Genetic predisposition (sometimes also known as genetic susceptibility) is the probability that an individual has to develop a disease due to its genetic component.
Genetic predisposition is determined based on specific genetic variations that are normally inherited from one of the parents. These genetic variations contribute to the development of a disease, but do not directly cause it. Which means that, for the same disease, a group of people with a high genetic predisposition will develop the disease, while another group will not.
GWAS studies focus on identifying genetic changes associated with a greater genetic predisposition for a specific disease. Although each associated genetic variant has a small effect, having variations in numerous genes can significantly increase the risk of disease. The combination of these effects generates a metric known as the polygenic score or "polygenic score”Which is expected to serve as a guide in the future to make decisions in the field of health.
This image explains very well the focus of the GWAS studies, the analysis of very frequent variants, with little impact (bottom right). There is a inverse relationship between the impact of a genetic variant (effect size) and the frequency with which we find it in the population (Alelle Freq.), something very logical from an evolutionary perspective (mutations with a great impact, which fortunately are rare)
Although the genetic component of a person cannot be altered, changes in their environment and in their lifestyle (nutrition, smoking ...) are capable of reducing or increasing the risk of developing a disease normally with a greater impact than they have our genes on their own.
The polygenic value can only explain the relative risk of the disease. Why relative? The data used to generate this score comes from large-scale genomic studies. These studies detect variants in the genome by comparing groups with a disease (cases) and healthy groups (control).
That is why the polygenic value compares the risk of a person with the risk of other people, all of them with a different genetic makeup.
However, What can change my risk? There are three main factors to consider:
- The advancement of science: The best example is the discovery of new variants. What does this mean? Publication of new studies on a disease or on any other trait. The addition of new variants will change your result, increasing their confidence levels. Another thing that can affect your results is the modification of the weight of each of the variants.
- Study size: The number of people included in the study is relevant to increase the confidence levels of the results. And not only that, but the number of people your results are compared to: the higher the better, as the statistical confidence of the results increases.
- The distribution of risk: When we assess your relative predisposition (by comparing it to a reference population), how the risk is distributed affects the results.
When we talk about polygenic value we always speak of probability, not certainty, this being a key limitation for its implementation in the clinic (the weakest evidence is found in populations with non-European ancestry).
At ADNTRO we work every day to improve our algorithms and the information we provide to our clients. For this reason, we think that the trend variable can be really useful for use in Bayesian algorithms as the “a priori” probability (adjusted and normalized).
@adntro We keep your DNA up to date! And remember "Everything changes, nothing remains" (Heraclitus, 3000 BC).