Jessica van Setten1, Ivana Išgum1, Sonali Pechlivanis1, Vinicius Tragante1, Pim A de Jong1, Joanna Smolonska1, Mathieu Platteel1, Per Hoffmann1, Matthijs Oudkerk1, Harry J de Koning1, Markus M Nöthen1, Susanne Moebus1, Raimund Erbel1, Karl-Heinz Jöckel1, Max A Viergever1, Willem P Th M Mali1, Paul I W de Bakker2. 1. From the Department of Medical Genetics, Center for Molecular Medicine (J.v.S., P.I.W.d.B.), Image Sciences Institute (I.I., M.A.V.), Department of Cardiology (V.T.); Department of Radiology (P.A.d.J.), Department of Epidemiology, Julius Center for Health Sciences and Primary Care (P.I.W.d.B.), University Medical Center Utrecht, Utrecht, The Netherlands; Institute for Medical Informatics, Biometry and Epidemiology (S.P., S.M.), Clinic of Cardiology, West-German Heart Centre (R.E.), University Hospital Essen, Essen, Germany; Department of Genetics (J.S., M.P.), Department of Epidemiology (J.S.), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; Institute of Human Genetics (P.F., M.M.N.), Department of Genomics, Life and Brain Center (P.F., M.M.N.), University of Bonn, Bonn, Germany; Division of Medical Genetics, University Hospital and Department of Biomedicine, University of Basel, Basel, Switzerland (P.F.); Department of Radiology-Radiodiagnostics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (M.O.); and Department of Public Health, Erasmus Medical Center, Rotterdam, The Netherlands (H.J.d.K.). 2. From the Department of Medical Genetics, Center for Molecular Medicine (J.v.S., P.I.W.d.B.), Image Sciences Institute (I.I., M.A.V.), Department of Cardiology (V.T.); Department of Radiology (P.A.d.J.), Department of Epidemiology, Julius Center for Health Sciences and Primary Care (P.I.W.d.B.), University Medical Center Utrecht, Utrecht, The Netherlands; Institute for Medical Informatics, Biometry and Epidemiology (S.P., S.M.), Clinic of Cardiology, West-German Heart Centre (R.E.), University Hospital Essen, Essen, Germany; Department of Genetics (J.S., M.P.), Department of Epidemiology (J.S.), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; Institute of Human Genetics (P.F., M.M.N.), Department of Genomics, Life and Brain Center (P.F., M.M.N.), University of Bonn, Bonn, Germany; Division of Medical Genetics, University Hospital and Department of Biomedicine, University of Basel, Basel, Switzerland (P.F.); Department of Radiology-Radiodiagnostics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (M.O.); and Department of Public Health, Erasmus Medical Center, Rotterdam, The Netherlands (H.J.d.K.). pdebakker@umcutrecht.nl.
Abstract
BACKGROUND: Coronary artery calcification (CAC) is widely regarded as a cumulative lifetime measure of atherosclerosis, but it remains unclear what is the relationship between calcification and traditional risk factors for coronary artery disease (CAD) and myocardial infarction (MI). This study characterizes the genetic architecture of CAC by evaluating the overall impact of common alleles associated with CAD/MI and its traditional risk factors. METHODS AND RESULTS: On the basis of summary-association results from the CARDIoGRAMplusC4D study of CAD/MI, we calculated polygenic risk scores in 2599 participants of the Dutch and Belgian Lung Cancer Screening (NELSON) trial, in whom quantitative CAC levels (Agatston scores) were determined from chest computerized tomographic imaging data. The most significant polygenic model explained ≈14% of the observed CAC variance (P=1.6×10(-11)), which points to a residual effect because of many as yet unknown loci that overlap between CAD/MI and CAC. In addition, we constructed risk scores based on published single-nucleotide polymorphism associations for traditional cardiovascular risk factors and tested these scores for association with CAC. We found nominally significant associations for genetic risk scores of low-density lipoprotein-cholesterol, total cholesterol, and body mass index, which were successfully replicated in 2182 individuals of the Heinz Nixdorf Recall Study. CONCLUSIONS: Pervasive polygenic sharing between CAC and CAD/MI suggests that a substantial fraction of the heritable risk for CAD/MI is mediated through arterial calcification. We also provide evidence that genetic variants associated with serum lipid levels and body mass index influence CAC levels.
