Association between lipid-lowering drug targets and the risk of cystic kidney disease: a drug-target Mendelian randomization analysis
Year: 2025
Type: article
Abstract: Evidence regarding the causal relationship between lipid-lowering drugs and cystic kidney disease, including polycystic kidney disease (PKD), was limited. This study aimed to evaluate the causal relationship between lipid phenotypes mediated by lipid-lowering drug targets—3-hydroxy-3-methyl glutaryl coenzyme A reductase (HMGCR), proprotein convertase subtilisin/kexin type-9 (PCSK9), and Niemann-Pick C1-like 1 (NPC1L1)—and the risk of cystic kidney disease and PKD. Genetic variants encoding lipid-lowering drug targets—HMGCR, PCSK9, and NPC1L1—from published genome-wide association study (GWAS) statistics were collected to perform drug target Mendelian randomization (MR) analysis. Summary statistics for the GWAS of cystic kidney disease and PKD were obtained from the FinnGen consortium and the European Bioinformatics Institute. Inverse variance weighting (IVW) was used as the primary MR analysis method, with sensitivity analyses conducted to ensure the robustness of the results. Increased gene expression of HMGCR was associated with an elevated risk of cystic kidney disease (IVW-MR: odds ratio [OR] = 3.05, 95% confidence interval [CI] = 1.19–7.84, p = 0.02) and PKD (IVW-MR: OR = 2.13, 95% CI = 1.01–4.46; p = 0.045). There was no evidence of causal effects of PCSK9 and NPC1L1 targets on cystic kidney disease and PKD. Cochran’s Q test, MR-PRESSO, and MR-Egger intercept tests showed no heterogeneity or horizontal pleiotropy among the instrumental variables. This study supported that increased HMGCR expression was associated with an increased risk of cystic kidney disease and PKD, suggesting potential benefits of statin therapy for cystic kidney disease and PKD. Further research is necessary to elucidate specific mechanisms and potential therapeutic applications of HMGCR inhibitors.
Source: Figshare
Authors: Zhiwen Lian, Zijie Liang, Qiyan Chen, Chao Xie, Yaozhong Kong
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6902278843
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