Albert Prats-Uribe1, Sergi Sayols-Baixeras2, Alba Fernández-Sanlés3, Isaac Subirana4, Robert Carreras-Torres5, Gemma Vilahur6, Fernando Civeira7, Jaume Marrugat8, Montserrat Fitó9, Álvaro Hernáez10, Roberto Elosua11. 1. Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Preventive Medicine and Public Health Unit, Parc de Salut Mar-Universitat Pompeu Fabra-ISGLOBAL, Barcelona, Spain; Centre for Statistics in Medicine, Botnar Research Centre, NDORMS, University of Oxford, Oxford, United Kingdom. Electronic address: albert.pratsu@gmail.com. 2. Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Campus del Mar, Universitat Pompeu Fabra, Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Molecular Epidemiology and Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden. Electronic address: ssayols@gmail.com. 3. Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Campus del Mar, Universitat Pompeu Fabra, Barcelona, Spain; MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom. Electronic address: alba.fernandez-sanles@bristol.ac.uk. 4. Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Consorcio CIBER, M.P. Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain. Electronic address: isubirana@imim.es. 5. Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Spain. Electronic address: rcarreras@idibell.cat. 6. Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular Program-ICCC, Research Institute-Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Barcelona, Spain. Electronic address: gvilahur@santpau.cat. 7. Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Lipid Unit, Hospital Universitario Miguel Servet, IIS Aragon, Zaragoza, Spain. Electronic address: civeira@unizar.es. 8. Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Girona Heart Registre Research Group (REGICOR), IMIM, Barcelona, Spain. Electronic address: jmarrugat@imim.es. 9. Cardiovascular Risk and Nutrition Research Group, IMIM, Barcelona, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain. Electronic address: mfito@imim.es. 10. Cardiovascular Risk and Nutrition Research Group, IMIM, Barcelona, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain; Cardiovascular Risk, Nutrition, and Aging Research Unit, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain; Blanquerna School of Life Sciences, Universitat Ramon Llull, Barcelona, Spain. Electronic address: alvaro.hernaez1@gmail.com. 11. Cardiovascular Epidemiology and Genetics Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Consorcio CIBER, M.P. Enfermedades Cardiovasculares (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Medicine Department, Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), Vic, Spain. Electronic address: relosua@imim.es.
Abstract
BACKGROUND: To assess whether genetically determined quantitative and qualitative HDL characteristics were independently associated with coronary artery disease (CAD). METHODS: We designed a two-sample multivariate Mendelian randomization study with available genome-wide association summary data. We identified genetic variants associated with HDL cholesterol and apolipoprotein A-I levels, HDL size, particle levels, and lipid content to define our genetic instrumental variables in one sample (Kettunen et al. study, n = 24,925) and analyzed their association with CAD risk in a different study (CARDIoGRAMplusC4D, n = 184,305). We validated these results by defining our genetic variables in another database (METSIM, n = 8372) and studied their relationship with CAD in the CARDIoGRAMplusC4D dataset. To estimate the effect size of the associations of interest adjusted for other lipoprotein traits and minimize potential pleiotropy, we used the Multi-trait-based Conditional & Joint analysis. RESULTS: Genetically determined HDL cholesterol and apolipoprotein A-I levels were not associated with CAD. HDL mean diameter (β = 0.27 [95%CI = 0.19; 0.35]), cholesterol levels in very large HDLs (β = 0.29 [95%CI = 0.17; 0.40]), and triglyceride content in very large HDLs (β = 0.14 [95%CI = 0.040; 0.25]) were directly associated with CAD risk, whereas the cholesterol content in medium-sized HDLs (β = -0.076 [95%CI = -0.10; -0.052]) was inversely related to this risk. These results were validated in the METSIM-CARDIoGRAMplusC4D data. CONCLUSIONS: Some qualitative HDL characteristics (related to size, particle distribution, and cholesterol and triglyceride content) are related to CAD risk while HDL cholesterol levels are not.
BACKGROUND: To assess whether genetically determined quantitative and qualitative HDL characteristics were independently associated with coronary artery disease (CAD). METHODS: We designed a two-sample multivariate Mendelian randomization study with available genome-wide association summary data. We identified genetic variants associated with HDL cholesterol and apolipoprotein A-I levels, HDL size, particle levels, and lipid content to define our genetic instrumental variables in one sample (Kettunen et al. study, n = 24,925) and analyzed their association with CAD risk in a different study (CARDIoGRAMplusC4D, n = 184,305). We validated these results by defining our genetic variables in another database (METSIM, n = 8372) and studied their relationship with CAD in the CARDIoGRAMplusC4D dataset. To estimate the effect size of the associations of interest adjusted for other lipoprotein traits and minimize potential pleiotropy, we used the Multi-trait-based Conditional & Joint analysis. RESULTS: Genetically determined HDL cholesterol and apolipoprotein A-I levels were not associated with CAD. HDL mean diameter (β = 0.27 [95%CI = 0.19; 0.35]), cholesterol levels in very large HDLs (β = 0.29 [95%CI = 0.17; 0.40]), and triglyceride content in very large HDLs (β = 0.14 [95%CI = 0.040; 0.25]) were directly associated with CAD risk, whereas the cholesterol content in medium-sized HDLs (β = -0.076 [95%CI = -0.10; -0.052]) was inversely related to this risk. These results were validated in the METSIM-CARDIoGRAMplusC4D data. CONCLUSIONS: Some qualitative HDL characteristics (related to size, particle distribution, and cholesterol and triglyceride content) are related to CAD risk while HDL cholesterol levels are not.
Authors: Elena Grao-Cruces; Lourdes M Varela; Maria E Martin; Beatriz Bermudez; Sergio Montserrat-de la Paz Journal: Nutrients Date: 2021-03-16 Impact factor: 5.717