Download PDF
Thromb Haemost 2022; 122(08): 1296-1303
DOI: 10.1055/a-1711-0946
Coagulation and Fibrinolysis

Exploring Pleiotropic Effects of Lipid Modifiers and Targets on Measures of the Coagulation System with Genetics

C. Mary Schooling
1   Division of Epidemiology and Biostatistics, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
2   Environmental, Occupational, and Geospatial Health Sciences, Graduate School of Public Health and Health Policy, City University of New York, New York, United States
,
Shiu Lun Au Yeung
1   Division of Epidemiology and Biostatistics, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
,
Jie V. Zhao
1   Division of Epidemiology and Biostatistics, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
› Author Affiliations Funding This study had no funding.
› Further Information
    Permissions and Reprints

Abstract

Background Statins have long been suspected to have pleiotropic effects via thrombotic factors. Randomized controlled trials are too limited to be definitive. We examined the associations of genetically mimicking effects of statins, PCSK9 inhibitors, and alternative lipid targets (in genes LDLR, APOC3, and LPL) on key indicators of coagulation system function, i.e., prothrombin time (PT) and activated partial thromboplastin time (aPTT).

Methods We assessed the effect of established genetic mimics of effects of lipid modifiers and alternative lipid treatment targets on PT (n = 58,110) and aPTT (n = 37,767), all transformed to z-scores, using Mendelian randomization taking advantage of Biobank Japan. Ischemic heart disease (IHD) was a control outcome.

Results Genetically mimicked effects of statins increased PT by 0.31 standard deviation (SD) per SD increase in low-density lipoprotein (95% confidence interval [CI]: 0.10–0.51) based on rs12916 but did not affect aPTT. Genetically mimicking effects of targeting LDLR increased PT based on rs688 (0.33 SD per SD increase in triglyceride, 95% CI: 0.03–0.63) but did not affect aPTT. Genetically mimicking effects of PCSK9 inhibitors or targeting APOC3 or LPL had no effect on PT or aPTT. Genetically mimicking effects of statins, PCSK9 inhibitors, and alternative lipid targets reduced risk of IHD in Biobank Japan.

Conclusion Statins, and possibly targeting LDLR, may also act via a coagulation cascade factor, likely specific to the extrinsic or common pathway. Further elucidation of the mechanistic pathway may facilitate development of new interventions and inform use of statins particularly in relation to use of other anticoagulants.

Keywords

lipid modifiers - statins - Mendelian randomization - prothrombin time - activated partial thromboplastin time - platelets

Note

This study only uses publicly available summary data. This study only uses publicly available R packages to conduct the analysis. The code used to arrange the data for analysis is available on request.


Author Contributions

C.M.S. designed and implemented the study. S.L.A.Y. and J.V.Z. reviewed the first draft and contributed to the intellectual content and approved the final version.


