Michael G Levin1,2,3, Verena Zuber4,5,6, Venexia M Walker7,8, Derek Klarin9,10, Julie Lynch11,12, Rainer Malik13, Aaron W Aday14, Leonardo Bottolo15,16, Aruna D Pradhan17,18, Martin Dichgans19,20, Kyong-Mi Chang2,3, Daniel J Rader2,21,22,23, Philip S Tsao24,25, Benjamin F Voight21,22,26,3,23, Dipender Gill27,28,29, Stephen Burgess4,30, Scott M Damrauer7,3. 1. Division of Cardiovascular Medicine (M.G.L.), University of Pennsylvania Perelman School of Medicine, Philadelphia. 2. Department of Medicine (M.G.L., K.-M.C., D.J.R.), University of Pennsylvania Perelman School of Medicine, Philadelphia. 3. Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA (M.G.L., K.-M.C., B.F.V., S.M.D.). 4. MRC Biostatistics Unit (V.Z., S.B.), School of Clinical Medicine, University of Cambridge, UK. 5. Department of Epidemiology and Biostatistics (V.Z.), Imperial College London, UK. 6. Dementia Research Institute (V.Z.), Imperial College London, UK. 7. Department of Surgery (V.M.W., S.M.D.), University of Pennsylvania Perelman School of Medicine, Philadelphia. 8. Medical Research Council Integrative Epidemiology Unit, University of Bristol, UK (V.M.W.). 9. Malcolm Randall VA Medical Center, Gainesville, FL (D.K.). 10. Department of Surgery, University of Florida, Gainesville (D.K.). 11. VA Informatics and Computing Infrastructure, Department of Veterans Affairs, Salt Lake City Health Care System, UT (J.L.). 12. University of Utah School of Medicine, Salt Lake City (J.L.). 13. Institute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-University, Munich, Germany (R.M.). 14. Vanderbilt Translational and Clinical Cardiovascular Research Center, Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN (A.W.A.). 15. Department of Medical Genetics (L.B.), School of Clinical Medicine, University of Cambridge, UK. 16. The Alan Turing Institute, London, UK (L.B.). 17. Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (A.D.P.). 18. Division of Cardiovascular Medicine, VA Boston Medical Center, MA (A.D.P.). 19. Institute for Stroke and Dementia Research, University Hospital of Ludwig-Maximilians-University, Munich, Germany (M.D.). 20. German Center for Neurodegenerative Diseases (DZNE), Munich, Germany (M.D.). 21. Institute for Translational Medicine and Therapeutics (D.J.R., B.F.V.), University of Pennsylvania Perelman School of Medicine, Philadelphia. 22. Department of Genetics (D.J.R., B.V.F.), University of Pennsylvania Perelman School of Medicine, Philadelphia. 23. Munich Cluster for Systems Neurology (SyNergy), Germany (D.J.R., B.F.V.). 24. Palo Alto VA Healthcare System, CA (P.S.T.). 25. Department of Medicine, Division of Cardiovascular Medicine, and Stanford Cardiovascular Institute, Stanford University, Palo Alto, CA (P.S.T.). 26. Department of Systems Pharmacology and Translational Therapeutics (B.V.F.), University of Pennsylvania Perelman School of Medicine, Philadelphia. 27. Department of Epidemiology and Biostatistics (D.G.), Imperial College London, UK. 28. Clinical Pharmacology and Therapeutics Section, Institute for Infection and Immunity, St. George's, University of London, UK (D.G.). 29. Novo Nordisk Research Centre Oxford, Old Road Campus, UK (D.G.). 30. BHF Cardiovascular Epidemiology Unit (S.B.), School of Clinical Medicine, University of Cambridge, UK.
