Our own peer-reviewed research
Here's what we've published, who signed it with us, and the literature we rely on to interpret your DNA. Everything links to the original paper: the idea is that you don't have to take our word for it.
Our publications
A neural network that uses how much information each variant contributes to better separate high risk from low risk. It was tested against independent data from the UK Biobank and the German Diabetes Study.
Int. J. Mol. Sci. 2026, 27(7), 2966 Enhancing Type 1 Diabetes Polygenic Risk Prediction Through Neural Networks and Entropy-Derived Insights
Read the full paper 10.3390/ijms27072966A model that combines the polygenic risk score with variables like age or sex, instead of looking at genetics alone. In validation, it identified 8 out of 10 real cases (a sensitivity of 0.80).
Genes 2025, 16(4), 377 Development of a k-Nearest Neighbors Model for the Prediction of Late-Onset Alzheimer’s Risk by Combining Polygenic Risk Scores and Phenotypic Variables
Read the full paper 10.3390/genes16040377Institutions that co-author with us
They appear as co-authors on the papers above, not as commercial agreements or sponsorships. You can open either DOI and check the list of affiliations.
Beyond doing our own research, we interpret every variant using public, reference scientific databases: the UK Biobank, ClinVar, CPIC, dbSNP, and the GWAS Catalog. These are two different things, and both matter: some are our own studies, the others are the literature we work from.
A prediction model estimates probabilities across a population; it doesn't diagnose an individual. Your genetics has an influence, but it doesn't determine the outcome.
Who vouches for the science
This isn't an anonymous “scientific team”. These are the people who build the models and sign the publications, with their qualifications and academic ID so you can check it yourself.
Dr. Jair Tenorio-Castano
Geneticist
Geneticist and researcher at the Instituto de Genética Médica y Molecular of Hospital Universitario La Paz. Co-authors our polygenic risk score publications, and his ORCID lists the rest of his work.
Qualifications and affiliations
Sandra Ferreiro López
Bioinformatician · Head of science
Builds the machine learning models we use to calculate the polygenic risk score. She's the first author on the late-onset Alzheimer's model we published in Genes.
Qualifications and affiliations
Dra. Marta Alonso-Bernáldez
Nutrigenetics
PhD in nutrigenomics: her thesis focuses precisely on how genetics translates into dietary recommendations. Co-authors our polygenic risk score publications.
Qualifications and affiliations
Who we work with and what backs us
