Attaching a patient's genome to an electronic medical record will enable a variety of prediction scenarios dependent on disease aetiology, prevalence and prevention and treatment options. For some diseases, such as age-related macular degeneration, the high accuracy of genetic prediction could be applied to entire populations so that regular ophthalmological examinations for at-risk individuals could allow early detection and treatment of this degenerative disease. For rarer diseases, population screening is less useful due to low positive predictive values, but genetic prediction could be applied when patients present with early symptoms. For instance, while the rarity of Crohn's disease results in a low positive predictive value in the population, genetic data could aid in the diagnosis of a patient who presents with early symptoms such as abdominal pain, diarrhoea and weight loss. Complex risk prediction also interacts with clinical genetics because some diseases, such as diabetes, have similar presentation of both complex and monogenic forms (41). An accurate prediction of either must take into account the possibility of different underlying genetic models: conditional on disease symptoms, the probability of having a monogenic mutation increases as complex disease risk decreases.
