Abstract: Provided are methods and models for an alternative source of disease risk, which identifies not genetic variants for a phenotype per se, but variants for variability itself. Also provided are methods and models for a genome-scale, gene-specific analysis of DNA methylation in the same individuals over time, in order to identify a personalized epigenomic signature that may correlate with common genetic disease. Also provided are methods and models for simulating stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease.

Abstract: The present invention discloses methods, computer program and system to overcome the limitation of the current clinical practice. This is achieved by using information technology and the vast amount of epidemiological data available to create algorithms that calculate the risk or severity profile of an individual with any given disease. The individual profile presents the current condition and/or position of the individual in comparison with the mean base curve of the total population and in accordance with upper and lower risk limits. The individual profile is then fitted with its optimal use of healthcare resources, such as medication, surgery, laser treatment, surveillance and follow-up, to optimize and individualize the health outcome of this individual, and at the same time optimize and individualize the allocation of healthcare resources within the system.