So far they have helped calculate the risk of diseases caused by a single gene, for example of the approximately 8 thousand rare diseases known so far, but now
genetic tests are preparing for a step forward
, the most difficult and ambitious:
calculating the probability of having a complex disease
, i.e.
caused by a large number of genes,
such as type 2 diabetes resulting from the action of as many as
700
genes or atherosclerosis, in which
350
genes are implicated .
There are ten complex diseases for which as many tests are ready for clinical trials.
Described in the journal Nature Medicine, the result is thanks to the Broad Institute which includes the Massachusetts Institute of Technology and Harvard University.
It is one of the five major studies just published by the 'All of Us' project.
"We hope that in the future this type of information can be used in preventive medicine to help people adopt lifestyles that reduce the risk of disease", observes the first author of the research, Niall Lennon, scientific director of the Broad Clinical Labs .
With type 2 diabetes, the tests cover very common diseases such as type 1 diabetes, atrial fibrillation, breast and prostate cancer, chronic kidney disease and coronary artery disease, hypercholesterolemia, asthma and obesity.
"All together, they are responsible for 92% of deaths in the world", observes geneticist Giuseppe Novelli, director of the Medical Genetics Laboratory of the Tor Vergata Polyclinic.
"They are complex and multifactorial diseases, due - he continues - to the combined action of multiple genes and the interaction of these with the environment. For many years we had the tools to map and study them, but something was missing".
The missing element has now been found thanks to the 'All of Us' project which, by bringing to light the genomes of ethnic minorities, people in poverty and the elderly, has broadened the reference base on which to calculate risk.
"So far the genetic databases are almost all European - observes Novelli - and small populations are not present. The authors of the research, which is interesting and which goes towards integrated genomics tools, decided to fill the gap by calculating familiarity. They thus integrated the probabilistic data with ancestrality, i.e. with the ethnic origin of origin in which the factors are more present".
The result is an algebraic summation called 'polygenic risk calculation': a number which, thanks to ethnic data, acquires greater depth, even if "the tests are not diagnostic but probabilistic".
The challenge, for the geneticist, is to communicate these numbers correctly, "avoiding anxiety injections".
This is what the Predictive and Precision Medicine program launched in recent days at the Tor Vergata Polyclinic aims to do.
How long the road may still be, however, is also indicated by the new data collected by Novelli's group and currently being published, according to which "even in complex diseases there are black swans, i.e. rare variants capable of making a difference" .
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