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Genetic Risk of Coronary Artery Disease, Features of Atherosclerosis, and Coronary Plaque Burden

Morten Krogh Christiansen, Louise Nissen, Simon Winther and 10 more

Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease · 2020

doi:10.1161/jaha.119.014795 (opens in a new tab)

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Abstract

Background Polygenic risk scores (PRSs) based on risk variants from genome‐wide association studies predict coronary artery disease (CAD) risk. However, it is unknown whether the PRS is associated with specific CAD characteristics. Methods and Results We consecutively included 1645 patients with suspected stable CAD undergoing coronary computed tomography angiography. A multilocus PRS was calculated as the weighted sum of CAD risk variants. Plaques were evaluated using an 18‐segment model and characterized by stenosis severity and composition (soft [0%‐19% calcified], mixed‐soft [20%‐49% calcified], mixed‐calcified [50%‐79% calcified], or calcified [≥80% calcified]). Coronary artery calcium score and segment stenosis score were used to characterize plaque burden. For each standard deviation increase in the PRS, coronary artery calcium score increased by 78% (P=4.1e‐26) and segment stenosis score increased by 16% (P=2.4e‐29) in the fully adjusted model. The PRS was associated with a higher prevalence of obstructive plaques (odds ratio [OR]: 1.78, P=5.6e‐16), calcified (OR: 1.69, P=6.5e‐17), mixed‐calcified (OR: 1.67, P=7.3e‐9), mixed‐soft (OR: 1.45, P=1.6e‐6), and soft plaques (OR: 1.49, P=2.5e‐6), and a higher prevalence of plaque in each coronary vessel (all P<1.0e‐4). However, when analyzing data on a plaque level (3007 segments with plaque in 849 patients) the PRS was not associated with stenosis severity, plaque composition, or localization (all P>0.05). Conclusions Our results suggest that polygenic risk based on large genome‐wide association studies increases CAD risk through an increased burden of coronary atherosclerosis rather than promoting specific plaque features. Clinical Trial Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT02264717.

Abstract licence: CC BY-NC

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