Abstract
BACKGROUND: Lipoprotein-related traits have been consistently identified as risk factors for atherosclerotic cardiovascular disease, largely on the basis of studies of coronary artery disease (CAD). The relative contributions of specific lipoproteins to the risk of peripheral artery disease (PAD) have not been well defined. We leveraged large-scale genetic association data to investigate the effects of circulating lipoprotein-related traits on PAD risk. METHODS: Genome-wide association study summary statistics for circulating lipoprotein-related traits were used in the mendelian randomization bayesian model averaging framework to prioritize the most likely causal major lipoprotein and subfraction risk factors for PAD and CAD. Mendelian randomization was used to estimate the effect of apolipoprotein B (ApoB) lowering on PAD risk using gene regions proxying lipid-lowering drug targets. Genes relevant to prioritized lipoprotein subfractions were identified with transcriptome-wide association studies. RESULTS: ApoB was identified as the most likely causal lipoprotein-related risk factor for both PAD (marginal inclusion probability, 0.86; P=0.003) and CAD (marginal inclusion probability, 0.92; P=0.005). Genetic proxies for ApoB-lowering medications were associated with reduced risk of both PAD (odds ratio,0.87 per 1-SD decrease in ApoB [95% CI, 0.84-0.91]; P=9×10-10) and CAD (odds ratio,0.66 [95% CI, 0.63-0.69]; P=4×10-73), with a stronger predicted effect of ApoB lowering on CAD (ratio of effects, 3.09 [95% CI, 2.29-4.60]; P<1×10-6). Extra-small very-low-density lipoprotein particle concentration was identified as the most likely subfraction associated with PAD risk (marginal inclusion probability, 0.91; P=2.3×10-4), whereas large low-density lipoprotein particle concentration was the most likely subfraction associated with CAD risk (marginal inclusion probability, 0.95; P=0.011). Genes associated with extra-small very-low-density lipoprotein particle and large low-density lipoprotein particle concentration included canonical ApoB pathway components, although gene-specific effects were variable. Lipoprotein(a) was associated with increased risk of PAD independently of ApoB (odds ratio, 1.04 [95% CI, 1.03-1.04]; P=1.0×10-33). CONCLUSIONS: ApoB was prioritized as the major lipoprotein fraction causally responsible for both PAD and CAD risk. However, ApoB-lowering drug targets and ApoB-containing lipoprotein subfractions had diverse associations with atherosclerotic cardiovascular disease, and distinct subfraction-associated genes suggest possible differences in the role of lipoproteins in the pathogenesis of PAD and CAD.
BACKGROUND: Lipoprotein-related traits have been consistently identified as risk factors for atherosclerotic cardiovascular disease, largely on the basis of studies of coronary artery disease (CAD). The relative contributions of specific lipoproteins to the risk of peripheral artery disease (PAD) have not been well defined. We leveraged large-scale genetic association data to investigate the effects of circulating lipoprotein-related traits on PAD risk. METHODS: Genome-wide association study summary statistics for circulating lipoprotein-related traits were used in the mendelian randomization bayesian model averaging framework to prioritize the most likely causal major lipoprotein and subfraction risk factors for PAD and CAD. Mendelian randomization was used to estimate the effect of apolipoprotein B (ApoB) lowering on PAD risk using gene regions proxying lipid-lowering drug targets. Genes relevant to prioritized lipoprotein subfractions were identified with transcriptome-wide association studies. RESULTS: ApoB was identified as the most likely causal lipoprotein-related risk factor for both PAD (marginal inclusion probability, 0.86; P=0.003) and CAD (marginal inclusion probability, 0.92; P=0.005). Genetic proxies for ApoB-lowering medications were associated with reduced risk of both PAD (odds ratio,0.87 per 1-SD decrease in ApoB [95% CI, 0.84-0.91]; P=9×10-10) and CAD (odds ratio,0.66 [95% CI, 0.63-0.69]; P=4×10-73), with a stronger predicted effect of ApoB lowering on CAD (ratio of effects, 3.09 [95% CI, 2.29-4.60]; P<1×10-6). Extra-small very-low-density lipoprotein particle concentration was identified as the most likely subfraction associated with PAD risk (marginal inclusion probability, 0.91; P=2.3×10-4), whereas large low-density lipoprotein particle concentration was the most likely subfraction associated with CAD risk (marginal inclusion probability, 0.95; P=0.011). Genes associated with extra-small very-low-density lipoprotein particle and large low-density lipoprotein particle concentration included canonical ApoB pathway components, although gene-specific effects were variable. Lipoprotein(a) was associated with increased risk of PAD independently of ApoB (odds ratio, 1.04 [95% CI, 1.03-1.04]; P=1.0×10-33). CONCLUSIONS: ApoB was prioritized as the major lipoprotein fraction causally responsible for both PAD and CAD risk. However, ApoB-lowering drug targets and ApoB-containing lipoprotein subfractions had diverse associations with atherosclerotic cardiovascular disease, and distinct subfraction-associated genes suggest possible differences in the role of lipoproteins in the pathogenesis of PAD and CAD.
Authors: John Michael Gaziano; John Concato; Mary Brophy; Louis Fiore; Saiju Pyarajan; James Breeling; Stacey Whitbourne; Jennifer Deen; Colleen Shannon; Donald Humphries; Peter Guarino; Mihaela Aslan; Daniel Anderson; Rene LaFleur; Timothy Hammond; Kendra Schaa; Jennifer Moser; Grant Huang; Sumitra Muralidhar; Ronald Przygodzki; Timothy J O'Leary Journal: J Clin Epidemiol Date: 2015-10-09 Impact factor: 6.437
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Authors: Brian A Ference; John J P Kastelein; Kausik K Ray; Henry N Ginsberg; M John Chapman; Chris J Packard; Ulrich Laufs; Clare Oliver-Williams; Angela M Wood; Adam S Butterworth; Emanuele Di Angelantonio; John Danesh; Stephen J Nicholls; Deepak L Bhatt; Marc S Sabatine; Alberico L Catapano Journal: JAMA Date: 2019-01-29 Impact factor: 56.272
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