Over the last decade, Connected Health (CH) has shown great value in the management of chronic disease (CD), but has limited application in preventing these diseases that remain a huge burden to the society. Technological advances have made determination of genetic predisposition to disease possible and have gained wide use in oncology to develop more effective and individualized treatment strategies-Personalized Medicine. There is growing interest in the application of these genetic tests in predicting risk for complex genetic diseases; even, direct-to-consumer tests are increasingly becoming available and affordable. CH has shown great potential in collecting phenotypic data, which can be overlaid on genomic data to deliver a more precise and personalized preventive care that better engages patients. The goal of a CH program that uses genetic data would be to monitor individuals' risk factors and predict the onset of CD. This prediction would be coupled with coaching to delay or prevent the onset of disease. However, the challenge remains that many CDs are due to complex interaction between genes and modifiable environmental risk factors that are still under-studied.