Statistical significance and predictive power comes first.
Based on analyzing multitudes of peer-reviewed, statistically-sound studies, we are now able to associate single base-pair variations (known as SNP) in a gene with a change in a certain enzyme activity. Along with supportive evidence from biochemical research and epidemiological studies, it is possible to anticipate how these variants change a biochemical response or even an organ performance. Such changes are the basis for the differences in how people react to various substances, like food, allergens and pollutants. These SNP are what's behind our differences in metabolism, body build, behavior and in our looks.
As scientists around the world publish multitudes of human genetic studies each year, we follow a rigorous quality assurance process to sift through the large data sets. We make sure that each of our tests and interpretations is always based on statistically-sound studies with a large cohort. Top choice are meta-analysis studies, which pool and compare many studies to reach a significantly strong conclusion. These days it is already possible to find Gene-Wide Association Studies (GWAS) and meta-analysis studies that pool as much as half a million individuals.
Statistical significance is of P-value of 5% or better, with added Bonferroni correction when multiple factors are tested.