Synergy among Genes and Genes-Environment on Coronary Artery Disease Risk and Prognosis

Author(s): Maria Isabel Mendonça, Marina Santos, Margarida Temtem, Débora Sá, Francisco Sousa, Eva Henriques, Sónia Freitas, Sofia Borges, Mariana Rodrigues, Graça Guerra, António Drumond, Ana Célia Sousa, Roberto Palma Reis

Introduction: Genetic and environmental factors contribute to predisposition to cardiovascular disease (CVD). Complex pathophysiological processes that may modulate this effect are unknown.

Objective: Evaluate whether genetic and environmental interactions may confer CAD susceptibility and assess CAD recurrence among patients prospectively followed up. Methods: A case-control study including 3161 participants, 1724 CAD patients (78.7% male) and 1437 controls (76.3% male) were followed prospectively (5.6±4.5 years). We evaluated the gene-gene interplay of 33 SNPs associated with CAD using the Multifactor Dimensionality Reduction (MDR) to estimate the best gene-gene model for CAD risk. Multivariate regression analysis confirmed the MDR method and evaluated the environmental impact on genetic risk. Kaplan-Meier assessed the survival curves, and Cox proportional regression analysis was performed with a hazard ratio (HR) for recurrent events.

Results: After MDR, the allelic interaction between TCF21 rs12190287 (GC) and APOE rs7412/rs429358 (ε3/ε4, ε4/ε4) was the best model with the highest likelihood for CAD, confirmed by the classic logistic regression (OR=1.99, 95%CI 1.39–2.87; p<0.0001). Additionally, the genetic interaction with environmental factors synergistically increases the individual’s propensity to CAD. Kaplan-Meier showed patients’ cumulative risk for events (HR) 70% higher in the risk model vs the nonrisk combination. After Cox regression, TCF21 and APOE combination were independently associated with CV events occurrence, with statistical significance (p=0.014).

Conclusions: Our findings identified two genetic loci with the best interaction for CAD risk. This combination should be further investigated to clarify the underlying mechanism of CAD susceptibility and better understand CAD pathophysiology providing personalized information for potential new therapies.