Supplementary Material



Publication History

Received: 05 December 2020

Accepted: 30 November 2021

Accepted Manuscript online:
01 December 2021

Article published online:
20 January 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Ip CK, Jin DM, Gao JJ. et al. Effects of add-on lipid-modifying therapy on top of background statin treatment on major cardiovascular events: a meta-analysis of randomized controlled trials. Int J Cardiol 2015; 191: 138-148
    CrossrefPubMedGoogle Scholar
  • 2 Rosenson RS, Tangney CC. Antiatherothrombotic properties of statins: implications for cardiovascular event reduction. JAMA 1998; 279 (20) 1643-1650
    CrossrefPubMedGoogle Scholar
  • 3 Mitropoulos KA, Armitage JM, Collins R. et al; The Oxford Cholesterol Study Group. Randomized placebo-controlled study of the effects of simvastatin on haemostatic variables, lipoproteins and free fatty acids. Eur Heart J 1997; 18 (02) 235-241
    CrossrefPubMedGoogle Scholar
  • 4 Lowe G, Rumley A, Norrie J. et al. Blood rheology, cardiovascular risk factors, and cardiovascular disease: the West of Scotland Coronary Prevention Study. Thromb Haemost 2000; 84 (04) 553-558
    PubMedGoogle Scholar
  • 5 Shaw SM, Fildes JE, Yonan N, Williams SG. Pleiotropic effects and cholesterol-lowering therapy. Cardiology 2009; 112 (01) 4-12
    CrossrefPubMedGoogle Scholar
  • 6 An K, Huang R, Tian S. et al. Statins significantly reduce mortality in patients receiving clopidogrel without affecting platelet activation and aggregation: a systematic review and meta-analysis. Lipids Health Dis 2019; 18 (01) 121
    CrossrefPubMedGoogle Scholar
  • 7 Macchia A, Laffaye N, Comignani PD. et al. Statins but not aspirin reduce thrombotic risk assessed by thrombin generation in diabetic patients without cardiovascular events: the RATIONAL trial. PLoS One 2012; 7 (03) e32894
    CrossrefPubMedGoogle Scholar
  • 8 Mobarrez F, He S, Bröijersen A. et al. Atorvastatin reduces thrombin generation and expression of tissue factor, P-selectin and GPIIIa on platelet-derived microparticles in patients with peripheral arterial occlusive disease. Thromb Haemost 2011; 106 (02) 344-352
    PubMedGoogle Scholar
  • 9 Tehrani S, Mobarrez F, Antovic A. et al. Atorvastatin has antithrombotic effects in patients with type 1 diabetes and dyslipidemia. Thromb Res 2010; 126 (03) e225-e231
    CrossrefPubMedGoogle Scholar
  • 10 Koh KK, Quon MJ, Han SH, Ahn JY, Lee Y, Shin EK. Combined therapy with ramipril and simvastatin has beneficial additive effects on tissue factor activity and prothrombin fragment 1+2 in patients with type 2 diabetes. Atherosclerosis 2007; 194 (01) 230-237
    CrossrefPubMedGoogle Scholar
  • 11 Bartok A, Steiner S, Seidinger D. et al. Atorvastatin reduces thrombin generation after percutaneous coronary intervention independent of soluble tissue factor. Thromb Res 2005; 115 (06) 469-474
    CrossrefPubMedGoogle Scholar
  • 12 Orsi FA, Biedermann JS, Kruip MJHA. et al. Rosuvastatin use reduces thrombin generation potential in patients with venous thromboembolism: a randomized controlled trial. J Thromb Haemost 2019; 17 (02) 319-328
    CrossrefPubMedGoogle Scholar
  • 13 Schol-Gelok S, de Maat MPM, Biedermann JS. et al. Rosuvastatin use increases plasma fibrinolytic potential: a randomised clinical trial. Br J Haematol 2020; 190 (06) 916-922
    CrossrefPubMedGoogle Scholar
  • 14 Wang L, Rockwood J, Zak D, Devaraj S, Jialal I. Simvastatin reduces circulating plasminogen activator inhibitor 1 activity in volunteers with the metabolic syndrome. Metab Syndr Relat Disord 2008; 6 (02) 149-152
    CrossrefPubMedGoogle Scholar
  • 15 Krysiak R, Okopien B. Effect of simvastatin on hemostasis in patients with isolated hypertriglyceridemia. Pharmacology 2013; 92 (3–4): 187-190
    CrossrefPubMedGoogle Scholar
  • 16 Gill D, Georgakis MK, Walker VM. et al. Mendelian randomization for studying the effects of perturbing drug targets. Wellcome Open Res 2021; 6: 16
    CrossrefPubMedGoogle Scholar
  • 17 Lin L, Zhao L, Gao N. et al. From multi-target anticoagulants to DOACs, and intrinsic coagulation factor inhibitors. Blood Rev 2020; 39: 100615
    CrossrefPubMedGoogle Scholar
  • 18 Rodriguez BAT, Bhan A, Beswick A. et al; FinnGen Study. A platelet function modulator of thrombin activation is causally linked to cardiovascular disease and affects PAR4 receptor signaling. Am J Hum Genet 2020; 107 (02) 211-221
    CrossrefPubMedGoogle Scholar