BACKGROUND:Coronary artery calcification (CAC) is widely regarded as a cumulative lifetime measure of atherosclerosis, but it remains unclear what is the relationship between calcification and traditional risk factors for coronary artery disease (CAD) and myocardial infarction (MI). This study characterizes the genetic architecture of CAC by evaluating the overall impact of common alleles associated with CAD/MI and its traditional risk factors. METHODS AND RESULTS: On the basis of summary-association results from the CARDIoGRAMplusC4D study of CAD/MI, we calculated polygenic risk scores in 2599 participants of the Dutch and Belgian Lung Cancer Screening (NELSON) trial, in whom quantitative CAC levels (Agatston scores) were determined from chest computerized tomographic imaging data. The most significant polygenic model explained ≈14% of the observed CAC variance (P=1.6×10(-11)), which points to a residual effect because of many as yet unknown loci that overlap between CAD/MI and CAC. In addition, we constructed risk scores based on published single-nucleotide polymorphism associations for traditional cardiovascular risk factors and tested these scores for association with CAC. We found nominally significant associations for genetic risk scores of low-density lipoprotein-cholesterol, total cholesterol, and body mass index, which were successfully replicated in 2182 individuals of the Heinz Nixdorf Recall Study. CONCLUSIONS: Pervasive polygenic sharing between CAC and CAD/MI suggests that a substantial fraction of the heritable risk for CAD/MI is mediated through arterial calcification. We also provide evidence that genetic variants associated with serum lipid levels and body mass index influence CAC levels.
Authors: Iván Ferraz-Amaro; Robert Winchester; Peter K Gregersen; Richard J Reynolds; Mary Chester Wasko; Anette Oeser; Cecilia P Chung; C Michael Stein; Jon T Giles; Joan M Bathon Journal: Arthritis Rheumatol Date: 2017-03 Impact factor: 10.995
Authors: Luis Fernando Escobar Guzman; Cristian Andres Escobar Guzman; Neuza Helena Moreira Lopes Journal: Cardiol Res Pract Date: 2020-04-14 Impact factor: 1.866
Authors: Sander W van der Laan; Tove Fall; Aicha Soumaré; Alexander Teumer; Sanaz Sedaghat; Jens Baumert; Delilah Zabaneh; Jessica van Setten; Ivana Isgum; Tessel E Galesloot; Johannes Arpegård; Philippe Amouyel; Stella Trompet; Melanie Waldenberger; Marcus Dörr; Patrik K Magnusson; Vilmantas Giedraitis; Anders Larsson; Andrew P Morris; Janine F Felix; Alanna C Morrison; Nora Franceschini; Joshua C Bis; Maryam Kavousi; Christopher O'Donnell; Fotios Drenos; Vinicius Tragante; Patricia B Munroe; Rainer Malik; Martin Dichgans; Bradford B Worrall; Jeanette Erdmann; Christopher P Nelson; Nilesh J Samani; Heribert Schunkert; Jonathan Marchini; Riyaz S Patel; Aroon D Hingorani; Lars Lind; Nancy L Pedersen; Jacqueline de Graaf; Lambertus A L M Kiemeney; Sebastian E Baumeister; Oscar H Franco; Albert Hofman; André G Uitterlinden; Wolfgang Koenig; Christa Meisinger; Annette Peters; Barbara Thorand; J Wouter Jukema; Bjørn Odvar Eriksen; Ingrid Toft; Tom Wilsgaard; N Charlotte Onland-Moret; Yvonne T van der Schouw; Stéphanie Debette; Meena Kumari; Per Svensson; Pim van der Harst; Mika Kivimaki; Brendan J Keating; Naveed Sattar; Abbas Dehghan; Alex P Reiner; Erik Ingelsson; Hester M den Ruijter; Paul I W de Bakker; Gerard Pasterkamp; Johan Ärnlöv; Michael V Holmes; Folkert W Asselbergs Journal: J Am Coll Cardiol Date: 2016-08-30 Impact factor: 24.094