In order to truly understand what a DNA estimate is, we have to get a little bit scientific. The DNA testing companies use something called “sample populations” in order to give you your ethnicity estimate. Their laboratories compare your DNA with that of thousands of people from all over the world. In order to become a part of the same population, the participants would have needed to prove that they and their ancestors have lived in the same geographic area for several generations. Their DNA is then grouped by geographic area.
The results of mixed DNA profiles may therefore provide reduced match probabilities when compared with non-mixed profiles. It may be possible for a scientist to be able to assess the relative amount of DNA contributed by different donors in a DNA mixture. If one person has contributed a clear and distinct majority of the DNA detected, that part of the profile may be referred to as the “Major Contribution”.
Most of the services we tested use genotyping to read your DNA. Genotyping looks for specific markers in your genetic code. For something like ancestry testing, genotyping is effective because it identifies known variants in your DNA. Scientifically speaking, genotyping’s weakness is that it can only recognize previously identified markers. This is one reason DNA tests’ accuracy relies so heavily on the DNA database size; there must be enough information available and identified genetic variants in the database to recognize new customers’ markers.
Familial hypercholesterolemia (FH) is a genetic condition associated with very high levels of cholesterol in the blood, specifically low-density lipoprotein (LDL), or "bad" cholesterol. High cholesterol due to FH increases the risk for early cardiovascular disease, which can lead to a heart attack. This test includes 24 genetic variants linked to FH.
In Newman’s view, the genie is out of the bottle with home genetic-testing kits. He says that while the kits could potentially provide data in the future, right now, they lack “clinical utility” – they look at genetic variants that, individually, have a very low chance of predicting specific health risks, as there are too many variables: “It’s like the Opportunity Knocks clap-o-meter, with some people further along the scale, and therefore more likely to get the condition and then people at the other end of the scale, who are unlikely to get it.”