Skin age is not determined solely by what we can observe with the naked eye, such as wrinkles or changes in texture. It is also related to processes that take place at the molecular level, including the proteins present in cells, which are essential molecules for tissue function.
This study was the first thesis completed as part of the scientific cooperation agreement between Fiocruz and IP Montevideo, a collaboration that aims to strengthen the exchange and joint generation of knowledge between the two institutions.
As part of the study, women aged between 20 and 80 applied quinoa bioester (a cosmetic ingredient obtained through the purification and distillation of quinoa seed oil) to one of their forearms for 30 days, while a control formulation was applied to the other. The researchers then analysed thousands of proteins present in skin samples to identify the changes produced by the treatment.
Based on these data, they developed a machine learning model trained to recognise which combinations of proteins were associated with different skin ages.
The results showed that, following treatment with the quinoa-derived compound, the model estimated a lower molecular age for the treated skin compared with the skin that received the control formulation. Among participants over 50, this difference reached a median of 16 years.
However, this does not mean that the skin literally became 16 years younger. The estimate reflects the fact that the protein profile observed after treatment displayed characteristics that the model associated with younger skin profiles.
The findings, published in the scientific journal Communications Biology, demonstrate the potential of combining molecular analyses and artificial intelligence to study skin ageing and develop more objective tools for assessing whether a cosmetic product actually produces changes associated with this process.
Beyond the compound studied, the research opens the door to new ways of measuring what happens inside the skin and gaining a better understanding of the biological mechanisms associated with ageing.
