Background The 10-year Atherosclerotic Cardiovascular Disease (ASCVD) risk score is the standard approach to predict risk of incident cardiovascular events and recently, addition of CAD polygenic scores (PGSCAD) have been evaluated. Although age and sex strongly predict the risk of CAD, their interaction with genetic risk prediction has not been systematically examined. Objectives This study performed an in-depth evaluation of age and sex effects in genetic CAD risk prediction. Methods The population-based Norwegian HUNT2 cohort of 51,036 individuals was used as the primary dataset. Findings were replicated in the UK Biobank (372,410 individuals). Models for 10-year CAD risk were fitted using Cox proportional hazards and Harrells concordance index, sensitivity, and specificity were compared. Results Inclusion of age and sex interactions of PGSCAD to the prediction models increased C-index and sensitivity likely countering the observed survival bias in the baseline. The sensitivity for females was lower than males in all models including genetic information. The two-step approach identified a total of 82.6% of incident CAD cases (74.1% by ASCVD risk score and an additional 8.5% by the PGSCAD interaction model). Conclusion These findings highlight the importance and complexity of genetic risk in predicting CAD. There is a need for modeling age and sex-interactions terms with polygenic scores to optimize detection of individuals at high-risk, those who warrant preventive interventions. Sex-specific studies are needed to understand and estimate CAD risk with genetic information.

Clinicians have historically used family history and other risk prediction algorithms to guide patient care and preventive treatment such as statin therapeutics for coronary artery disease. As polygenic scores move towards clinical use, we have begun to consider the interplay of these scores with other predictors for optimal second generation risk prediction. Here, we assess the use of family history and polygenic scores as independent predictors of coronary artery disease and type 2 diabetes. We highlight considerations for use of family history as a predictor of these two diseases after evaluating their effectiveness in the Trøndelag Health Study and the UK Biobank. From these, we advocate for collection of high resolution family history variables in biobanks for future prediction models.

1Background: Thoracic aortic dissection is an emergent life-threatening condition. Routine 2 screening for genetic variants causing thoracic aortic dissection is not currently performed for 3 patients or their family members. 4 Methods:We performed whole exome sequencing of 240 patients with thoracic aortic dissection 5 (n=235) or rupture (n=5) and 258 controls matched for age, sex, and ancestry. Blinded to case-6 control status, we annotated variants in 11 genes for pathogenicity. 7Results: Twenty-four pathogenic variants in 6 genes (COL3A1, FBN1, LOX, PRKG1, SMAD3, 8 TGFBR2) were identified in 26 individuals, representing 10.8% of aortic cases and 0% of controls. 9Among dissection cases, we compared those with pathogenic variants to those without and found 10 that pathogenic variant carriers had significantly earlier onset of dissection (41 vs. 57 years), higher 11 rates of root aneurysm (54% vs. 30%), less hypertension (15% vs. 57%), lower rates of smoking 12 (19% vs. 45%), and greater incidence of aortic disease in family members. Multivariable logistic 13 regression showed significant risk factors associated with pathogenic variants are age <50 [odds 14 ratio (OR) = 5.5; 95% CI: 1.6-19.7], no history of hypertension (OR=5.6; 95% CI: 1.4-22.3) and 15 family history of aortic disease (mother: OR=5.7; 95% CI: 1.4-22.3, siblings: OR=5.1; 95% CI 16 1.1-23.9, children: OR=6.0; 95% CI: 1.4-26.7). 17 Conclusions: Clinical genetic testing of known hereditary thoracic aortic dissection genes should 18 be considered in patients with aortic dissection, followed by cascade screening of family 19 members, especially in patients with age-of-onset of aortic dissection <50 years old, family 20 history of aortic disease, and no history of hypertension. 21 22 23 Keywords: thoracic aortic dissection, aortic rupture, gene sequencing, precision health 24 Dianna M. Milewicz (Dianna.M.Milewicz@uth.tmc.edu) has no conflicts of interest to disclose. 1 Cristen J. Willer (cristen@med.umich.edu) has no conflicts of interest to disclose. 2 Bo Yang (boya@med.umich.edu) has no conflicts of interest to disclose. 3 4 AUTHORS 5