) was also associated with advanced (MVMR ORIVW per SD = 1.078; 95% CI 0.999 to 1.163; P = 0.055) and early age onset PCa (MVMR ORIVW per SD = 1.150; 95% CI 1.015,1.303; P = 0.028). Although multiple estimation methods were utilised to minimise the effect of pleiotropy, the presence of any unmeasured pleiotropy cannot be excluded and may limit our findings.
Conclusions: We observed that genetically predicted Lp(a) concentrations were associated with an increased PCa risk. Future studies are required to understand the underlying biological pathways of this finding, as it may inform PCa prevention through Lp(a)-lowering strategies.
期刊介绍:
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