  • 19 Keech A, Collins R, MacMahon S. et al. Three-year follow-up of the Oxford Cholesterol Study: assessment of the efficacy and safety of simvastatin in preparation for a large mortality study. Eur Heart J 1994; 15 (02) 255-269
    CrossrefPubMedGoogle Scholar
  • 20 Gill D, Monori G, Georgakis MK, Tzoulaki I, Laffan M. Genetically determined platelet count and risk of cardiovascular disease. Arterioscler Thromb Vasc Biol 2018; 38 (12) 2862-2869
    CrossrefPubMedGoogle Scholar
  • 21 Schooling CM, Zhao JV, Au Yeung SL, Leung GM. Investigating pleiotropic effects of statins on ischemic heart disease in the UK Biobank using Mendelian randomisation. eLife 2020; 9: 9
    CrossrefPubMedGoogle Scholar
  • 22 Kanai M, Akiyama M, Takahashi A. et al. Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases. Nat Genet 2018; 50 (03) 390-400
    CrossrefPubMedGoogle Scholar
  • 23 Nagai A, Hirata M, Kamatani Y. et al; BioBank Japan Cooperative Hospital Group. Overview of the BioBank Japan Project: study design and profile. J Epidemiol 2017; 27 (3S): S2-S8
    CrossrefPubMedGoogle Scholar
  • 24 Terao C, Suzuki A, Momozawa Y. et al. Chromosomal alterations among age-related haematopoietic clones in Japan. Nature 2020; 584 (7819): 130-135
    CrossrefPubMedGoogle Scholar
  • 25 Ishigaki K, Akiyama M, Kanai M. et al. Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases. Nat Genet 2020; 52 (07) 669-679
    CrossrefPubMedGoogle Scholar
  • 26 Ference BA, Ray KK, Catapano AL. et al. Mendelian randomization study of ACLY and cardiovascular disease. N Engl J Med 2019; 380 (11) 1033-1042
    CrossrefPubMedGoogle Scholar
  • 27 Carter P, Vithayathil M, Kar S. et al. Predicting the effect of statins on cancer risk using genetic variants from a Mendelian randomization study in the UK Biobank. eLife 2020; 9: 9
    CrossrefPubMedGoogle Scholar
  • 28 McCaw ZR, Lane JM, Saxena R, Redline S, Lin X. Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies. Biometrics 2020; 76 (04) 1262-1272
    CrossrefPubMedGoogle Scholar
  • 29 Bowden J, Del Greco M F, Minelli C, Davey Smith G, Sheehan NA, Thompson JR. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic. Int J Epidemiol 2016; 45 (06) 1961-1974
    PubMedGoogle Scholar
  • 30 Freeman G, Cowling BJ, Schooling CM. Power and sample size calculations for Mendelian randomization studies using one genetic instrument. Int J Epidemiol 2013; 42 (04) 1157-1163
    CrossrefPubMedGoogle Scholar
  • 31 Hernán MA, Sauer BC, Hernández-Díaz S, Platt R, Shrier I. Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses. J Clin Epidemiol 2016; 79: 70-75
    CrossrefPubMedGoogle Scholar
  • 32 Minelli C, Del Greco M F, van der Plaat DA, Bowden J, Sheehan NA, Thompson J. The use of two-sample methods for Mendelian randomization analyses on single large datasets. Int J Epidemiol 2021; 50 (05) 1651-1659
    CrossrefPubMedGoogle Scholar
  • 33 Willer CJ, Schmidt EM, Sengupta S. et al; Global Lipids Genetics Consortium. Discovery and refinement of loci associated with lipid levels. Nat Genet 2013; 45 (11) 1274-1283
    CrossrefPubMedGoogle Scholar
  • 34 Bowden J, Del Greco M F, Minelli C. et al. Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption. Int J Epidemiol 2019; 48 (03) 728-742
    CrossrefPubMedGoogle Scholar
  • 35 Lou XY, Qin CZ, Bao MH. et al. Analysis of Niemann-Pick C1-like 1 (NPC1L1) genetic polymorphisms and haplotypes in Chinese Han population. Pharmazie 2015; 70 (09) 581-585
    PubMedGoogle Scholar
  • 36 Kashiwabara Y, Kobayashi Y, Koba S. et al. Gene polymorphism and frequencies of the NPC1L1 gene (rs2072183, rs217434 and rs217428) in Japanese patients with dyslipidemia. J Clin Pharm Ther 2014; 39 (05) 551-554
    CrossrefPubMedGoogle Scholar
  • 37 O'Donnell JS, O'Sullivan JM, Preston RJS. Advances in understanding the molecular mechanisms that maintain normal haemostasis. Br J Haematol 2019; 186 (01) 24-36
    CrossrefPubMedGoogle Scholar
  • 38 Katsiki N, Reiner Ž, Tedeschi Reiner E. et al. Improvement of endothelial function by pitavastatin: a meta-analysis. Expert Opin Pharmacother 2018; 19 (03) 279-286
    CrossrefPubMedGoogle Scholar
  • 39 Krysiak R, Zmuda W, Okopień B. The effect of ezetimibe and simvastatin on hemostasis in patients with isolated hypercholesterolemia. Fundam Clin Pharmacol 2012; 26 (03) 424-431
    CrossrefPubMedGoogle Scholar
  • 40 Gagliano-Jucá T, Pencina KM, Guo W. et al. Differential effects of testosterone on circulating neutrophils, monocytes, and platelets in men: findings from two trials. Andrology 2020; 8 (05) 1324-1331
    CrossrefPubMedGoogle Scholar