The first results of a local genomics program suggest that genetic risk scores can be correlated with concrete clinical indicators, opening the way for the use of genetic testing in preventive medicine.

The initial results of the genomics study conducted by MedLife, based on more than 3,000 tests, indicate a correlation between genetic predispositions and clinical data already used in medical practice—blood tests and patient history. The key stake is not technological, but practical: if these correlations are confirmed on a larger scale, genomic testing could become a working tool in preventive medicine.

Preliminary data shows, for example, that individuals with a high genetic risk for type 2 diabetes have significantly higher blood glucose levels and up to twice the likelihood of developing the disease. The relationship is reversed for those with low risk. Similar correlations have also been observed for cardiovascular and metabolic conditions.

The model used is based on polygenic risk scores (PRS), correlated with existing clinical data. A relevant element is the sample structure: the average age of 41 suggests that the tool captures risks before disease onset, not just its effects.

From an operational perspective, the company is attempting to build an integrated model: genomic data, laboratory analyses, imaging, and lifestyle information. At the same time, models are being tested on large datasets—approximately one million CT and MRI images and over 20 million laboratory tests.

Low-pass genomic testing is expected to become available to the general public at an announced price of 1,430 RON. The company does not anticipate rapid adoption, but rather a gradual one, dependent on the integration of these tools into routine medical practice.

The results are preliminary and cover approximately 75% of the targeted sample, which currently limits the generalization of conclusions. However, they outline a direction: a shift from diagnosis to probabilistic risk assessment based on individual data.