medRxiv. 2023 Nov 4:2023.11.03.23298055. doi: 10.1101/2023.11.03.23298055. Preprint.
IMPORTANCE: Earlier identification of high coronary artery disease (CAD) risk individuals may enable more effective prevention strategies. However, existing 10-year risk frameworks are ineffective at earlier identification. Understanding the variable importance of genomic and clinical factors across life stages may significantly improve lifelong CAD event prediction.
OBJECTIVE: To assess the time-varying significance of genomic and clinical risk factors in CAD risk estimation across various age groups.
DESIGN SETTING AND PARTICIPANTS: A longitudinal study was performed using data from two cohort studies: the Framingham Offspring Study (FOS) with 3,588 participants aged 19-57 years and the UK Biobank (UKB) with 327,837 participants aged 40-70 years. A total of 134,765 and 3,831,734 person-time years were observed in FOS and UKB, respectively.
MAIN OUTCOMES AND MEASURES: Hazard ratios (HR) for CAD were calculated for polygenic risk scores (PRS) and clinical risk factors at each age of enrollment. The relative importance of PRS and Pooled Cohort Equations (PCE) in predicting CAD events was also evaluated by age groups.
RESULTS: The importance of CAD PRS diminished over the life course, with an HR of 3.58 (95% CI 1.39-9.19) at age 19 in FOS and an HR of 1.51 (95% CI 1.48-1.54) by age 70 in UKB. Clinical risk factors exhibited similar age-dependent trends. PRS significantly outperformed PCE in identifying subsequent CAD events in the 40-45-year age group, with 3.2-fold more appropriately identified events. The mean age of CAD events occurred 1.8 years earlier for those at high genomic risk but 9.6 years later for those at high clinical risk (p<0.001). Overall, adding PRS improved the area under the receiving operating curve of the PCE by an average of +5.1% (95% CI 4.9-5.2%) across all age groups; among individuals <55 years, PRS augmented the AUC-ROC of the PCE by 6.5% (95% CI 5.5-7.5%, p<0.001).
CONCLUSIONS AND RELEVANCE: Genomic and clinical risk factors for CAD display time-varying importance across the lifespan. The study underscores the added value of CAD PRS, particularly among individuals younger than 55 years, for enhancing early risk prediction and prevention strategies.
KEY POINTS QUESTION: How do genomic and clinical risk factors contribute to coronary artery disease (CAD) risk across a broad age range?
FINDINGS: This longitudinal observational study across two cohorts found that both genomic and clinical risk factors exhibit age-dependent significance for CAD risk. Polygenic risk scores (PRS) are most informative for individuals younger than 55 years, improving the predictive accuracy of current risk equations for these individuals.
MEANING: The study emphasizes the need to incorporate the dynamic effects of cardiovascular risk factors, particularly genomic risk, for more accurate early-life risk prediction and efficient CAD prevention strategies.