Sonali Pechlivanis1, Susanne Moebus1,2, Nils Lehmann1, Raimund Erbel1, Amir A Mahabadi3, Per Hoffmann4,5, Karl-Heinz Jöckel1, Markus M Nöthen4, Hagen S Bachmann6. 1. Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Duisburg-Essen, Essen, Germany. 2. Centre for Urban Epidemiology, University Hospital Essen, Essen, Germany. 3. Department of Cardiology and Vascular Medicine, West German Heart and Vascular Center, University Hospital Essen, Essen, Germany. 4. Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany. 5. Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland. 6. Institute of Pharmacology and Toxicology, Centre for Biomedical Education and Research, Witten/Herdecke University, Witten, Germany.
Abstract
BACKGROUND: Atherosclerosis is the primary cause of coronary artery disease (CAD). Several observational studies have examined the association of traditional CAD risk factors with the progression of coronary artery calcification (CAC). In our study we investigated the effect of 11 different genetic risk scores associated with CAD and CAD risk factors on the progression of CAC. METHODS AND RESULTS: We included 3097 participants from the Heinz Nixdorf Recall study who had available CAC measurements at baseline (CACb) and at the 5-year follow-up (CAC5y). A weighted genetic risk score for CAD and each of the CAD-associated risk factors was constructed. Multiple regression analyses were applied to i) the difference between the observed log(CAC5y+1) (log(obs)) and expected log(CAC5y+1) (log(exp)) at the 5-year follow-up following the individual's log(CACb+1) percentile for the time between scans (log(obs)-log(exp)) and ii) the 5-year CAC progression, defined as 5*(log(CAC5y+1)-log(CACb+1))/time between the scans, adjusted for age, sex, and log(CACb+1) as well as for risk factors. The median percent deviation from the expected (CAC5y+1) and the 5-year progression of (CAC+1) in our study were 0 (first quartile: Q1; third quartile: Q3: -0.32; 0.48) and 45.4% (0%; 171.0%) respectively. In the age-, sex- and log(CACb+1)-adjusted model, the per-standard deviation (SD) increase in CAD genetic risk score was associated with the percent deviation from the expected (CAC5y+1) (9.7% (95% confidence interval: 5.2%; 14.5%), p = 1.6x10-5) and the 5-year progression of CAC (7.1% (3.0%; 11.4%), p = 0.0005). The CAD genetic risk score explains an additional 0.6% of the observed phenotypic variance for "log(obs)-log(exp)" and 0.4% for 5-year progression of CAC. Additionally, the per-SD increase in the CAC genetic risk score was associated with the percent deviation from the expected (CAC5y+1) (6.2% (1.9%; 10.8%, p = 0.005)) explaining an additional 0.2% of the observed phenotypic variance. However, the per-SD increase in the CAC genetic risk score was not associated with the 5-year progression of CAC (4.4% (0.4%; 8.5%), p = 0.03) after multiple testing. Adjusting for risk factors did not change the results. None of the other genetic risk scores showed an association with the percent deviation from the expected (CAC5y+1) or with the 5-year progression of CAC. CONCLUSIONS: The association of the CAC genetic risk score and the CAD genetic risk score provides evidence that genetic determinants for CAC and CAD influence the progression of CAC.
BACKGROUND:Atherosclerosis is the primary cause of coronary artery disease (CAD). Several observational studies have examined the association of traditional CAD risk factors with the progression of coronary artery calcification (CAC). In our study we investigated the effect of 11 different genetic risk scores associated with CAD and CAD risk factors on the progression of CAC. METHODS AND RESULTS: We included 3097 participants from the Heinz Nixdorf Recall study who had available CAC measurements at baseline (CACb) and at the 5-year follow-up (CAC5y). A weighted genetic risk score for CAD and each of the CAD-associated risk factors was constructed. Multiple regression analyses were applied to i) the difference between the observed log(CAC5y+1) (log(obs)) and expected log(CAC5y+1) (log(exp)) at the 5-year follow-up following the individual's log(CACb+1) percentile for the time between scans (log(obs)-log(exp)) and ii) the 5-year CAC progression, defined as 5*(log(CAC5y+1)-log(CACb+1))/time between the scans, adjusted for age, sex, and log(CACb+1) as well as for risk factors. The median percent deviation from the expected (CAC5y+1) and the 5-year progression of (CAC+1) in our study were 0 (first quartile: Q1; third quartile: Q3: -0.32; 0.48) and 45.4% (0%; 171.0%) respectively. In the age-, sex- and log(CACb+1)-adjusted model, the per-standard deviation (SD) increase in CAD genetic risk score was associated with the percent deviation from the expected (CAC5y+1) (9.7% (95% confidence interval: 5.2%; 14.5%), p = 1.6x10-5) and the 5-year progression of CAC (7.1% (3.0%; 11.4%), p = 0.0005). The CAD genetic risk score explains an additional 0.6% of the observed phenotypic variance for "log(obs)-log(exp)" and 0.4% for 5-year progression of CAC. Additionally, the per-SD increase in the CAC genetic risk score was associated with the percent deviation from the expected (CAC5y+1) (6.2% (1.9%; 10.8%, p = 0.005)) explaining an additional 0.2% of the observed phenotypic variance. However, the per-SD increase in the CAC genetic risk score was not associated with the 5-year progression of CAC (4.4% (0.4%; 8.5%), p = 0.03) after multiple testing. Adjusting for risk factors did not change the results. None of the other genetic risk scores showed an association with the percent deviation from the expected (CAC5y+1) or with the 5-year progression of CAC. CONCLUSIONS: The association of the CAC genetic risk score and the CAD genetic risk score provides evidence that genetic determinants for CAC and CAD influence the progression of CAC.
Authors: Ji Sun Nam; Min Kyung Kim; Joo Young Nam; Kahui Park; Shinae Kang; Chul Woo Ahn; Jong Suk Park Journal: Lipids Health Dis Date: 2020-07-02 Impact factor: 3.876
Authors: Neda M Bogari; Ashwag Aljohani; Anas Dannoun; Osama Elkhateeb; Masimo Porqueddu; Amr A Amin; Dema N Bogari; Mohiuddin M Taher; Faruk Buba; Reem M Allam; Mustafa N Bogari; Francesco Alamanni Journal: Saudi J Biol Sci Date: 2020-06-24 Impact factor: 4.219