The relationship between lipoprotein A and other lipids with prostate cancer risk: A multivariable Mendelian randomisation study

BackgroundNumerous 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 findingsData 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. ConclusionsWe 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. Author summary Why was this study done? Prostate cancer (PCa) is geographically and clinically very heterogeneous, and, as a result, its risk factors may differ according to disease aggressiveness.The established PCa risk factors are mainly non-modifiable, which challenge PCa prevention efforts.Previous observational research has identified associations between blood lipids and PCa, though results remain inconclusive.The aim of this study was to identify evidence for any association between several blood lipids (i.e., LDL, HDL, TG, apoA, apoB, and Lp(a)) and total, advanced, as well as early age onset PCa. What did the researchers do and find? The researchers used genetic variants that are known to be associated with each of the blood lipids, to test whether they were associated with any of the 3 PCa outcomes.This Mendelian randomisation (MR) analysis can reduce the existence of confounding factors and reverse causation, given that genetic variants are randomly allocated and independently assorted during meiosis. MR provides complementary evidence to observational research.This study provided evidence for a positive association between genetically predicted lipoprotein A (Lp(a)) concentrations, but not with other lipids, and risk of total, advanced, and early age onset PCa. What do these findings mean? Elevated Lp(a) could play a potentially important role in increasing the risk of PCa.It remains, however, unclear whether Lp(a) is the causal factor, given that its pathophysiological mechanisms have not been well studied.These findings provide rationale for further Lp(a) research to understand its functionality and role in PCa, which could lead to repurposing lipid drugs for high-risk individuals that target Lp(a) directly and study their effectiveness against PCa.