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21 March 2016Genome-wide association study of coronary and aortic calcification in lung cancer screening CT
Arterial calcification has been related to cardiovascular disease (CVD) and osteoporosis. However, little is known about the role of genetics and exact pathways leading to arterial calcification and its relation to bone density changes indicating osteoporosis. In this study, we conducted a genome-wide association study of arterial calcification burden, followed by a look-up of known single nucleotide polymorphisms (SNPs) for coronary artery disease (CAD) and myocardial infarction (MI), and bone mineral density (BMD) to test for a shared genetic basis between the traits. The study included a subcohort of the Dutch-Belgian lung cancer screening trial comprised of 2,561 participants. Participants underwent baseline CT screening in one of two hospitals participating in the trial. Low-dose chest CT images were acquired without contrast enhancement and without ECG-synchronization. In these images coronary and aortic calcifications were identified automatically. Subsequently, the detected calcifications were quantified using coronary artery calcium Agatston and volume scores. Genotype data was available for these participants. A genome-wide association study was conducted on 10,220,814 SNPs using a linear regression model. To reduce multiple testing burden, known CAD/MI and BMD SNPs were specifically tested (45 SNPs from the CARDIoGRAMplusC4D consortium and 60 SNPS from the GEFOS consortium). No novel significant SNPs were found. Significant enrichment for CAD/MI SNPs was observed in testing Agatston and coronary artery calcium volume scores. Moreover, a significant enrichment of BMD SNPs was shown in aortic calcium volume scores. This may indicate genetic relation of BMD SNPs and arterial calcification burden.
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Bob D. de Vos, Jessica van Setten, Pim A. de Jong, Willem P. Mali, Matthijs Oudkerk, Max A. Viergever, Ivana Išgum, "Genome-wide association study of coronary and aortic calcification in lung cancer screening CT," Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97841L (21 March 2016); https://doi.org/10.1117/12.2217024