These unique combinations were shown to play a role in skin protection, premature aging and determining future outcomes for our skin.
Proprietary algorithm that combines your DNA information into a simple score for each skin category.
Visually represents the skins genetic risk factors portrayed across the skin aging processes of skin.
Our software has the ability to analyse and extract insights from large, complex datasets to reveal patterns and trends leading to recommendations for a unique array of topical, nutritional and professional treatments based on our DNA testing and statistical outcomes.
Positioned in specific skin categories these gene combinations have been shown to play a role in skin protection, premature aging and determining future wellbeing of our skin.
The field of genetics is growing and what we now know is that there is no single gene responsible for a single trait.
For example it takes multiple genes working together to create healthy skin.
SkinDNA® is the only skin test on the market that combines multiple genetic markers together within a single category allow us to create a much more in-depth picture of how your skin is functioning.
Lifestyle data is useful in discovering DNA connections.
Using lifestyle data collected from all age ranges allows us to longitudinally study the aging process and associated trends which then support the scientific evidence for the genes we test.
For example, we can look at lifestyle to discover specific DNA outcomes that correlate with visible traits, such as skin color, hair color and eye color.
With over 12 years of data collection, our database represents one of the largest privately held dermagenetics databases in the world.
Our data allows us to discover distinctive skin aging traits that are shared between groups of people.
As the original inventors of the skin genomics industry, we have been able to collect and observe large datasets from different populations and age groups in order to map skin aging trends in younger people and learn how they manifest in older populations.
The larger the dataset the more precise and accurate genetic information becomes.
