Eeva Sliz1,2, Johannes Kettunen1,2,3, Michael V Holmes4,5,6,7, Clare Oliver Williams8,9, Charles Boachie10, Qin Wang1,2,3,11, Minna Männikkö12, Sylvain Sebert1,2,13, Robin Walters5, Kuang Lin5, Iona Y Millwood5, Robert Clarke5, Liming Li14,15, Naomi Rankin16, Paul Welsh16, Christian Delles16, J Wouter Jukema17, Stella Trompet17,18, Ian Ford10, Markus Perola19,20,21, Veikko Salomaa19, Marjo-Riitta Järvelin1,2,22,23, Zhengming Chen5, Debbie A Lawlor7,24, Mika Ala-Korpela1,2,3,7,11,24,25,26, John Danesh8,27,28, George Davey Smith7,24, Naveed Sattar16, Adam Butterworth8,27, Peter Würtz29,30. 1. Center for Life Course Health Research, University of Oulu, Oulu, Finland. 2. Biocenter Oulu, Oulu, Finland. 3. Computational Medicine, Faculty of Medicine, University of Oulu, Finland. 4. Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK. 5. Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK. 6. National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospital, Oxford, UK. 7. Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK. 8. MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. 9. Homerton College, University of Cambridge, Cambridge, UK. 10. Robertson Centre for Biostatistics, Boyd Orr Building, University of Glasgow, Glasgow, UK. 11. Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. 12. Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu, Oulu, Finland. 13. Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, UK. 14. Chinese Academy of Medical Sciences, 9 Dongdan San Tiao, Beijing, China. 15. Department of Global Health, School of Public Health, Peking University, Beijing, China. 16. Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK. 17. Leiden University Medical Centre, Leiden, The Netherlands. 18. Department of Internal Medicine, section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands. 19. National Institute for Health and Welfare, Helsinki, Finland. 20. Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland. 21. University of Tartu, Estonian Genome Center, Tartu, Estonia. 22. Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK. 23. Unit of Primary Care, Oulu University Hospital, Oulu, Finland. 24. Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK. 25. NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland. 26. Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, VIC, Australia. 27. National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, United Kingdom. 28. Wellcome Trust Sanger Institute, Hinxton, United Kingdom. 29. Diabetes and Obesity Research Program, University of Helsinki, Helsinki, Finland. 30. Nightingale Health Ltd, Helsinki, Finland.
Abstract
Background: Both statins and PCSK9 inhibitors lower blood low-density lipoprotein cholesterol (LDL-C) levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these two lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial and compared the results with the effects of genetic inhibition of PCSK9, acting as a naturally occurring trial. Methods: 228 circulating metabolic measures were quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5,359 individuals (2,659 on treatment) in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial at 6-months post-randomization. The corresponding metabolic measures were analyzed in eight population cohorts (N=72,185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors. Results: Scaled to an equivalent lowering of LDL-C, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R 2=0.88). Alterations in lipoprotein lipid composition and fatty acid distribution were similar. However, discrepancies were observed for very-low-density lipoprotein (VLDL) lipid measures. For instance, genetic inhibition of PCSK9 had weaker effects on lowering of VLDL-cholesterol compared with statin therapy (54% vs. 77% reduction, relative to the lowering effect on LDL-C; P=2x10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no significant effects on amino acids, ketones, or a marker of inflammation (GlycA) whereas statin treatment weakly lowered GlycA levels. Conclusions: Genetic inhibition of PCSK9 had similar metabolic effects to statin therapy on detailed lipid and metabolite profiles. However, PCSK9 inhibitors are predicted to have weaker effects on VLDL lipids compared with statins for an equivalent lowering of LDL-C, which potentially translate into smaller reductions in cardiovascular disease risk.
Background: Both statins and PCSK9 inhibitors lower blood low-density lipoprotein cholesterol (LDL-C) levels to reduce risk of cardiovascular events. To assess potential differences between metabolic effects of these two lipid-lowering therapies, we performed detailed lipid and metabolite profiling of a large randomized statin trial and compared the results with the effects of genetic inhibition of PCSK9, acting as a naturally occurring trial. Methods: 228 circulating metabolic measures were quantified by nuclear magnetic resonance spectroscopy, including lipoprotein subclass concentrations and their lipid composition, fatty acids, and amino acids, for 5,359 individuals (2,659 on treatment) in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) trial at 6-months post-randomization. The corresponding metabolic measures were analyzed in eight population cohorts (N=72,185) using PCSK9 rs11591147 as an unconfounded proxy to mimic the therapeutic effects of PCSK9 inhibitors. Results: Scaled to an equivalent lowering of LDL-C, the effects of genetic inhibition of PCSK9 on 228 metabolic markers were generally consistent with those of statin therapy (R 2=0.88). Alterations in lipoprotein lipid composition and fatty acid distribution were similar. However, discrepancies were observed for very-low-density lipoprotein (VLDL) lipid measures. For instance, genetic inhibition of PCSK9 had weaker effects on lowering of VLDL-cholesterol compared with statin therapy (54% vs. 77% reduction, relative to the lowering effect on LDL-C; P=2x10-7 for heterogeneity). Genetic inhibition of PCSK9 showed no significant effects on amino acids, ketones, or a marker of inflammation (GlycA) whereas statin treatment weakly lowered GlycA levels. Conclusions: Genetic inhibition of PCSK9 had similar metabolic effects to statin therapy on detailed lipid and metabolite profiles. However, PCSK9 inhibitors are predicted to have weaker effects on VLDL lipids compared with statins for an equivalent lowering of LDL-C, which potentially translate into smaller reductions in cardiovascular disease risk.
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Authors: Nicolas Perrot; Vincenza Valerio; Donato Moschetta; S Matthijs Boekholdt; Christian Dina; Hao Yu Chen; Erik Abner; Andreas Martinsson; Hasanga D Manikpurage; Sidwell Rigade; Romain Capoulade; Elvira Mass; Marie-Annick Clavel; Thierry Le Tourneau; David Messika-Zeitoun; Nicholas J Wareham; James C Engert; Gianluca Polvani; Philippe Pibarot; Tõnu Esko; J Gustav Smith; Patrick Mathieu; George Thanassoulis; Jean-Jacques Schott; Yohan Bossé; Marina Camera; Sébastien Thériault; Paolo Poggio; Benoit J Arsenault Journal: JACC Basic Transl Sci Date: 2020-07-01