Lipids, lipid-lowering drug target genes and pancreatic cancer: a Mendelian randomization study.
1/5 보강
[BACKGROUND] Pancreatic cancer (PC) is a malignant tumor with a low survival rate.
- p-value p = 0.0453
- p-value p = 0.0369
- 95% CI 0.25-1.00
APA
Zhan Y, Zhang K, et al. (2025). Lipids, lipid-lowering drug target genes and pancreatic cancer: a Mendelian randomization study.. International journal of clinical pharmacy, 47(3), 747-754. https://doi.org/10.1007/s11096-025-01866-7
MLA
Zhan Y, et al.. "Lipids, lipid-lowering drug target genes and pancreatic cancer: a Mendelian randomization study.." International journal of clinical pharmacy, vol. 47, no. 3, 2025, pp. 747-754.
PMID
39821006 ↗
Abstract 한글 요약
[BACKGROUND] Pancreatic cancer (PC) is a malignant tumor with a low survival rate. Lipid modifiers show potential for PC therapy, but evidence is lacking.
[AIM] This Mendelian randomization (MR) study aimed to explore the relationship between lipid traits, and lipid-lowering drug target genes with PC risk.
[METHOD] Genetic instrumental variables associated with lipid traits and lipid-lowering drug target genes were used to perform MR analyses of PC risk. MR estimation was based on genome-wide association study data from two large sample sets, and the MR results were meta-analyzed to assess their impact on PC risk. To ensure the reliability of lipid-modifying drug targets, we conducted a Summary Data-based Mendelian Randomization (SMR) analysis. Additionally, a two-step MR analysis was employed to explore potential mediating effects.
[RESULTS] In two independent datasets, HMG-CoA reductase (HMGCR) inhibition was statistically associated with a lower risk of PC (OR 0.50, [95% CI 0.25-1.00]; p = 0.0453). The results were further supported by SMR analysis, which showed a similar association (OR 0.51, [95% CI 0.28-0.96]; p = 0.0369). Mediation analysis revealed that 11.69% of the protective effect of HMGCR inhibitors on PC is mediated through lower BMI levels. No significant effect of lipid traits and the other eight lipid-lowering drug targets on PC risk was found.
[CONCLUSION] This study suggests that HMGCR may be a potential drug target for the treatment or prevention of PC, providing important insights into the use of lipid-targeted drugs in PC therapy.
[AIM] This Mendelian randomization (MR) study aimed to explore the relationship between lipid traits, and lipid-lowering drug target genes with PC risk.
[METHOD] Genetic instrumental variables associated with lipid traits and lipid-lowering drug target genes were used to perform MR analyses of PC risk. MR estimation was based on genome-wide association study data from two large sample sets, and the MR results were meta-analyzed to assess their impact on PC risk. To ensure the reliability of lipid-modifying drug targets, we conducted a Summary Data-based Mendelian Randomization (SMR) analysis. Additionally, a two-step MR analysis was employed to explore potential mediating effects.
[RESULTS] In two independent datasets, HMG-CoA reductase (HMGCR) inhibition was statistically associated with a lower risk of PC (OR 0.50, [95% CI 0.25-1.00]; p = 0.0453). The results were further supported by SMR analysis, which showed a similar association (OR 0.51, [95% CI 0.28-0.96]; p = 0.0369). Mediation analysis revealed that 11.69% of the protective effect of HMGCR inhibitors on PC is mediated through lower BMI levels. No significant effect of lipid traits and the other eight lipid-lowering drug targets on PC risk was found.
[CONCLUSION] This study suggests that HMGCR may be a potential drug target for the treatment or prevention of PC, providing important insights into the use of lipid-targeted drugs in PC therapy.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
- Humans
- Pancreatic Neoplasms
- Mendelian Randomization Analysis
- Genome-Wide Association Study
- Lipids
- Hydroxymethylglutaryl-CoA Reductase Inhibitors
- Hypolipidemic Agents
- Polymorphism
- Single Nucleotide
- Hydroxymethylglutaryl CoA Reductases
- Drug target Mendelian randomization
- Genetics
- Lipid-lowering drug target
- Pancreatic cancer
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