Automatic numerical optimization is playing an increasingly central role in aircraft development. In previous work, the authors demonstrated the feasibility of high-fidelity dataset-based shape optimization for aircraft design. While aerodynamics is captured using high-fidelity Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) simulations, other disciplines such as mass, structure and flight mechanics are included at a lower fidelity level, reflecting a pragmatic multi-disciplinary approach. Current work introduces structural elasticity into the dataset. The aerodynamic analysis produces detailed sets of load conditions, allowing for accurate structural analysis. No a-priori assumptions must be made regarding which regions of the envelope are decisive for the aircraft structure sizing. This reduces structural design risks significantly and enables robust aeroelastic optimizations, including the effect of elasticity on performance as well as stability and control. Effects and implications introduced by the elastification of the aerodynamic dataset on the aircraft optimization are analyzed and discussed.