Abstract
BACKGROUND: The genetically predicted lipid-lowering effect of HMGCR or PCSK9 variant can be used to assess drug proxy effects on kidney function. METHODS: Mendelian randomization (MR) analysis-identified HMGCR and PCSK9 genetic variants were used to predict the low-density lipoprotein (LDL) cholesterol-lowering effects of medications targeting related molecules. Primary summary-level outcome data for log-estimated glomerular filtration rate (eGFR; creatinine) were provided by the CKDGen Consortium (n = 1,004,040 European) from a meta-analysis of CKDGen and UK Biobank data. We also conducted a separate investigation of summary-level data from CKDGen (n = 567,460, log-eGFR [creatinine]) and UK Biobank (n = 436,581, log-eGFR [cystatin C]) samples. Summary-level MRs using an inverse variance weighted method and pleiotropy-robust methods were performed. RESULTS: Summary-level MR analysis indicated that the LDL-lowering effect predicted genetically by HMGCR variants (50-mg/dL decrease) was significantly associated with a decrease in eGFR (-1.67%; 95% confidence interval [CI], -2.20% to -1.13%). Similar significance was found in results from the pleiotropy-robust MR methods when the CKDGen and UK Biobank data were analyzed separately. However, the LDL-lowering effect predicted genetically by PCSK9 variants was significantly associated with an increase in eGFR (+1.17%; 95% CI, 0.10%-2.25%). The results were similarly supported by the weighted median method and in each CKDGen and UK Biobank dataset, but the significance obtained by MR-Egger regression was attenuated. CONCLUSION: Genetically predicted HMG-CoA reductase inhibition was associated with low eGFR, while genetically predicted PCSK9 inhibition was associated with high eGFR. Clinicians should consider that the direct effect of different types of lipid-lowering medication on kidney function can vary.
14 Authors
- Sehoon Park
- Seong Geun Kim
- Soojin Lee
- Yaerim Kim
- Semin Cho
- Kwangsoo Kim
- Yong Chul Kim
- Seung Seok Han
- Hajeong Lee
- Jung Pyo Lee
- Kwon Wook Joo
- Chun Soo Lim
- Yon Su Kim
- Dong Ki Kim
1 Application
Application ID | Title |
53799 | Impact of genetic and environmental factors on the health-related outcomes in chronic kidney disease patients |