Summary a group of American mathematicians and biologists have developed algorithms to polygenic models. For the ordinary people they are known as “genetically determined diseases” or ailments provoked by the activity of specific genes. But, in practice, there are an enormous number of combinations of these genes and only now, scientists understood about how to diagnose to consider the impact of all of them.

One gene for whatever function he did not answer, rarely becomes the cause of the disease, almost all diseases are inherently polygenic provoked by the activities of groups or subsets of genes, often unrelated. American scientists have developed a model, which can accommodate a very large number of different combinations of genes. And applied it to the estimation algorithm according to the methods of analysis of “big data” received frighteningly accurate tool.

As an example, the study of the probability of coronary artery disease, which depend on the 6.6 million positions in the genome. On the basis of patient data from the British health database Biobank, the authors of the methodology concluded that 8% of people the probability of this disease is three times higher than for all others. The lower the level of risk under the new system leaves you only 1 chance out of 100 to get sick, but guarantees the highest index of the disease in 11 % of cases.

It seems that with this variation on forecast accuracy and not talking, but look at the situation from the other side. Data can be obtained on the basis of DNA analysis, for any person, starting from the first minutes of life. And make a plan – in what conditions it is better to live, what to eat and drink, what drugs to take, never to get sick with something specific. For a businessman, a sports coach, a recruiter of astronauts, the difference is 10 % for the argument to make a choice between the candidates not to waste dozens of years and effort into the preparation of the less promising person. And how overjoyed the insurance company with their dynamic tariffs… because of that technology yet and do not think to implement. Let it remain within the laboratory.
Source — Broad Institue